Godina / Year 2015 ZAGREB Lipanj / June Broj / No 15

29. travanj 2015, Budimpešta, Generalna skupština EFNDT-a29 April 2015, Budapest, EFNDT General Assembly

Miro Džapo, direktor HDKBR-a – novi član

Upravnog odbora EFNDT-a

Visit our new website www.hdkbr.hr

Hrvatsko Društvo za Kontrolu Bez Razaranja - punopravni član EFNDT-a i ICNDT-a

Izdavač: HDKBR Hrvatsko društvo za kontrolu bez razaranjaPublisher: CrSNDT Croatian Society of Non Destructive TestingDirektor / Director: mr.sc. Miro Džapo, dipl.ing.

Tajništvo/Secretariat:HIS, Petra Berislavića 6. 10000 Zagreb, RHTel: +385 (01) 60 40 451 Fax:+385 (01) 61 57 129E-mail: hdkbr@hdkbr.hr, tajnistvo@hdkbr.hr Website: www.hdkbr.hr

Izdavački odbor/Editorial Board:Prof. dr. sc. - Vjera Krstelj (Glavni urednik/Editor-in-Chief)Dr.sc. Dubravko Miljković (Izvršni urednik/Executive Editor)Dr.sc. Dario AlmesbergerProf.dr.sc. Nenad GucunskiMr.sc. Irena LeljakProf.dr.sc. Lovre Krstulović OparaDr.sc. Bojan Milovanović

Suradnici/Collaborators:Mag. Ivan Smiljanić (tehnička podrška/technical support)Martina Alviž, prof. (lektor hrvatskog i engleskog jezika/proofreading)Sandro Bura (priprema za tisak/Layout Editor)

Sadržaj / Content

Poruka predsjednice Message from the President

Intervju: mr. sc. Miro Džapo, direktor HDKBR-a – novi član Upravnog odbora EFNDT-aEUROPSKA FEDERACIJA ZA NERAZORNA ISPITIVANJA (EFNDT)

Lovre Krstulović-Opara, Mislav Ljubenkov, Željko Domazet:The APPLICATION of PULSED THERMOGRAPHY IMAGE PROCESSING METHOD to LONGWAVE BOLOMTERIC INFRARED CAMERAS

Dubravko Miljković:BRIEF REVIEW of MOTOR CURRENT SIGNATURE ANALYSIS

Yuriy Yaremenko, Unna Germany:OPPORTUNITIES FOR the REDUCTION of SUBSTANCES and EQUIPMENT IMPACT on PERSONNEL in PENETRANT and MAGNETIC PARTICLES TESTING

Berislav Nadinić, Marko Rušev:REACTOR PRESSURE VESSEL FLANGE SEALING SURFACES PROFILOMETRY SYSTEM

HDKBR Centar za obrazovanje HDKBR Centar za certifikaciju

NORMIZACIJA

HDKBR Info izlazi četiri puta godišnje/ distribucija 300 kom/broj Godišnja pretplata 300 HRK. Časopis je besplatan za članove HDKBR-a.HDKBR Info možete pratiti na www.hdkbr.hrCrSNDT journal is published four times a year/distribution: 300 copies per issue.Annual subscription - 40 Euro. The journal is free of charge for CrSNDT members An online version is available at www.hdkbr.hr

DOSTAVA PRILOGAHDKBR poziva članove i sve koji imaju materijale zanimljive čitateljima ovog časopisa da ponude priloge. Znanstveni i stručni radovi bit će recenzirani od strane međunarodno priznatih stručnjaka. Za reprodukciju publiciranih radova i izvadaka potrebno je osigurati dozvolu. Tekstovi i mišljenja autora u časopisu ne moraju biti u suglasju sa stavovima HDKBR-a i uredništva. Uredništvo ne nosi odgovornost za pogreške i propuste autora radova.

PAPER SUBMISSIONCrSNDT invites contributions that will be interesting for readers of HDKBR Info Journal. Technical papers submitted are peer-reviewed by internationaly rec-ognized experts. Permission should be obtained for reproduction of individual articles and extracts. The articles and views expressed in the publication are not necessarily in line with CrSNDT, editor and editorial. No liability is accepted for errors or omission.

OGLAŠAVANJE/ADVERTISEMENTCijena oglašavanja/The cost for advertising is:

Stranica/Page in journal Cijena za 4 broja /Cost for 4 numbers per year

Zadnja/The last page(cover page A4 size) 8000 HRK 1080 Euro or 1380 $ (US)

Unutarnja/Inside page (A4 size) 4000 HRK 540 Euro or 690 $ (US)

Unutarnja/Inside pages(A4/2 size; half page) 2000 HRK 270 Euro or 395 $ (US)

Cijena oglasa u samo jednom broju iznosi pola cijene godišnjeg oglašavanja. The price of advertisement published (in only one journal issue) is half of the yearly cost.

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Poruka predsjednice

Poštovani čitatelji, kolege i kolegice, prijatelji HDKBR-a,

Nakon duže pauze, HDKBR je 2011. godine nastavio s izdavanjem časopisa HDKBR Info, četiri broja godišnje, koji se tiska i šalje članovima HDKBR-a, udrugama NDT-a u Europskoj uniji i šire, te našim prijateljima i suradnicima koji s interesom prate postignuća HDKBR-a i njegovih članova, znanstvene i stručne radove u području naše djelatnosti i općenito djelatnost u našoj zemlji i svijetu u području nerazornih ispitivanja. S velikim zadovoljstvom moramo napomenuti da nam nije nedostajalo ni radova ni sadržaja o događanjima u HDKBR-u. U 2014. godini izdali smo dva broja koje možete naći na web stranicama HDKBR-a. Obzirom na sve težu situaciju u industriji, većina tvrtki i NDT djelatnika radi izvan granica Hrvatske nastojeći se održati u ovim teškim danima recesije u kojima se gasi mnogo industrijskih postrojenja. Poznato je da u takvim situacijama najprije ponestaje sredstava za kvalitetu i održavanje.

Situacija je još teža u 2015. godini, te se recesija i teško stanje za naše kolege u industriji i u obrazovanju nastavlja do te mjere da smo bili prisiljeni otkazati našu međunarodno poznatu konferenciju MATEST 2015 za koju je postojao veliki interes naših kolega iz inozemstva, ali nažalost premali broj sudionika iz Hrvatske nije mogao opravdati održavanje. Dio radova koji su bili prijavljeni za MATEST možete pročitati u ovom broju.

HDKBR će i dalje nastaviti sa izdavanjem časopisa i omogućiti našim stručnjacima da objave radove, međutim do vremena kada će Hrvatska revitalizirati svoju industriju i ojačati proizvodnju, teško je očekivati potrebnu podršku i redovito tiskanje.

HDKBR je tijekom svoje 50-godišnje povijesti djelovanja doživljavao i prebrodio mnoge teškoće i prepreke pa možemo očekivati ne samo daljnje teškoće, već i uspjehe kao i do sada. Kao predsjednica ne samo HDKBR-a, već i HIS-a (Hrvatski inženjerski savez), u čijem okrilju uz više od trideset udruga djeluje i HDKBR, poznata mi je slična situacija pa i znatno teža u drugim inženjerskim udrugama, međutim nitko ne posustaje i ne samo da se traži izlaz, već se nude i naziru dobra rješenja. Reindustrijalizacija je rješenje kojim Europska unija nastoji poboljšati svoju ekonomiju te je reindustrijalizaciju uključila u strategiju Europske unije (EU Strategy 2020). Hrvatska se mora uključiti i što prije to učinimo, manje će biti problema u budućnosti.

Može li itko zamisliti industriju bez inženjera i tehničara, bez NDT-a i potrebne kvalitete u gradnji i održavanju? To dalje znači da moramo sačuvati HDKBR u kojem se generiraju, osposobljavaju i potvrđuju svoju osposobljenost naši NDT stručnjaci. Svatko ovome može i mora doprinijeti.

S velikim interesom i nadom očekujemo vaš doprinos ovim nastojanjima.

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Prof. dr. sc. Vjera Krstelj

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Message from the President

Dear readers, colleagues and friends of CrSNDT,

After a long pause, CrSNDT continued to publish HDKBR Info journal in 2011, four times per year, which is published and sent to CrSNDT members, NDT societies in and outside the European Union, our friends and associates who follow our achievements with great interest, but also scientific articles in the NDT field and NDT activities in general in our country and abroad. We have to emphasize with great pleasure that we did not lack papers nor content on CrSNDT events. In 2014 we had two issues which can be found on the society’s web page. Because of the difficult situation in the industry, many Croatian companies and NDT persons are working outside Croatia trying to keep pace and fight difficult days of recession in which many industrial plants are closing. It is a well-known fact that in those situations, resources for quality and maintenance are first to be reduced.

The situation in 2015 is even worse and recession and difficult conditions for our colleagues in the industry and in education are getting so serious to the extent that we were forced to cancel our internationally recognized MATEST 2015 conference. Although many foreign colleagues showed interest in it, due to the small number of Croatian participants, the conference could not take place. Some of the papers intended for MATEST can be read in this issue.

CrSNDT will continue to publish the journal and enable all out experts to publish their papers, but unfortunately, by the time Croatia revitalizes its industry and strengthen production, it will be hard to expect necessary support and regular publishing.

During its 50 year old history, CrSNDT has had and overcome many difficulties and obstacles so we can expect not only more difficulties, but also many successes as it has been the case before. As a President of both CrSNDT and HIS (Croatian Engineering Association) which is the umbrella organization of CrSNDT and more than thirty other associations, I am familiar with similar and even worse situations in other associations. However, no one is giving up and everyone is looking for a way out of recession and good solutions are one the way.

Reindustrialization is a solution by which the European Union is trying to improve its economics and reindustrialization has been included in the EU strategy 2020. Croatia should be included as well and the sooner we do that, the fewer problems we will have in the future.

Can anyone imagine industry without engineers and technicians, NDT and necessary quality in building and maintenance? That means we have to keep and protect CrSNDT, in which our NDT experts are gathered, trained and certified. Anyone can and has to contribute to this.

With great interest and hope, I expect your contribution to these endeavors.

Prof. Vjera Krstelj, Ph.D.

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EUROPSKA FEDERACIJA ZA NERAZORNA ISPITIVANJA (EFNDT)

Budimpešta, 29. travnja 2015.

Europska federacija za nerazorna ispitivanja, EFNDT (European Federation for Non- Destructive Testing) je na sjednici Skupštine održanoj u Budimpešti, 29. travnja 2015. godine, izabra-la nove čelnike svoje udruge. Nakon tri godine uspješnog vođenja EFNDT-a od bivšeg predsjednika dr. Matthiasa Purschkea, zamjenika predsjednika prof. dr. Petera Trampusa i Glavne tajnice gospođe Jutte Koehn, za predsjednika je jednoglasno izabran prof. dr. Peter Trampus, koji je ujedno i predsjednik mađarskog NDT društva. Zamjenikom predsjednika proglašen je gospodin Roger Lyon iz Britanskog instituta za nerazorna ispitivanja, BINDT, a dužnost Glavne tajnice obavljat će gospođa Annamária Nagy, djelatnica Mađarskog društva za nerazorna ispitivanja.

Upravni odbor – novi sastav

Predsjednik: Peter Trampus MađarskaZamjenik: Roger Lyon V. BritanijaČlanovi odbora:Gerhard Aufricht AustrijaDominique Moussebois BelgijaMiro Džapo HrvatskaEtienne Martin FrancuskaAnton Erhard NjemačkaAlexander Mullin Rusija Goran Sofronić SrbijaFermin Gomez Španjolska

U veselom raspoloženju predsjednici/predstavnici nacionalnih NDT društava završili su sjednicu u očekivanju daljnjeg uspješnog djelovanja EFNDT-a na dobrobit NDT struke, NDT profesionalaca i kvalitete općenito.

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HRVATSKO DRUŠTVO ZA KONTROLU BEZ RAZARANJA

Intervju: mr. sc. Miro Džapo, direktor HDKBR-a i član Upravnog odbora EFNDT-a

• Od 29. travnja ove godine član ste Upravnog odbora EFNDT-a, što je veliko priznanje za, Hrvatsko društvo za kontrolu bez razaranja, Hrvatski inženjerski savez i – Vas osobno. Je li Vas iznenadio ulazak u Upravni odbor? Na što su bila usmjerena pitanja tijekom procedure ispitivanja kandidata za Upravni odbor? Koliko traje Vaš mandat? Na što se, odnosno na koju se agendu fokusira ovaj sastav Upravnog odbora EFNDT–a ?

Na ovako postavljeno pitanje moram priznati da se i sam iznenadim jer za mene i za nas članove HDKBR-a postalo je normalno da smo tako intenzivno uključeni u rad Europske federacije za nerazorna ispitivanja, EFNDT-a, budući da je naša predsjednica prof.dr.sc. Vjera Krstelj bila član Upravnog odbora EFNDT-a od osnutka EFNDT-a, uz prvog predsjednika dr. Schnitgera, predsjednika njemačkog NDT društva, a potom je nakon nekoliko mandata, 16. siječnja 2009. godine, izabrana za predsjednicu EFNDT-a. Od 8. ožujka 2012. godine u mandatu novog predsjednika, bivši predsjednik, odnosno naša predsjednica prof. Krstelj, član je Uprave do izbora novog predsjednika.Dakle, do izbora sadašnjeg predsjednika EFNDT-a, te mog izbora u Upravni odbor EFNDT-a, HDKBR sudjeluje u Upravi EFNDT-a od Osnivačke skupštine EFNDT-a, a ja sam osigurao kontinuitet prema budućnosti.

Član Upravnog odbora EFNDT-a

HDKBR

Direktor

Mr.sc. Miro Džapo

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Odabir mene za člana Upravnog odbora, ponovna je potvrda snage naše udruge i ugleda HDKBR-a u Europskoj federaciji, a naravno da sam osobno ponosan što sam uspio postići takav ugled među kolegama u Europskoj federaciji jer za ulazak u Upravni odbor nisu bile velike mogućnosti budući da je teško zamislivo da u Upravni odbor ne uđu predsjednici ili direktori NDT društava velikih država, kao što su Njemačka, Engleska, Francuska, Rusija, Španjolska i konačno, predstavnik Belgije s obzirom da je ured EFNDT-a u Bruxellesu. Ostaju, dakle, dva do tri mjesta na koja pretendiraju mnoge druge europske zemlje i vrlo kvalitetni predsjednici, odnosno direktori europskih NDT udruga.Zaista sam ponosan što sam odabran za člana Upravnog odbora, ali i sretan jer HDKBR ovime ponovno potvrđuje svoj ugled te nam se pruža mogućnost izvrsne suradnje i utjecaja na razvoj naše profesije. Zato na vaše pitanje je li me iznenadio moj izbor, moram odgovoriti da me nije iznenadio, upravo suprotno. S obzirom na moju suradnju s EFNDT-om i NDT udrugama u Europi, moram bez lažne skromnosti reći da bi me iznenadilo da nisam bio izabran.Mandat članova Upravnog odbora traje tri godine. Moj izuzetno dobar odnos s novim predsjednikom EFNDT-a, sveučilišnim profesorom Peterom Trampusom, olakšat će nam suradnju i, vjerujem, do-prinijeti daljnjem uspješnom razvoju EFNDT-a i realizaciji utvrđene strategije. • U čemu vidite svoj mogući osobni doprinos u radu EFNDT-a ?

Moj će doprinos prvenstveno biti vezan uz produbljivanje postojećih dobrih odnosa i uspješne suradnje sa članicama EFNDT-a, putem osiguravanja provođenja zacrtanih strateških zadata-ka i djelovanjem u Upravnom odboru na način da svaka članica ima interes i koristi od članstva. Osobno se želim više založiti za kvalitetan sustav obrazovanja i certifikacije jer smatram da neovisno o potpisivanju MRA ugovora (multilateralnog priznavanja certifikata), postoji još puno prostora za poboljšanja i djelovanja u smjeru izvrsnosti unutar EFNDT-a.

• Priznati ste stručnjak za ispitivanje nuklearnih elektrana. Koliko ste ih i na kojim lokacijama u svojoj karijeri do sada ispitali? Pamtite li pritom i neke posebne trenutke odnosno specifične situaciije?

Najprije želim napomenuti da svaki istraživač, stručnjak, ispitivač i osoba koja želi djelovati u području nerazornih ispitivanja mora imati iskustva u ispitivanju, odnosno mora poznavati konstrukciju objekata koji se ispituju. S druge strane, razvoj opreme i tehnologija u našoj struci toliko brzo napreduje da se vrlo brzo nađete izvan potrebnih znanja i zato morate trajno učiti. Nuklearne elektrane koje ispitujem su moj način održavanja u struci, naravno ne baš lagani način za održavanje “kondicije”, ali meni jako drag način i osvježenje u mom poslu.Do sada sam sudjelovao u ispitivanju preko tridesetak NE, većinom u SAD-u. Moram priznati da nemam loših iskustva, a povremeno bude i komičnih situacija.

• Koliko šira i uža specijalistička javnost prepoznaju važnost i značaj HDKBR-a kao jedinog ovlaštenog izdavatelja certifikata na području kontrole bez razaranja, odnosno kao jedinu nacionalnu instituciju ovlaštenu za certifikaciju NDT osoblja?

Tu se javljaju određeni problemi na kojima ćemo morati ozbiljno raditi. Naime, informiranost unutar naše industrije je nedovoljna i pojedini poduzetnici i pojedinci provode obrazovanje u okviru neodgovarajućih tečajeva i institucija, neznajući da njihova nevažeća uvjerenja i certifikate dobro informirane institucije ne priznaju. Neki se tečajevi održavaju čak na fakultetima, točnije u prostorijama fakulteta čime se sudionici donekle zavaravaju jer misle da fakultet daje garanciju i da sudjeluje u tom poslovanju. Činjenica je da fakultet možda ima neke koristi od održavanja takvih seminara i tečajeva iznajmljujući opremu i prostore za održavanje, ali bitno je tko izdaje certifikat za ispitivanje nerazornim metodama i je li ta institucija ili udruga akreditirana. Imali smo slučajeve da su se ispitivači – djelatnici vrlo poznatih tvrtki, morali vraćati iz inozemstva i u potpunosti ponoviti obrazovanje i provjeru znanja, kako bismo im mogli izdati certifikate koji su priznati svuda u Europi i

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šire jer je HDKBR za sada jedini akreditirani centar za izdavanje certifikata za ispitivanje nerazornim metodama, a certifikati su priznati također putem MRA.

• Što valja učiniti da HDKBR postane više vidljiv i prepoznatljiv?

Na ovo pitanje je lako odgovoriti, ali provedba je nešto teža. Naime, treba informirati javnost, treba osigurati propise i ponašanje koje će osigurati da tvrtke i pojedinci ne plaćaju, i tako gube sredstva, školovanjem ljudi na neodgovarajućim tečajevima i seminarima.

Ako se uzme u obzir da su radna mjesta NDT ispitivača u mnogim zemljama relativno dobro plaćena, te da usred recesije u Hrvatskoj brojne tvrtke i pojedinci sada ostvaruju profit u inozemstvu, a s druge strane, pogreška ili previd neke pukotine u konstrukciji, npr. aviona, termoelektrane, neke posude pod pritiskom, a da ne spominjem nuklearne elektrane, može izazvati katastrofalne posljedice. Zato moramo biti vrlo ozbiljni i dobro organizirani pri stvaranju kadra u ovom našem tako osjetljivom i odgovornom području djelovanja.

Svaku tvrtku i pojedinca molimo da prije slanja djelatnika na obrazovanje i certifikaciju dobro provjeri tko organizira tečaj i ispit, neovisno gdje se to održava, na fakultetu, ministarstvu ili bilo kojoj ustanovi koja možda samo iznajmljuje prostorije, te je radi toga istaknuta u adresi održavanja.

HDKBR je vidljiv i prepoznatljiv onima koji vide i trude se znati.

• S čime ste više, a s čime manje zadovoljni što se aktivnosti HDKBR–a kao udruge tiče? Na što ste posebno ponosni?

Kao direktor, osobito mi je drago što je HDKBR prepoznat kao aktivan član i svjetske organizacije ICNDT, s čijim članicama, tj. nacionalnim društvima je također potpisan MRA, odnosno ugovor o međusobnom priznavanju certifikata. Ujedno treba naglasiti da smo jedni od prvih članica EFNDT-a koji smo akreditirani prema novoj normi HRN EN IS/IEC 17024:2013 i to od Hrvatske akreditacijske agencije, čime smo započeli novi petogodišnji ciklus certificiranja NDT osoblja u području nerazornih ispitivanja. Posebnu pozornost bih skrenuo i na nedavno potpisani Sporazum o suradnji s američkim društvom ASNT-om, što nam daje dodatnu vrijednost. U proteklih pet godina ne samo da smo u Hrvatskoj certificirali više od 1000 osoba nego smo i u Izraelu certificirali više od 150 osoba, što nam daje dodatnu težinu izvan granica Hrvatske.

Istaknuo bih i da je HDKBR jedna od članica Hrvatskog inženjerskog saveza, HIS-a, u čijem okrilju nalazi ne samo adresu već lijepu suradnju s tridesetak drugih inženjerskih udruga. Nažalost, sada nije povoljno vrijeme za udruge, prvenstveno tehničkih struka jer društvo i šira javnost gotovo da zaboravljaju tehniku i one koji mogu pomoći u izlasku iz ove financijski teške situacije. Nezadovoljan sam sa stavom prema udrugama tehničkog područja koje ne primaju nikakvu potporu.

Ukratko, ponosan sam na činjenicu da udruga živi, radi i uspješno napreduje unatoč nepovoljnoj ekonomskoj situaciji, koja nas čak štoviše, potiče da pomičemo vlastite granice i na ljestvici kvalitete budemo uz bok ostalim europskim i svjetskim društvima.

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THE APPLICATION OF PULSED THERMOGRAPHY IMAGE PROCESSING METHOD TO LONGWAVE BOLOMTERIC

INFRARED CAMERASLovre, Krstulović-Opara, University of Split, Faculty of Electrical Engineering, Mechanical

Engineering and Naval Architecture, Split, CROATIA, Lovre.Krstulovic-Opara@fesb.hrMislav, Ljubenkov, University of Split, Faculty of Electrical Engineering, Mechanical Engineering

and Naval Architecture, Split, CROATIA, mljubenk@fesb.hrŽeljko, Domazet, University of Split, Faculty of Electrical Engineering, Mechanical Engineering and

Naval Architecture, Split, CROATIA, Zeljko.Domazet@fesb.hr

ABSTRACT - Pulsed infrared thermography is a NDT method for evaluating polymer reinforced structures. As our former research was performed on advantageous cooled middle-wave camera, in this contribution gradient based image processing method has been applied on long-wave bolometric cameras. Different wavelengths and camera sensitivities have been compared on prefabricated specimen. To demonstrate the capability of approach, examples from floating vehicles industry have been presented.Keywords: non-destructive testing, infrared thermography, bolometric cameras

1. INTRODUCTIONThermography, as a non-destructive testing (NDT) method, is used mostly as passive ob-serving method for evaluating structures and materials such as reinforced polymers. It is already a standard procedure performing passive thermographic inspection on aircrafts after landing, where search for ice inclusions due to the interlaminar humidity penetration is performed [1]. For such applications mostly bolometric long-wave (LW) infrared (IR) ther-mal cameras are used. Active thermography is mostly used in research [2 to 10] and in some advanced industries as a quality control system, e.g. wind turbine [11] and aircraft [12] industry. For such applications mostly cooled middle-wave (MW) cameras and halogen or Xenon lamps, as heat source, are used. Reason for using more expensive MW thermal imaging cameras is sensitivity (mostly 0.02°C) and high frame rates capable of capturing dynamic changes in heat flow. We have performed extensive research based on cooled MW IR camera with InSb detector and active pulsed thermography (PT), as well as pulsed phase thermograph (PPT) approach [13 to 17]. When comparing two basic groups of IR cameras; MW have

high frame rate (up to 700 Hz), high sensitiv-ity (0,02÷0,015°C) and high price, making them laboratory stationary equipment. LW IR cameras are characterized by lower frame rates (around 60 Hz) and lower sensitivity (0,1÷0,05°C). LW cameras, due to lower price and ease to han-dle, are more often used in praxis and research. To promote active IR thermographic NDT for LW camera users, presented research is an application of knowledge obtained in the field of MW IR thermography to the field LW IR cameras. The idea is without having expensive MW IR cameras and IR research software, it should be possible to use same PT or PPT approaches with cheaper LW cameras, avoiding need for research software that provides IR image in a raw data format. Raw data field of temperatures is exported in matrix form, which can be mathematically modified afterwards. We have used standard Matlab routines to extract matrix of tempera-tures from JPEG image, which is a common output format of IR cameras. Temperatures, represented as a grayscale image level in matrix format, can be mathematically processed by known PT image processing methods used in NDT evaluation.

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1. INTRODUCTION

2. IMAGE PROCESSINGBased on standard Matlab package, JPEG images are loaded into MatLab and transformed into matrix form of size equivalent to camera detector size. As our primary concern is gradient based image processing [14], exact temperature interpretation is not essential as gradient method enables locating zones of interest without need for exact temperature level. First step is to read image to the Matlab and turn it to the greyscale image.

B=imread(‘thermal_image.JPG’);

C=rgb2gray(B);

Thermal gradient [14] is obtained as

grad T= (∂T/∂x, ∂T/∂y), (1)

where x, y are horizontal and vertical directions of a pixel position in the pixel map. Gradient function flattens differences in thermal field with lower gradient values, while keeping visible zones with higher thermal gradient. The result is a clear image of transition zones between anomalies and undamaged structure. Significant advantage of gradient based method is elimination of unequal heating influences and background reflections, what is a common problem in active thermography. In Matlab, following command calculates thermal gradient.

[Gx, Gy] = imgradientxy(C);

G=Gx+Gy;

After the gradient matrix is created, matrix is exported to a JPEG image that enables visual interpretation of thermograms and location of anomalies.

imagesc(G);

3. COMPARISON OF MW AND LW PT IMAGES To evaluate gradient based image processing, when applied on different wavelengths, comparison is made between cooled MW InSb Flir SC 5000 camera (resolution 320x256 pixels, sensitivity 0.02°C) and bolometric cameras Flir E60 (resolution 320x240 pixels, sensitivity 0.05°C) and Flir i7 (resolution 140x140 pixels, sensitivity 0.1°C). Thermal pulse is generated by preheating specimens with 1kW halogen lamp on 40 cm of distance and 2 min duration of preheating. Images are taken just after turning off and removing lamp from specimen. Emissivity coefficients are: 0.98 for uncoated

GRP in MW spectrum, 0.975 for coated GRP in MW spectrum, 0.95 for coated and uncoated GRP in LW spectrum.

Figure 1 Experimental setup

To compare different wavelengths and characteristics of thermal cameras, vacuum cured glass reinforced polymer (GRP) specimen is used (97 x 97 x 10.5 mm) [17]. To evaluate sensitivity specimen has several blind holes (diameter of 5 and 10 mm) with variable depth (2, 4, 6 and 8 mm) and two channels (5 and 10 mm width) with variable depth (0 to 10.4 mm).

D10C10

B10A10

A5B5

C5D5

S5

S10

Line 1

Line 2

Figure 2 GRP vacuum cured test specimen with machined anomalies

Figure 3 Thermal image (up) and gradient (down) acquired by MW 320x256/0.02°C camera

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Figure 4 Thermal image and gradient acquired by LW 320x240/0.05°C camera

Figure 5 Thermal image and gradient acquired by LW 140x140/0.1°C camera

All presented IR images (Figures 3 to 5) are taken from unmachined side. Cameras are kept at the same distance, where different lenses influenced the specimen image size. MW 320x256/0.02°C camera has narrowest lens (25 mm / 1:3.0), LW 320x240/0.05°C has 25°x19° lens and LW 140x140/0.1°C has widest 29°x29° lens. Thermal images are as grayscale images loaded to Matlab and converted to the greyscale matrix.

Figure 6 Matlab Colour scale for 320x256/0.02°C MW, 320x240/0.05°C LW and 140x140/0.1°C LW

thermal image

To compare sensitivity, greyscale level is displayed across lines 1 and 2 crossing over blind holes and compared with line 3 crossing in between, i.e. area with no anomalies (Figure 2). Sensitivity (grayscale contrast) is defined as difference between lines L1, L2 and line L3. Blind Ø10 holes are named with letters A10 (deepest) to D10 (shallowest), while Ø5 holes are named with letters A5 (deepest) to D5 (shallowest).

Figure 7 Grayscale level (up) and grayscale

contrast (down) acquired by 320x256/0.02°C MW camera

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Figure 8 Grayscale level and contrast acquired by 320x240/0.05°C LW camera

Figure 9 Grayscale level and contrast acquired by 140x140/0.1°C LW camera

Both LW cameras are showing very good sensitivity in comparison to MW cooled camera, proving the applicability of gradient based puled thermography method to the LW spectrum.

Comparison of wavelengths and cameras has been made for the specimen impacted with 19.61 J impactor [13] according to DIN 6038.

GRP specimen, described in [17], has been preheated for 2 minutes. Gradient function is applied on greyscale images. Colour scale (images imported in Matlab and displayed with same scale, Figure 14) is giving too confusing images. Gradient method enables locating the damage for the case of the 320x256/0.02°C MW and 320x240/0.05°C LW camera. 140x140/0.1°C LW camera is not giving clear result. When comparing all images, it can be concluded that method is not dependent on wavelength, but it is influenced by sensitivity and resolution of the camera itself, what is this case is low pixel size and sensitivity of 140x140/0.1°C LW camera. On the right side of specimen is the black PVC insulation tape used for comparing emissivity.

Figure 10 Impacted specimen

Figure 11 Thermal image and gradient acquired by 320x256/0.02°C MW camera

Figure 12 Thermal image and gradient (320x240/0.05°C LW camera)

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Figure 13 Thermal image and gradient (140x140/0.1°C LW camera)

Figure 14 Colour scale for 320x256/0.02°C MW, 320x240/0.05°C LW and 140x140/0.1°C LW

thermal image

Comparison has been made on example of impacted and severely delaminated specimen where delaminated zones are detectible on all cameras. Only MW camera gives clear image of zone where glass fiber rupture occurred. This example shoves clear benefit of MW cameras over LW cameras and evaluation limits when using LW cameras. Therefore, LW cameras can be used for detecting delamination zones, but LW cameras are not appropriate for detecting glass fiber ruptures. As in the example before, colored scale images are not so clear when performing NDT surveys (images are made after importing in Matlab).

Figure 15 Impacted and severely delaminated specimen

Figure 16 Thermal image and gradient acquired by 320x256/0.02°C MW camera

Figure 17 Thermal image and gradient acquired by 320x240/0.05°C LW camera

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Figure 18 Thermal image and gradient acquired by 140x140/0.1°C LW camera

Figure 19 Colour scale thermal image for 320x256/0.02°C MW, 320x240/0.05°C LW and

140x140/0.1°C LW

4. THE APPLICATOION OF GADINENT BASED IMAGE PROCESSING ON FLOATING VEHICLESInspecting GRP boats is of particular interest due to the robustness and short inspection duration of IR based methods. Here some typical images of 20,5 m sailing boat survey and work-boat catamaran survey are demonstrating ability of IR thermography. First group of images shows IR (320x240/0.05°C LW) NDT survey of a 20,5 m sailing boat still under construction in the workshop (Figures 20 to 25).

Figure 20 Air pockets in the gelcoat (image, thermal image and gradient)

Figure 21 Air pockets and unequal gelcoat thickness in bow region

Figure 22 Detail of stern structure

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Figure 23 Resin inclusion near structural reinforcement

Figure 24 Confirmation and evaluation of structural reinforcement

Figure 25 Improper bonding of reinforcement (left) and U form resin inclusion (right)

Application of gradient based image processing improves locating and validating anomalies, as well as inspecting structural details as reinforcements. Anomalies are visible on pure thermal images, but gradient method improves distinguishing anomalies from reflections and effects of unequal heating.

Last example (Figure 26) is a catamaran work-boat, where survey of crane structural support enabled locating delamination and cracks within GRP structure caused by misaligned flange reinforcement in clamping zone. Here IR (320x240/0.05°C LW) NDT survey was the base for properly reinforcing flange support and repairing GRP structure. Preheating time was here as well 2 minutes. Thermal image in Figure 26 is created as panoramic image from 5 thermal images (a Flir Tools plus software option).

Figure 26 Debonding and fractures in GRP structure in the zone of flange support

5. CONCLUSIONPresented research proved that LW IR cameras can be used for NDT of GRP floating vehicles, expect the case when glass fibres rupture is considered. Method is robust, fast and applicable for MW and LW spectrum. Gradient based image processing eliminates reflections and influences of unequal heating. The presented image processing is not obtained from a raw image containing pixel-wise temperature distribution, but from a JPEG grayscale image. Such an approach enables image processing in academic research community without need for scientific camera software, supposing that standard Matlab software is available. Although

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temperature amounts are lost, gradient based image processing is applicable to the grayscale images. As LW IR cameras are more and more in use, we hope that presented approach will help users entering the field of pulsed IR thermography, as a NDT method.

6. REFERENCES[1] Grispen, R.: Thermal imaging helps to detect

water ingress in airplanes, Applications in maintenance and asset management, Maintworld 2, 2011.

[2] Miller, B. F.: The feasibility of using thermography to detect subsurface voids in painted wooden panels. Journal of the American Institute for Conservatory, Vol. 16, Number 2, 27-35, 1977.

[3] Ibarra-Castanedo, C.: Quantitative subsurface defect evaluation by pulsed phase thermog-raphy: Depth retrieval with the phase. Ph.D. thesis, Faculté des sciences et de génie, Université Laval, Québec, 2005.

[4] Maladague, X., Galmiche, F., Ziadi, A.: Advances in pulse phase thermography. Infrared Physics & Technology, Vol. 43, 175-181, 2002.

[5] Ibarra-Castanedo, C., González, D., Galmiche, F., Maldague, X. P., Bendada, A.: Discrete signal transforms as a tool for processingand analyzing pulsed thermographic data. Thermosense XXVIII, Vol. 6205, 2006.

[6] Sakagami, T., Kubo, S.: Applications of pulse heating thermography and lock-in thermography to quantitative nondestructive evaluations. Infrared physics and Technology, 43, 211-218, 2002.

[7] Carlomagno, G. M., Meola, C.: Comparison between thermographic techniques for frescoes NDT, NDT&E International 35 (2002) 559–565

[8] Roche, J.M., Balageas, D.: Common tools for quantitative pulse and step-heating thermography-Part II: experimental validation. The 12th International Conference on Quantitative InfraRed Thermography (QIRT 2014), Jul 2014, BORDEAUX, France, 2014. dfgdfgdgdfgdfgdfgdfgdfg

[9] Milovanović, B., Banjad Pečur, I.: Detecting defects in reinforced concrete using the method of infrared thermography, HDKBR info, 11, 3-13, 2013.

[10] Flir Application story series: FLIR thermal imaging cameras help detect material failures in bikes, www.flir.com

[11] Flir Application story series: Advanced FLIR thermal imaging cameras help standardize testing of wind turbine blades, www.flir.com

[12] Ullman, T. , Aoki, R., Schmidt, T.: Lock-in Thermography for Process Integrated Non-Destructive Evaluation of Carbon Fibre Reinforced Aircraft Structures. 10th International Conference on Quantitative InfraRed Thermograpy, July 27-20, Quebec, Canada, 2010.

[13] Krstulović-Opara, L., Klarin, B., Neves, P., Domazet Ž.: Thermal imaging and Thermoelastic Stress Analysis of impact damage of composite materials. Engineering Failure Analysis, Vol. 18, 713–719, 2011.

[14] Krstulović-Opara, L., Klarin, B., Garafulić, E., Domazet, Ž.: Application of gradient based IR thermography to the GRP structures inspection. Key Engineering Materials, Vols.488-489, 682-685, 2011.

[15] Krstulovic-Opara, L., Domazet, Ž., Klarin, B., Garafulić, E.: The Application of IR Thermography to the NDT and Thermal Stress Analysis, HDKBR info, 6/7, 17-22, 2012.

[16] Krstulović-Opara, L., Domazet, Ž., Garafulić, E.: Detection of osmotic damages in GRP boat hulls, Infrared Physics & Technology, Vol. 60, 359-364, 2013.

[17] Garafulić, E. , Krstulović-Opara, L., Domazet, Ž.: Detection of material anomalies based on infrared thermography image processing, Proceedings of NDT week in Zagreb , 7.-12. October, Zagreb, Croatia, 3-13, 2013.

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BRIEF REVIEW OF MOTOR CURRENT SIGNATURE ANALYSIS

Dubravko, MILJKOVIĆ, HEP, Zagreb, CROATIA, Phone: (1)6113032; dmiljkovic@hep.hr

ABSTRACT - Motor electrical current signature analysis (MCSA) is sensing an electrical signal con-taining current components that are direct by-product of unique rotating flux components. Anomalies in operation of the motor modify harmonic content of motor supply current. This paper presents brief introductory review of the method including fundamentals, fault detection techniques and current signatures of various faults.

Keywords: induction motor, current, signature analysis, MCSA, fault detection, condition monitoring

1. INTRODUCTIONInduction motors are widely used in industrial drives because they are rugged, reliable and economical, [1]. They became an industry workhorse and play a pivotal role in industry for conversion of electrical into mechanical energy, [2]. Motor Current Signature Analysis (MCSA) is a condition monitoring technique used to diagnose problems in induction motors, [3-12]. Concept originates from early 1970s and was first proposed for use in nuclear power plants for inaccessible motors and motors placed in hazardous areas, [13]. It is rapidly gain-ing acceptance in industry today. Tests are performed online without interrupting production with motor running under the load at normal operating conditions, [4,13]. MCSA can be used as predictive mainte-nance tool for detecting common motor faults at early stage and as such prevent expensive catastrophic failures, production outages and extend motor lifetime. It can be used as a diagnostic tool and powerful addition to vibra-tion and thermal monitoring (verifying a fault with more than one technology), [14-16]. MCSA is method from wider field of Electrical Signature Analysis (ESA), [17], useful for analyzing not only electrical induction motors, but also gener-ators, power transformers as well as other elec-tric equipment. Most popular of these techniques are: Current Signature Analysis (CSA), Voltage Signature Analysis (VSA), Extended Park’s Vector Approach (EPVA) and Instantaneous Power Signature Analysis (IPSA), [11]. ESA also

includes Motor Circuit Analysis, [18], involving analysis of resistance, impedance, inductance, phase angle, current/frequency response and insulation to ground faults, [19].

2. MOTOR CURRENT SIGNATURE ANALYSIS BASICSMotor Current Signature Analysis is the tech-nique used to analyze and monitor the trend of dynamic energized systems, [11].

Figure 1 Stator current monitoring system

MCSA is monitoring stator current (more pre-cisely supply current) of the motor, [7]. Typical stator current monitoring system is illustrated in Figure 1. Single stator current monitoring system is commonly used (monitoring only one of the three phases of the motor supply current). Motor stator windings are used as transducer in MCSA, picking the signals (induced currents) from the rotor (but also revealing information about the state of the stator).

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Motor current is sensed by a Current Sensor (clamp probe, current transformer) with resis-tive shunt across its output, [21], and recorded in time domain. Picked current signal is then led to a spectrum analyzer or specialized MCSA instrument. In ideal case motor current should be pure sinusoidal wave. In reality in motor current many harmonics are present. Current spectrum of a typical induction motor is illustrat-ed in Figure 2. Various electrical and mechani-cal fault conditions present in the motor further modulate motor current signal and contributes to additional sideband harmonics. Faults in motor components produce corresponding anomalies in magnetic field and change the mutual and selfinductance of motor that appear in motor supply current spectrum as sidebands around line (supply, grid) frequency, [22]. Based on fault signatures motor faults can be identified and its severity accessed. Frequency range of interest in MCSA is typically 0-5 kHz, [11]. This, according to a Nyquist theorem, requires sam-ple rate of at least 10000 samples per second. During the test motor should be run at loading greater then 70%. It should be noted that fault signals detected in motor supply current may also be influenced by operation of neighboring motors and system’s environmental noise.

3. FAULTS THAT CAN BE DETECTED WITH MCSAThe major faults of electrical machines can broadly be classified by the following [3,13,23]:

a. Static and/or dynamic air-gap irregularities.b. Broken rotor bar or cracked rotor end-rings.c. Stator faults (opening or shorting of one coil or more of a stator phase winding)d Abnormal connection of the stator windings.

e. Bent shaft (akin to dynamic eccentricity) which can result in a rub between the rotor and stator, causing serious damage to stator core and windings.f. Bearing and gearbox failures

The most common faults are bearing faults, stator faults, rotor faults and eccentricity or any combination of these faults. When analyzed statistically, about 40% of the faults correspond to bearing faults, 30-40% to stator faults, 10% to rotors faults, while remaining 10% belong to a variety of other faults, [11,24]. Frequencies induced by each fault depend on the particu-lar characteristic data of the motor (like syn-chronous speed, slip frequency and pole-pass frequency) as well as operating conditions, [2,18,25]. Main classes of faults that can be detected with MCSA are listed bellow.

3.1. AIR-GAP ECCENTRICITY

Air-gap eccentricity represents a condition when air gap distance between the rotor and the stator is not uniform. Two types of abnormal air-gap eccentricity exist: static and dynamic. In case of static eccentricity the position of minimal radial air gap is fixed, while in case of dynamic eccentricity position of

Figure 2 Current spectrum of induction motor, [20]

Figure 3 Air gap: a) normal (concentric), b) static eccentricity and c) dynamic eccentricity

minimal air gap follows turning of the rotor. Normal (concentric) state, static and dynamic eccentricity are illustrated in Figure 3, [26]. As the rotor bars recede or approach the stator magnetic fields, they cause a change to the cur-rent in the stator. In case of static eccentricity sideband components appear at frequencies determined by (1), [3] and shown in Figure 4, [3-5,8,11,18,25].

where

(1)

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fec is eccenticity frequencyfg is electrical supply (grid) frequencyR is the number of rotor barss = slipp = pole-pairsnd = ±1nws = 1, 3, 5, 7 …

The slip is determined from (2)

starting duty cycles (with fivefold the full load bar currents) and pulsating mechanics loads (like reciprocating machinery). They can cause sparking and overheating in a motor, [4]. By examining the frequency spectrum of the stator currents, early stages of rotor bar failures can be detected, [5,18,25,27-29]. When broken rotor bars are present, current components in stator windings can be detected at frequencies given by (4), [5]:

(2)

where

s is per unit slipNr is rotor speedNs is synchronous speed

Central frequency fc on Figures 4 and 5 is determined by (3):

where R is the number of rotor bars.

Figure 4 Air gap – static eccentricity [11]

When dynamic eccentricity is present, frequency components from static eccentricity are further modulated with the rotational frequency fr, as shown in Figure 5.

Figure 5 Air gap- dynamic eccentricity [11]

3.2. BROKEN ROTOR BARS

Primary causes of broken bars are direct online

(3)

(4)

where

fbrb is broken rotor bar frequencyfg is electrical supply (grid) frequencyp is number of pole pairss is per unit slipk = 1, 2, 3, …

Figure 6 Frequency spectrum from motor with broken rotor bars, [29]

Upper and lower sidebands around supply com-ponent separated by twice the slip frequency are shown in Figure 6. The slip frequency is determined from (5):

(5)

where

fslip is slip frequencyfg is electrical supply (grid) frequencys is per unit slip

As a simple rule, if the difference between the main and sideband components is greater than 50 dB rotor has no faults, when difference is in range between 40 and 50 dB there is probably one bar broken and with difference less than 40 dB there are several broken bars or broken end ring, [23].

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3.3. BEARINGS DAMAGE

Motor bearings faults are more difficult to detect then rotor cage problems, [5,7]. Four types of bearing misalignments exist, as is described in [5]. Such misalignments are common result of defective bearing installation. MCSA can detect bearing faults by detection of frequency com-ponents f0 and f1 that are for most bearings with between six and twelve balls determined by (6) and (7), [5, 25]:

(6)

(7)

where

f0 is lower frequency,f1 is upper frequency,n is the number of balls in the bearingsfrm is the rotor’s mechanical frequency

Frequencies due to bearing damage are illustrated in Figure 7.

Figure 7 Sideband frequency components due to bearing damage

3.4. SHORTED TURNS IN STATOR WINDINGS

Most stator failures are related to stator wind-ings. Shorted turns produce excessive heat in stator coil and current imbalance, [13]. MCSA exploits the fact that rotating flux waves can induce corresponding components in the stator windings, [3,30]. Motor current components that are influenced only by shorted turns can be detected at frequencies shown in Figure 8 and described by (8):

where

fst is the component related to shorted turnfg is electrical supply (grid) frequencyn = 1,2,3,…

(8)

Figure 8 Frequency components corresponding to shorted turns, [3]

3.5. Load Effects

Electrical motors are converters of electrical energy to a mechanical torque. Load torque may vary with rotor position. These variations cause corresponding variations in the motor current. In that case supply current will contain spectral components related to load torque variability, [5,31]. Variability in load torque at multiples of rotational speed mfr produces stator currents at frequencies fload as described in (9):

wherefload frequencies related to load torque variationfs is electrical supply (grid) frequencyfr is rotational frequencyp is number of pole pairss is per unit slipm=1, 2, 3, ...

Example of MCSA applied to monitoring gear vibrations (produced by load fluctuations on the gearbox) is described in [22].3.6. EQUIPMENT WEARWith equipment wear motor current spectrum changes as well. This is applicable to transmis-sion system failures and attached load failures. There is not available general formula for fre-quency components associated with equipment wear. However, since most wear is random, faults appear in current spectrum as change in tilt (noise floor), Figure 9, [4].

(9)

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Figure 9 Change in current spectrum due to equipment wear, [4]

Multiple faults present in induction motor can be detected simultaneously, as described in [31]. Fault detection is not limited only to large mo-tors powered by 50 Hz o 60 Hz current, but also on smaller motors, like one used in airborne application and powered by 400 Hz current, [32].

Brief intro regarding practical application of MCSA for previously mentioned faults and more, bypassing advanced math and complex considerations can be found in [22,33].

4. FAULT DETECTION TECHNIQUESAs already mentioned, motor faults modify the harmonic content of motor supply current. Several methods may be used in preprocessing stage for extracting features of measured motor supply current for the sake of comparison with known motor fault signatures, [21].

4.1. FAST FOURIER TRANSFORM

Motor current readings are recorded in time domain. After the signal conditioning analog-to-digital conversion is performed. Spectar of the motor current is typically analyzed using some of spectral analysis techniques. If signal is represented by x(t) as N discrete samples it can be expressed as a sum of N sinusoidal compo-nents of frequencies ωi, and phase shifts θi, as described in (10) and (11):

(10)

(11)

where ωi, is circular frequency and fs signal sampling rate.

Same signal expressed using sinus and cosinus terms is given in (12):

Values of coefficients can be determined by Discrete Fourier Transform, (13),(14),(15):

(12)

(13)

(14)

(15)

where

is cosinus term, is sinus term amplitude for frequency component i.For analyzing signals in frequency domain the most common technique used is Fast Fourier Transform (FFT), [34]. It is a computational efficient version of Discrete Fourier Trans-form algorithm that greatly reduces the nec-essary number of computations (from O(N2) to O(NlogN)). After applying FFT to stator supply current, amplitudes of resulting fre-quency components are normalized by the value of the amplitude of first harmonic. The normalization process reduces influences of motor’s load conditions, [25]. FFT is suitable for characterization of stationary signals. How-ever it is not suitable for signals with transitory characteristics, [5].

4.2. INSTANTANEOUS POWER FFT

Application of instantaneous power requires additional measurement of supply voltage (it is not considered strict MCSA as it needs additional instantaneous voltage measure-ments). Instantaneous Power p(t) is the product of supply voltage u(t) and the motor current i(t), (16):

iaibiA

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(16)

Amount of information provided by instan-taneous power is greater than available in motor supply current alone (including less noise and well bounded dynamic range of remaining harmonics in the absence of power grid component) providing more reliable analysis, [5,11], as shown in Figure 10, [5].

Figure 10 a) stator current spectrum,b) instantaneous power spectrum, from [5]

a) b)

4.3. DEMODULATED CURRENT SPECTRUM

Carrier frequency (50 Hz in EU, 60 Hz in USA) presents the dominant peak in the FFT spec-trum. Lot of the information is blurred in the noise floor of the current spectrum. Demodulation is the process of removing the carrier frequency from the spectrum. Use of demodulation as a step in MCSA is illustrated in Figure 11. After the carrier frequency is removed, the remaining frequencies related to repetitive load variations appear distinctively in the demodulated current spectrum, [9,20], as shown in Figure 12

Figure 11 Use of demodulation step in MCSA

Figure 12 a) Machine current spectrum and b) demodulated spectrum, [20]

Interesting approach for removing fundamen-tal component in MCSA using synchronous reference frame is described in [35].

4.4. WAVELET ANALYSIS

Disadvantage of a Fourier series expansion is that it provides only frequency resolution but lacks time resolution. Wavelet is a basis func-tion isolated with respect to time or spatial loca-tion and frequency or wavenumber, [36,37]. It enables analysis localized in the time-frequency or the time-scale domain, [5]. Wavelet transform decomposes a signal into a family of wavelets, providing a time-frequency representation of the signal. [38, 39]. Wavelets are irregular in shape and finite in length. They can be success-fully applied to analysis of signals with transitory characteristics and variable spectral content, [38]. The Continuous Wavelet Transform (CWT) for a continuous signal x(t) is defined by follow-ing relation, (17):

(17)

Where g(t) is the mother or basic wavelet,* denotes a complex conjugate, a is the scale factor and τ is a time shift, [37].

The complex-valued Morlet’s wavelet is common choice for signal analysis using the CWT. Morlet’s wavelet, shown in Figure 13, is defined in (18):

Figure 13 Morlet wavelet

(18)

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In real world we are dealing with discrete (sam-pled) signal and Discrete Wavelet Transform (DWT) is used. DWT is any wavelet transform for which the wavelets are discretely sampled. Because of localization property of wavelets, the wavelet transform can represent the signal of interest with few coefficients. One algorithm for application of MCSA during startup tran-sients using wavelets is described in [40].

4.5. PARK’S VECTOR APPROACH

This approach requires current sensing not on one but on all three phases, Figure 14. Park’s current vector can be computed from the symmetrical three-phased current system, having the components: ia, ib and ic giv-ing Park’s vector components id and iq, as described in (19) and (20), [5]:

Figure 14 Block Diagram of MCSA using Park’s vector approach

When no faults are present in the motor previous components may be expressed as follows, (21), (22):

(19)

(20)

(21)

(22)

where iM is the maximal value of the sup-ply phase current and ω is its frequency. Presented in a plane vector components id and iq produce circular pattern. In the presence of various faults supply current contains sideband components and circular pattern will be distort-ed, [24,38,41,42]. Method for damage detection is based on detection of the distortion suffered by circle of Park. The three phases of currents in a healthy motor can be described by simple reference figure shown in Figure 15. Faults in motor contribute to distortion of the reference figure, as shown in Figure 16.

Figure 15 Reference figure – healthy motor

Figure 16 Distorted figure - faulty motor

Instead of detecting distortion in shapes of Park’s vector patterns in Enhanced Park’s Vector Approach (EPVA) magnitudes that Park’s vector takes through time are monitored and analyzed, [11,24], Figure 17. Value of the radius oscillates between its extreme values

twice during each power grid cycle. When analyzed in frequency domain, these oscil-lations appear in the spectrum as frequency component located at twice the motor supply frequency, [11,24]. The amplitude value of this frequency component is related to

Figure 17 Block Diagram of the EPVA technique

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Figure 18 Use of demodulation step in MCSA

the relevance of the fault, [24]. Example of faults present in the stator coils is shown in Figure 18.

5. ARTIFICIAL INTELLIGENCE TECHNIQUES APPLIED TO MCSARecognition of motor current fault signatures requires from user considerable degree of expertise and experience. After fault signa-ture is obtained it can be used for diagnostics, either by experienced engineer/technician or using some of techniques from the field of Artificial Intelligence (AI). Expert systems and various pattern recognition techniques from the field of Artificial Intelligence (AI) can be applied to MCSA.

Automatic diagnosis and analysis of MCSA using expert system as is illustrated in block diagram shown in Figure 19, according to [11].

Figure 19 Automatic diagnosis and analysis system

Expert system may also employ fuzzy logic knowledge and rules, [31], that may be ex-pressed using linguistic variables, fuzzy mem-bership functions and IF-THEN rules, Figure 20. Domain expert knowledge in such a system may be expressed in more natural way.

Figure 20 Fuzzy logic applied to MCSA

When a sufficient number of current signatures that correspond to various motor fault condi-tions are available, statistical methods may be applied for the task of data classification. General overview of a system

Figure 21 MCSA using statistical pattern recognition (drugačija slika)

that uses statistical pattern recognition is illustrated in Figure 21. After the signal conditioning, analog-to-digital conversion is performed. Some of preprocessing techniques are used (FFT, wavelets, etc) are used for feature extraction. Dimensionality reduction follows in the next step. Classification of unknown cur-rent signature is preformed by statistical pattern recognition with recognizers previously trained on a large number of correct and faulty signatures.

Support Vector Machine (SVM) is a machine learning method successfully applied to a wide

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range classification and pattern recogni-tion problems. The most important benefit is efficiency of SVM in high dimensional classifica-tion problems. SVM can be applied to MCSA as well, as described in [43].

Classification can also be performed using decision trees like Classification And Regres-sion Tree (CART). Application and comparison of three different classification methods (CART, Discriminant Analysis and SVM) applied to MCSA is described in [44] and illustrated in Figure 22. System consists of four steps: data acquisition, feature extraction, feature selection and fault classification. During feature extrac-tion statistical parameters are calculated from acquired current signal. Feature selection and dimensionality reduction is performed using Principal Component

Analysis (PCA). Trained classifier can detect most common faults: stator winding interturn short (I), rotor dynamic eccentricity (E) as well as both of these faults (B). Output H corre-sponds to a healthy motor state.

Artificial Neural Networks (ANN) with their learn-ing and generalization are particularly suitable for performing pattern classification. Examples of ANN used as statistical pattern recognizers for MCSA are described in [26,41,44,45]. ANN are trained, mostly using supervised learn-ing, on datasets involving normal and faulty conditions.

Figure 22 Automatic motor current signature classification

Figure 23 Neural net MCSA of induction motor, [26]

Figure 24 Inputs and outputs of the ANN

Solution for detection of air-gap eccentricity using artificial neural network is described in [26], and illustrated in Figures 23 and 24. Two different types of inputs to ANN are used, spec-trum of the motor current organized in a number of frequency beans and motor speed (from the tachometer). Inputs have been properly scaled before feeding the ANN. The ANN has been trained using supervised learning on 120 data-sets (including 20 datasets representing the eccentricity fault condition). There are two outputs available from the ANN, one corresponding to a healthy motor and another for presence of an eccentricity fault.

System for detection of bearing faults in three phase induction motor using MCSA combined with ANN is described in [29]. Magnitudes of side band frequencies are fed to ANN that is later trained in supervised mode on available datasets representing normal and faulty condi-tions under various loads (no-load, half load and full load).

6. SOFTWARE AND EQUPMENT FOR INDUSTRIAL APPLICATIONSBeside conventional use of MCSA with inter-pretation of measured data by skilled engineer/technicians new generation of interesting prod-ucts has emerged. Various automatic diagnosis and analysis systems have been developed.

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Some products specifically developed for easier application of the MCSA are mentioned bellow.

AnomAlert Motor Anomaly Detector is a sys-tem of software and networked hardware that continuously identifies faults on electric motors and their driven equipment, [46]. It’s operation is based on energy determined in 12 spectral frequency ranges. System posses learning ability and alarming function based on sta-tistical analysis. It does not for the most part provide precision diagnostic of particular fault but reports indication of particular categories of faults for closer inspection.

Today various expert systems exist to aid and simplify the diagnosis process. One such system is Electric Motor Performance Analysis & Trending Hardware (EMPATH) developed by Framatome ANP, [47]. System consists of a laptop computer with signal conditioning and acquisition board and analyzing software.

ALL-TEST is a system for troubleshooting equipment using Electrical Signature Analysis. An ALL-TEST Pro kit includes ALLTEST IV PRO 2000 motor circuit analyzer, the ALL-TEST PRO OL motor current signature analyzer, EMCAT motor management software, Power System Manager software, and ATPOL MCSA software, [48].

System for automatic monitoring and diagnosis of faults in induction motors that can be operated remotely (including web interface) and in real-time is described in [25], with block diagram shown in Figure 25. It can trigger alarms whenever a fault is detected including turning off a motor in case of a short-circuit detection.

Figure 25 General view of the system, from [25]

Končar Institute has developed the Fault Detec-tor Smart Sensor (FDSS). It provides on-line analysis, measured data export, detailed off-line measurement data analysis, data storage and wireless data transfer, [49].

7. CONCLUSIONSElectrical machinery is the powerhouse of the modern industry. Failures of induction motors cause production downtime and may gen-erate large losses in terms of maintenance and lost revenue. Timely detection of incipi-ent motor faults is hence of great importance. Developing motor faults have its counterparts in waveform and harmonic content of the motor supply current. MCSA can be applied everywhere in industry where induction motors are used enabling non-intrusive on-line (even remote) analysis of motor supply current and detects faults while motor is still operational and with-out interrupting its service. It can be efficiently applied to detection and the localization for variety of motor faults. As such it is important contribution to tools for condition monitoring of induction motors.

All references listed below can be found on the internet.

8. REFERENCES[1] J. R. Bednarczyk, Induction Motor Theory, PDH Center, 2012[2] E. J. Thornton and J. K. Armintor, The fundamentals of AC electric induction motor design and application, Proceedings of twentieth international pump users symposium, Houston, Texas, March 17-20, 2003[3] W. T. Thomson and R. J. Gilmore: Motor Current Signature Analysis to Detect Faults in Induction Motor Drives – Fundamentals, Data Interpretation, and Industrial Case Histories, Proceeding of the Thirty-Second Turbomachin-ery Symposium, Houston, Texas, Sept. 2003[4] W. T. Thomson, On-Line Motor Current Signature Analysis Prevents Premature Failure of large Induction Motor Drives, |ME - Mainte-nance & Asset Management, Vol. 24, No. 3, May/June 2009, pp. 30-35[5] M. El H. Benbouzid, A Review of Induction Motors Signature Analysis as a Medium for Faults Detection, IEEE Transac-tions on Industrial Electronics, Vol. 47, No. 5, Oct. 2000

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[6] N Mehala and R. Dahiya, Motor Current Signature Analysis and its Applications in Induction Motor Fault Diagnosis, International Journal of Systems Applications, Engineering & Development Volume 2, Issue 1, 2007, pp. 20-35[7] A Singhal and M A. Khandekar: Bear-ing Fault Detection in Induction Motor Using Motor Current Signature Analysis, International Journal of Advanced Research in Electrical, Electronics and Instrumentation Engineering Vol. 2, Issue 7, July 2013, pp. 3258-3264[8] K. V. Kumar, S. S. Kumar and A. I. Selva-kumar: A Review of Voltage and Current Signa-ture Diagnosis in Industrial Drives, International Journal of Power Electronics and Drive System (IJPEDS) Vol. 1, No. 1, Sept. 2011, pp. 75-82[9] P. Pillay and Z. Xu: Motor Current Signature Analysis, Thirty-First IAS Annual Meeting, Industry Applications Conference, ‘96, San Diego, California, 1996[10] A. Gheitasi, Motors fault recognition using distributed current signature analysis, PhD Thesis, School of Engineering, Auckland University of Technology, 2012[11] E. L. Bonaldi, L. E. de Lacerda de Oliveira, J. G. B. da Silva, G. Lambert-Torresm and L. E. Borges da Silva, Predictive Maintenance by Electrical Signature Analysis to Induction Motors, Induction Motors – Modeling and Control, Chapter 20[12] A. Gheitasi, Motors Fault Recogni-tion Using Distributed Current Signature Analysis, PhD Thesis, Auckland University of Technology,School of Engineering, 2013[13] A. Korde: On-Line Condition Monitoring of Motors Using Electrical Signature Analyisis, Recent Advances in Condition Based Plant Maintenance, 17-18 May 2002, Mumbay[14] H. W. Penrose, The Multy-Technology Approach to Motor Diagnostics, 2004, ALL-TEST Pro[15] H. W. Penrose, The Multi-Technology Approach to Motor Diagnostics, ALL-TEST Pro[16] D. Miljković, Review Of Machine Con-dition Monitoring Based On Vibration Data, Proceedings MIPRO 2008 - Vol. III, CTS & CIS, Opatija, Croatia, 2008[17] D. V. Ferree and N. Burstein, Electrical Signature Analysis, UltraCheck Diagnostics Group

[18] H. W. Penrose: Applications for Motor Current Signature Analysis, 2004 ALL-TEST Pro[19] H. W. Penrose, Motor Circuit Analysis Concept and Principle, ALL-TEST Pro, 2004[20] D. Fossum, Identifying Mechanical Faultes with Motor Current Signature Analy-sis, http://www.reliableplant.com/Read/28633/ motor-current-signature-analysis[21] N. Mehla and R. Dahiya: An Approach of Condition Monitoring of Induction Motor Using MCSA, International Journal of Systems Appli-cations, Engineering & Development Vol. 1, No. 1, 2007, pp. 13-17[22] C. Kar and A. R. Mohanty, Monitoring gear vibrations through motor current signature analysis and wavelet transform, Mechanical Systems and Signal Processing, Vol. 20, Issue 1, January 2006, pp. 158–187[23] D. Shreve, Motor Current Signature Analysis Theory and Practice, GE Bently, Commtest, ppt, 6th Annual Meeting, 2013[24] C. J. Verucchi, G. G. Acosta and F. A. Benger, A review on fault diagnosis of induction machines, Lat. Am. appl. res. Vol. 38, No. 2., Bahía Blanca abr. 2008[25] J. I. Terra, M. Castelli, J. P. Fossati, M. Andrade, Analía Conde and M. Martínez- Iturralde, Faults Detection and Remote Moni-toring System for Induction Motors using MCSA Technique EPIM 2010, 26-27 Nov 2010, Urugvay[26] Q. S. Al-Sabbagh and H. E. Alwan, Detection of Static Air-Gap Eccentricity in Three Phase Induction Motor by Using Artificial Neural Network (Ann), Journal of Engineering, No. 4 Vol. 15, December 2009, pp. 4176-4192[27] C. Harlişca, R.P. Hangiu, L. Szabó and H. Silaghi, Broken Rotor Bars Detection in Squirrel-Cage Induction Machines by Motor Current Signature Analysis Method Scientific Bulletin of the Electrical Engineering Faculty – Year 11 No. 3 (17)[28] M. S. Welsh, Detection of Broken Rotor Bars in Induction Motors Using Stator Current Measurements, MSc Thesis, MIT, Columbia, May 1988[29] H. Jivayee and I. Culbert, Detecting Broken Rotor Bars Prevents Catastrophic Damage, Maintenance Technology, November 2004

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[30] K. V. Kumar and S. S. Kumar, Lab-VIEW based Condition Monitoring of Induction Machines, I.J. Intelligent Systems and Applica-tions, Vol. 4, No. 3, April 2012, pp. 56-62[31] M. Zeraoulia. A. Mamoune, H. Mangel and M. E. H. Benbouzid, A Simple Fuzzy Logic Approach for Induction Motors Stator Condition Monitoring, J. Electrical Systems Vol. 1, Issue 1, March 2005, pp. 15-25[32] S. Haus, H. Mikat and M. Nowara, S. T. Kandukuri, U. Klingauf, and M. Buderath: Fault Detection based on MCSA for a 400Hz Asynchronous Motor for Airborne Applications, International Journal of Prognostics and Health Management, 2013[33] H. W. Penrose, Practical Motor Current Signature Analysis: Analysis: Taking the Mystery Out of MCSA Taking the Mystery Out of MCSA, ALL-TEST Pro[34] K. S. Gaeid, H. W. Ping, M. Khalid and A. L. Salih, Fault Diagnosis of Induction Motor Using MCSA and FFT, Electrical and Electronic Engineering, Vol.1, No. 2, 2011, pp. 85-92[35] E. R. Bonaldi, L. E. de L. de Oliveira, L. E. B. da Silva and G. L. Torres, Removing the Fundamental Component in MCSA Using the Synchronous Reference Frame Approach, IEEE International Symposium on Industrial Electronics, Vol. 2, pp. 913- 918, 9-11 June 2003, Rio de Janeiro, Brazil[36] E. Arobone, Introduction to wavelets, lecture notes [ppt], University of San Diego, 2009 [37] N. V. Thakor, B. Gramatikov and D. Sherman, “Wavelet (Time-Scale) Analysis in Biomedical Signal Processing”, The Biomedical Engineering Handbook: Second Edition., Ed. Joseph D. Bronzino, Boca Raton: CRC Press LLC, 2000[38] N. Mehala, Current Signature Analysis for Condition Monitoring of Motors, Int. Journal of Electronics and Computer Science Engineering, Vol. 1, No. 3, 2013[39] C. Torrence and G. P. Compo, A Practical Guide to Wavelet Analysis, Bulletin of the American Meteorological Society, Vol. 79, No. 1, January 1998

[40] H. Douglas, P. Pillay and A. K. Ziarani, A New Algorithm for Transient MCSA Using Wavelets, IEEE Transactions on Industry Applications, Vol. 40, No. 5, September/ October 2004[41] T. G. Amaral, V. F. Pires, J. F. Martins, A. J. Pires and M. M. Crisóstomo, Image Processing based Classifier for Detection and Diagnosis of In-duction Motor Stator Fault, in “Image Processing”, book edited by Yung-Sheng Chen, December 1, 2009[42] S. M. Shashidhara and P. S. Raju, Stator Winding Fault Diagnosis of Three-Phase Induction Motor by Park’s Vector Approach, International Journal of Advanced Research in Electrical, Electronics and Instrumentation Engineering, Vol. 2, Issue 7, July 2013[43] S. Pöyhönen, Support Vector Machine Based Classification in Condition Monitor-ing of Induction Motors, PhD Thesis, Helsinki University of Technology, June 2004[44] V. N. Ghate and S. V. Dudul, Artificial Neural Network Based Fault Classifier For Three Phase Induction Motor, International Journal of Computational Intelligence Research, Vol. 5, No. 1, 2009, pp. 25–36[45] Khazaee M., Ahmadi H., Omid M., Banakar A. and Moosavian A.: Feature- level fusion based on wavelet transform and artificial neural network for fault diagnosis of planetary gearbox using acoustic and vibration signals, Insight, Vol. 55, Issue 6, June 2013, pp. 323-330[46] C. T. Hatch: AnomAlert: Under the Hood, Orbit, Vol. 32, No. 2, Apr. 2012[47] EMPATH, Areva, http://www.us. areva-np.com/ultracheck/EMPATH.htm[48] H. W. Penrose, Applications for Motor Current Signature Analysis, ALL-TEST P[49] Fault Detection Smart Sensor, Končar Institute, http://www.koncar-institut.hr/docs/ koncarinstHR/documents/205/Original.pdf

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INGOPPORTUNITIES FOR THE REDUCTION OF

SUBSTANCES AND EQUIPMENT IMPACT ON PERSONNEL IN PENETRANT AND MAGNETIC

PARTICLES TESTINGYuriy, Yaremenko, MR CHEMIE GmbH, Unna, GERMANY, Yaremenko@MR-Chemie.de

ABSTRACT - Penetrant testing (PT) and magnetic particles inspection (MPI) are widespread meth-ods of non-destructive testing which are not required a lot of investments for manual application and are simple in terms of discontinuous interpretation. On the other hand, work with chemicals requires special precautions, safety instructions and disposal limitations. Growing demand among customers to decrease impact of consumables and equipment on personnel and environment, shift producers’ priorities to develop new, safer solutions. This work offers to consider some results of MR Chemie company in development of free of dangerous components consumables for PT and MPI and to look closer at aspects of ultraviolet irradiation, as part of fluorescent PT and MPI methods, which affect on personnel safety.

Keywords: penetrnant and magnetic inspection, safety,precosions, ultraviolet irradiation, protection of human health and the environment, ultraviolet hazard aspects, UV equipment

1.1. TEST MEDIA PERFORMANCE AND HAZARD CONSEQUENCES

When we consider parameters which influence the probability of discontinues detection by Penetrant testing (PT) and Magnetic particles inspection (MPI), besides process variables and conditional variables, professionals stress the importance of test media properties. Chemi-cal composition of the test media brings on the top of tests’ performance such qualitative parameters as wetting ability, which is responsi-ble for parts coverage by test media in PT and MPI; viscosity, which links to magnetic particles mobility during magnetization in MPI; washing ability – parameter affecting on background during interpretation in PT, etc.From the beginning of PT and MPI methods invention, consumers and producers of test media were focused on achieving highest qualitative parameters of the test media. In that times kerosene, naphtha and AZO dye pigments were widely used in test media production, as they were the simplest and easiest way to maximize test media’s performance. On the other hand, these substances were (and are) distinct risk factors, initiating such serious dis-eases like skin cancer, genetic damage and other fatal impacts, as well as they were subject of disposal limitations.

1.2. REACH REGULATION

In order to ensure a high level of protection of human health and the environment from the risks that can be posed by chemicals, so called REACh regulation by European Chemical Agen-cy (ECHA) was found. Since 2007, the regula-tion has been regularly updated, bringing more restrictions for the chemicals circulation and better transparency in dangerous substances identification for the end user. Upcoming version of REACh, which is awaited for release at the end of 2015, is bringing more changes (below are listed some of these changes):• Candidates list of carcinogen, mutagenic

and toxic substances continues to expand and draw up 161 substances (on Dec 2014)

• Threshold concentrations, when substance counted as hazard, are being decreased for a lot of products

• Health and other hazard phrases are being rephrased with greater emphasis on the danger impact

• Hazard pictograms graphical conversion to GHS (Globally Harmonized System of Classification and Labeling of Chemicals)

As result, much more substances should be declared by producers as dangerous and labeled accordingly.

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APPLICATION CHANGES

MR Chemie company were eager to meet this challenge and alongside with our standard products (which do not have AZO-dye pigments, and most of them counted as bio-degradable) to develop line of consumables which are recognized as free of dangerous components according to the upcoming new version of REACh regulation. These products are labeled as ECO LINE and have additionally such properties as:• Not hazard (even not irritant)• Not flammable • Do not contain volatile organic compounds

(VOC)• Have optimal removability and wetting

ability• Have no foaming effect and have high

particles mobility• Have increased fluorescence brightnessIt is worth mentioning, that development of such properties ought to change recipes substantially, which result in several changes in application of the test media. Products, which are in aerosol cans supplied, have narrower and not homoge-neous spraying pattern; for application of aque-ous developer and white contrast paint pneu-matic spray guns are necessary, also increased application and dryness time should be taken into account; Pre-cleaning procedures before water-based test media application should be handled thoroughly. Nevertheless, more and more customers adapt these changes in favor of safer operation.

2.1. ULTRAVIOULET IRRADIATION AS PART OF INTERPRETATION PROCESS

Ultraviolet (UV) irradiation is a part of interpre-tation process in fluorescent sub-methods of PT and MPI. Therefore exposure to UV and its hazard consequences should be considered by Health and Safety Executives inherently with test media hazards.UV filtered spectacles, masks and cloth-ing which covers exposed parts of the body are essential part of protective measures for operators. Alongside with the operator, the risk of exposure for surrounding personnel is always existent. Therefore, comprehensive approach to protective measures is needed, and UV basics, UV harmful impact and types of artificial sources should be studied more thoroughly.

UV light is electromagnetic radiation with a wavelength shorter than visible light, but longer than X-rays. Whole UV spectrum lies in the range of 100 – 400 nm and typically cannot be seen by human eye. Basically, UV is classi-fied in 3 wavelength bands. Short wavelength UV-C [100…280nm], middle wavelength UV-B [280…315nm] and long – UV-A [315…400nm]. In non-destructive testing, there is UV-A spectrum permissible with a peak at 365 ± 5 nm. According to EN ISO 3059, particular requirements to the UV spectrum profile are prescribed as well. Such strict approach to ap-proved UV wavelength is caused by the fact that different UV wavelength bands have differ-ent influence on human. Let us look at these main differences.

2.2. ULTRAVIOULET HAZARD ASPECTS

Parts of human body affected by UV are eyes and skin. The lens of the eyeball is more sensitive to UV-A and part of UV-B bands. Starting from 300 nm this and higher wavelength of the UV are absorbed by lens and cause pro-tein changes. On the other hand, the layer of the skin called epidermis is more sensitive to UV-B irradiation, whereas UV-A is passing by to deeper layer, i.e. the dermis. UV-B spectrum plays a key role in DNA changes in epidermis cells, and both UV-B and UV-A contribute to skin aging (photoaging). It is worth mentioning that alongside with UV spectrum, there is another harmful light band belonging to visual spectrum, namely violet light [400 … 490 nm]. This light band affects the back wall of the eyeball and its element called macula. Typical diagnoses caused by each band of wavelength are: conjunctivitis and cataract for the eyes affected by UV-A and UV-B; Macula degeneration for the eyes affected by violet light emission; erytherma, elastosis (photoaging) and skin cancer for the skin – mainly by UV-B.After the overview of causes leading to the most harmful consequences to the human health, it is important to consider the relationship between the wavelengths of the light emitted and power of its effects. 2.3. WAVELENGTH AND THE POWER OF EXPOSURE CORRELATION

European Directive 2006/25/EC set require-ments regarding personnel protection exposed by the artificial optical radiation to the eyes and to the skin.

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INGUV exposure limits values for 8 hours shift

draw up: 30 J/m2 for the general UV spectrum (180-400 nm) and 104 J/m2 for UV-A band only.These values shows that biophysical impact of the UV-B and UV-C spectrum dose is

seen as a lot more harmful than UV-A. Graphical interpretation, as shown in Figure 1, describes detailed relationship between biophysical impact of different UV bands, using Action spectrum Index, S(λ)

Figure 1 Biophysical impact of UV irradiation as a function of wavelength. Graphical interpretation of the data obtained from 2006/25/EC Directive

When we impose on this graphic Xenon, Mercury or other type of conventional UV source (Figure 2) and compare the overlay with the spectrum of UV Light Emitted Diodes (LEDs) (Figure 3), it clearly shows that conventional UV sources have much more

intensive effects on operator than UV based on LED source. Taking into account logarith-mic scale of action spectrum index S(λ), the harmful influence becomes sizable even at UV spectrum with low intensity.

Figure 2 Selective example of Xenon UV Lamp spectrum with built-in UV filter

Figure 3 MR 97 UV LED Lamp spectrum

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ING Moreover, in course of time, UV filter age

and the borders of intercepted spectrum expand, and unwished UV wavelengths (which emitted unfiltered conventional UV source) are amplified. On the other hand, LEDs produce narrower UVA spectrum and do not irradiate UVB spectrum at all, no matter whether these

irradiations are filtered additionally or not. Besides UV spectrum, Health and Safety executives need to pay attention to violet light band, whose harmful spectrum sometimes underestimated. Figure 4 shows difference in action of Violet light spectrum in association with Macula degeneration diagnosis.

Figure 4 Photochemical impact of Violet light spectrum. Graphical interpretation of the data obtained from 2006/25/EC Directive

Alongside with the conventional UV sources, UV Lamps with any kind of UV source, which produce spectrum of visible light in wavelength 400 – 490 nm should be avoided. Furthermore, violet background is typically registered on in-spected surface, during its exposure under per-missible 365 nm UV. The higher the concentra-tion of UV beam, the more intense the violet light emissions back to the operator. 3. SUMMARYThus, there are a list of preventive measures, which have to be taken into account for the impact reduction of consumables and UV equipment when perform PT or MPI.For consumables:• Pay attention to symbols and hazard

phrases labeled on product AND mentioned in Safety Data Sheets (SDS)

• Avoid products with carcinogenic, mutagenic, toxic and other serious harmful effects

• Consider products free of hazard symbols For UV equipment:• Use protective equipment against UV

irradiation • Avoid UV sources with any portion of UVB

spectrum • For conventional UV sources, as mercury,

xenon, etc., replace UV filter regularly • Avoid any UV sources with violet light

irradiation [400…490 nm] • Consider UV sources based on LED

technology • Avoid UV sources with high intensity and

concentrated UV beams

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REACTOR PRESSURE VESSEL FLANGE SEALING SURFACES PROFILOMETRY

SYSTEMBerislav, Nadinić, HRID Ltd., Zagreb, CROATIA, berislav.nadinic@hrid-ndt.hr

Marko, Rušev, HRID Ltd., Zagreb, CROATIA, marko.rusev@hrid-ndt.hr

ABSTRACT - VVER 1000/1200 Reactor Pressure Vessel (RPV) and Reactor Pressure Vessel Head (RPVH) sealing surfaces inspection is one of the crucial RVP inspections which assures safety of the operation. HRID has developed camera - laser based system for the determination of the profile of the sealing surface. Results of such profilometry can induce corrective actions which will ensure better fitting of the reactor pressure vessel and reactor pressure vessel head providing leakage free operation.

Keywords: reactor pressure vessel, VVER 1000, sealing surface, profilometry, laser, camera, eddy current

1. INTRODUCTIONTo assure excellent interface between reactor pressure vessel sealing surface and reactor pressure vessel head sealing surface the profilometry of both sealing surfaces is a must. Such inspection assures trouble free operation of reactor vessels. This article describes the state of the art design of the HRID reactor flange sealing surfaces profilometry system. The name of this HRID system in further text is HPROF (HRID PROFilometry).

2. HPROF INSPECTION SYSTEM Inspection system for reactor pressure vessel (RPV) sealing surfaces uses three different independent systems with the aim to collect independent information about status of sealing surfaces. Those systems are the following:1. Laser inspection system which is use to

establish profilometry of the sealing surfaces.

2. Video inspection system which is used for identification of status of the surfaces (dirt, corrosion products, cracks, dents, etc.)

3. Eddy current inspection system which has purpose to justify results of video and laser findings but also identify small cracks under

1. corrosion products, or of such sizes which cannot be detected by video or/and laser techniques.

Use of three independent systems is great advantage of HRID HPROF solution and assures all relevant information regarding status of VVER 1000 reactor sealing surfaces.

The general concept of inspection system is given in Figure 1.

3. TECHNICAL DESCRIPTION of HPROF SYSTEMThe design of the system for the inspection of the control tubes provides the following characteristics:

• failure-free operation;• long lasting durability;• easy serviceability; • easy maintenance.

The system is designed with all precautions in regard to safe operation, user friendly utilization and environment.

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4. EXAMINATION APPROACH

The examination techniques that are used for pre-service and in-service inspections are evaluated against inspection goals defined by applicable codes/standards. The goals are defined as follows:• To examine all defined examination areas/

volumes by optimized scanning sequence and to the maximal possible extent;

• To provide simple operation of the inspection equipment;

• To minimize the inspection time with no effect to data quality

• To apply the state of the art equipment and/or components which are proven in the VVER inspections;

• To minimize exposure rates to the personnel involved in examinations and equipment manipulation;

• To define the examination system which will fulfill all predefined requirements;

• To provide all technical evaluations for detection of minimal defect size defined in applicable codes.

In addition to previous basic requirements,

Figure 1 HRID HPROF inspection system

HRID defined its additional goal which needs to provide more reliable and high efficiency examinations. These additional goals include application of the system with capability of permanent data storage. Stored data can be analyzed at any time after inspection is performed.

5. MANIPULATORS DESIGNFor scanning sealing surfaces on reactor pressure vessel one type of manipulator is used and for scanning sealing surfaces of reactor pressure vessel head the other type of manipu-lator is used. Both manipulators use wheels for its fixing on object of inspection but their design is different because of location of sealing surfaces.

In Figure 2 all details of manipulator for reactor pressure vessel sealing surfaces is given with related details. In Figure 3 is given picture of reactor pressure vessel (RPV) sealing surface scanner. In Figure 4 all details of manipula-tor for reactor pressure vessel head (RPVH)) sealing surfaces is given with all related details. In Figure 5 is given picture of RPVH scanner

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Figure 2 Manipulator for reactor pressure vessel sealing surfaces

Figure 3 RPV flange scanner for sealing surfaces

Figure 4 Manipulator for RPVH sealing surfaces

Figure 5 RPVH flange scanner

6. LASER PROFILOMETRY EQUIPMENT DESIGNLaser profilometry measuring techniques give unparallel precision of measurement shapes, surfaces etc. For purposes of RPV and RPVH sealing surfaces profilometry Laser measurement system was chosen. This system assures accu-racy of measurement on the level of 0,016 mm.

Table 1 Technical characteristic of the Laser 3D profilometry

The technical characteristic of the Laser 3D profilometry measuring system are shown in Table 1.

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Other specifications are shown in Table 2.

Table 2 Other specifications

In Figure 6 is given picture of Laser profilom-etry system – Sensor Head. In Figure 7 is given example of software presentation of sealing groove profile.

Figure 6 Picture of Laser Profilometry system - Sensor Head

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Figure 7 Selling groove profile determined by laser and software measurements

Characteristics of Laser 3D software for data acquisition and data analysis:

1. 3D machine vision software used with Laser sensor head delivers accurate, real-time 3D position information to improve vision per-formance.

2. 3D software delivers accurate, real-time, three-dimensional information about irregu-larities on RPV sealing surface. Related to any kind of irregularities the software can submit information about size of irregularity (LxWxH in mm), its volume in mm3, and any cross section profile of the irregularity.

3. 3D software tolerate non-uniform lighting4. Application performance is enhanced by

high-precision calibration algorithms that adjust for optical distortion and laser position, and synchro-nize cameras with moving elements.

7. VIDEO SYSTEM DESIGNVideo system consists of one SCAUT camera si shown in Figure 8 with characteristics given in Table 3.

Resolution horizontal/vertical

2592 pixels x 1944 pixels

Resolution 5 MPPixel Size horizontal/vertical 2.20 µm x 2.20 µm

Frame Rate 14.0 fpsMono/Color Color

Table 3 Characteristics of SCAUT camera

Figure 8 Video camera

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SCAUT cameras are running by HRID HDVIEW software which allows running camera, recording of data (.wmv, or .mov formats), measuring defects etc. only by computer.

8. EDDY CURRENT INSPECTION SYSTEMEddy current inspection system consists of eddy current instrument OMNI 200R with AM 203 module and HRID matrix eddy current probe (custom design for RPV sealing surfaces).

Picture of OMNI 200R eddy current instrument is given in Figure 9.

Custom matrix eddy current probe is made from 16 plus point coils with radius of 6 mm, which are examining with one pass the complete sealing surface. For groove inspection two pancake coils are used because for grooves pancake probes demonstrated greater sensitivity. The picture of this probe is given in Figure 10.

9. CONCLUSIONS Developed inspection system gave excellent multi method inspection possibilities which obtain all necessary information about defects as well gradual changes of sealing surface. Use of this system raise the safety level of nuclear power plant operation and practically exclude any possibility of leakage between RPV and RPVH.

Figure 9 OMNI 200R eddy current instrument

Figure 10 HRID matrix eddy current probe for inspection of sealing surfaces

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TEČAJEVI za KVALIFIKACIJU i CERTIFIKACIJU

CENTAR ZA OBRAZOVANJE CENTAR ZA CERTIFIKACIJU

TEČAJEVI ISPITI

Radiografska kontrola RT 2 6. - 16. 7. 2015. 17. 7. 2015.

Penetrantska kontrola PT 1 20. - 22. 7. 2015. 23. 7. 2015.

Vizualna kontrola VT 1 7. - 8. 9. 2015. 9. 9. 2015.Magnetska

kontrola MT 2 21. - 23. 9. 2015. 24. 9. 2015.

Penetrantska kontrola PT 1 5. - 6. 10. 2015. 7. 10. 2015.

Penetrantska kontrola PT 2 12. - 14. 10. 2015. 15. 10. 2015.

Ultrazvučna kontrola UT 1 26.10. - 5.11.2015. 6. 11. 2015.

Vizualna kontrola VT 2 10. - 12. 11. 2015. 13. 11. 2015.

Radiografska kontrola RT 2 23.11.-3.12.2015. 4. 12. 2015.

Ultrazvučna kontrola UT 2 7. - 17. 12. 2015. 18. 12. 2015.

Opći dio 3. stupanj 21. - 25. 9. 2015. 21. - 25. 9. 2015.

Glavna MetodaVT3, PT3, MT3, UT3,

RT321. - 25. 9. 2015. 21. - 25. 9. 2015.

Hrvatsko društvo za kontrolu bez razaranja uspješno je okončalo prelazak na novo izdanje norme HRN EN ISO/IEC 17024:2013 Ocjenjivanje sukladnosti – Opći zahtjevi za tijela koja provode certifikaciju osoblja.

HDKBR je, kroz djelovanje Centra za certifikaciju, tijelo akreditirano za provedbu postupaka certifikacije osoba za nerazorna ispitivanja. Slijedom zahtjevnih aktivnosti prilagodbe ustrojstva i poslovanja zahtjevima novog izdanja akreditacijske norme HRN EN IS/IEC 17024:2013, Hrvatska akreditacijska agencija provela je ocjenu osposobljenosti HDKBR-a. Ocjena HAA rezultirala je izda-vanjem Potvrde o akreditaciji broj 5060 koja ima valjanost do 15. rujna 2019. godine.

HDKBR je jedino hrvatsko tijelo za certifikaciju osoba za nerazorna ispitivanja koja akreditirani status neprekidno održava od mjeseca rujna 2004. godine.

38

HD

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Više o certifikaciji na www.hdkbr.hr ili telefonski u tajništvu HDKBR-a.

39

POPIS NORMIU nastavku prilažemo kratki podsjetnik na norme koje su u 2015. godini prošle reviziju ili su na neki drugi način uvrštene prihvaćanjem u bazu podataka HZN-a.

U skladu s pravilima međunarodnih i europskih organizacija za normizaciju HZN može međunarodnu/europsku normu prihvatiti na dva načina: a) prihvaćanjem međunarodne/europske norme u izvorniku (oznaka: pr) b) prihvaćanjem norme uz prevođenje na hrvatski jezik (oznaka: pp)

Nacrt hrvatske norme (nHRN) daje se na javnu raspravu i davanje primjedaba u roku od dva mjeseca. Ako pristignu primjedbe tehničke prirode, tekst se vraća HZN/TO-u koji ga je izradio na daljnje razmatranje. Faza razvoja 40.20 oznaka je dokumenta kada se pokreće javna rasprava. Oznaka nkHRN je za one norme koje su konačni nacrt hrvatski norme za razliku od nrHRN kada je norma u fazi radnog nacrta. (više vidi: www.hzn.hr)

GLASANJE ENQUIRY BALLOTS (Javna rasprava) 2015. GODINA

ISO CEN Rok za glasanje Trenutni status u HZN-u

prEN ISO 5577 2015-08-07nHRN EN ISO 5577

faza 40.20

ISO CEN Rok za glasanje Trenutni status u HZN-u

FprEN ISO 16946već bio prEN ISO 16946,

prijedlog br. 281/20122015-01-06

HRN EN ISO 16946:2015

Objava: 3/2015

FprEN ISO 18563-1već bio prEN ISO 18563-1,

prijedlog br. 330/20132015-01-20

nkHRN EN ISO 18563-150.20

FprEN ISO 18490već bio prEN ISO 18490,

prijedlog br. 330/20132015-01-20 HRN EN ISO 18490:2015 Objava:

3/2015

FprEN ISO 9934-1već bio prEN ISO 9934-1,

prijedlog br. 330/20132015-06-09

nkHRN EN ISO 9934-1

ZA POVLAČENJE:HRN EN ISO 9934-1:2003

HRN EN ISO 9934-1:2003/A1:2007

FprEN ISO 9934-2već bio prEN ISO 9934-2,

prijedlog br. 330/20132015-06-09

nkHRN EN ISO 9934-2

ZA POVLAČENJE:HRN EN ISO 9934-2:2003

FprEN ISO 9934-3već bio prEN ISO 9934-3,

prijedlog br. 330/20132015-06-09

nkHRN EN ISO 9934-3

ZA POVLAČENJE:HRN EN ISO 9934-3:2004

FprEN 13018

Nacrt prvi put2015-11-25

Postojeća norma i amandman:ZA POVLAČENJE:HRN EN 13018:2001

HRN EN 13018/A1:2007

GLASANJE FORMAL VOTE (Službeno glasanje) 2015. GODINA

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DODATAK:

prEN ISO 5577Nerazorno ispitivanje -- Ultrazvučno ispitivanje -- Terminološki rječnik (ISO/DIS 5577:2015; prEN ISO 5577)Non-destructive testing -- Ultrasonic testing -- Vocabulary (ISO/DIS 5577:2015; prEN ISO 5577)

HRN EN ISO 16946:2015Nerazorno ispitivanje -- Ultrazvučno ispitivanje -- Specifikacija za stepeničasti radni etalon (ISO 16946:2015; EN ISO 16946:2015)Non-destructive testing -- Ultrasonic testing -- Specification for step wedge calibration block (ISO 16946:2015; EN ISO 16946:2015)

nkHRN EN ISO 18563-1Nerazorno ispitivanje -- Karakterizacija i provjera ultrazvučne opreme s faznim sondama -- 1. dio: Instrumenti (ISO/FDIS 18563-1:2014; FprEN ISO 18563-1)Non-destructive testing -- Characterization and verification of ultrasonic phased array equipment -- Part 1: Instruments (ISO/FDIS 18563-1:2014; FprEN ISO 18563-1)

HRN EN ISO 18490:2015Nerazorno ispitivanje -- Provjera vida osoblja koje provodi NDT (ISO 18490:2015; EN ISO 18490:2015)Non-destructive testing -- Evaluation of vision acuity of NDT personnel (ISO 18490:2015; EN ISO 18490:2015)

nkHRN EN ISO 9934-1Nerazorno ispitivanje -- Ispitivanje magnetnim česticama -- 1. dio: Opća načela (ISO/FDIS 9934-1:2015; FprEN ISO 9934-1)Non-destructive testing -- Magnetic particle testing -- Part 1: General principles (ISO/FDIS 9934-1:2015; FprEN ISO 9934-1)

nkHRN EN ISO 9934-2Nerazorno ispitivanje -- Ispitivanje magnetnim česticama -- 2. dio: Ispitna sredstva (ISO/FDIS 9934-2:2015; FprEN ISO 9934-2)Non-destructive testing -- Magnetic particle testing -- Part 2: Detection media (ISO/FDIS 9934-2:2015; FprEN ISO 9934-2)

nkHRN EN ISO 9934-3Nerazorno ispitivanje -- Ispitivanje magnetnim česticama -- 3. dio: Oprema (ISO/FDIS 9934-3:2015; FprEN ISO 9934-3)Non-destructive testing -- Magnetic particle testing -- Part 3: Equipment (ISO/FDIS 9934-3:2015; FprEN ISO 9934-3)

HRN EN 13018:2001Nerazorno ispitivanje -- Vizualno ispitivanje -- Opća načela (EN 13018:2001)Non-destructive testing -- Visual testing -- General principles (EN 13018:2001)

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