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    STUDY ON THE CHARACTERISTICS OF THE LEAKAGE ACOUSTIC

    EMISSION IN CAST IRON PIPE BY EXPERIMENT

    Zhang Jian-li

    School of Municipal and Environmental Engineering

    Harbin Institute of Technology, HITHarbin, China

    [email protected]

    Guo Wei-xing

    Sinoma International Engineering (Tianjin) Co., LtdChina National Non-metallic Materials Corporation,

    sinomaTianjin, China

    [email protected]

    AbstractThe correlator based on acoustic signals is widely

    used in leak detection and location in water distribution pipe.

    The accuracy of the localization results depend heavily on the

    signal-to-noise ratio (SNR) of the acoustic signals that used for

    calculation. But at present, the study on characteristics of leak

    acoustic emission in the cast iron pipe is insufficient. So in thispaper, taken the cast iron pipe as the research object, several

    cases of acoustic emission phenomenon in the leaking pipe

    were studied by experiment in the municipal pipeline test

    bench. They are the different characteristic of the signals from

    the pipe with leakage and no-leakage, the different acoustic

    emission characteristics of the leakage in cast iron pipe under

    different hydraulic conditions, and some of the external

    interference to the acquisition of signals, etc. The experiment

    results show that the acoustic emission phenomenon

    age in the pipe is very complex and the components of the

    frequencies in the leak noises are very rich. The

    autocorrelation of leak signals is poor; however the

    autocorrelation of the ambient noises is very strong. And the

    impact of different hydraulic conditions on amplitude is

    evident but the distribution of the spectrum is not obvious.

    Keywords- acoustic emission; joint time-frequency analysis;

    leak detection; autocorrelation

    I. INTRODUCTION

    With the progress of chinas urbanization, the scale of thenetwork of water distribution pipes is becoming bigger andbigger. But with the years increasing, the crack and leakageof the pipelines that provide water for industrial productionand people life continuously under high pressure happensoccasionally. So some pipeline leak detection methods ariseone after another. A leak from a water supply pipe generatesnoise, which can be used for leak detection and location.

    Acoustic leak detection techniques have been shown to beeffective [1- 3] and are in common use in the water industry.Other methods of leak detection which have been used withvarying degrees of success are tracer gas [4], thermography[5], flow and pressure modeling [6], ground penetrating radar(GPR) [7]. Although no-acoustic technologies show somepromise, they are more complex and time-consuming [8, 9],and may fail to detect leaks in practical situations. In leakdetection surveys using acoustic signals, the most widelyused technique for locating leaks is the correlation technique.This is used to estimate the time delay between two

    measured acoustic/vibration signals, is central to this process.Important factors in the detect ability of the leak are thesignal-to-noise ratio (SNR) and the amount of a prioriknowledge [10]. But it is found that the introduction forspectrum and attenuation characteristics of the leakage

    acoustic signal of cast iron pipe is not much presented in theliterature. So it is necessary to detect the leakage acousticemission characteristics of the cast iron pipe in detail forrecognition of the leak, and provide the basis for thedeveloping of leak detection device.

    II. TEST BENCH

    The experiments that study on the acoustic emissioncharacteristics of leak in cast iron pipe were carried out onthe bench shown in fig.1. Where 1 is a pressure tank withvolume of 2m3, mainly for maintaining pressure bycontaining air inflated by compressor though 7; where 2 is apressure tank with volume of 0.6m3, mainly used for waterstorage for leaking experiment; ball valve 3 is used for

    selecting the pipe for experiment. The leak source issimulated by small valve 4 with diameter of 5mm thatinstalled on the pipe. Meanwhile, to reduce the impact ofsound reflection form pipe ends, so the sound-absorbingdevice was installed In pipe ends, as labeled 9 in thefig.1.Duo to the low pressure of tap water, the valve betweentank 1 and tank 2 must be closed and the vent valve on thetop of tank 2 must be opened before filling water into tank 2though re-filling pipe 6, and then, close the re-filling valveand vent valve when water filling finished. Adjust thepressure of tank 1 in order to achieve the required pressure,and then experiments can begin. In the experiment, theacoustic signals were captured by piezoelectricaccelerometers with frequency response of 0.5~10 kHz.

    Figure 1. Test bench for leakage simulation

    2011 International Conference on Instrumentation, Measurement, Computer, Communication and Control

    978-0-7695-4519-6/11 $26.00 2011 IEEE

    DOI 10.1109/IMCCC.2011.39

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    III. CHARACTERISTICS OF LEAKAGE ACOUSTIC EMISSION

    IN CAST IRON PIPE

    A. Comparison of The Leak Signals and Ambient Noises

    It can be seen in the (a) of the fig.2 that no matter whichgraph of the ambient noises, the amplitude is small. In theTime-domain waveform, although wave amplitude is very

    small, it is shown periodical characteristic clearly. May bedue to there are equipments with frequency conversion wasworking at the same time in the public laboratory. To preventthe influence of power frequency, signals that below 500Hzhave been filtered out, so the signals below 500 Hz in thefrequency spectrum are considered the electric noise broughtafter the filter, and the signals above 500 Hz can beconsidered the mixing of ambient noise and leakage acousticemission signals caused by pipe leak. It is can be seen fromthe spectrum that the ambient noise is concentrated in lowfrequency. In the Autocorrelogram of ambient noises, thepeak is not obvious, and the attenuation on both side of peakare very slow. So it is show that the autocorrelation ofbackground noises is very strong, and the majority of

    background noises are colored noise, comprised of a varietyof inherent frequency noise signals with little randomness.When leakage occurs as shown in fig.2 (b), the changes inthe spectrum are very great. First in Time-domain waveformthe amplitude significantly increased. And in the frequencyspectrum, not only the amplitude increased, but also thespectrum range has been largely broadened. So it is visiblethe leak in cast iron pipe generate a wide range of spectrumacoustic signals. Meanwhile, in the autocorrelogram of leaksignals, the peak is very prominent and sharp and theattenuation is rapid. This illustrate that the leakage acousticsignals with little autocorrelation and very random. It is theessential difference between leak signals and ambient noises.For the signal energy has increased significantly induced byleak, there are three energy distribution bands were presentedin the time-frequency spectrum, respectively, 1000~1500Hz,2500~3500Hz ,5000~6000Hz. This is another big differencebetween the pipe with leaking and without leaking.

    Figure 2. A comparison of signals from ambient and from leaking pipe

    B. The Characteristics of Leak Signals under Different

    Pressure

    It is found that different pressure result in differentamplitude in the time-domain waveform. Under the case offixed size of leaking orifice, the higher the pressure, thegreater the leakage flow rate becomes. And also the degree

    that leaking water jets interact with the pipe wall is enhanced.So the rms value that represents energy of the acousticsignals increased, as shown in fig.3. However, with theincrease of the pressure, there is no obvious regularity infrequency domain, which coincident with the conclusionfrom Gao [11].

    Figure 3. The rms value changes with pressure

    C. The Characteristics of Leak Signals Under Different

    Distance form Leaking Source

    The stationary random signals of leak noise in differentdistances away from leaking source, under the pressure of0.3Mp, were researched. It is common sense that any signalswould decay during transmission. As shown in fig.4, the rmsvalues were plotted according the distance away from theleak, and the trend of the rms value attenuation with distanceincreasing was fitted into a line. Then we can see theattenuation rate is -0.11dB/m for cast iron pipe in this case.In addition to the amplitude of signals decreased with thedistance increasing, we also found that the frequencyspectrum tend to scattered. Maybe with the increasing ofdistance, the signal-to-noise ratio decreased, and the noisesignals showed up which not prominent before.

    Figure 4. The trend of the rms value changes with distance away from

    leak

    D. The Influence of Different Leaking Flow Rate

    Fig.5 (a) shows the waveform that acquired from the pipewith 2mm-diameter orifice. And the waveform acquiredfrom the pipe with 5mm-diameter orifice is shown in fig.5(b). From the comparison of (a) and (b) in fig.5, we canfound that the influence of leaking flow rate to the acousticsignal energy is great. At least within a certain range, thebigger the flow rate, the greater the energy of the leak signalsare. The small energy of the leak signals not only results in

    the acquisition of signal very difficult, but also there isanother disadvantage that the useful signals may submerge inthe ambient noises. This advantage can be seen in theautocorrelogram in fig.6. The degree of autocorrelation forthe ambient noises is strong, while the degree ofautocorrelation for leak noise is relatively weak, as shown infig.6 (a), (c). If the energy of the leak signals is weak, theautocorrelogram reflects more the characteristics of theambient noises, as shown in fig.6 (b).

    (a) (b)

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    Figure 5. Waveforms acquired under different leakage

    ((a)leakage with 2mm-diameter orifice, (b)leakage with 5mm-diameterorifice)

    Figure 6. autocorrelogram

    (a) no-leakage bleak with 2m-diameter orificecleak with

    5mm-diameter orifice

    E. The Influence of Submerged Jets on The Leak Signals

    A rubber tube was attached to the pipe outside the leak tosimulate the underground pipe submerged jets. Forcomparison, fig.7 (a) ,(b) show the waveforms and frequencyspectrums that one acquired from leaking pipe in the air andthe other from leaking pipe with rubber tube attached outsidethe leak, separately. It is found no obvious differences. Thisis because the sensor that acquired the acoustic signals wasstill attached to the leaking pipe. And the acoustic wave thatinduced by leaking water is still transmitted through theleaking pipe. Most of the leaks in underground pipe are thecase of submerged. So we can infer that the acousticcharacteristics of the leak signals generated submerged bywater are no big different with that generated in air.

    Figure 7. The waveform and frequency spectrum

    ((a) with a rubber tube, (b) without a rubber tube)

    F. The Noise Generated by The Impact of Water Jets on

    The Pipe Wall

    The signals that fig.8(a) showing are generated byleaking pipe itself. And the signals fig.8 (b) showing aregenerated by the impact of water jets from other pipe. Fromthe comparison of the two figures we can found that thespectrum of noises generated by impacts of water jets on the

    pipe wall is mainly concentrated into low frequency rang.The spectrum distribution bands are 500~1500Hz and2500~3000Hz, as can be seen in fig.8 (b). For the burst ofbubbles cannot take place on the pipe wall in this case, it canbe concluded that the real spectrums generated by the waterjets interacting with the pipe wall distribute in low frequencyrange.

    Figure 8. Waveform and spectrum of noise generated by water jets

    ((a) noise generated by leaking pipe itself, (b) noise generated by impact ofwater jets from other pipe)

    G. The Spectrum Range of The Signals from Leaking Pipe

    As can be seen in Fig.9, most of the signals in the castiron pipes induced by leaking water are non-stationaryrandom signals. There are always somewhat insoluble gasexists in the water that transported by the pipe, and also

    when the leakage occurs, the dissolved gases will beseparated as the pressure reducing. The bubbles near theleaking orifice will burst out with the jet of water. If thebubbles away from the leaking orifice, it will move to thelow pressure area with the leaking flow, then burst out.Furthermore, duo to the high-speed of the water stream,inside of the sharp orifice edge will more likely to form anegative pressure zone and then make the gas exhalationmore easily. So leakage often accompanied by the bubblebursting. In fig. 9 (a), it shows a sudden bubble burst, in thesteady flow. From the time-frequency spectrum, it canclearly be seen the time the bubble burst and its spectrumband above the frequency of 6000Hz, correspondingly, itbehaved for a short time of violent vibration in the time-

    domain waveform. Therefore we can conclude that thebubble burst would produce great energy. Since the majorityof leak acoustic signals are generated by the jet of water, thesignal spectrum distribution concentrated around the 1000Hz.Fig. 9(b) represents the situation that the jet flow of watercarried a lot of gas. That lots of gas burst out continuouslywith the jet flow of water result in continuous gas plugvibration. So we can see most amplitude of the time-domainwaveforms is very large. Furthermore most of the signal

    (a)

    (b)

    (a)

    (b)

    (a)

    (b)

    (c)

    (a)

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    spectrums distribute in the high frequency band of5000~6000Hz. All of them are displayed clearly and vivid inthe time-frequency spectrum. The case of fig. 9(c) showingis the case that the component of air in the leaking flow iseven large and mixed with water more evenly. So theleakage jet became uniform gas - liquid two-phase flow. Andtherefore another frequency band appeared, that is the band

    of frequency between 8000Hz and 9000Hz representing thegas leaking frequency band, which result is similar to thatYang [12] has achieved.

    IV. SUMMARY

    In this paper, the characteristics of leak signals in castiron water distribution pipe have been investigated thoughtime-domain, frequency-domain, time-frequency domain,and the autocorrelogram under many controlled conditions atan experimental leak detection bench. The main findings ofthe investigation can be summarized as follows.

    x The energy of leak noise is much higher than theambient noises. Furthermore, the greater the leakflow rate the higher the energy is.

    x The amplitude of leak signals diminished rapidlywith distance, at a rate of about 0.11dB/m.

    x The spectrums of leak signals distribute widely. Thespectrums induced by water flow are in lowfrequency that below 3000Hz and the spectrumsinduced by bubbles burst are in high frequency thatabove 5000Hz.

    x The autocorrelogram of leak noise is sharper thanthat of ambient noise much more.

    ACKNOWLEDGMENT

    The authors would like to thank for the financial supportfrom the National Science & Technology Pillar Program inthe Eleventh Five-year Plan Period (2006BAJ03A05-05).

    REFERENCES

    [1] M. Fantozzi, G.D. Chirico, E. Fontana, F. Tonolini, Leak inspectionon water pipelines by acoustic emission with cross-correlationmethod, Annual Conference Proceeding, American Water WorksAssociation, Engineering and Operations, San Antonio, Texas, 1993,PP.609-621.

    [2] H.V. Fuchs, R. Riehle, Ten years of experience with leak detectionby acoustic signal analysis, Applied Acoustics, vol. 31,1991,pp.1~19.

    [3] D.A.Liston, J.D.Liston, Leak detection techniques, Journal of theNew England Water Works Association ,vol. 106,1992, pp.103~108.

    [4] R.W.Healy, T.T.Bartos, C.A.Rice, Groundwater chemistry near animpoundment for produced water, Powder River Basin, Wyoming,USA. Journal of Hydrology,vol. 403, 2011,pp.37~48.

    [5] G.J.Weil, Non contact, remote sensing of buried water pipeline leaksusing infrared thermography, Water Resources Planning andManagement and Urban Water Resources, 1993,pp.404~407.

    [6] R.S.Pudar, J.A.Liggett, Leaks in pipe networks,Journal ofHydraulic Engineering, American Society of Civil Engineers,vol.118,1992, pp.1031~1046.

    [7] K.W.Sneddon, G.R.Olhoeft, M.H.Powers, Determining and mappingDNAPL saturation values from noninvasive GPR measurements,Symposium on the Application of Geophysics to Environmental andEngineering Problems, Arlington, Virginia, 2000,pp.293~302.

    [8] O.Hunaidi, Ground-penetrating radar for detection of leaks in buriedplastic water distribution pipes, Seventh International Conference onGround-Penetrating Radar, Lawrence, Kansas, 1998,pp.783~ 786.

    [9] O.Hunaidi, W.Chu, A. Wang, W. Guan, Detecting leaks in plasticpipes, Journal of the American Water Works Association,vol. 92,2000, pp.82~94.

    [10] Y.Gao, M.J. Brennan, P.F. Joseph A comparison of time delayestimators for the detection of leak noise signals in plastic waterdistribution pipes, Journal of Sound and Vibration,vol. 292, 2006, pp.552~570.

    [11] O.Hunaidi, W.T.Chu. Acoustical characteristics of leak signals inplastic water distribution pipes, Applied Acoustics.vol. 58, 1999,pp.235~254.

    [12] YANG Li-jian,LI Jia-qi,GAO Song-wei, Leakage monitoringmethod of natural gas pipeline based on inside-listening, Journal ofShenyang University of Technology.vol. 33,Janary 2011,pp. 93 ~ 107.

    Figure 9. The leak signals in several situations

    (a) (b) (c)

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