Precise acoustical leak detection calls for robust time-delay estimates, which minimize the probability of false alarms in the face of dispersive propagation, multiple reflections, and uncorrelated background noise. Providing evidence that higher order modes and multi-reflected signals behave like sets of correlated noise, this work uses a regression model to optimize residual complexity in the presence of both correlated and uncorrelated noise. This optimized residual complexity (ORC) is highly robust since it takes into account both the level and complexity of noise. The lower complexity of the dispersive modes and multiple reflections, compared to the complexity of the plane mode, points to the robustness of ORC against multiple reflections and dispersion. Experimental investigations using recorded sounds of gas leaking from a pipe confirm the robustness of ORC against multiple reflections. Numerical simulations also show robustness against dispersive modes, even when they disturb the linearity of the cross-spectrum phase. Comparisons with other methods—mutual information, cross correlation, and residual complexity—underline the general advantages of ORC in terms of robustness in the presence of reflection and dispersion, against both correlated and uncorrelated noise, and to short signals.
References
1.
P. S.
Murvay
and I.
Silea
, “A survey on gas leak detection and localization techniques
,” J. Loss Prev. Process Ind.
25
, 966
–973
(2012
).2.
D. G.
Murdock
, S. V.
Stearns
, R T.
Lines
, D.
Lenz
, D. M.
Brown
, and C. R.
Philbrick
, “Applications of real-world gas detection: Airborne natural gas emission lidar (ANGEL) system
,” J. Appl. Remote Sens.
2
(1
), 023518
(2008
).3.
S. C.
Huang
, W. W.
Lin
, M. T.
Tsai
, and M. H.
Chen
, “Fiber optic in-line distributed sensor for detection and localization of the pipeline leaks
,” Sens. Actuators A
135
(2
), 570
–579
(2007
).4.
M.
Nikles
, “Long-distance fiber optic sensing solutions for pipeline leakage, intrusion and ground movement detection
,” in Fiber Optic Sensors and Applications VI
, International Society for Optics and Photonics, Orlando, FL (April 13, 2009
), Vol. 7316
(2
), pp. 1
–13
.5.
H. V.
Fuchs
and R.
Riehle
, “Ten years of experience with leak detection by acoustic signal analysis
,” Appl. Acoust.
33
(1
), 1
–19
(1991
).6.
Q.
Xu
, L.
Zhang
, and W.
Liang
, “Acoustic detection technology for gas pipeline leakage
,” Process Safety Env. Protection
91
(4
), 253
–261
(2013
).7.
L.
Meng
, L.
Yuxing
, W.
Wuchang
, and F.
Juntao
, “Experimental study on leak detection and location for gas pipeline based on acoustic method
,” J. Loss Prev. Process Ind.
25
(1
), 90
–102
(2012
).8.
F.
Viola
and W. F.
Walker
, “A spline-based algorithm for continuous time-delay estimation using sampled data
,” IEEE Trans. Ultrasonics Ferroelectr. Freq. Control
52
(1
), 80
–93
(2005
).9.
Z.
Wang
, J.
Li
, and R.
Wu
, “Time-delay- and time-reversal-based robust capon beamformers for ultrasound imaging
,” IEEE Trans. Med. Imaging
24
(10
), 1308
–1322
(2005
).10.
S. J.
Franklin
, A.
Finn
, and J.
Meade
, “Time delay estimation of acoustic tones with unpredictable frequency variations under low signal to noise ratio conditions
,” J. Acoust. Soc. Am.
137
(4
), 2437
–2438
(2015
).11.
Z. H.
Michalopoulou
and M.
Picarelli
, “Gibbs sampling for time-delay and amplitude estimation in underwater acoustics
,” J. Acoust. Soc. Am.
117
(2
), 799
–808
(2005
).12.
G. C.
Carter
, “Time delay estimation for passive sonar signal processing
,” IEEE Trans. Acoustics Speech Sign Process.
29
(3
), 463
–470
(1981
).13.
Q.
Xue
, H.
Wang
, C.
Yang
, and Z.
Cui
, “Dynamical lag correlation exponent based method for gas–solid flow velocity measurement using twin-plane electrical capacitance tomography
,” Meas. Sci. Technol.
23
(8
), 085301
(2012
).14.
D.
Breakey
and C.
Meskell
, “Comparison of metrics for the evaluation of similarity in acoustic pressure signals
,” J. Sound Vib.
332
(12
), 3605
–3609
(2013
).15.
Y.
Gao
, M. J.
Brennan
, P. F.
Joseph
, J. M.
Muggleton
, and O.
Hunaidi
, “A model of the correlation function of leak noise in buried plastic pipes
,” J. Sound Vib.
277
(2
), 133
–148
(2004
).16.
A.
Mostafapour
and S.
Davoodi
, “Leakage locating in underground high pressure gas pipe by acoustic emission method
,” J. Nondestruct. Eval.
32
(2
), 113
–123
(2013
).17.
D. B.
Yoon
, J. H.
Park
, and S. H.
Shin
, “Improvement of cross-correlation technique for leak detection of a buried pipe in a tonal noisy environment
,” Nucl. Eng. Technol.
44
(8
), 977
–984
(2012
).18.
E. Y.
Kim
, M. S.
Kim
, and S. K.
Lee
, “Identification of the impact location in a gas duct system based on acoustic wave theory and the time frequency
,” in Experimental Mechanics
(Springer
, New York
, 2011
), Vol. 51
(6
), 947
–958
.19.
L. E.
Rewerts
, R. R.
Roberts
, and M. A.
Clark
, “Dispersion compensation in acoustic emission pipeline leak location
,” Rev. Prog. Quant. Nondestruct. Eval.
16
, 427
–434
(1997
).20.
S.
Li
, U.
Wen
, P.
Li
, X.
Dong
, and Y.
Mu
, “Leak location in gas pipelines using cross-time frequency spectrum of leakage-induced acoustic vibrations
,” J. Sound Vib.
333
(17
), 3889
–3903
(2014
).21.
Th. M.
Cover
and J. A.
Thomas
, Elements of Information Theory
, 2nd ed. (Wiley
, New York
, 2005
), Chap. 2
, pp. 14
–20
.22.
A.
Kraskov
, H.
Stögbauer
, and P.
Grassberger
, “Estimating mutual information
,” Phys. Rev. E
69
(6
), 066138
(2004
).23.
W.
Li
, “Mutual information functions versus correlation functions
,” J. Stat. Phys.
60
(5-6
), 823
–837
(1990
).24.
A.
Roche
, G.
Malandain
, and N.
Ayache
, “Unifying maximum likelihood approaches in medical image registration
,” Int. J. Imaging Syst. Technol.
11
(1
), 71
–80
(2000
).25.
A.
Myronenko
and X.
Song
, “Intensity-based image registration by minimizing residual complexity
,” IEEE Trans. Med. Imaging
29
(11
), 1882
–1891
(2010
).26.
K.
Baik
, J.
Jiang
, and T. G.
Leighton
, “Acoustic attenuation, phase and group velocities in liquid-filled pipes: Theory, experiment, and examples of water and mercury
,” J. Acoust. Soc. Am.
128
(5
), 2610
–2624
(2010
).27.
I. H.
Chung
and K. H.
Kim
, “Asymptotic properties of the one-step m-estimators in nonlinear regression model
,” Commun. Korean Math. Soc.
7
(2), 293
–306
(1992
).28.
29.
H.
Zayyani
, M.
Babaie-Zadeh
, and C.
Jutten
, “An iterative Bayesian algorithm for sparse component analysis in presence of noise distortion
,” IEEE Trans. Sign. Process.
57
(11
), 4378
–4390
(2009
).30.
A.
Ghaffari
and E.
Fatemizadeh
, “Robust Huber SM for image registration in the presence of spatially-varying intensity distortion
,” Sign. Process.
109
, 54
–68
(2015
).31.
A.
Ghaffari
and E.
Fatemizadeh
, “Sparse-induced similarity measure: Mono-modal image registration via sparse-induced similarity measure
,” IET Image Process.
8
(12
), 728
–741
(2014
).32.
Y.
Gao
, M. J.
Brennan
, and P. F.
Joseph
, “On the effects of reflections on TDE for leak detection in buried plastic water pipes
,” J. Sound Vib.
325
(3
), 649
–663
(2009
).33.
J.
Bolton
and E.
Gold
, “The application of cepstral techniques to the measurement of transfer functions and acoustical reflection coefficients
,” J. Sound Vib.
93
(2
), 217
–233
(1984
).34.
M.
Taghvaei
, S. B. M.
Beck
, and W. J.
Staszewski
, “Leak detection in pipelines using cepstrum analysis. I
,” Meas. Sci. Technol.
17
(2
), 367
–372
(2006
).35.
Y.
Gao
, M. J.
Brennan
, and P. F.
Joseph
, “A comparison of time delay estimators for the detection of leak noise signals in plastic water distribution pipes
,” J. Sound Vib.
292
(3
), 552
–570
(2006
).36.
M.
Broadhead
, R. L.
Field
, and J. H.
Leclere
, “Sensitivity of the deconvolution of acoustic transients to Green's function mismatch
,” J. Acoust. Soc. Am.
94
, 994
–1002
(1993
).37.
M.
Broadhead
and L. A.
Pflug
, “Performance of some sparseness criterion blind deconvolution methods in the presence of noise
,” J. Acoust. Soc. Am.
107
, 885
–893
(2000
).38.
J. H.
DiBiase
, Harvey F.
Silverman
, and M. S.
Brandstein
, “Robust localization in reverberant rooms
,” in Microphone Arrays
(Springer
, Berlin
, 2001
), pp. 157
–180
.39.
W. Jun.
Zeng
, X.
Jiang
, X. L.
Li
, and X. D.
Zhang
, “Deconvolution of sparse underwater acoustic multipath channel with a large time-delay spread
,” J. Acoust. Soc. Am.
127
, 909
–919
(2010
).40.
D. L.
Donoho
and J. M.
Johnstone
, “Ideal spatial adaptation by wavelet shrinkage
,” Biometrika
81
(3
), 425
–455
(1994
).41.
F.
Almeida
, M.
Brennan
, P.
Joseph
, S.
Whitfield
, M.
Dray
, and A.
Paschoalini
, “On the acoustic filtering of the pipe and sensor in a buried plastic water pipe and its effect on leak detection: An experimental investigation
,” Sensors
14
(3
), 5595
–5610
(2014
).42.
43.
S. E.
Fried
, S. C.
Walker
, W. S.
Hodgkiss
, and W. A.
Kuperman
, “Measuring the effect of ambient noise directionality and split-beam processing on the convergence of the cross-correlation function
,” J. Acoust. Soc. Am.
134
(3
), 1824
–1832
(2013
).44.
L. E.
Kinsler
, A. R.
Frey
, A. P.
Coppes
, and J. V.
Sanders
, Fundamentals of Acoustics
(Wiley
, New York
, 2000
), p. 120
.45.
X.
Jiang
, T.
Kirubarajan
, and W. J.
Zeng
, “Robust time-delay estimation in impulsive noise using Lp-correlation
,” Meas. Sci. Technol.
17
(2
), 1
–4
(2013
).© 2016 Acoustical Society of America.
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