Gas leak locating in steel pipe using wavelet transform and cross-correlation method

Pipelines leakage in power plant, petrochemical complexes, and refineries can lead to explosion, pollution, and severe physical damages, so precise and on time leak locating is very important. There are many techniques for detecting and locating the leakage. In this research, we represent the leak locating principle in pressurized gas pipelines by using acoustic emission theory. An algorithm for finding the location of continuous acoustic waves resulted from leakage is provided by MATLAB software. The used leak locating technique is a combination of wavelet transform, filtering, and cross-correlation methods. The resulted acoustic emission signals were analyzed into high and low frequencies by wavelet transform and available noises on them were omitted completely by filtering. Then de-noised acoustic emission signals were reconstructed. Time differences of de-noised waves were calculated precisely by using cross-correlation function. For studying the accuracy of used method, acoustic emission testing was done by continuous leakage source. The resulted signals of leakage were recorded by two acoustic sensors in two sides of leakage source, and time difference and leak location were calculated by using the algorithm. Several tests were done by changing sensor distance from leakage source and error percent of less than 3 % was resulted in leak locating that indicated high precision of used algorithm.

[1]  A. E. G. Benz Use of Acoustic emission techniques for detection of discontinuities , 1998 .

[2]  John Alexander Steel,et al.  Acoustic Emission Source Location for Steel Pipe and Pipeline Applications: The Role of Arrival Time Estimation , 2006 .

[3]  G. Qi Wavelet-based AE characterization of composite materials , 2000 .

[4]  Robert Lewis Reuben,et al.  AE mapping of engines for spatially located time series , 2005 .

[5]  Osama Hunaidi,et al.  Acoustical characteristics of leak signals in plastic water distribution pipes , 1999 .

[6]  Anthony N. Tafuri,et al.  A reference standard for the development of acoustic emission pipeline leak detection techniques , 1999 .

[7]  Arup K. Maji,et al.  Acoustic Emission Source Location Using Lamb Wave Modes , 1997 .

[8]  Karen Margaret Holford,et al.  Acoustic Emission Source Location , 1999 .

[9]  M. Gorman,et al.  Source location in thin plates using cross-correlation , 1991 .

[10]  M. Hamstad,et al.  A WAVELET TRANSFORM APPLIED TO ACOUSTIC EMISSION SIGNALS: PART 1: SOURCE IDENTIFICATION # , 2002 .

[11]  P. De Baets,et al.  Classification of wavelet decomposed AE signals based on parameter-less self organised mapping , 2011 .

[12]  H. Inoue,et al.  Time Frequency Analysis of Dispersive Waves by Means of Wavelet Transform , 1995 .

[13]  Zhou Jin,et al.  Safety detection of braking system based on wavelet packet and neural network , 2005 .

[14]  Olivier Rioul,et al.  Fast algorithms for discrete and continuous wavelet transforms , 1992, IEEE Trans. Inf. Theory.