Pipeline Network Features and Leak Detection by Cross-Correlation Analysis of Reflected Waves

Beck, Steven; Curren, M. D.; Sims, Neil D.; Stanway, R.

doi:10.1061/(asce)0733-9429(2005)131:8(715)

Cited by 86 publications

(47 citation statements)

References 13 publications

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“…Furthermore, the generated results are compared with the cross-correlation and cepstrum leak detection methods. [6][7][8] There are various types of transient leak detection methods, using different signal processing approaches notably by the Sheffield 9 and Perugia groups. [10][11][12] Leak detection based on the cross-correlation method has been used for leak detection purposes in several studies.…”

Section: Introductionmentioning

confidence: 99%

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Leak detection using cepstrum of cross-correlation of transient pressure wave signals

Motazedi

Beck

2017

Proceedings of the Institution of Mechanical Engineers, Part C:

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A new leak detection method is proposed here which is based on the cepstrum of the cross-correlation of the pressure signals from two transducers. Computational simulations of leaks with different properties, size, position and shape, in a straight pipe and a T-Junction network were studied. The proposed method was successful in estimating leakages and the pipeline features with a high precision. For the results with a straight pipe, this method is considerably more accurate than using the cross-correlation leak detection method or the cepstrum method alone. However, the results obtained by cepstrum and cepstrum of cross-correlation for the T-Junction case were quite accurate, while cepstrum alone showed a slightly better precision.

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Section: Introductionmentioning

confidence: 99%

“…[10][11][12] Leak detection based on the cross-correlation method has been used for leak detection purposes in several studies. Beck et al 6,7 applied the cross-correlation and its derivatives to identify pipeline features and a leaks, using one sensor. The experimental and numerical results were in an acceptable range.…”

Section: Introductionmentioning

confidence: 99%

Leak detection using cepstrum of cross-correlation of transient pressure wave signals

Motazedi

Beck

2017

Proceedings of the Institution of Mechanical Engineers, Part C:

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“…Different researchers have analyzed different characteristics of hydraulic pipeline systems (acoustic, pressure and flow measurements). All of these methods apply fundamental signal processing functions, such as cross-correlation [13] , wavelet transforms [14] [15] (Continuous, Discrete), Fast Fourier Transform (FFT) [16] [17] [18] [19] and Cepstrum Analysis [20], in conjunction with other sophisticated mechanisms (Artificial Neural Network (ANN), Support Vector Machine (SVM) and Genetic Algorithm (GA)) to achieve an individual goal.…”

Section: Introductionmentioning

confidence: 99%

“…Similarly, Ferrante and Brunone [26] established wavelet analysis of experimental data to expose the singularity, which is the indication of the occurrence of a burst. Beck et al [13] recommended the application of a cross-correlation method to the analysis of a reflected pressure wave to identify the features (junction, branch, node, etc.) of pipelines and leaks.…”

Section: Introductionmentioning

confidence: 99%

Event Detection and Localization in Urban Water Distribution Network

et al. 2014

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Abstract-Urban water supply and distribution system infrastructure is aging rapidly and the frequency of pipe burst increases. These events can be very expensive due to water supply disruptions, and damage to surrounding properties and infrastructures. Therefore, methods of detecting and localizing underground burst events in real time can be very helpful in mitigating these impacts. In this research, a cost-effective wireless sensor network was developed for real time monitoring, analyzing and modeling of urban water distribution systems. This paper presents an application of a proposed Joint Time Frequency Analysis for detecting events in water distribution pipelines. The idea behind this method is based on the detection of pressure fluctuations induced by the burst. This proposed approach for event detection employs a spectrogram, one of the Joint Time Frequency Analysis approaches. The feasibility of the proposed method is tested through emulated leak-off experiments and is validated with monitoring data in an operational system. The results demonstrate that the proposed method has the potential to assist in the management water infrastructure by monitoring existing conditions and providing real-time feedback in case of the failure.

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“…Covas et al (2005) focused on leakage detection in pipe systems by means of the standing wave difference method. Beck et al (2005) described a method to detect pipeline features and leaks using the cross-correlation techniques of pressure wave measurements. Misiunas et al (2005) proposed a continuous monitoring approach on the basis of the timing of the initial and reflected pressure transient waves induced by the break.…”

Section: Introductionmentioning

confidence: 99%

Detection of Local Wall Stiffness Drop in Steel-Lined Pressure Tunnels and Shafts of Hydroelectric Power Plants Using Steep Pressure Wave Excitation and Wavelet Decomposition

Hachem

Schleiss

2012

J. Hydraul. Eng.

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A new monitoring approach for detecting, locating, and quantifying structurally weak reaches of steel-lined pressure tunnels and shafts is presented. These reaches arise from local deterioration of the backfill concrete and the rock mass surrounding the liner. The change of wave speed generated by the weakening of the radial-liner supports creates reflection boundaries for the incident pressure waves. The monitoring approach is based on the generation of transient pressure with a steep wave front and the analysis of the reflected pressure signals using the fast Fourier transform and wavelet decomposition methods. Laboratory experiments have been carried out to validate the monitoring technique. The multilayer system (steel-concrete-rock) of the pressurized shafts and tunnels is modeled by a one-layer system of the test pipe. This latter was divided into several reaches having different wall stiffnesses. Different longitudinal placements of a steel, aluminum, and PVC pipe reach were tested to validate the identification method of the weak section.

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Pipeline Network Features and Leak Detection by Cross-Correlation Analysis of Reflected Waves

Cited by 86 publications

References 13 publications

Leak detection using cepstrum of cross-correlation of transient pressure wave signals

Leak detection using cepstrum of cross-correlation of transient pressure wave signals

Event Detection and Localization in Urban Water Distribution Network

Detection of Local Wall Stiffness Drop in Steel-Lined Pressure Tunnels and Shafts of Hydroelectric Power Plants Using Steep Pressure Wave Excitation and Wavelet Decomposition

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