Comparative study of instantaneous frequency based methods for leak detection in pipeline networks

Ghazali, Mohd Imran; Beck, Steven; Shucksmith, James; Boxall, Joby; Staszewski, Wiesław J.

doi:10.1016/j.ymssp.2011.10.011

Cited by 124 publications

(66 citation statements)

References 24 publications

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“…Among them, transient pressure wave‐based methods were exploited to detect and locate faults and leakages on different types of water pipes, and it was used to settle multidefects detection and complex pipeline connection situations . But the pressure peaks can potentially damage the pipes . Vibration signals of the pipe shell recorded by accelerometers were used to detect the burst leak signals of plastic water pipes, but the detectable frequency range of accelerometers is very narrow and low so it is not suitable for continuous gas leak signals on steel pipes.…”

Section: Introductionmentioning

confidence: 99%

“…10,11 But the pressure peaks can potentially damage the pipes. 12 Vibration signals of the pipe shell recorded by accelerometers were used to detect the burst leak signals of plastic water pipes, 13 but the detectable frequency range of accelerometers is very narrow and low so it is not suitable for continuous gas leak signals on steel pipes. AE method has been verified to be efficient to detect leaks on both water pipes and gas pipes.…”

Section: Introductionmentioning

confidence: 99%

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Experimental validation of gas leak detection in screw thread connections of galvanized pipe based on acoustic emission and neural network

Gong

Song

2019

Struct Control Health Monit

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Summary Galvanized steel pipes with screw thread connections are widely used in the household part of urban gas distribution system. For such pipes, leakages usually occur at the connections as opposed to the pipe bodies. A leak detection method has been proposed for galvanized steel pipes on the basis of acoustic emission (AE) and neural network. From the viewpoint of engineering application, this work conducts a thorough experimental investigation on the efficiency, accuracy, and applicability conditions of the method. An experimental platform consisting of one trunk pipe and three branch pipes with different diameters is set up to simulate the various leak scenarios. After feature extraction and analysis of the AE signals, a classifier on the basis of back propagation neural network is built for gas leak identification. The applicability of the classifier is investigated quantitatively considering different pipe diameters, number of connections, and leak rate. It validates that the proposed leak detection model can achieve an average accuracy above 95% of the leak with flow above 0.052 L/s on the trunk pipe, on the premise that the signals pass through no more than four screw thread connections. Then, the leak with flow above 0.1 L/s on branch pipes can be detected under the same sensor arrangement.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Experimental validation of gas leak detection in screw thread connections of galvanized pipe based on acoustic emission and neural network

Gong

Song

2019

Struct Control Health Monit

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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%

“…The errors for identifying the location of leaks, with the flow rates of 0.20, 0.25, 0.30 and 0.40 L/s, were claimed to be less than 0.7%. Ghazali et al 9 studied the analysis of a transient pressure wave in a live water distribution system using a variety of instantaneous frequency (IF) techniques. Methods such as, Hilbert Transform (HT), Normalised Hilbert Transform (NHT), Direct Quadrature (DQ), Teager Energy Operator (TEO) and cepstrum were applied to the system.…”

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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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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“…2 of 15 induced hydraulic transients can detect and locate leaks within a wide range, but the pressure peaks can potentially damage the pipes [10,16]. Acoustic emission (AE) monitoring has been proven as an effective method for detecting very small leaks over long distances [11,16]; however, its effectiveness may depend on the possibility of artificially amplifying the leak noise by injecting gas or increasing the fluid pressure in the monitored pipes (procedures that are not always allowed during normal operation), and it may be less effective with plastic pipes as well.…”

mentioning

confidence: 99%

Autocorrelation Analysis of Vibro-Acoustic Signals Measured in a Test Field for Water Leak Detection

2018

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Featured Application: The proposed method may be adopted for developing and implementing an automated system for the early detection of leaks occurring in service pipes of water distribution networks.Abstract: Reducing losses in water distribution networks is a worldwide challenge and all utilities are developing proper strategies for the active control of leaks. Temporary or permanent grids of units for the continuous monitoring of pipelines through vibro-acoustic measurements are probably the most commonly adopted leak detection systems. Such systems generally rely on the definition of proper thresholds to detect increments in the vibration levels associated with leaks. Since the thresholds are strongly dependent on the local boundary conditions of the monitored network, the initial setup is costly and time consuming, and the risk of undetected leaks or false alarms increases. This work aims to investigate leak detection methods based on the inherent properties of the measured signals instead of their relative amplitude. In particular, the possibility of detecting water leaks in small-diameter plastic pipes by analyzing the autocorrelation function of vibro-acoustic signals is assessed. An experimental campaign is conducted in a full-scale test facility that simulates the actual network. The measurements concerning artificially generated leaks are attained by two accelerometers and one hydrophone. The experimental results confirm the effectiveness of the proposed approach, which is therefore proven as a promising tool for leak detection.2 of 15 induced hydraulic transients can detect and locate leaks within a wide range, but the pressure peaks can potentially damage the pipes [10,16]. Acoustic emission (AE) monitoring has been proven as an effective method for detecting very small leaks over long distances [11,16]; however, its effectiveness may depend on the possibility of artificially amplifying the leak noise by injecting gas or increasing the fluid pressure in the monitored pipes (procedures that are not always allowed during normal operation), and it may be less effective with plastic pipes as well. Tracer gas techniques can reliably provide leak detection and location [4,16]; nonetheless, they are not suitable for all kinds of leaks and the isolation of the monitored pipe from the network is typically required. Thermography can detect and locate leaks over large areas [4,12], but its effectiveness may be affected by seasonal temperatures and thermal noise (e.g., large urban areas). Ground penetrating radar (GPR) is also characterized by a large monitoring area and high accuracy [4,[13][14][15]; nonetheless, the detection may be hampered by underground anomalies and buried objects other than pipes, and also because of the sizeable amount of signal attenuation in wet soil with high clay content. Electrical resistivity tomography (ERT) can provide leak detection and location [14,15], but has a low resolution and requires inserting electrodes in the ground, which is not always viable. Time domain reflectometr...

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Comparative study of instantaneous frequency based methods for leak detection in pipeline networks

Cited by 124 publications

References 24 publications

Experimental validation of gas leak detection in screw thread connections of galvanized pipe based on acoustic emission and neural network

Experimental validation of gas leak detection in screw thread connections of galvanized pipe based on acoustic emission and neural network

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

Autocorrelation Analysis of Vibro-Acoustic Signals Measured in a Test Field for Water Leak Detection

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