Leak detection in water-filled plastic pipes through the application of tuned wavelet transforms to Acoustic Emission signals

Ahadi, Majid; Bakhtiar, Mehrdad Sharif

doi:10.1016/j.apacoust.2010.02.006

Cited by 167 publications

(75 citation statements)

References 11 publications

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“…It has also confirmed that acoustic emission techniques are often enormously faster than traditional non-acoustic methods, such as ultrasonic, infrared thermography, tracer gas, electromagnetic scanning, and ground penetrating radars [3][4][5]. Conventional fixed acoustic methods are focused on longitudinal deployment, and due to the availability of various types of water pipe materials with extensive properties, these methods also demand a proper placement of sensors regarding the type of material.…”

Section: Introductionmentioning

confidence: 99%

“…The Short-Time Fourier Transform (STFT) is employed in the context of time-frequency analysis; although simple to use, the accuracy of STFT is confined to the window size. Hence, STFT is not particularly popular for the acoustic signal investigation in water distribution pipelines [3,9,26], considering all of the frequencies analyses with identical resolutions.…”

Section: Introductionmentioning

confidence: 99%

“…Since the past two decades, the investigation of the acoustic emission signal with a high capability of wavelet transformation has changed the way of thinking and has brought significant efforts [3,[26][27][28][29][30][31]. A number of studies have demonstrated that the WT can be applied in the analysis of acoustic signals effectively.…”

Section: Introductionmentioning

confidence: 99%

“…Boczar [35,36] has analyzed the acoustic emissions caused by the electric discharge in air, applying WT without considering the significance of choice of the mother wavelet. Ahadi [3] has proposed and emphasized the importance of mother wavelet for leak detection in plastic water pipes. However, the author selected optimal mother wavelet "Gauss27" in the context of shape only; whereas, other correlated mother wavelets are not explored.…”

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

The Free-Swimming Device Leakage Detection in Plastic Water-filled Pipes through Tuning the Wavelet Transform to the Underwater Acoustic Signals

Kumar

Zhu

et al. 2017

Water

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Abstract:The conventional fixed acoustic sensors leak detection methods have been demonstrated to be very practical for locating leakages in water distribution pipelines. However, these methods demand proper installation of sensors, and therefore cannot be implemented on buried long water distribution pipelines for condition assessment, early leak detection, and the estimation of leak size effect. Due to these limitations, a free-swimming device is developed. The free-swimming device with the potential of high acoustic sensitivity is capable of detecting the small underwater leakages in the plastic water-filled pipes. Despite the fact that a number of factors influence the underwater acoustic signals, such as water flow noise. Therefore, the interpretation of the leakage and influence of leakage size is considerably challenging from the underwater measured signals. The new method is proposed for reliable leakage detection by tuning the wavelet transform to underwater water acoustic signals. In this method, firstly, Short-Time Fourier Transforms (STFT) of underwater acoustic signals over a relatively long time-interval is monitored to capture the leakage-signals signature. The captured signals efficiently lead in the selection of mother wavelet (tuned wavelet) for the excellent signal localization in the time-frequency domain. Finally, the acoustic signals are analyzed in the tuned wavelet transform to detect the events. In this paper, the practical application of the proposed method, the controlled experiments are designed, and acoustic signals are collected from an experimental setup by launching the free-swimming device. The measured acoustic signals are used to identify the leakage-signals signature from unwanted interfering signals (instantaneous pipe vibrations, water flow noise, pipe's natural frequencies, and background noise). The evaluation of results validated that the free-swimming device and the tuned wavelet transform together can efficiently lead to reliable underwater leakage detection, as well as the influence of the leakage size in plastic water-filled pipes.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

The Free-Swimming Device Leakage Detection in Plastic Water-filled Pipes through Tuning the Wavelet Transform to the Underwater Acoustic Signals

Kumar

Zhu

et al. 2017

Water

View full text Add to dashboard Cite

show abstract

“…As a conventional AE source localized method, Time difference of arrival algorithm (TDOA) has become the popular tool to recognize the AE source in laboratory. However, the localized accuracy of TODA is sensitive to preset AE signal threshold, dispersion and effective velocity during propagation process of waves and background noise etc., [2]. Besides, it is inconvenient and rather costly to use TDOA method for large rotary machinery since its large scale distribution of sensors for signal reception.…”

Section: Introductionmentioning

confidence: 99%

AE Sound Source Localization Using Nearfield MUSIC Algorithm Based on Fourth-Order Cumulants

Li¹,

Yang²,

Li³

et al. 2016

IJSIP

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Acoustic Emission (AE) source localization is a useful implement to diagnose the incipient faults in rotating machine. This paper proposes an improved Near-field Multiple Signal Classification method using four-order cumulants (NFC-MUSIC) to accurately locate the faults position. In order to overcome dispersion effect and revised velocity, the feature sub narrow band is extracted by Wavelet Packet reconstitution (WPR) and Modal Plate Wave Theory (MPWT). For multi-source decorrelation and increasing localized resolution, the four-order cumulants of observed signal can be selected for localization. The experiment results indicate that the improved method can accurately locate multirubbing faults. It is an efficient way to assist incipient rubbing faults diagnosis.

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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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Leak detection in water-filled plastic pipes through the application of tuned wavelet transforms to Acoustic Emission signals

Cited by 167 publications

References 11 publications

The Free-Swimming Device Leakage Detection in Plastic Water-filled Pipes through Tuning the Wavelet Transform to the Underwater Acoustic Signals

The Free-Swimming Device Leakage Detection in Plastic Water-filled Pipes through Tuning the Wavelet Transform to the Underwater Acoustic Signals

AE Sound Source Localization Using Nearfield MUSIC Algorithm Based on Fourth-Order Cumulants

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

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