Investigation of the relationship between internal fluid leakage through a valve and the acoustic emission generated from the leakage

Kaewwaewnoi, W.; Prateepasen, Asa; Kaewtrakulpong, Pakorn

doi:10.1016/j.measurement.2009.10.005

Cited by 77 publications

(52 citation statements)

References 9 publications

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“…In our previous work [7], we proposed a theoretical relationship between an AE signal power in form of AE 2 RMS to a liquid leakage rate acquired from a PC-based AE system. We extended the finding for gas in this work.…”

Section: Mathematical Modelmentioning

confidence: 99%

“…opening and closing) and the detection of the wear or leakage in check valves [2,3]. Several research works studied the effects of AE parameters on valve and fluid variables such as pressure, types of gas and valve [4][5][6][7]. It was found that only AE RMS had a good correlation with those variables; whereas others AE parameters were reported to have insignificant influence.…”

Section: Introductionmentioning

confidence: 99%

“…To apply the Lighthill's principle on the valve leakage, the sound power, P s , which had been derived in terms of the fluid variable [7], was given by:…”

mentioning

confidence: 99%

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Smart portable noninvasive instrument for detection of internal air leakage of a valve using acoustic emission signals

2011

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Section: Mathematical Modelmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Smart portable noninvasive instrument for detection of internal air leakage of a valve using acoustic emission signals

2011

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“…Prateepasen et al 17 presented a smart portable non-invasive instrument to detect internal air leakage of a valve using the AE signal; the AE RMS parameter was used to infer the leakage rate. Kaewwaewnoi et al 18 proposed a theoretical investigation of the AE to detect the internal leakage rate through a valve.…”

Section: Introductionmentioning

confidence: 99%

Experimental investigation of the fault diagnosis of typical faults in reciprocating compressor valves

Wang

Gao

Zheng

et al. 2015

Proceedings of the Institution of Mechanical Engineers, Part C:

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The failure of suction/discharge valves is the most common cause of unscheduled compressor shutdowns; therefore, the in-time fault diagnosis of valves is crucial to the reliable operation of reciprocating compressors. Major valve faults include leakage, valve flutter, delayed closing, and improper lift. To determine the features for diagnosing these typical valve faults, this paper presents an experimental study of the fault diagnosis of reciprocating compressor valves with acoustic emission technology and simulated valve motion. The measured AE signals and simulated valve motions of normal and failed valves are studied. The results of the fault diagnosis indicate that an earlier occurrence of the suction process can diagnose suction valve leakage and that an earlier occurrence of the discharge process can be used for detecting discharge valve leakage. The leakage also causes an increase in the amplitude of the continuous acoustic emission signal. Valve faults resulting from improper valve lift can be diagnosed by the amplitude of the burst acoustic emission signal. The number of burst acoustic emission signals and the shape of the simulated valve motion can be used to monitor the valve flutter conditions. The location where the valve closes can diagnose a valve-delayed closing fault.

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“…Lee et al [8] used AE testing to detect a check valve under controlled flow loop conditions. Kaewwaewnoi et al [7] investigated the relationship between an internal fluid leak through a valve and the AE generated from the leak. Prateepasen et al [10] presented a low-cost instrument based on the AE technique to predict the leak rate.…”

Section: Introductionmentioning

confidence: 99%

Intelligent leak level recognition of gas pipeline valve using wavelet packet energy and support vector machine model

Zhang¹,

Li²,

Ji³

et al. 2013

Insight

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AEThis paper presents an acoustical signal analysis scheme model for intelligent recognition of the leak level of a gas pipeline valve. The scheme is based on wavelet packet energy theory and a support vector machine (SVM) model. In this approach, the acoustical signal of the leak is obtained using an acoustic emission (AE) sensor. The energy of each node at the fourth level of the wavelet packet decomposed signal is extracted as a leak feature for the SVM classification process. SVM is applied to perform recognition of the leak level and the performance of the classification process due to the kernel function for the SVM and classifier is evaluated in terms of its accuracy, Cohen's kappa and training time. The experimental results demonstrate that the intelligent recognition model based on the wavelet packet energy feature parameter and SVM classifier (with linear kernel function) is optimal for recognising the leak level of a gas pipeline valve.

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Investigation of the relationship between internal fluid leakage through a valve and the acoustic emission generated from the leakage

Cited by 77 publications

References 9 publications

Smart portable noninvasive instrument for detection of internal air leakage of a valve using acoustic emission signals

Smart portable noninvasive instrument for detection of internal air leakage of a valve using acoustic emission signals

Experimental investigation of the fault diagnosis of typical faults in reciprocating compressor valves

Intelligent leak level recognition of gas pipeline valve using wavelet packet energy and support vector machine model

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