Evaluation of Internal Leak in Valve Using Acoustic Emission Method

Lee, Sang-Guk; Park, Jong Hyuck; Yoo, Keun Bae; Lee, Sun Ki; Hong, Sung-Yull

doi:10.4028/www.scientific.net/kem.326-328.661

Cited by 16 publications

(6 citation statements)

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“…The results demonstrated that the frequency components related with leakage could be clearly picked up from AE signal with background noise [23]. Lee et al studied the AE characteristics of leakage in two valves (the steam ball valve and water ball valve) under a situation of different leakage modes, and it can be concluded that the leakage rate of valves is directly proportional to the sound amplitude [24]. Recently, the rate of gas leakage of a valve was estimated by the theoretical relationship between the features of AE signals and internal leakage rate of valves [25].…”

Section: The Acoustic Emission (Ae) In Valvesmentioning

confidence: 99%

Nondestructive Detection of Valves Using Acoustic Emission Technique

Jin

Heng-hu

Hong

et al. 2015

Advances in Materials Science and Engineering

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The applications of acoustic emission (AE) technique in detection of valves are presented in this review, and the theoretical models and experimental results of nondestructive detection of valves using AE are provided. The generation of AE signals and the basic composition of AE detection system are briefly explained. The applications of AE technique in valves are focused on condition monitoring, failure, cavitation detection, and the development of portable measuring devices. All results prove that the AE technique works well in the detection of valves.

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Section: The Acoustic Emission (Ae) In Valvesmentioning

confidence: 99%

Nondestructive Detection of Valves Using Acoustic Emission Technique

Jin

Heng-hu

Hong

et al. 2015

Advances in Materials Science and Engineering

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“…Among them, AE technology is based on the principle that the transient elastic wave will be generated when the valve leaks and the AE signal will be sent out. The health state of the valve could be judged by collecting and analysing the valve internal leakage AE signal (VILAES) [4, 5]. As a dynamic detection method, the energy detected by AE technology comes from the measured object itself rather than provided by the detection instruments like ultrasonic and radiographic inspection technologies.…”

Section: Introductionmentioning

confidence: 99%

Mixed multiple‐variable modelling of acoustic emission signals for valve internal leakage detection

2021

IET Science Measure & Tech

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Theoretical analysis and experimental data show that the acoustic emission (AE) technology can detect the internal leakage state of the valve online. One of its key technologies is to determine the relationship between the characteristic of valve internal leakage AE signal (VILAES) and leakage rate and various parameters. However, most of the currently established models are a single-variable model. In addition, the repeated and verification experiments are rarely introduced, and most experiments are conducted under a large leakage rate. To this end, the mixed multiple-variable model is built to describe the relationship between the characteristics of VILAES and leakage rates, pressures, valve calibres and flow coefficients for the same type of valve. In the experiments, two rounds of experiments were performed for the same valve; then, a round of experiments was carried out after moving the sensor, and two rounds of experiments were conducted for two valves with the same parameters. In modelling, the VILAES is filtered first, and then the characteristics of the filtered signal are calculated. The mixed multiple-variable model is established by the leastsquares support vector machine. The results show that the mixed multiple-variable model could realise online internal leakage for valves with different calibres and flow coefficients under different pressures.

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“…Several kinds of techniques, including acoustic emission (AE) [4], vibration monitoring [5,6] and cavity dynamic pressure [7], have been used for the detection of valve internal leakage. Among these techniques, AE has witnessed a wide application in the detection of valve internal leakage both qualitatively and quantitatively, because it possesses the advantage of nonintrusive, high sensitivity and strong anti-interference ability [8][9][10].…”

Section: Introductionmentioning

confidence: 99%

Valve Internal Leakage Rate Quantification Based on Factor Analysis and Wavelet-BP Neural Network Using Acoustic Emission

Zhao

Zhu

et al. 2020

Applied Sciences

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Valve internal leakage is easily found because of various defects resulting from environmental factors and load fluctuation. The timely detection of valve internal leakage is of great significance to the safe operation of pipelines. As an effective means for detecting valve internal leakage, the acoustic emission technique is characterized by nonintrusive and strong anti-interference ability, which can realize the in situ monitoring of the valve running status in real time. In this paper, acoustic emission signals from an internal leaking valve were obtained experimentally. Then, the dimensionality reduction technology based on factor analysis was introduced to the processing of valve internal leakage detection data. Next, the wavelet decomposition was carried out to decompose the sample feature set into four subsets. Finally, the decomposed sample feature sets were inputted into the error backpropagation (BP) neural network quantitative model, respectively. The optimized results show that the predicted internal leakage rate by the wavelet-BP neural network model has good precision with an error of less than 10%. The wavelet-BP neural network model can realize the analysis of the valve internal leakage rate quantitatively and has good robustness, which provides technical support and guarantees the safe operation of natural gas pipeline valves.

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Evaluation of Internal Leak in Valve Using Acoustic Emission Method

Cited by 16 publications

References 0 publications

Nondestructive Detection of Valves Using Acoustic Emission Technique

Nondestructive Detection of Valves Using Acoustic Emission Technique

Mixed multiple‐variable modelling of acoustic emission signals for valve internal leakage detection

Valve Internal Leakage Rate Quantification Based on Factor Analysis and Wavelet-BP Neural Network Using Acoustic Emission

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