Mixed multiple‐variable modelling of acoustic emission signals for valve internal leakage detection
Abstract 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 leak...
Main Authors: | , , |
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Format: | Article |
Language: | English |
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Wiley
2021-08-01
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Series: | IET Science, Measurement & Technology |
Subjects: | |
Online Access: | https://doi.org/10.1049/smt2.12049 |
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author | Guo‐Yang Ye Ke‐Jun Xu Wen‐Kai Wu |
author_facet | Guo‐Yang Ye Ke‐Jun Xu Wen‐Kai Wu |
author_sort | Guo‐Yang Ye |
collection | DOAJ |
description | Abstract 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 least‐squares 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. |
first_indexed | 2024-04-12T20:53:04Z |
format | Article |
id | doaj.art-ee62cdd750b144d083b8a986db83255e |
institution | Directory Open Access Journal |
issn | 1751-8822 1751-8830 |
language | English |
last_indexed | 2024-04-12T20:53:04Z |
publishDate | 2021-08-01 |
publisher | Wiley |
record_format | Article |
series | IET Science, Measurement & Technology |
spelling | doaj.art-ee62cdd750b144d083b8a986db83255e2022-12-22T03:17:05ZengWileyIET Science, Measurement & Technology1751-88221751-88302021-08-0115648749810.1049/smt2.12049Mixed multiple‐variable modelling of acoustic emission signals for valve internal leakage detectionGuo‐Yang Ye0Ke‐Jun Xu1Wen‐Kai Wu2School of Electrical and Automation Engineering Hefei University of Technology Hefei ChinaSchool of Electrical and Automation Engineering Hefei University of Technology Hefei ChinaSchool of Electrical and Automation Engineering Hefei University of Technology Hefei ChinaAbstract 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 least‐squares 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.https://doi.org/10.1049/smt2.12049Signal detectionInterpolation and function approximation (numerical analysis)Digital signal processingNumerical analysisTestingMechanical components, systems and devices |
spellingShingle | Guo‐Yang Ye Ke‐Jun Xu Wen‐Kai Wu Mixed multiple‐variable modelling of acoustic emission signals for valve internal leakage detection IET Science, Measurement & Technology Signal detection Interpolation and function approximation (numerical analysis) Digital signal processing Numerical analysis Testing Mechanical components, systems and devices |
title | Mixed multiple‐variable modelling of acoustic emission signals for valve internal leakage detection |
title_full | Mixed multiple‐variable modelling of acoustic emission signals for valve internal leakage detection |
title_fullStr | Mixed multiple‐variable modelling of acoustic emission signals for valve internal leakage detection |
title_full_unstemmed | Mixed multiple‐variable modelling of acoustic emission signals for valve internal leakage detection |
title_short | Mixed multiple‐variable modelling of acoustic emission signals for valve internal leakage detection |
title_sort | mixed multiple variable modelling of acoustic emission signals for valve internal leakage detection |
topic | Signal detection Interpolation and function approximation (numerical analysis) Digital signal processing Numerical analysis Testing Mechanical components, systems and devices |
url | https://doi.org/10.1049/smt2.12049 |
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