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 |
| Published: |
Wiley
2021-08-01
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| Series: | IET Science, Measurement & Technology |
| Subjects: | |
| Online Access: | https://doi.org/10.1049/smt2.12049 |
| Summary: | 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. |
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| ISSN: | 1751-8822 1751-8830 |