Cargando…
Research on Signal Feature Extraction of Natural Gas Pipeline Ball Valve Based on the NWTD-WP Algorithm
The measured signals of internal leakage detection of the large-diameter pipeline ball valve in natural gas pipeline systems usually contain background noise, which will affect the accuracy of internal leakage detection and sound localization of internal leakage points due to the interference of noi...
Autores principales: | , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2023
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10222710/ https://www.ncbi.nlm.nih.gov/pubmed/37430703 http://dx.doi.org/10.3390/s23104790 |
_version_ | 1785049764582129664 |
---|---|
author | Yang, Lingxia Li, Shuxun Wang, Zhihui Hou, Jianjun Zhang, Xuedong |
author_facet | Yang, Lingxia Li, Shuxun Wang, Zhihui Hou, Jianjun Zhang, Xuedong |
author_sort | Yang, Lingxia |
collection | PubMed |
description | The measured signals of internal leakage detection of the large-diameter pipeline ball valve in natural gas pipeline systems usually contain background noise, which will affect the accuracy of internal leakage detection and sound localization of internal leakage points due to the interference of noise. Aiming at this problem, this paper proposes an NWTD-WP feature extraction algorithm by combining the wavelet packet (WP) algorithm and the improved two-parameter threshold quantization function. The results show that the WP algorithm has a good feature extraction effect on the valve leakage signal, and the improved threshold quantization function can avoid the defects of the traditional soft threshold function and hard threshold function, such as discontinuity and the pseudo-Gibbs phenomenon, when reconstructing the signal. The NWTD-WP algorithm is effective in extracting the features of the measured signals with low signal/noise ratio. The denoise effect is much better than that of the traditional soft and hard threshold quantization functions. It proved that the NWTD-WP algorithm can be used for studying the existing safety valve leakage vibration signals in the laboratory and the internal leakage signals of the scaled-down model of the large-diameter pipeline’s ball valve. |
format | Online Article Text |
id | pubmed-10222710 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-102227102023-05-28 Research on Signal Feature Extraction of Natural Gas Pipeline Ball Valve Based on the NWTD-WP Algorithm Yang, Lingxia Li, Shuxun Wang, Zhihui Hou, Jianjun Zhang, Xuedong Sensors (Basel) Article The measured signals of internal leakage detection of the large-diameter pipeline ball valve in natural gas pipeline systems usually contain background noise, which will affect the accuracy of internal leakage detection and sound localization of internal leakage points due to the interference of noise. Aiming at this problem, this paper proposes an NWTD-WP feature extraction algorithm by combining the wavelet packet (WP) algorithm and the improved two-parameter threshold quantization function. The results show that the WP algorithm has a good feature extraction effect on the valve leakage signal, and the improved threshold quantization function can avoid the defects of the traditional soft threshold function and hard threshold function, such as discontinuity and the pseudo-Gibbs phenomenon, when reconstructing the signal. The NWTD-WP algorithm is effective in extracting the features of the measured signals with low signal/noise ratio. The denoise effect is much better than that of the traditional soft and hard threshold quantization functions. It proved that the NWTD-WP algorithm can be used for studying the existing safety valve leakage vibration signals in the laboratory and the internal leakage signals of the scaled-down model of the large-diameter pipeline’s ball valve. MDPI 2023-05-16 /pmc/articles/PMC10222710/ /pubmed/37430703 http://dx.doi.org/10.3390/s23104790 Text en © 2023 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Yang, Lingxia Li, Shuxun Wang, Zhihui Hou, Jianjun Zhang, Xuedong Research on Signal Feature Extraction of Natural Gas Pipeline Ball Valve Based on the NWTD-WP Algorithm |
title | Research on Signal Feature Extraction of Natural Gas Pipeline Ball Valve Based on the NWTD-WP Algorithm |
title_full | Research on Signal Feature Extraction of Natural Gas Pipeline Ball Valve Based on the NWTD-WP Algorithm |
title_fullStr | Research on Signal Feature Extraction of Natural Gas Pipeline Ball Valve Based on the NWTD-WP Algorithm |
title_full_unstemmed | Research on Signal Feature Extraction of Natural Gas Pipeline Ball Valve Based on the NWTD-WP Algorithm |
title_short | Research on Signal Feature Extraction of Natural Gas Pipeline Ball Valve Based on the NWTD-WP Algorithm |
title_sort | research on signal feature extraction of natural gas pipeline ball valve based on the nwtd-wp algorithm |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10222710/ https://www.ncbi.nlm.nih.gov/pubmed/37430703 http://dx.doi.org/10.3390/s23104790 |
work_keys_str_mv | AT yanglingxia researchonsignalfeatureextractionofnaturalgaspipelineballvalvebasedonthenwtdwpalgorithm AT lishuxun researchonsignalfeatureextractionofnaturalgaspipelineballvalvebasedonthenwtdwpalgorithm AT wangzhihui researchonsignalfeatureextractionofnaturalgaspipelineballvalvebasedonthenwtdwpalgorithm AT houjianjun researchonsignalfeatureextractionofnaturalgaspipelineballvalvebasedonthenwtdwpalgorithm AT zhangxuedong researchonsignalfeatureextractionofnaturalgaspipelineballvalvebasedonthenwtdwpalgorithm |