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Extraction and Application of Hydraulic Support Safety Valve Characteristic Parameters Based on Roof Pressure Data
The safety valves of powered supports control the maximum working resistance, and their statuses must be known to ensure the safety of both the support and the overlying strata. However, the inspection of powered support valves involves manual or semiautomated operations, the costs of which are high...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10649293/ https://www.ncbi.nlm.nih.gov/pubmed/37960552 http://dx.doi.org/10.3390/s23218853 |
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author | Xing, Keke Cheng, Jingyi Wan, Zhijun Sun, Xin Yan, Wanzi Lv, Jiakun Xue, Minti |
author_facet | Xing, Keke Cheng, Jingyi Wan, Zhijun Sun, Xin Yan, Wanzi Lv, Jiakun Xue, Minti |
author_sort | Xing, Keke |
collection | PubMed |
description | The safety valves of powered supports control the maximum working resistance, and their statuses must be known to ensure the safety of both the support and the overlying strata. However, the inspection of powered support valves involves manual or semiautomated operations, the costs of which are high. In this study, an extreme point extraction method was developed for the determination of the characteristic parameters of safety valves using roof pressure data, and a safety valve state monitoring module was constructed. Using the longwall face of 0116(3)06 with top coal caving in the Mindong Mine as an example, the characteristic parameters of the safety valves were extracted, including the peak, reseating, and blowdown pressures, as well as the recovery and unloading durations. The results of the field tests showed the following: (1) The amplitude threshold method based on extreme points can be used to accurately extract characteristic parameters, and the distribution of the characteristic parameters of the safety valves follows either a Gaussian or an exponential distribution. (2) The mining pressure analysis results, derived from the characteristic parameters, closely align with the in situ mining pressure observations. This method can be used for the online monitoring of safety valve conditions, increasing the operational efficiency and quality of safety valve inspections. |
format | Online Article Text |
id | pubmed-10649293 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-106492932023-10-31 Extraction and Application of Hydraulic Support Safety Valve Characteristic Parameters Based on Roof Pressure Data Xing, Keke Cheng, Jingyi Wan, Zhijun Sun, Xin Yan, Wanzi Lv, Jiakun Xue, Minti Sensors (Basel) Article The safety valves of powered supports control the maximum working resistance, and their statuses must be known to ensure the safety of both the support and the overlying strata. However, the inspection of powered support valves involves manual or semiautomated operations, the costs of which are high. In this study, an extreme point extraction method was developed for the determination of the characteristic parameters of safety valves using roof pressure data, and a safety valve state monitoring module was constructed. Using the longwall face of 0116(3)06 with top coal caving in the Mindong Mine as an example, the characteristic parameters of the safety valves were extracted, including the peak, reseating, and blowdown pressures, as well as the recovery and unloading durations. The results of the field tests showed the following: (1) The amplitude threshold method based on extreme points can be used to accurately extract characteristic parameters, and the distribution of the characteristic parameters of the safety valves follows either a Gaussian or an exponential distribution. (2) The mining pressure analysis results, derived from the characteristic parameters, closely align with the in situ mining pressure observations. This method can be used for the online monitoring of safety valve conditions, increasing the operational efficiency and quality of safety valve inspections. MDPI 2023-10-31 /pmc/articles/PMC10649293/ /pubmed/37960552 http://dx.doi.org/10.3390/s23218853 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 Xing, Keke Cheng, Jingyi Wan, Zhijun Sun, Xin Yan, Wanzi Lv, Jiakun Xue, Minti Extraction and Application of Hydraulic Support Safety Valve Characteristic Parameters Based on Roof Pressure Data |
title | Extraction and Application of Hydraulic Support Safety Valve Characteristic Parameters Based on Roof Pressure Data |
title_full | Extraction and Application of Hydraulic Support Safety Valve Characteristic Parameters Based on Roof Pressure Data |
title_fullStr | Extraction and Application of Hydraulic Support Safety Valve Characteristic Parameters Based on Roof Pressure Data |
title_full_unstemmed | Extraction and Application of Hydraulic Support Safety Valve Characteristic Parameters Based on Roof Pressure Data |
title_short | Extraction and Application of Hydraulic Support Safety Valve Characteristic Parameters Based on Roof Pressure Data |
title_sort | extraction and application of hydraulic support safety valve characteristic parameters based on roof pressure data |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10649293/ https://www.ncbi.nlm.nih.gov/pubmed/37960552 http://dx.doi.org/10.3390/s23218853 |
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