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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.
Afiliação
  • Xing K; School of Mines, China University of Mining and Technology, Xuzhou 221116, China.
  • Cheng J; Artificial Intelligence Research Institude, China University of Mining and Technology, Xuzhou 221116, China.
  • Wan Z; School of Mines, China University of Mining and Technology, Xuzhou 221116, China.
  • Sun X; School of Mines, China University of Mining and Technology, Xuzhou 221116, China.
  • Yan W; School of Mines, China University of Mining and Technology, Xuzhou 221116, China.
  • Lv J; School of Mines, China University of Mining and Technology, Xuzhou 221116, China.
  • Xue M; School of Mines, China University of Mining and Technology, Xuzhou 221116, China.
Sensors (Basel) ; 23(21)2023 Oct 31.
Article em En | MEDLINE | ID: mdl-37960552
ABSTRACT
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 0116306 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.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Revista: Sensors (Basel) Ano de publicação: 2023 Tipo de documento: Article País de afiliação: China

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Revista: Sensors (Basel) Ano de publicação: 2023 Tipo de documento: Article País de afiliação: China