DATA-DRIVEN METHOD FOR ACCURATELY IDENTIFYING THE FAULT SOURCE OF HYDRAULIC SUPPORT SYSTEM

The invention provides a data-driven method for accurately identifying the fault source of hydraulic support system. First, when the hydraulic support system fails, the abnormal data mining method is used to accurately separate the abnormal working parameters, and then they are input into Bayesian n...

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Bibliographische Detailangaben
Hauptverfasser:	SHU Tong, WANG Enyuan, LIU Jinhu, FENG Xingzhen, CHEN Qinghua, LI Jianfeng, ZHAO Jiyun, SHI Binghua, WANG Jinxin
Format:	Patent
Sprache:	eng
Schlagworte:	CALCULATING COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS COMPUTING CONTROL OR REGULATING SYSTEMS IN GENERAL CONTROLLING COUNTING EARTH DRILLING FIXED CONSTRUCTIONS FUNCTIONAL ELEMENTS OF SUCH SYSTEMS MINING MINING OR QUARRYING MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS ORELEMENTS PHYSICS REGULATING
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Beschreibung
Zusammenfassung:	The invention provides a data-driven method for accurately identifying the fault source of hydraulic support system. First, when the hydraulic support system fails, the abnormal data mining method is used to accurately separate the abnormal working parameters, and then they are input into Bayesian network as symptom nodes. Through Bayesian network decoupling operation, the real fault source causing the failure can be accurately found, and the coupling relationship of different faults in the hydraulic support system on abnormal symptoms can be effectively decoupled, so that the diagnosis result is more accurate, which provides technical guidance for the maintenance and management of the hydraulic support system.