Research On Fault Diagnosis Expert System Of Shearer Based On Ontology

Shearer is one of the key equipment for underground coal mining, and its safe operation is a key factor to ensure safe production. Because of the complexity of its own structure, because of the complexity of its own structure, the coal mining machine is complicated, and there are various kinds of coupling and uncertain factors,which make the fault complex and difficult to be found. In this paper, the method of fuzzy reasoning and ontology is used to study the fault diagnosis technology of coal mining machine, which is of great significance to the safe operation of coal miner and to promote the efficient production of fully mechanized coal mining face.Firstly, based on the structure of the coal mining machine, the components of the coal mining machine are analyzed and the coal miner fault is collected and classified and sorted. The failure of the coal mining machine is divided into mechanical fault,electrical fault and hydraulic fault. Obtain the internal relationship between the fault source, the cause of the fault and the fault symptoms, summarize the characteristics of the shearer fault, and build the fault diagnosis model of the shearer.Secondly, based on the analysis of coal miner system and fault, a knowledge modeling method of coal miner fault knowledge based on descriptive logic is proposed. OWL DL language and protege ontology modeling tool are used to model the miner ontology, and the concept and attribute and instance of shearer is established, the rule base of coal miner is established by SWRL rule, and the logistic consistency check of Shearer fault knowledge is carried out.Thirdly, according to the characteristics of the complexity and uncertainty of the shearer's fault, this paper proposes a fuzzy reasoning system based on the three-tier structure by using the reasoning method of fuzzy reasoning and expert system. The system includes fuzzy knowledge base, fuzzy Reasoning machine, interpretation mechanism and man-machine interface, and the use of MySQL database for self-knowledge storage design of the shearer, including data structure design and data storage.Finally, the overall structure of the shearer fault diagnosis system is designed, and the expert system of coal miner fault diagnosis is developed by Java language and Jena API. The login module, the knowledge base management module, the fault diagnosis module and the help module are designed. The feasibility and effectiveness of the expert system of the shearer fault diagnosis system are proved by the failure of the historical fault instance, which is of great significance to the fault diagnosis field of the shearer.