Fault Information Processing And Reasoning Mechanism Research For Electric Traction Shearer

Electric traction shearer (ETS) is composed of several systems and it is also one of most complicated electronic systems in the coal mine. There is a high chance to get into trouble because of the extremely hard work condition and the worker's wrong operation. At present, these machines are regular checked and repaired by the technicians according to their past experience. With the mining equipment market competition becomes increasingly fierce and the product reliability requirements to be emphasized, the current method have not meeting these requirements yet. So, it is very important to start the research on the fault diagnosis information processing and reasoning mechanism for ETS, this work is the foundation to establish a set of ETS fault diagnosis expert system.Firstly, this paper introduced the intelligent theory of fault diagnosis, including the structure and working principle of expert system, emphasis on knowledge base and reasoning module. The theory and practicability of fault tree analysis (FTA) and expert system tool CLIPS was analyzed.Secondly, based on the fault-diagnosis data record, this paper analyzed the information structure and used the FTA method to build the ETS fault tree structure, according to the quality and quantity analyzing; and got the reason and affecting factors for fault. Finally, the author used VC++6.0 embedded CLIPS to establish a framework of ETS fault diagnosis expert system and gave an application case.In the end, the advantage and disadvantage of these methods was summarized and point out the direction for future work on this research.