Research Of The Remote Fault Diagnosis Expert System Based On Multi-reasoning And Feedback

With the development of modern science and technology, the manufacturing equipment is becoming more and more complex in the structure, perfect in function and automated development. So the fault diagnosis becoming more and more important which guarantees equipment security, highly effective and operates reliably. The real-time monitoring, timely treatment and diagnosis for the whole operation process of equipment not only has great economic benefits but also has far-reaching social significance. But now the traditional fault diagnosis techniques can not adapt to modern sophisticated machinery fault diagnosis request. Remote fault diagnosis and intelligent fault diagnosis have become an important research direction and an inevitable trend in the modern fault diagnosis research field.Through the analysis to fault diagnosis'content and method, as well as the trend of development, research the technology which adapts to complex equipment fault diagnosis at this stage. In this paper, fault monitoring expert system and remote fault diagnosis expert system which based on multi-reasoning mechanism and feedback are proposed.This dissertation's primary content as follows: First, based on the review of the failure diagnosis development process, this paper studied the theory and application of various methods, and we choose expert system as fault diagnosis method for manufacturing industry equipment finally; Second,this paper has analyzed the fault tree analytic method and the related concept about abductive reasoning, proposed fault tree model of the transmission chain, established a focus on monitoring expert system which based on abductive reasoning mechanism;Third, this paper has done the thorough research to the expert system which based on rule-based reasoning and the case-based reasoning, and introduced the feedback mechanism, established the remote failure diagnosis system.The fault monitoring expert system can greatly reduce the amount of data and improve the efficiency and quality of the monitoring system; The remote fault diagnosis based on multi-reasoning and feedback can solve the bottleneck problem of the knowledge acquisition, which is a self-learning, self-correcting and self-improving fault diagnosis expert system.