Study Of Intelligent Fault Diagnosis Technology Of Electrical Equipment Based On RS-FNN

For the occurrence maintenance to the mining electrical equipment, while fault occurs, what their symptoms appear certain fuzzy character. The paper then leads to fuzzy theory and take transformer for example. For the complexity fault phenomenon, if two faults take place at the same time, the rough sets are used to analyze. When a fault is made sure, the multi-layer neural network technology could locate its exact part of fault. The fault kind can be known by single neural network, while multi-layer neural network know not only the fault type, but also the part of fault part.The paper analyzes the technology of fault diagnosis of the electrical equipment. Subsequently, it designs the supervisory and detection system of electrical equipment online, which is carrying on between university and enterprise. The system is made of intelligence fault diagnosis of local area network and remote fault diagnosis. It means that we may develop a set of fault diagnosis according to electrical equipment of coal mine firstly before the technology of the remote fault diagnosis develops perfectly. The system has interface of internet, then it could be connected to internet and realize the remote fault diagnosis of electrical equipment.The paper leads the advanced fault diagnosis theory nowadays and internet technology to coal mine field. It enables electrical equipment of remote coal mine to be supervised and diagnosed remotely. Furthermore, it also resolves the problem of shortness of talent during the course of coal mine development.New complicated electrical equipment has widely been used in produce of coal mine. Traditional maintenance after fault has not meet the need of safe produce, so, supervisory and detection on electrical equipment of coal mine would realize the forecast maintenance. It will play an important to the safe produce and benefit of the coal mine.