Research On Fault Diagnosis System Of Mine Hoist Based On BP Arithmetic

Along with the rapid development of modern industry and the science and technology, the structure of modern equipment is becoming more and more complex, so the security and reliability of the equipments' movement gets the universal attention of the society. Therefore, the technology of fault diagnosis has obtained rapid development this year in home and abroad.In end of 80's of last century, the scientist applied the artificial neural networks in the fault diagnosis. From then on, the neural network technology has held the important status in the field of intelligent fault diagnosis, because of its characteristics which include the real-time character, excellent anti-jamming ability, high accuracy of fault diagnosis.Aiming at the importance of mine hoist in mine production, this paper did the research on the current problem of mine hoist fault diagnosis. At first, I discussed the concept, characteristic and basic factors of the NN theory. Then, I took the most widespread neural network - BP neural network as the object of study to carry on discussion and comparison for several kinds of the improved BP study algorithm thoroughly.Afterwards, on the basis of the introduction of composition structure and work characteristic of mine hoist, unified the request of the fault diagnosis system, I developed the fault diagnosis system which took the BP neural network algorithmic as the core, took Borland C++ Builder as user interface, and took Matlab as backstage service routine. Finally, I applied this system in the fault diagnosis of mine hoist hydraulic pressure station module, which indicated that the performance this system conforms to requirement of fault diagnosis basically.