Research On Remote Monitoring And Fault Diagnosis System For Mine Hoist System Based On Neural Network

Fault diagnosis of Mine hoist is always a quite require and significative task in the field of coal mine security. The text makes research and design for the realization of the fault diagnosis of Mine hoist break system. According to the characteristic of Mine hoist break system, adopting the manual neural network BP arithmetic and using the prevalent embedded system to gather data, the text realizes the fault diagnosis of Mine hoist braking system.At the first, the text simply the monitor measure and the system constitution of Mine hoist equipment at present, and introduces the general situation of the manual Neural Network, nitially introduced the neural network study method and also emphasizes the applying of it in the hoist fault diagnosis;Then, according to use embedded system to carry on the hardware design to have the low power loss, the integration rate high, volume small, the cost is low and so on the superior artillery, we choosing section performance outstanding ARM chip S3C44B0X, designed the hardware connection electric circuit. Because S3C44B0X does not have MMU, this causes the system does not have enough hardware support hypothesized memory management technology, therefore this system uses μClinux embedded operating system.Finally, through research to the elevator braking system, we established fault diagnosis system based on the BP neural network, and makes certain the number of neural cell in every layer of Neural Network in the basis of fault diagnosis' practicality needs, in order to realize the training of the network. Through the analysis of the simulation, we prove the feasibility of this design.