The Research Of Mine Hoist Fault Diagnosis System Based On Embedded

The mine hoist system is one of the mine four systems, known as the throat of the mine, hoist system security is very important. From the protection mode of thinking ahead of departure to study the failure of elevator harbinger of early failures and to make forecasts is currently a challenge.In this paper, researching and designing the fault diagnosis of hoist , general discussion the composition of the mine hoist ,and making the fault analysis of its various parts. The ARM S3C2440 as the core to design of embedded data acquisition hardware system, and is based on linux operating system to enhance the development of the driver of data acquisition part of high accuracy and fast speed.Integrated test and diagnostic techniques of modern intelligence, researched and developed fault diagnosis system of hoist based on BP neural network. Application of three-layer BP neural network can realize an arbitrary non-linear input-output relationship, used in the fault pattern recognition, the results are convergent solution. Therefore, we introduced intelligence BP network in the process of the diagnosis.using a variety of failure information as samples, using Matlab toolbox for simulation, to some failures as an example of the network training, the trained neural network has been tested and reached effects of a diagnosis, can reach the identification of hoist failure mode.