Research on Fault Diagnosis System of Mine Hoist Based on BP Algorithm

This article introduces the research of a fault diagnosis system for mine hoists based on BP algorithm. The system aims to improve the reliability and safety of mine hoists. This article collected operational data of mine hoists and extracted fault data as the training set of the model. Then, a BP neural network model was established on the MATLAB software platform, and the model parameters were optimized and adjusted. Finally, use this model for real-time monitoring. The contribution of this study is to propose a fault diagnosis system for mine hoists based on BP algorithm. This system can achieve real-time monitoring of mine hoist data, while greatly improving the quality of diagnosis system’s judgment and prediction of mine hoist status. At the same time, the system has the function of data visualization, which enables users to understand the running status of the system more intuitively, and provides a more convenient and efficient operating platform for engineering technicians and managers.The controller is used to control all components to achieve stable operation; The sensor detects abnormal conditions in real time, such as overload or fault; It also provides information about the operation status and other related parameters. Finally, after receiving the data from the sensor, it will automatically adjust its parameters according to different operating modes.