Research and Application of Fault Prediction Technology for Coal Mining Equipment
To solve the problem of frequent equipment failures leading to unplanned shutdowns and affecting production efficiency in coal mining equipment operation,time-series alignment technology is used to process equipment monitoring data.A fault prediction model is constructed based on Long Short Term Memory(LSTM)network.By analyzing the data of the coal mining machine in Shangwan Coal Mine of Shendong Coal Group Company of National Energy Group,factors closely related to the faults are selected for model training and testing.The experimental results show that the model can effectively predict the overheating trip fault of the coal mining machine,achieving a 26 min advance early warning,significantly improving the safety and reliability of the equipment,and is of great significance for improving the fault early warning capability of coal mining equipment.
coal mining equipmentfault predcitionLong Short Term Memory Networktime series data
国家科技期刊平台
NSTL
万方数据
