Design and implementation of intelligent inspection system for coal mine mechanical equipment based on deep learning algorithm
This article introduces an intelligent inspection system for coal mining machinery based on deep learning algorithms,with a focus on utilizing Bidirectional Long Short-Term Memory(Bi-LSTM)Networks to process and analyze the operational status of the equipment.The system integrates modules for sensor data collection,data preprocessing,and the construction and optimization of deep learning models,thereby achieving efficient prediction and accurate detection of faults in coal mining machinery.Experimental results indicate that the Bi-LSTM network surpasses traditional ARIMA models and unidirectional LSTM networks in crucial performance metrics such as accuracy and F1-score,thereby validating the effectiveness and superiority of this system in the realm of intelligent inspection for coal mining machinery.
deep learningcoal mining machineryintelligent inspectionBidirectional Long Short-Term Memory Networks
万方数据
维普
