Research on the remote monitoring and fault diagnosis system of coal mine electromechanical equipment
On the basis of in-depth analysis of the particularity of equipment in the coal mine environment,this study fully integrates signal processing,machine learning and deep learning technologies,and designs and realizes a set of efficient remote monitoring and fault diagnosis system.Through automatic data collection and intelligent fault diagnosis,the system can effectively make up for the problems of traditional monitoring methods,such as large human resources investment and narrow monitoring coverage.Using advanced deep learning model,the system realizes real-time monitoring and automatic fault diagnosis,and improves the accuracy and timeliness of monitoring.The research results show that the system has successfully realized the comprehensive monitoring,automatic fault diagnosis and prediction and early warning in the practical application,provided innovative solutions for the management of coal mine mechanical and electrical equipment,and promoted the digital transformation of the coal mine industry.
万方数据
维普
