Design and Application of Intelligent Maintenance System for Mechanical and Electrical Equipment in Underground Space Based on Deep Learning
An intelligent maintenance system for electromechanical equipment in underground space based on deep learning is designed.The system uses stacked noise reduction self encoder as the core of the fault detection model,through learning the inherent law of equipment operation data,to achieve effective detection of potential faults,and timely implement maintenance measures for electromechanical equipment based on the detection results.The results show that the system has good performance in the fault detection task of various underground space electromechanical equipment,and has high application potential.
NETL
NSTL
万方数据
