With the rapid development of industrial automation and intelligent manufacturing,intelligent electrical equipment plays an increasingly important role in the production process.Equipment failures not only affect production efficiency but also pose safety hazards.Intelligent fault diagnosis technology for electrical equipment based on machine learning analyzes equipment operating data to achieve early fault detection and prevention.This study explores methods for monitoring the status and predicting faults of electrical equipment using deep learning algorithms,enhancing the accuracy and efficiency of fault diagnosis.The research results indicate that this technology can effectively reduce maintenance costs and improve the reliability of equipment operation.
维普
万方数据