基于机器学习的智能电气设备故障诊断技术研究

Research on Intelligent Fault Diagnosis Technology for Electrical Equipment Based on Machine Learning

随着工业自动化和智能制造的快速发展,智能电气设备在生产过程中扮演着越来越重要的角色。设备故障不仅影响生产效率,还可能带来安全隐患。基于机器学习的智能电气设备故障诊断技术,通过分析设备运行数据,实现故障的早期识别与预防。本研究探讨了利用深度学习算法对电气设备进行状态监测和故障预测的方法,以提高故障诊断的准确性和效率。研究结果表明,该技术能够有效降低维护成本,提升设备运行的可靠性。

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.