现代科学仪器2024，Vol.41Issue(4)：43-49,7.
基于人工智能和深度学习的电力设备故障诊断方法
A Fault Diagnosis Method for Power Equipment Based on Artificial Intelligence and Deep Learning
李鹏刚 1刘伟轩 1王锋 1吴学煊 1王海龙 1夏金领1
作者信息
- 1. 天津浩源汇能股份有限公司,天津 301821
- 折叠
摘要
Abstract
A power equipment fault diagnosis method based on artificial intelligence and deep learning is proposed to address the issue of low accuracy caused by neglecting noise elimination in traditional association rule algorithms.By capturing signal changes during normal operation of the equipment,collecting frequency domain fault data,and mapping it into a comprehensive grayscale fault image using metric spatial distance,overfitting functions are used to eliminate image noise and obtain pure fault data.Artificial intelligence algorithms are used to fuse these data to form a single feature set of equipment fault vectors.A fault diagnosis model is constructed through deep learning,and vector data is input,Output fault types to achieve accurate diagnosis.The simulation experiment results show that this method has higher diagnostic accuracy and practical application value.关键词
人工智能/深度学习/电力设备/故障诊断Key words
artificial intelligence/deep learning/electrical equipment/fault diagnosis/分类
电子信息工程引用本文复制引用
李鹏刚,刘伟轩,王锋,吴学煊,王海龙,夏金领..基于人工智能和深度学习的电力设备故障诊断方法[J].现代科学仪器,2024,41(4):43-49,7.
