Research on Fault Diagnosis of Electrical Equipment Based on Deep Learning and Infrared Imaging Technology
- Resource Type
- Conference
- Authors
- Yang, Jingjing; Ma, Jinliang; Li, Mingming; Wang, Feifei
- Source
- 2023 IEEE 11th Joint International Information Technology and Artificial Intelligence Conference (ITAIC) Information Technology and Artificial Intelligence Conference (ITAIC), 2023 IEEE 11th Joint International. 11:195-199 Dec, 2023
- Subject
- Computing and Processing
Engineering Profession
Robotics and Control Systems
Fault diagnosis
Deep learning
Substations
Image color analysis
Big Data
Smart grids
Convolutional neural networks
electrical equipment
fault diagnosis
deep learning
infrared imaging
intelligence
- Language
- ISSN
- 2693-2865
The increasing number of unstructured data in electric power big data presents new challenges for the traditional processing method based on artificial diagnosis. As a typical unstructured data, infrared fault image is vital in researching electric power big data. Based on studying the fault diagnosis method of electrical equipment based on deep learning, this paper proposes image recognition technology based on deep learning for the intelligent diagnosis of infrared images of electrical equipment in the substation. On this basis, a model that can accurately and quickly diagnose most equipment faults in the substation is established to meet the requirements of the highly intelligent substation in constructing a smart grid.