Deep-learning-based system-scale diagnosis of a nuclear power plant with multiple infrared cameras
Comprehensive condition monitoring of large industry systems such as nuclear power plants (NPPs) is essential for safety and maintenance. In this study, we developed novel system-scale diagnostic technology based on deep-learning and IR thermography that can efficiently and cost-effectively classify...
Main Authors: | Ik Jae Jin, Do Yeong Lim, In Cheol Bang |
---|---|
Format: | Article |
Language: | English |
Published: |
Elsevier
2023-02-01
|
Series: | Nuclear Engineering and Technology |
Subjects: | |
Online Access: | http://www.sciencedirect.com/science/article/pii/S1738573322004934 |
Similar Items
-
Bearing Fault Diagnosis via Improved One-Dimensional Multi-Scale Dilated CNN
by: Jiajun He, et al.
Published: (2021-11-01) -
A Review of Fault Diagnosis Methods for Rotating Machinery Using Infrared Thermography
by: Rongcai Wang, et al.
Published: (2022-09-01) -
Application of Fault Overlay Method and CNN in Infrared Image of Detecting Inter-Turn Short-Circuit in Dry-Type Transformer
by: Yen-Chih Huang, et al.
Published: (2022-12-01) -
An Evaluation of Gearbox Condition Monitoring Using Infrared Thermal Images Applied with Convolutional Neural Networks
by: Yongbo Li, et al.
Published: (2019-05-01) -
Bearing Fault Diagnosis Based on Multi-Scale CNN and Bidirectional GRU
by: Taher Saghi, et al.
Published: (2022-12-01)