Current development status of intelligent diagnosis technology for nuclear power equipment

Chaomin Gong; Shuming Chen; Weiwei Feng

doi:10.1117/12.3051493

18 November 2024 Current development status of intelligent diagnosis technology for nuclear power equipment

Chaomin Gong, Shuming Chen, Weiwei Feng

Author Affiliations +

Proceedings Volume 13403, International Conference on Algorithms, High Performance Computing, and Artificial Intelligence (AHPCAI 2024) ; 1340339 (2024) https://doi.org/10.1117/12.3051493
Event: International Conference on Algorithms, High Performance Computing, and Artificial Intelligence, 2024, Zhengzhou, China

Abstract

Nuclear power safety has always been a key focus within and outside the industry. To ensure the safe operation of nuclear power equipment, various methods have emerged, including empirical judgment, regular inspections, and expert systems. However, with the demand for automation and intelligence, traditional diagnostic methods and the inability to meet the current new situation, intelligent diagnosis has become a mainstream and trend. In recent years, intelligent diagnostic technology based on artificial intelligence has gradually attracted people's attention due to its unique advantages. This technology can accurately identify fault patterns and provide effective decision support by mining and analyzing a large amount of data, greatly improving work efficiency. This article aims to review the development of intelligent diagnostic technology, introduce the practical application of intelligent diagnostic technology, and provide suggestions for future improvements. Firstly, the core components, main diagnostic steps, and classification of diagnostic methods of intelligent diagnostic technology were elaborated. Secondly, some research and applications of intelligent diagnostic technology in nuclear power equipment were demonstrated, demonstrating its enormous potential in achieving automation and precise services. Then, the existing problems and shortcomings were pointed out, and corresponding improvement suggestions were proposed. This article focuses on the enormous potential of intelligent diagnostic technology in this field, and analyzes the challenges and development trends faced by nuclear power equipment diagnostic technology from three perspectives: model performance improvement, multimodal fusion, and interpretability.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Chaomin Gong, Shuming Chen, and Weiwei Feng "Current development status of intelligent diagnosis technology for nuclear power equipment", Proc. SPIE 13403, International Conference on Algorithms, High Performance Computing, and Artificial Intelligence (AHPCAI 2024) , 1340339 (18 November 2024); https://doi.org/10.1117/12.3051493

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KEYWORDS

Diagnostics

Data modeling

Nuclear power plants

Deep learning

Neural networks

Artificial intelligence

Machine learning

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