arXiv · 2411.17707
A Composite Fault Diagnosis Model for NPPs Based on Bayesian-EfficientNet Module
Abstract
This article focuses on the faults of important mechanical components such as pumps, valves, and pipelines in the reactor coolant system, main steam system, condensate system, and main feedwater system of nuclear power plants (NPPs). It proposes a composite multi-fault diagnosis model based on Bayesian algorithm and EfficientNet large model using data-driven deep learning fault diagnosis technology. The aim is to evaluate the effectiveness of automatic deep learning-based large model technology through transfer learning in nuclear power plant scenarios.
Explore related subjects
Keep this discovery
Siwei Li, Jiangwen Chen, Hua Lin, Wei Wang. 2024-11-13. A Composite Fault Diagnosis Model for NPPs Based on Bayesian-EfficientNet Module. https://arxiv.org/abs/2411.17707
Cite the original work for its findings. Save a collection to share your selection of sources.