Research Article
Fault Diagnosis of Large-Scale Railway Maintenance Equipment Based on GA-RBF Neural Network
@INPROCEEDINGS{10.1007/978-3-031-28816-6_10, author={Hairui Wang and Yuanbo Li and Wenqi Zhang and Yusu Duan and Guifu Zhu}, title={Fault Diagnosis of Large-Scale Railway Maintenance Equipment Based on GA-RBF Neural Network}, proceedings={Context-Aware Systems and Applications. 11th EAI International Conference, ICCASA 2022, Vinh Long, Vietnam, October 27-28, 2022, Proceedings}, proceedings_a={ICCASA}, year={2023}, month={3}, keywords={Large-scale railway maintenance equipment Fault diagnosis RBF neural network optimized by genetic}, doi={10.1007/978-3-031-28816-6_10} }- Hairui Wang
Yuanbo Li
Wenqi Zhang
Yusu Duan
Guifu Zhu
Year: 2023
Fault Diagnosis of Large-Scale Railway Maintenance Equipment Based on GA-RBF Neural Network
ICCASA
Springer
DOI: 10.1007/978-3-031-28816-6_10
Abstract
At present, the large-scale railway maintenance equipment adopts a diesel engine as the main power plant. Therefore the diesel engine in the event of failure, will seriously affect the large-scale railway maintenance equipment of the normal work. Exploring advanced diesel engine condition monitoring and fault diagnosis technology and looking for practical and effective diesel engine fault diagnosis method, which has already become a research subject widely concerned by many experts at home and abroad. In this paper, genetic algorithm (GA) is used to optimize the parameters of radial basis function (RBF) neural network for diesel engine fault diagnosis, experimental results show the validity of this prediction method, and the accuracy of the proposed algorithm was verified by comparative.
