Fault diagnosis of turbo-generator based on RBF neural networks

Rui-Xin Li; Dong-Feng Wang; Pu Han; Jun Zhang

doi:10.1109/ICMLC.2003.1260116

Proceedings of the 2003 International Conference on Machine Learning and Cybernetics

Fault diagnosis of turbo-generator based on RBF neural networks

Year: 2003, Volume: 5, Pages: 3125,3126,3127,3128,3129

DOI Bookmark: 10.1109/ICMLC.2003.1260116

Authors

Rui-Xin Li, Coll. of Mech. Eng., Tianjin Univ., China
Dong-Feng Wang
Pu Han
Jun Zhang

Abstract

In this paper, the structure and working principle of Radial Basis Function (RBF) Neural Network (NN) are analyzed. A new method for constructing and training of parallel RBF-NN is proposed. A compound heuristic Genetic Algorithm (GA) based on Singular Value Decomposition (SVD) is introduced for structure training of RBF-NN. Based on the advanced strategies proposed above, RBF-NN is used for fault diagnosis of turbo-generator. Computer simulation experimental results show that the approach is effective.

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Fault diagnosis of turbo-generator based on RBF neural networks

Authors

Abstract

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