Chapter
Sep 21, 2015
Fault Diagnosis for the Gearbox of a High-Speed Train on Generalized Congruence Neural Networks
Publication: ICTE 2015
Abstract
Aiming at the existence of convergence is very slow and there are many local minima problems of BP neural network, put forward an improved generalized congruence neural network (GCNN). Improved GCNN neural network has better generalization ability, learning speed, small relative error, easy to operate. The GCNN applied to fault diagnosis examples of high-speed train gearbox, experiments show that: GCNN neural network can achieve the status of intelligent gearbox fault diagnosis effectively, recognize and classify the pattern effectively, complete fault intelligent diagnosis.
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Published In
ICTE 2015
Pages: 2209 - 2215
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© 2015 American Society of Civil Engineers.
History
Published online: Sep 21, 2015
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National Laboratory for Rail Transportation, Southwest Jiaotong University, Chengdu 610031, China. E-mail: [email protected]
School of Transportation and Logistics, Southwest Jiaotong University, Chengdu 610031, China. E-mail: [email protected]
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ASCE Library Cards let you download journal articles, proceedings papers, and available book chapters across the entire ASCE Library platform. ASCE Library Cards remain active for 24 months or until all downloads are used. Note: This content will be debited as one download at time of checkout.
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Terms of Use: ASCE Library Cards are for individual, personal use only. Reselling, republishing, or forwarding the materials to libraries or reading rooms is prohibited.