Studies of Synchronous Rotor Gear Monitoring Technique Based on Ant Colony Neural Network

Abstract:

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In this paper, the nonlinear mapping relationship between characteristic parameters of failures and failure types is realized by using neural network through extracting characteristic variables of failures during operation of the gear. Aiming at the problems of neutral network such as slow convergence speed and existence of local minima, the neural network is optimized and the ant colony neural network is established by using the ant colony algorithm to realize rapid and accurate determination of failure status of a gear from characteristic parameters of failures. In addition, validity of the established model is verified through experiments.

Info:

Periodical:

Edited by:

Dongye Sun, Wen-Pei Sung and Ran Chen

Pages:

382-386

DOI:

10.4028/www.scientific.net/AMM.121-126.382

Citation:

Y. J. Chen and Q. H. Zhao, "Studies of Synchronous Rotor Gear Monitoring Technique Based on Ant Colony Neural Network", Applied Mechanics and Materials, Vols. 121-126, pp. 382-386, 2012

Online since:

October 2011

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Price:

$35.00

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