Paper Title:
Studies of Synchronous Rotor Gear Monitoring Technique Based on Ant Colony Neural Network
  Abstract

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
Chapter
Chapter 1: Materials Science and Engineering
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, 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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