Rapid response neural network for rotor system diagnosis

Guanghua Xu; Lin Jiang; Liangsheng Qu

doi:10.1117/12.217507

28 August 1995 Rapid response neural network for rotor system diagnosis

Guanghua Xu, Lin Jiang, Liangsheng Qu

Proceedings Volume 2620, International Conference on Intelligent Manufacturing; (1995) https://doi.org/10.1117/12.217507
Event: International Conference on Intelligent Manufacturing, 1995, Wuhan, China

Abstract

With the rapid growth of industrial application of ANN, an intelligent diagnostic system for a large rotor system based on probabilistic neural network is developed and introduced into practice. Due to its intelligence and rapid response without human interference, it is called rapid response neural net (RRN). In this paper, the principles of construction, net architecture, and feature selection are discussed. Minimum information loss in preprocessing net and correct architecture selection are emphasized in constructing a PNN of high performance. In order to reduce the amount of real training data, the counterexamples of real data are adopted. Some training and testing results of RRN are given. The practical effects in two chemical complexes are analyzed. Both of them indicate that RRN possesses good function.

Citation Download Citation

Guanghua Xu, Lin Jiang, and Liangsheng Qu "Rapid response neural network for rotor system diagnosis", Proc. SPIE 2620, International Conference on Intelligent Manufacturing, (28 August 1995); https://doi.org/10.1117/12.217507

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