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Proceedings Paper

Prognosis of vibration condition for large turbo-generator set using artificial neural network
Author(s): Shuyi Pei; Xiao Li; Liangsheng Qu
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Paper Abstract

The prognosis of vibration condition for a turbo-generator set using artificial neural networks is raised in this paper. Its effectiveness is compared with the traditional prediction method using auto regressive (AR) model. Moreover, a synthetical prediction method based on multi- factor inputs is presented. The results indicate that the accuracy of prognosis using neural networks is higher and more effective.

Paper Details

Date Published: 28 August 1995
PDF: 6 pages
Proc. SPIE 2620, International Conference on Intelligent Manufacturing, (28 August 1995); doi: 10.1117/12.217531
Show Author Affiliations
Shuyi Pei, Xi'an Jiaotong Univ. (China)
Xiao Li, Xi'an Jiaotong Univ. (China)
Liangsheng Qu, Xi'an Jiaotong Univ. (China)


Published in SPIE Proceedings Vol. 2620:
International Conference on Intelligent Manufacturing
Shuzi Yang; Ji Zhou; Cheng-Gang Li, Editor(s)

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