Frontiers of Mechanical Engineering >

2010 , Vol. 5 >Issue 1: 118 - 124

DOI: https://doi.org/10.1007/s11465-009-0084-z

Research articles

Intelligent diagnosis methods for plant machinery

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  • 1.Diagnosis and Self-recovery Engineering Research Center, Beijing University of Chemical Technology, Beijing 100029, China; 2.Graduate School of Bioresources, Mie University, Mie 514–8507, Japan; 3.College of Mechanical Engineering, Jiamusi University, Jiamusi 154007, China;

Published date: 05 Mar 2010

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Abstract

This paper reports several intelligent diagnostic approaches based on artificial neural network and fuzzy algorithm for plant machinery, such as the diagnosis method using the wavelet transform, rough sets, and fuzzy neural network; the diagnosis method based on the sequential inference and fuzzy neural network; the diagnosis approach by the possibility theory and certainty factor model; and the diagnosis method on the basis of the adaptive filtering technique and fuzzy neural network. These intelligent diagnostic methods have been successfully applied to condition diagnosis in different types of practical plant machinery.

Key words： intelligent diagnosis; neural network; fuzzy algorithm; adaptive filtering; plant machinery

Cite this article

Huaqing WANG, Peng CHEN, Shuming WANG, . Intelligent diagnosis methods for plant machinery[J]. Frontiers of Mechanical Engineering, 2010 , 5(1) : 118 -124 . DOI: 10.1007/s11465-009-0084-z

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