Rotating Machine Fault Diagnosis Based on Optimal Morphological Filter and Local Tangent Space Alignment

Rotating Machine Fault Diagnosis Based on Optimal Morphological Filter and Local Tangent Space Alignment

In order to identify the fault of rotating machine effectively, a new method based on the morphological filter optimized by particle swarm optimization algorithm (PSO) and the nonlinear manifold learning algorithm local tangent space alignment (LTSA) is proposed. Firstly, the signal is purified by t...

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Bibliographic Details
Main Authors:	Shaojiang Dong, Lili Chen, Baoping Tang, Xiangyang Xu, Zhengyuan Gao, Juan Liu
Format:	Article
Language:	English
Published:	Hindawi Limited 2015-01-01
Series:	Shock and Vibration
Online Access:	http://dx.doi.org/10.1155/2015/893504

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