Rotating Machine Fault Diagnosis Based on Optimal Morphological Filter and Local Tangent Space Alignment
Joint Authors
Xia, Ming
Tang, Baoping
Chen, Lili
Xu, Xiangyang
Gao, Zhengyuan
Dong, Shaojiang
Source
Issue
Vol. 2015, Issue 2015 (31 Dec. 2015), pp.1-9, 9 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2015-09-20
Country of Publication
Egypt
No. of Pages
9
Main Subjects
Abstract EN
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 the morphological filter; the filter’s structure element (SE) is selected by PSO method.
Then the filtered signals are decomposed by the empirical mode decomposition (EMD) method, and the extract features are mapped into the LTSA to extract the character features; then the support vector machine (SVM) model is used to achieve the rotating machine fault diagnosis.
The proposed method is evaluated by vibration signals measured from bearings with faults.
Results show that the method can effectively remove the noise and extract the fault features, so the rotating machine fault diagnosis can be achieved effectively.
American Psychological Association (APA)
Dong, Shaojiang& Chen, Lili& Tang, Baoping& Xu, Xiangyang& Gao, Zhengyuan& Xia, Ming. 2015. Rotating Machine Fault Diagnosis Based on Optimal Morphological Filter and Local Tangent Space Alignment. Shock and Vibration،Vol. 2015, no. 2015, pp.1-9.
https://search.emarefa.net/detail/BIM-1078378
Modern Language Association (MLA)
Dong, Shaojiang…[et al.]. Rotating Machine Fault Diagnosis Based on Optimal Morphological Filter and Local Tangent Space Alignment. Shock and Vibration No. 2015 (2015), pp.1-9.
https://search.emarefa.net/detail/BIM-1078378
American Medical Association (AMA)
Dong, Shaojiang& Chen, Lili& Tang, Baoping& Xu, Xiangyang& Gao, Zhengyuan& Xia, Ming. Rotating Machine Fault Diagnosis Based on Optimal Morphological Filter and Local Tangent Space Alignment. Shock and Vibration. 2015. Vol. 2015, no. 2015, pp.1-9.
https://search.emarefa.net/detail/BIM-1078378
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1078378