A Morphological Filtering Method Based on Particle Swarm Optimization for Railway Vehicle Bearing Fault Diagnosis
Joint Authors
Huang, Yan
Lin, Jianhui
Liu, Zechao
Huang, Chenguang
Source
Issue
Vol. 2019, Issue 2019 (31 Dec. 2019), pp.1-16, 16 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2019-12-24
Country of Publication
Egypt
No. of Pages
16
Main Subjects
Abstract EN
With the rapid development of high-speed railway, the fault diagnosis of railway vehicles has become more and more important for ensuring the operating safety.
The MF is a nonlinear signal processing method which can extract the modulated faulty information via reshaping the analyzed signal.
However, the choices of operators and structure elements (SE) are numerous and complicated to determine the best MF solution for different bearing faulty signals.
In this paper, the particle swarm optimization (PSO) was introduced to optimize the effect of MF among several classical MF operators and different SE parameters.
The proposed method applied PSO to select the best MF result with respect to the fitness function adopting kurtosis.
A set of bearing signals with additional interference of wheel-track excitement are analyzed to verify the effectiveness of the proposed method.
The results demonstrated that the proposed method is capable of obtaining the optimized solution and accurately extracting the fault information.
Furthermore, the shaft rotation frequency and wheel-track interference were reduced by the proposed method.
American Psychological Association (APA)
Huang, Yan& Lin, Jianhui& Liu, Zechao& Huang, Chenguang. 2019. A Morphological Filtering Method Based on Particle Swarm Optimization for Railway Vehicle Bearing Fault Diagnosis. Shock and Vibration،Vol. 2019, no. 2019, pp.1-16.
https://search.emarefa.net/detail/BIM-1211055
Modern Language Association (MLA)
Huang, Yan…[et al.]. A Morphological Filtering Method Based on Particle Swarm Optimization for Railway Vehicle Bearing Fault Diagnosis. Shock and Vibration No. 2019 (2019), pp.1-16.
https://search.emarefa.net/detail/BIM-1211055
American Medical Association (AMA)
Huang, Yan& Lin, Jianhui& Liu, Zechao& Huang, Chenguang. A Morphological Filtering Method Based on Particle Swarm Optimization for Railway Vehicle Bearing Fault Diagnosis. Shock and Vibration. 2019. Vol. 2019, no. 2019, pp.1-16.
https://search.emarefa.net/detail/BIM-1211055
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1211055