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Please use this identifier to cite or link to this item: http://repository.iitr.ac.in/handle/123456789/23792
Title: Fault diagnosis of rolling element bearing using autonomous harmonic product spectrum method
Authors: Patil A.P.
Mishra, B. K.
Harsha, Suraj Prakash
Published in: Proceedings of the Institution of Mechanical Engineers, Part K: Journal of Multi-body Dynamics
Abstract: Maintenance planning plays a critical role in the process industry, where any unplanned maintenance may lead to a significant loss. Condition monitoring happens to aid maintenance planning and has become an inherent part of the maintenance activity. Physical parameters such as vibration, acoustic emission, current, etc., are used for condition monitoring, out of which vibration is the most preferred parameter and is widely used in the industry. Vibration data is measured near to bearings, which themselves are monitored for their condition, and hence rolling element bearing (REB) is the focus of this study. REBs are monitored for the presence of a fault in them as well as for their severity. Fault diagnosis of REB using harmonic product spectrum (HPS) is proposed in this study. The proposed methodology's novelty lies in the signal pre-processing step, whose output is fed to the HPS method, which is used for defective raceway identification. The efficacy of HPS is assessed with parameter optimized Variational mode decomposition (VMD) and classical bandpass filtering method as pre-processors. It is observed that the HPS delivers better diagnostic results with the VMD method than the bandpass filtering method. Non-dominated sorting particle swarm optimization algorithm is deployed for parameter optimization of VMD. HPS combined with VMD as pre-processor forms an autonomous HPS(AHPS) algorithm, whose input is measured signal and output is defect frequency. The process is so designed that a raw signal, when fed to the algorithm, delivers the result as identification of a defective raceway. Unlike previously developed methods, the proposed method needs no manual intervention. Results obtained from simulated signals and signals recorded through experiments validate that the proposed methodology can be used effectively for fault diagnosis of REB. © IMechE 2021.
Citation: Proceedings of the Institution of Mechanical Engineers, Part K: Journal of Multi-body Dynamics, 235(3): 396-411
URI: https://doi.org/10.1177/1464419321994986
http://repository.iitr.ac.in/handle/123456789/23792
Issue Date: 2021
Publisher: SAGE Publications Ltd
Keywords: bandpass filtering
Harmonic product spectrum
kurtogram
particle swarm optimization
variational mode decomposition
ISSN: 14644193
Author Scopus IDs: 57220665728
55578538300
6603548398
Author Affiliations: Patil, A.P., Department of Mechanical and Industrial Engineering, Indian Institute of Technology, Roorkee, India
Mishra, B.K., Department of Mechanical and Industrial Engineering, Indian Institute of Technology, Roorkee, India
Harsha, S.P., Department of Mechanical and Industrial Engineering, Indian Institute of Technology, Roorkee, India
Funding Details: The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This study is sponsored by the All India Council for Technical Education India under the Quality Improvement Programme. All India Council for Technical Education, अभातशिप
Corresponding Author: Patil, A.P.; Department of Mechanical and Industrial Engineering, India; email: apatil@me.iitr.ac.in
Appears in Collections:Journal Publications [ME]

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