Motor Bearing Fault Source Localization Based on Sound and Robot Movement Characteristics

Manual inspection is often inefficient and easily misses detections for the extensive amount of mechanical equipment in industrial production. Incorporating acoustic measurement and diagnostics into mobile robots has multiple advantages. Utilizing the movement characteristics of the robot to search for the location with the best signal quality at different points can help it better adapt to the complex acoustic environment of industrial sites. The focus is on using nonsynchronous measurement technology, the robot can provide precise sequential movement, which can extend the lower frequency detection limit of the array. It is proved by simulation and experiments that the fault sound source of motor bearing can be accurately located based on robot moving characteristics. This method provides a valuable reference for non-contact monitoring of rotating machinery such as motors.

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Publication Details

Published
2024-10-31
DOI
https://doi.org/10.1109/icsmd64214.2024.10920535
Citations
3
Primary Topic
Industrial Technology and Control Systems
Type
article
Field-Weighted Citation Impact
0.98

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article

Motor Bearing Fault Source Localization Based on Sound and Robot Movement Characteristics

Guohua Sun, Xiaoxia Liang, Guojin Feng, Dong Zhen et al.
3 citations
Industrial Technology and Control Systems
0.98
article

Motor Bearing Fault Source Localization Based on Sound and Robot Movement Characteristics

Guohua Sun, Xiaoxia Liang, Guojin Feng, Dong Zhen, Fengshou Gu, Dong Lv
article en
3 citations

Abstract

Manual inspection is often inefficient and easily misses detections for the extensive amount of mechanical equipment in industrial production. Incorporating acoustic measurement and diagnostics into mobile robots has multiple advantages. Utilizing the movement characteristics of the robot to search for the location with the best signal quality at different points can help it better adapt to the complex acoustic environment of industrial sites. The focus is on using nonsynchronous measurement technology, the robot can provide precise sequential movement, which can extend the lower frequency detection limit of the array. It is proved by simulation and experiments that the fault sound source of motor bearing can be accurately located based on robot moving characteristics. This method provides a valuable reference for non-contact monitoring of rotating machinery such as motors.

University of Huddersfield (GB), Hebei University of Technology (CN), Chinese Academy of Sciences (CN), Institute of Acoustics (CN)
National Natural Science Foundation of China, Natural Science Foundation of Hebei Province
Climate action
Openalex Percentile: Top 22%
Industrial Technology and Control Systems
0.98
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Motor Bearing Fault Source Localization Based on Sound and Robot Movement Characteristics — Guohua Sun, Xiaoxia Liang, et al. · (2024) | TGRS Research Map | TGRS