Paper
12 December 2024 Fault diagnosis of rolling bearings based on parabolic acoustic mirror and support vector machine
Siwei Huang, Fang Liu, Xin Huang, Zehua Li, Hongqing Chen, Ziyu Yuan, Yongbin Liu
Author Affiliations +
Proceedings Volume 13439, Fourth International Conference on Testing Technology and Automation Engineering (TTAE 2024); 134390V (2024) https://doi.org/10.1117/12.3055389
Event: Fourth International Conference on Testing Technology and Automation Engineering (TTAE 2024), 2024, Xiamen, China
Abstract
In this paper, a new method for bearing acoustic detection is proposed based on the parabolic acoustic mirror, which uses the parabolic acoustic mirror instead of the traditional bearing end cap, places a directional microphone at the focal point of the parabolic acoustic mirror, and focuses the fault information signal emitted by the bearing at the directional microphone after the reflection of the parabolic acoustic mirror to achieve gain acquisition. At the same time, due to the inherent properties of the parabola, the non-parallel incident sound waves cannot converge at the focal point, so as to realize the directional acquisition of the bearing fault signal. Combined with the support vector machine, the acoustic features are extracted, and the high-dimensional features are reduced to three-dimensional features by using the KJADE algorithm, and they are input into the support vector machine as feature vectors for identification and classification of various bearings. Experiments show that the proposed method can accurately classify bearing faults.
(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.
Siwei Huang, Fang Liu, Xin Huang, Zehua Li, Hongqing Chen, Ziyu Yuan, and Yongbin Liu "Fault diagnosis of rolling bearings based on parabolic acoustic mirror and support vector machine", Proc. SPIE 13439, Fourth International Conference on Testing Technology and Automation Engineering (TTAE 2024), 134390V (12 December 2024); https://doi.org/10.1117/12.3055389
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KEYWORDS
Acoustics

Parabolic mirrors

Vibration

Feature extraction

Support vector machines

Signal processing

Machine learning

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