Motor diagnosis based on vibration imaging and CNN

ZhiYuan Xu; Zhuo Long; Libing Ren; Gongping Wu

doi:10.1117/12.3014951

4 March 2024 Motor diagnosis based on vibration imaging and CNN

ZhiYuan Xu, Zhuo Long, Libing Ren, Gongping Wu

Proceedings Volume 12981, Ninth International Symposium on Sensors, Mechatronics, and Automation System (ISSMAS 2023); 129813I (2024) https://doi.org/10.1117/12.3014951
Event: 9th International Symposium on Sensors, Mechatronics, and Automation (ISSMAS 2023), 2023, Nanjing, China

Abstract

In modern industry, motor failures are difficult to avoid. Traditional diagnosis methods are limited by feature extraction, and manual feature extraction can cause great variability. This paper proposes a diagnosis method based on vibration image and Convolutional Neural Network (CNN). By normalizing and binarizing the vibration data in one dimension, it forms the two-dimensional vibration images. Then, CNN completes the feature extraction and learning of image data, avoiding the limitations of traditional methods. A variety of common fault data can be generated by the motor fault state simulation of the experimental platform. After the test of experimental data, the proposed method can achieve 100% accuracy and realize error-free discrimination.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

ZhiYuan Xu, Zhuo Long, Libing Ren, and Gongping Wu "Motor diagnosis based on vibration imaging and CNN", Proc. SPIE 12981, Ninth International Symposium on Sensors, Mechatronics, and Automation System (ISSMAS 2023), 129813I (4 March 2024); https://doi.org/10.1117/12.3014951

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