Research on feature extraction and fault diagnosis technology of rolling bearing vibration signals based on Python

Zipeng Zhu; Shiyi Zhao; Jingxian He

doi:10.1117/12.3039595

4 September 2024 Research on feature extraction and fault diagnosis technology of rolling bearing vibration signals based on Python

Zipeng Zhu, Shiyi Zhao, Jingxian He

Author Affiliations +

Proceedings Volume 13259, International Conference on Automation Control, Algorithm, and Intelligent Bionics (ACAIB 2024); 132590P (2024) https://doi.org/10.1117/12.3039595
Event: Fourth International Conference on Automation Control, Algorithm, and Intelligent Bionics (ICAIB 2024), 2024, Yinchuan, China

Abstract

Bearings, as key components in rotating machinery, can experience failures that severely impact the normal operation of the equipment and the safety of production. In light of this, the paper proposes and implements a Python-based system design for bearing fault diagnosis and prediction. Initially, the bearing data is collected using displacement sensors and acceleration sensors. Then, in combination with FFT, wavelet transform, and other methods, the collected vibration signals undergo noise reduction processing to achieve the desired processing effect. Features reflecting the state of the bearing are extracted from the time, frequency, and time-frequency domains. Subsequently, machine learning algorithms such as Support Vector Machine (SVM), Random Forest (RF), and Neural Network (NN) are chosen for training and validating the fault diagnosis model. A comparison of multiple models is conducted to evaluate the performance of various algorithms. In the realm of fault type prediction, the prediction model is built on an Adam-optimized neural network. The prediction outcome enables the assessment of the deterioration trend of non-faulty bearings, thereby aiming to preemptively address potential hidden risks associated with bearings.

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

Citation Download Citation

Zipeng Zhu, Shiyi Zhao, and Jingxian He "Research on feature extraction and fault diagnosis technology of rolling bearing vibration signals based on Python", Proc. SPIE 13259, International Conference on Automation Control, Algorithm, and Intelligent Bionics (ACAIB 2024), 132590P (4 September 2024); https://doi.org/10.1117/12.3039595

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