Fault diagnosis of rolling bearing based on a mine fan bearing

Zheng-xu Zhang; Yi-xin Su; Shi-lin Zheng

doi:10.1117/12.2625267

12 December 2021 Fault diagnosis of rolling bearing based on a mine fan bearing

Zheng-xu Zhang, Yi-xin Su, Shi-lin Zheng

Proceedings Volume 12127, International Conference on Intelligent Equipment and Special Robots (ICIESR 2021); 121270A (2021) https://doi.org/10.1117/12.2625267
Event: International Conference on Intelligent Equipment and Special Robots (ICIESR 2021), 2021, Qingdao, China

Abstract

Rolling bearings are the most common and easily damaged link in mine fans, and there are many problems that can be improved in the acquisition and analysis of vibration signals. Through the establishment of a mining-based rotating machinery failure test platform, the bearing is subjected to fault simulation experiments and the collected signals are processed, and the collected bearing signals are compared without noise reduction processing and the use of noise reduction fusion spectrum algorithm and wavelet noise reduction method After noise reduction, the analysis results are processed by Hilbert transform and EMD (empirical modal analysis), and the frequency domain diagram obtained by comparing the frequency domain map is compared to observe the frequency of abnormal vibration to further infer the fault type. By comparing the analysis results obtained by different methods, they are compared and summarized, so as to promote the upgrading and improvement of processing methods, make accurate judgments on fan bearing faults and give feasibility opinions.

Citation Download Citation

Zheng-xu Zhang, Yi-xin Su, and Shi-lin Zheng "Fault diagnosis of rolling bearing based on a mine fan bearing", Proc. SPIE 12127, International Conference on Intelligent Equipment and Special Robots (ICIESR 2021), 121270A (12 December 2021); https://doi.org/10.1117/12.2625267

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