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논문 기본 정보

자료유형
학술대회자료
저자정보
Yingcheng Li (Tongji University) Yuantao Sun (Tongji University) Weihua Lin (Shanghai Zhenhua Heavy Industries) Bin Cao (Vantech Instruments) Yuan Liu (China Special Equipment Inspection and Research Institute)
저널정보
제어로봇시스템학회 제어로봇시스템학회 국제학술대회 논문집 ICCAS 2024
발행연도
2024.10
수록면
756 - 761 (6page)

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초록· 키워드

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The research on bearing degradation plays an important role in the health management and maintenance of the system.In response to the problems of environmental noise interference and low accuracy of degradation state evaluation during the service process of gearbox bearings, this paper proposes a degradation state evaluation method based on the VMD-CNN-BiLSTM model. Based on the fault identification of the entire life degradation process of bearings, the performance change law of the degradation process is analyzed, and the classification of degradation stages is achieved by combining fuzzy evaluation method. By optimizing the parameters in Variational Mode Decomposition (VMD), the reconstruction of the entire lifecycle vibration signal has been achieved, which helps to extract subsequent degradation features. At the same time, by constructing a trend degradation index for rolling bearings and analyzing the changes in the health status of bearings using membership functions, the classification of degradation states is achieved, providing a basis for scientific decision-making in diagnosis. Finally, the degradation process evaluation of rolling bearings is achieved, and applied to the gear bearings of port shore container cranes, providing a theoretical and methodological basis for preventive maintenance.

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Abstract
1. INTRODUCTION
2. VMD DECOMPOSITION BASED ON KURTOSIS AND CORRELATION COEFFICIENT
3.CONSTRUCTION OF DEGRADATION INDEX BASED ON CNN-BiLSTM
4. DEGRADATION STATE EVALUATION OF ROLLING BEARING BASED ON FUZZY EVALUATION
5. CONCLUSION
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