基于改进受限玻尔兹曼机的滚动轴承健康因子构建方法

doi:10.12305/j.issn.1001-506X.2023.09.39

Abstract

Abstract:

Aiming at the problems of low performance indicators and information redundancy of health factors constructed by traditional methods, a method for constructing health factors of rolling bearings based on the improved restricted Boltzmann machine (RBM) is proposed. Firstly, the time-domain and frequency-domain features of rolling bearing vibration monitoring signals are extracted to form a physical health factor set. Secondly, the slope of the number of nodes in the hidden layer of the RBM with time is introduced into the regularization term to extract the trend characteristics of the physical health factor set. Finally, the effectiveness of the proposed method is verified through full life cycle testing of rolling bearings. The experimental results show that compared with the principal component analysis (PCA) method and the traditional RBM virtual health factor construction method, the monotonicity of the virtual health factor based on the improved RBM is increased by 178.0% and 33.3% respectively, the trend is increased by 126.8% and 16% respectively, and the robustness is improved by 60% and 6.02% respectively.

Key words: rolling bearing, health indicator, restricted Boltzmann machine (RBM), regularization, evaluation criterion

CLC Number:

TN911.72

Shiyan SUN, Gang ZHANG, Weige LIANG, Bo SHE, Fuqing TIAN. Construction method of rolling bearing health indicator based on enhanced restricted Boltzmann machine[J]. Systems Engineering and Electronics, 2023, 45(9): 2979-2985.

Figures/Tables 8

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References 30

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模型	单调性	趋势性	鲁棒性
PCA	0.33	0.41	0.54
RBM	0.69	0.80	0.82
改进RBM	0.92	0.93	0.87

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Construction method of rolling bearing health indicator based on enhanced restricted Boltzmann machine

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