Bearing condition assessment of VAE based on deep probability optimization

YIN Aijun,CHEN Xiaomin,TAN Jian,WANG Yu

Journal of Vibration and Shock ›› 2021, Vol. 40 ›› Issue (20) : 186-192.

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PDF(1855 KB)
Journal of Vibration and Shock ›› 2021, Vol. 40 ›› Issue (20) : 186-192.

Bearing condition assessment of VAE based on deep probability optimization

  • YIN Aijun1,CHEN Xiaomin1,TAN Jian2,WANG Yu1
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Abstract

Variational auto-encoder (VAE) can be utilized to assess bearing operation condition based on vibration monitoring.A limitation of traditional VAE based evaluation method is the simplified Gaussian posterior distribution.The spatial representation of low-dimensional hidden variable is too simple to capture the real potential fault characteristics of vibration signal.Moreover, the evidence lower bound in traditional VAE is subject to inaccurate estimation.In this paper, distribution transformation was utilized to optimize VAE approximate posterior distribution.With the edge probability density calculated by applying optimized sampling algorithm, a bearing condition evaluation model was established based on deep probability optimization.Firstly, normalizing flows (NF) was employed to construct a complex and flexible approximate posterior distribution to realize distribution optimization.Then the Annealed Importance Sampling (AIS) algorithm with a series of intermediate distributions was introduced to complete optimal calculation of the edge probability density and establish the evaluation indicator.Comparative experiments on rolling bearing indicate that the proposed method is more sensitive to the degradation process, which verifies the effectiveness of proposed bearing condition assessment method.

Key words

deep probabilistic optimization / variational auto-encoder / normalizing flows / annealed importance sampling / bearing condition assessment

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YIN Aijun,CHEN Xiaomin,TAN Jian,WANG Yu. Bearing condition assessment of VAE based on deep probability optimization[J]. Journal of Vibration and Shock, 2021, 40(20): 186-192

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