基于比例加速退化建模的单台机载设备剩余寿命自适应预测

doi:10.12305/j.issn.1001-506X.2021.11.42

Abstract

Abstract:

Aiming at the problem that the existing prediction methods of remaining useful lifetime (RUL) for the airborne equipment cannot be applied to the accelerated degradation test scenarios under the condition of a single sample of the new research, this paper proposes an adaptive prediction method of RUL for the single equipment under the accelerated degradation scenario based on the proportional relationship model. Firstly, according to the ratio relationship of drift and diffusion coefficient in the Wiener process under accelerated degradation environment, a nonlinear stochastic degradation model considering individual differences and measurement errors is established. Secondly, for the situation that the accelerated degradation test has only a single sample, a parameter adaptive estimation method based on the joint algorithm of expectation maximum and Kalman filter is proposed. Then, the Kalman filter principle is used to online update the degradation state, and the probability density function of RUL is derived. Finally, through the analysis of the measured data for a single traveling wave tube under accelerated degradation test, the validity and advantages of this method are verified.

Key words: Wiener process, accelerated degradation modeling, proportion relationship, remaining useful lifetime, adaptive prediction

CLC Number:

TB114.3

Zhongyi CAI, Zezhou WANG, Yunxiang CHEN, Huachun XIANG, Lili WANG. Adaptive prediction of remaining useful lifetime for the single airborne equipment based on the proportional accelerated degradation modeling[J]. Systems Engineering and Electronics, 2021, 43(11): 3405-3412.

Figures/Tables 6

References 19

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Adaptive prediction of remaining useful lifetime for the single airborne equipment based on the proportional accelerated degradation modeling

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