一种新的基于可解释性置信规则库的飞轮健康状态评估模型

doi:10. 7527/S1000-6893. 2022. 27496

Abstract

Abstract:

The stable operation of the flywheel system has a great impact on the on-orbit safety of spacecraft， so it is very important to assess the health status of the flywheel system. When modeling the flywheel system health status assessment， it is required that the model not only deals with various uncertainties to ensure the accuracy of assessment results， but also has a transparent and reasonable assessment process and explicable and traceable assessment results. Therefore， based on the modeling method of Belief Rule Base （BRB）， a new explicable Belief Rule Base （BRB-e） flywheel system health assessment model based on explicable modeling is constructed. Firstly， explicable modeling criteria are defined according to the characteristics of flywheel system. On this basis， the reasoning process of BRB-e assessment model is designed. Then， based on the Whale Optimization Algorithm （WOA）， a parameter optimization method of BRB-e model with explicable constraints is proposed. Finally， the effectiveness of the model for flywheel system health status assessment is verified by a case study of the bearing components in a flywheel system. The comparative study shows that the BRB-e model proposed has certain advantages in accuracy of assessment results and explainability of the assessment process.

Key words: flywheel system, health status assessment, belief rule base, explicable modeling criteria, whale optimization algorithm

CLC Number:

V475.9

Xiaoyu CHENG, Peng HAN, Wei HE, Peng ZHANG, Xiaoxia HAN, Yingmei LI, You CAO. A new flywheel health status assessment model based on explicable belief rule base[J]. Acta Aeronautica et Astronautica Sinica, 2023, 44(S1): 172-184.

Figures/Tables 11

Fig.1

Fig.2

Fig.3

Table 1

Setting of reference points and referential values

指标	等级
指标	$H 1$	$H 2$	$H 3$	$H 4$
$x 1$	1.0	0.4	0.2	0
$x 2$	1.0	0.7	0.4	0
$H$	1.0	0.8	0.4	0.06

Table 1

Fig.4

Fig.5

Table 2

Fig.6

Fig.7

Table 3

Table A1

Confidence of BRB⁃e model with interpretable row constraints

序号	评估指标		初始置信度 $β 1, β 2, β 3, β 4$	置信度约束条件 $β 1, β 2, β 3, β 4$	优化后置信度 $β 1, β 2, β 3, β 4$
序号	$x 1$	$x 2$	初始置信度 $β 1, β 2, β 3, β 4$	置信度约束条件 $β 1, β 2, β 3, β 4$	优化后置信度 $β 1, β 2, β 3, β 4$
1	$H 1$	$H 1$	｛0.95， 0.05， 0.00， 0.00｝	｛0.95 ~ 1.00， 0.05 ~ 0.10， 0.00 ~ 0.05， 0.00 ~ 0.05｝	｛0.94，0.05，0.01，0.00｝
2	$H 1$	$H 2$	｛0.79， 0.21， 0.00， 0.00｝	｛0.75 ~ 0.83， 0.19 ~ 0.25， 0.00 ~ 0.05， 0.00 ~ 0.05｝	｛0.75，0.24，0.01，0.00｝
3	$H 1$	$H 3$	｛0.75， 0.20， 0.05， 0.00｝	｛0.70 ~ 0.80， 0.15 ~ 0.23， 0.00 ~ 0.28， 0.00 ~ 0.05｝	｛0.70，0.22，0.08，0.00｝
4	$H 1$	$H 4$	｛0.45， 0.40， 0.10， 0.05｝	｛0.40 ~ 0.48， 0.35 ~ 0.45， 0.05 ~ 0.15， 0.00 ~ 0.05｝	｛0.47，0.38，0.15，0.00｝
5	$H 2$	$H 1$	｛0.68， 0.32， 0.00， 0.00｝	｛0.60 ~ 0.72， 0.25 ~ 0.36， 0.00 ~ 0.05， 0.00 ~ 0.05｝	｛0.64，0.36，0.00，0.00｝
6	$H 2$	$H 2$	｛0.58， 0.37， 0.05，0.00｝	｛0.55 ~ 0.62， 0.30 ~ 0.40， 0.00 ~ 0.09， 0.00 ~ 0.05｝	｛0.55，0.36，0.09，0.00｝
7	$H 2$	$H 3$	｛0.50， 0.40， 0.10，0.00｝	｛0.45 ~ 0.55， 0.35 ~ 0.45， 0.05 ~ 0.14， 0.00 ~ 0.05｝	｛0.49，0.37，0.14，0.00｝
8	$H 2$	$H 4$	｛0.43， 0.42， 0.15， 0.00｝	｛0.39 ~ 0.45， 0.39 ~ 0.47， 0.10 ~ 0.18， 0 ~ 0.10｝	｛0.39，0.39，0.13，0.09｝
9	$H 3$	$H 1$	｛0.18，0.27， 0.40， 0.15｝	｛0.15 ~ 0.23， 0.22 ~ 0.30， 0.35 ~ 0.43， 0.10 ~ 0.2｝	｛0.23，0.30，0.37，0.10｝
10	$H 3$	$H 2$	｛0.10， 0.15， 0.50， 0.25｝	｛0.05 ~ 0.15， 0.10 ~ 0.19， 0.45 ~ 0.53， 0.20 ~ 0.29｝	｛0.09，0.19，0.48，0.24｝
11	$H 3$	$H 3$	｛0.00， 0.13， 0.57， 0.30｝	｛0.00 ~ 0.05， 0.10 ~ 0.16， 0.45 ~ 0.60， 0.25 ~ 0.35｝	｛0.00，0.16，0.59，0.25｝
12	$H 3$	$H 4$	｛0.00， 0.05， 0.60， 0.35｝	｛0.00 ~ 0.05， 0.00 ~ 0.10， 0.60 ~ 0.69， 0.30 ~ 0.39｝	｛0.01，0.03，0.60，0.36｝
13	$H 4$	$H 1$	｛0.00， 0.13， 0.57， 0.30｝	｛0.00 ~ 0.05， 0.10 ~ 0.19， 0.45 ~ 0.62， 0.25 ~ 0.35｝	｛0.01，0.19，0.45，0.35｝
14	$H 4$	$H 2$	｛0.00， 0.06， 0.24， 0.70｝	｛0.00 ~ 0.05， 0.00 ~ 0.13， 0.20 ~ 0.29， 0.65 ~ 0.73｝	｛0.00，0.02，0.29，0.69｝
15	$H 4$	$H 3$	｛0.00， 0.00， 0.15， 0.85｝	｛0.00 ~ 0.05， 0.00 ~ 0.05， 0.10 ~ 0.20， 0.80 ~ 0.89｝	｛0.00，0.00，0.20，0.80｝
16	$H 4$	$H 4$	｛0.00， 0.00， 0.00， 1.00｝	｛0.00 ~ 0.05， 0.00 ~ 0.05， 0.00 ~ 0.05， 0.95 ~ 1.00｝	｛0.00，0.02，0.03，0.95｝

Table A1

References 23

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迭代次数	种群大小
迭代次数	20	30	40
20	0.022 1	0.011 6	0.009 9
100	0.011 1	0.009 2	0.008 0
200	0.010 9	0.008 2	0.007 3
400	0.007 1	0.007 4	0.007 2
600	0.007 0	0.007 6	0.007 0
800	0.006 5	0.006 6	0.007 1
100 0	0.006 7	0.006 7	0.007 3
120 0	0.006 8	0.006 5	0.006 7

方法	训练样本
方法	20%	30%	50%	60%
BRB-e	0.009 4	0.007 8	0.007 8	0.006 5
WOA-BRB	0.007 9	0.007 6	0.006 6	0.001 8
PCMAES-BRB	0.011 0	0.009 7	0.008 6	0.001 8
DE-BRB	0.009 8	0.009 3	0.009 2	0.002 0
ELM	0.031 0	0.028 8	0.018 5	0.007 1
BPNN	0.019 5	0.008 1	0.004 4	0.003 2

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A new flywheel health status assessment model based on explicable belief rule base

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