首页 >

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

程晓玉1,韩鹏1,贺维1,张朋2,3,韩晓霞3,李英梅1,曹友3   

  1. 1. 哈尔滨师范大学
    2. 航天器在轨故障诊断与维修重点实验室
    3. 火箭军工程大学
  • 收稿日期:2022-05-22 修回日期:2022-06-18 出版日期:2022-06-24 发布日期:2022-06-24
  • 通讯作者: 贺维
  • 基金资助:
    中国博士后科学基金项目;黑龙江省自然科学基金项目;黑龙江省大学生创新实践项目;哈尔滨师范大学研究生质量培养提升工程项目;哈尔滨师范大学研究生学术创新项目

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

  • Received:2022-05-22 Revised:2022-06-18 Online:2022-06-24 Published:2022-06-24

摘要: 飞轮系统的稳定运行对于航天器在轨安全影响重大,因而对飞轮系统进行健康状态评估至关重要。在进行飞轮系统健康状态评估建模时,不仅要求模型能够处理各种不确定性以保障评估结果的准确性,同时要求其具有透明合理的评估过程与可解释、可追溯的评估结果。因此,本文在深入研究置信规则库(Belief Rule Base, BRB)建模方法的基础上,构建了一种新的基于可解释性建模的置信规则库(Explicable Belief Rule Base, BRB-e)飞轮系统健康状态评估模型。首先,结合飞轮系统特征对模型的可解释性建模准则进行定义;在此基础上,设计了BRB-e评估模型的推理过程;然后,基于鲸鱼优化算法(Whale Optimization Algorithm,WOA),提出了一种具有可解释性约束的BRB-e模型参数优化方法;最后,通过对某飞轮系统中轴承组件的评估案例研究,验证了模型在飞轮系统健康状态评估中的有效性。对比研究表明,BRB-e模型在评估结果准确性和评估过程可解释性方面具有一定的优势。

关键词: 飞轮系统, 健康状态评估, 置信规则库, 可解释性建模准则, 鲸鱼优化算法

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 sta-tus assessment, it is required that the model not only deal with various uncertainties to ensure the accuracy of the assessment results, but also have a transparent and reasonable assessment process and explicable and traceable assessment results. Therefore, based on the in-depth study of the modeling method of belief rule base (BRB), this paper constructs a new explicable belief rule base (BRB-e) flywheel system health assessment model based on expli-cable modeling. Firstly, the 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 in the flywheel system health status assessment is verified by a case study of bearing components in a flywheel system. The comparative study shows that BRB-e model has certain advantages in the ac-curacy of assessment results and the explainability of assessment process.

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