融合粗糙集与D-S证据理论的航空装备故障诊断

孙伟超; 李文海; 李文峰

doi:10.13700/j.bh.1001-5965.2015.0030

融合粗糙集与D-S证据理论的航空装备故障诊断

doi: 10.13700/j.bh.1001-5965.2015.0030

1.
海军航空工程学院研究生管理大队, 烟台 264001
2. 海军航空工程学院科研部, 烟台 264001

基金项目: 总装武器装备预研项目(9140A27020214JB14436)

详细信息

作者简介:
孙伟超(1986-),男,山东烟台人,博士研究生,ben_phoenix@163.com

通讯作者:
李文海(1969-),男,山东无棣人,教授,ythylwh@vip.163.com.cn,主要研究方向为复杂装备故障诊断.

中图分类号: TP181;V24
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- 被引次数: 0
出版历程
- 收稿日期: 2015-01-15
- 修回日期: 2015-04-17
- 网络出版日期: 2015-10-20

Avionic devices fault diagnosis based on fusion method of rough set and D-S theory

1.
Graduate Student's Brigade, Naval Aeronautical Engineering University, Yantai 264001, China
2. Department of Scientific Research, Naval Aeronautical Engineering University, Yantai 264001, China

摘要

摘要: 针对航空电子装备故障诊断中出现的多源诊断信息存在冲突的情况,基于粗糙集与证据理论在处理不确定问题时的优势,提出了一种融合粗糙集与证据理论的故障诊断方法.该方法利用粗糙集将信息源给出的诊断数据转化为证据理论中的mass函数,进行结果融合.同时,该方法给出边界粗糙熵的定义,并基于边界粗糙熵获得反映各信息源在诊断融合过程中重要度的动态权重参数,提出一种新的证据理论的冲突合成规则.仿真实验表明,该方法可以有效地提升诊断信息融合结果的准确性,在航空电子装备故障诊断方面有较好的实用价值.
- 边界粗糙熵 /
- 粗糙集 /
- D-S证据理论 /
- 冲突证据融合 /
- 故障诊断
Abstract: In order to solve the conflict of multi-sources information in the fault diagnosis process of avionics electric equipment, a method based on rough set theory and evidence theory for fault diagnosis was proposed. Because both rough set theory and evidence theory had advantages in dealing with uncertainty problems. The method proposed converted diagnostic data to mass function which was needed in evidence theory in order to fuse results with rough set theory. Meanwhile, the method defined boundary rough entropy, got dynamic weight parameters which reflected the significance of every information source used in fusion process with the entropy and improve the rule for conflicting evidence combination. The experiment shows that the method improves the fusion results' accuracy of diagnostic information effectively and has a good practical value in process of avionics electric fault diagnosis.
- boundary rough set entropy /
- rough set /
- D-S evidence theory /
- conflicting evidence fusion /
- fault diagnosis

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