基于模糊TOPSIS-FMEA的飞机IDG风险评价

doi:10.12305/j.issn.1001-506X.2022.06.35

摘要/Abstract

摘要：

在传统飞机电源系统失效模式及影响分析(failure mode and effects analysis, FMEA)法中, 采用风险评价指标属性值简单相乘的方法计算风险优先数, 造成风险评价指标不精确, 且主观因素导致属性值发生微小变化, 影响最终评价结果。通过在发生度、严重度和探测度这3个风险评价指标中引入模糊逼近理想解排序法(technique for order preference by similarity to an ideal solution, TOPSIS)理论进行风险评价, 去模糊化和归一化后构造加权判断矩阵, 确定逼近理想解排序法的正负理想解, 根据相对贴近度大小对各故障模式进行风险水平排序。与传统失效模式及影响分析法的对比验证了方法的有效性和实用性, 可为飞机电源系统其他组件风险水平评价提供有效参考。

关键词: 飞机电源系统, 风险评价, 失效模式及影响分析, 逼近理想解排序法

Abstract:

Due to simply multiplication when the risk priority numbers are calculated in traditional failure mode and effects analysis (FMEA), the risk evaluation indicators are inaccurate. And the slight changes of attribute values, caused by subjective factors, have a great impact on the final result. The fuzzy technique for order preference by similarity to an ideal solution (TOPSIS) theory is introduced into the occurrence, severity and detection degree to conduct a risk assessment, and after defuzzification and normalization, the weighted judgment matrix is constructed. Meanwhile, the positive and negative ideal solutions are determined by the technique for sequencing by approximate ideal solution, and the risk level of each fault mode is ranked according to the size of relative closeness. Compared with the traditional failure mode and effects analysis, the effectiveness and practicability of this method are verified, which can provide effective reference to the risk level assessment for other components of aircraft power system.

Key words: aircraft power system, risk assessment, failure mode and effects analysis (FMEA), technique for order preference by similarity to an ideal solution (TOPSIS)

中图分类号:

V215.7

石旭东, 成博源, 黄琨, 杨占刚. 基于模糊TOPSIS-FMEA的飞机IDG风险评价[J]. 系统工程与电子技术, 2022, 44(6): 2060-2064.

Xudong SHI, Boyuan CHENG, Kun HUANG, Zhangang YANG. Risk assessment of aircraft IDG based on fuzzy TOPSIS-FMEA[J]. Systems Engineering and Electronics, 2022, 44(6): 2060-2064.

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故障编号	故障模式	故障原因
F₁	CSD输出故障	发动机断开、发动机欠速等
F₂	PMG故障	永磁发电机绕组故障等
F₃	激励器故障	激励器定子绕组故障、激励器转子绕组故障等
F₄	旋转整流器故障	旋转整流器短路、开路等
F₅	主发电机故障	主发电机转子故障、定子故障、绕组单相接地、绕组相间短路等
F₆	发电机控制组件故障	发动机控制组件内部故障

符号	项目	人员级别	分值
L	资质水平	资深专家	5
		高级专家	4
		中级专家	3
		高级设计人员	2
		一般操作人员	1
E	工作经验	30年以上	6
		10~30年	4
		5~9年	2
		5年以下	1
F	熟悉程度	非常熟悉	5
F	熟悉程度	熟悉	2

语言术语	O	S	D	模糊数
VH	发生几乎不可避免	很严重	探测几乎无法实现	(8, 9, 10)
H	反复发生	比较严重	探测较难	(6, 7, 9)
M	偶尔发生	中等	中等	(4, 5, 6)
L	相对很少发生	相对不严重	探测较容易	(2, 4, 5)
VL	不太可能发生	不严重	探测特别容易	(0, 2, 3)

故障模式	O			S			D
故障模式	专家1	专家2	专家3	专家1	专家2	专家3	专家1	专家2	专家3
CSD输出故障	(2, 4, 5)	(6, 7, 9)	(2, 4, 5)	(4, 5, 6)	(2, 4, 5)	(2, 4, 5)	(6, 7, 9)	(4, 5, 6)	(2, 4, 5)
PMG故障	(6, 7, 9)	(6, 7, 9)	(4, 5, 6)	(2, 4, 5)	(2, 4, 5)	(4, 5, 6)	(4, 5, 6)	(6, 7, 9)	(4, 5, 6)
激励器故障	(6, 7, 9)	(4, 5, 6)	(6, 7, 9)	(4, 5, 6)	(4, 5, 6)	(6, 7, 9)	(8, 9, 10)	(4, 5, 6)	(4, 5, 6)
旋转整流器故障	(8, 9, 10)	(6, 7, 9)	(6, 7, 9)	(6, 7, 9)	(6, 7, 9)	(6, 7, 9)	(6, 7, 9)	(6, 7, 9)	(4, 5, 6)
主发电机故障	(2, 4, 5)	(0, 2, 3)	(4, 5, 6)	(6, 7, 9)	(4, 5, 6)	(4, 5, 6)	(6, 7, 9)	(2, 4, 5)	(2, 4, 5)
发动机控制组件故障	(0, 2, 3)	(0, 2, 3)	(4, 5, 6)	(0, 2, 3)	(0, 2, 3)	(2, 4, 5)	(2, 4, 5)	(0, 2, 3)	(2, 4, 5)

故障模式	与正理想解的欧氏距离	与负理想解的欧氏距离
CSD输出故障	0.326 4	0.381 4
PMG故障	0.294 8	0.475 6
激励器故障	0.219 0	0.475 0
旋转整流器故障	0	0.686 2
主发电机故障	0.427 0	0.347 7
发动机控制组件故障	0.686 2	0