贫信息背景下基于矩域灰点排序的灰FMECA模型

doi:10.12305/j.issn.1001-506X.2021.12.38

摘要/Abstract

摘要：

为解决贫信息背景下对系统进行故障模式、影响及危害性分析(failure mode, effects and criticality analysis, FMECA)受故障信息少、故障数据部分未知等问题限制, 同时为有限定量危害性矩阵分析方法的缺陷, 提出了适用于贫信息背景的灰FMECA模型。首先对危害性矩阵图进行规范化改进, 统一横纵坐标轴量纲, 提出危害度权重比概念以规范作图比例; 然后在危害度计算中引入区间灰数, 提出矩域灰点概念以表征故障模式难以确知的危害性; 最后依照不确定型决策思想给出矩域灰点的一般排序规则, 为贫信息背景的故障模式危害性排序提供解决方案。通过某航天飞机主发动机高压燃料涡轮泵进行案例研究, 验证了所提模型的有效性。

关键词: 贫信息, FMECA, 区间灰数, 矩域灰点, 危害性矩阵

Abstract:

Under the background of poor information, it is difficult to implement the failure mode, effects and criticality analysis (FMECA) on products due to limitations such as lack of failure information and uncertain failure data. At the same time, in order to overcome the drawbacks of the quantitative criticality matrix analysis method, a grey FMECA model suitable for poor information background is proposed. Firstly, the criticality matrix diagram is standardized, the dimensions of the horizontal and vertical axes are unified, and the concept of criticality weight ratio is proposed to standardize the mapping ratio. In addition, interval grey numbers are introduced into criticality calculation, and the concept of grey point in the rectangular region is proposed to characterize the hazards of failure modes that are difficult to ascertain.Finally, general ordering rules for grey points in the rectangular region are given according to the enlightenment from decision-making under uncertainty, which provide solutions to the ordering of the criticality of failure modes under poor information background. A case study of the high-pressure fuel turbopump in a space shuttle's main engine verifies the validity of the proposed model.

Key words: poor information, failure mode; effects and criticality analysis (FMECA), interval grey number, grey point in rectangular region, criticality matrix

中图分类号:

TB114.3

李志远, 刘思峰, 方志耕, 夏悦馨. 贫信息背景下基于矩域灰点排序的灰FMECA模型[J]. 系统工程与电子技术, 2021, 43(12): 3732-3740.

Zhiyuan LI, Sifeng LIU, Zhigeng FANG, Yuexin XIA. Grey FMECA model based on ordering of grey point in rectangular region under the background of poor information[J]. Systems Engineering and Electronics, 2021, 43(12): 3732-3740.

图/表 10

图1

图2

图3

图4

图5

图6

图7

表1

表2

图8

参考文献 29

1	MENCHINELLI A , INGIOSI F , PAMPHILI L , et al. A reliability engineering approach for managing risks in cubesats[J]. Aerospace, 2018, 5 (4): 121- 126. doi: 10.3390/aerospace5040121
2	邵维贵. FMECA和FTA在某型飞机起落架系统故障分析中的应用研究[D]. 成都: 西华大学, 2019.
	SHAO W G. Research on the FMECA and FTA of the landing gear system for a certain type of aircraft in failure analysis[D]. Chengdu: Xihua University, 2019.
3	GONG J Q , LUO Y P , QIU Z W , et al. Determination of key components in automobile braking systems based on ABC classification and FMECA[J]. Journal of Traffic and Transportation Engineering, 2020, doi: 10.1016/j.jtte.2019.01.008
4	齐新宇. 汽车发动机的状态监测及故障诊断技术的研究[D]. 长春: 吉林大学, 2018.
	QI X Y. Research on condition monitoring and fault diagnosis technology of automobile engine[D]. Changchun: Jilin University, 2018.
5	AHMED S , GU X C . Accident-based FMECA study of marine boiler for risk prioritization using fuzzy expert system[J]. Results in Engineering, 2020, 6, 100123. doi: 10.1016/j.rineng.2020.100123
6	BORAL S , CHATURVEDI S K , HOWARD I , et al. An integrated interval type-2 fuzzy sets and multiplicative half quadratic programming-based MCDM framework for calculating aggregated risk ranking results of failure modes in FMECA[J]. Process Safety and Environmental Protection, 2021, 150, 194- 222. doi: 10.1016/j.psep.2021.04.006
7	ŤAVODA P , KOVÁČ J , ȽUKASZCZYK Z Ƚ . Reliability analysis of forest machines due to FMEA method[J]. Management Systems in Production Engineering, 2018, 26 (4): 200- 206. doi: 10.1515/mspe-2018-0032
8	SHRESTHA S , MALLINENI J , YEDID I , et al. Determination of dominant failure modes using FMECA on the field deployed C-Si modules under hot-dry desert climate[J]. IEEE Journal of Photovoltaics, 2015, 5, 174- 182. doi: 10.1109/JPHOTOV.2014.2366872
9	SEYED H , SAFAEI N , ASGHARPOUR M J . Reprioritization of failures in a system failure mode and effects analysis by decision making trial and evaluation laboratory technique[J]. Reliability Engineering and System Safety, 2005, 91 (8): 872- 881.
10	CARPITELLA S , CERTA A , IZQUIERDO J . A combined multi-criteria approach to support FMECA analyses: a real-world case[J]. Reliability Engineering and System Safety, 2018, 169, 394- 402. doi: 10.1016/j.ress.2017.09.017
11	BOWLESJ B , PELÁEZC E . Fuzzy logic prioritization of failures in a system failuremode, effects and criticality analysis[J]. Reliability Engineering and System Safety, 1995, 50 (2): 203- 213. doi: 10.1016/0951-8320(95)00068-D
12	PETROVIĆ D V , TANASIJEVIĆ M , MILIĆ V , et al. Risk assessment model of mining equipment failure based on fuzzy logic[J]. Expert Systems with Applications, 2014, 41 (18): 8157- 8164. doi: 10.1016/j.eswa.2014.06.042
13	CATELANI M , CIANI L , VENZI M . Failure modes, mechanisms and effect analysis on temperature redundant sensor stage[J]. Reliability Engineering and System Safety, 2018, 180, 425- 433. doi: 10.1016/j.ress.2018.08.013
14	CERTA A , HOPPS F , INGHILLERI R . A Dempster-Shafer theory-based approach to the failure mode, effects and criticality analysis (FMECA) under epistemic uncertainty: application to the propulsion system of a fishing vessel[J]. Reliability Engineering and System Safety, 2017, 159, 69- 79. doi: 10.1016/j.ress.2016.10.018
15	RENJITH V R , JOSE K M , KUMAR P H . Fuzzy FMECA (failure mode effect and criticality analysis) of LNG storage facility[J]. Journal of Loss Prevention in the Process Industries, 2018, 56, 537- 547. doi: 10.1016/j.jlp.2018.01.002
16	李俨, 陈海, 张清江, 等. 无人机系统健康状态评估方法研究[J]. 系统工程与电子技术, 2011, 33 (3): 562- 567. doi: 10.3969/j.issn.1001-506X.2011.03.19
	LI Y , CHEN H , ZHANG Q J , et al. Assessment method of health condition for UAV systems[J]. Systems Engineering and Electronics, 2011, 33 (3): 562- 567. doi: 10.3969/j.issn.1001-506X.2011.03.19
17	陈光宇, 苏亮夫, 祁凌云. 基于TRIZ的复杂系统FMECA分析流程和方法研究[J]. 电子科技大学学报(社科版), 2013, 15 (2): 37- 41.
	CHEN G Y , SU L F , QI L Y . TRIZ-based FMECA analysis process and methods of complex systems[J]. Journal of University of Electronic Science and Technology of China(Social Sciences Edition), 2013, 15 (2): 37- 41.
18	GUGALIYA A , BORAL S , NAIKAN V N A . A hybrid decision making framework for modified failure mode effects and criticality analysis[J]. International Journal of Quality & Reliability Management, 2019, 36 (8): 1266- 1283.
19	王锦妮, 火建卫. 定量危害性矩阵分析方法研究[J]. 航空工程进展, 2016, 7 (1): 70- 77.
	WANG J N , HUO J W . Research on quantitative criticality matrix analysis method[J]. Advances in Aeronautical Science and Engineering, 2016, 7 (1): 70- 77.
20	WANG X F , ZHANG Y Z , SHEN G X . An improved FMECA for feed system of CNC machining center based on ICR and DEMATEL method[J]. The International Journal of Advanced Manufacturing Technology, 2016, 83 (1-4): 43- 54. doi: 10.1007/s00170-015-7551-y
21	LIU H C , YOU J X , DUAN C Y . An integrated approach for failure mode and effect analysis under interval-valued intuitionistic fuzzy environment[J]. International Journal of Production Economics, 2017, 207, 163- 172.
22	黄佳. 复杂不确定环境下FMEA改进及应用研究[D]. 上海: 上海大学, 2019.
	HUANG J. Research on FMEA improvement and application within complex and uncertain environment[D]. Shanghai: Shanghai University, 2019.
23	方志耕, 陈顶, 刘思峰. 贫信息背景的复杂装备可靠性预测现状与展望[J]. 指挥信息系统与技术, 2018, 9 (5): 1- 8.
	FANG Z G , CHEN D , LIU S F . Status and prospect of reliability prediction for complex equipment with poor information background[J]. Command Information System and Technology, 2018, 9 (5): 1- 8.
24	XIAO Q Z , SHAN M Y , GAO M Y , et al. Grey information coverage interaction relational decision making and its application[J]. Journal of Systems Engineering and Electronics, 2020, 31 (2): 359- 369. doi: 10.23919/JSEE.2020.000013
25	XIE N M , ZHU C Y , ZHENG J . Expansion modeling of discrete grey model based on multi-factor information aggregation[J]. Journal of Systems Engineering and Electronics, 2014, 25 (5): 833- 839. doi: 10.1109/JSEE.2014.00096
26	孟玉慈, 孙东旭, 梁媛. 利用历史故障信息提升机载计算机FMEA分析准确性[J]. 航空计算技术, 2017, 47 (4): 126- 129. doi: 10.3969/j.issn.1671-654X.2017.04.031
	MENG Y C , SUN D X , LIANG Y . Improving accuracy of airborne computer FMEA using historical fault information[J]. Aeronautical Computer Technique, 2017, 47 (4): 126- 129. doi: 10.3969/j.issn.1671-654X.2017.04.031
27	火建卫. 危害性矩阵分析中故障模式影响概率的确定方法[J]. 航空工程进展, 2015, 6 (2): 229- 231.
	HUO J W . Determination method of failure effect probability in criticality matrix analysis[J]. Advances in Aeronautical Science and Engineering, 2015, 6 (2): 229- 231.
28	曹颖赛, 刘思峰, 方志耕, 等. 多态系统可靠性分析广义灰色贝叶斯网络模型[J]. 系统工程与电子技术, 2018, 40 (1): 231- 237.
	CAO Y S , LIU S F , FANG Z G , et al. Genralized grey Bayesian network model for realiability analysis of multi-state system[J]. Systems Engineering and Electronics, 2018, 40 (1): 231- 237.
29	张元. 多目标不确定型决策方法研究及应用[D]. 荆州: 长江大学, 2018.
	ZHANG Y. A research and application of multi-objective uncertainty decision-making[D]. Jingzhou: Yangtze University, 2018.

[1]	高普梅, 湛军. 基于扰动信息的连续区间灰数灰色预测模型[J]. 系统工程与电子技术, 2019, 41(11): 2533-2540.
[2]	陈可嘉, 陈萍. 基于三参数区间灰数的TOPSIS决策方法[J]. 系统工程与电子技术, 2019, 41(1): 124-130.
[3]	钱丽丽, 刘思峰, 谢乃明. 基于熵权和区间灰数信息的灰色聚类模型[J]. 系统工程与电子技术, 2016, 38(2): 352-356.
[4]	王霞，党耀国. 基于Choquet积分的区间灰数多属性决策方法[J]. 系统工程与电子技术, 2015, 37(5): 1106-1110.
[5]	郭晓君，刘思峰，方志耕. 基于合成灰数灰度的区间灰数自忆性预测模型[J]. 系统工程与电子技术, 2014, 36(6): 1124-1129.
[6]	王大鹏，汪秉文，李睿凡. 考虑合成灰数灰度性质的改进区间灰数预测模型[J]. Journal of Systems Engineering and Electronics, 2013, 35(5): 1013-1017.
[7]	曾　波１，刘思峰２，李　川３，陈久梅１. 基于蛛网面积的区间灰数灰靶决策模型[J]. 系统工程与电子技术, 2013, 35(11): 2329-2334.
[8]	曾波. 基于核和灰度的区间灰数预测模型[J]. Journal of Systems Engineering and Electronics, 2011, 33(4): 821-824.
[9]	王洁方,刘思峰. 三参数区间灰数排序及其在区间DEA效率评价中的应用[J]. Journal of Systems Engineering and Electronics, 2011, 33(1): 106-0109.
[10]	李为相，张广明，李帮义. 基于区间灰数的α-PROMETHEE方法研究及应用[J]. Journal of Systems Engineering and Electronics, 2010, 32(4): 780-783.
[11]	刘思峰, 方志耕, 谢乃明. 基于核和灰度的区间灰数运算法则[J]. Journal of Systems Engineering and Electronics, 2010, 32(2): 313-316.
[12]	陈孝新, 刘思峰. 一种部分权重信息的灰色多属性群决策方法[J]. Journal of Systems Engineering and Electronics, 2009, 31(4): 843-846.