Risk assessment of aircraft IDG based on fuzzy TOPSIS-FMEA

被引：0
|
作者：
Shi X. [1 ]
Cheng B. [1 ]
Huang K. [1 ]
Yang Z. [1 ]
机构：
[1] College of Electronic Information and Automation, Civil Aviation University of China, Tianjin
来源：
Xi Tong Gong Cheng Yu Dian Zi Ji Shu/Systems Engineering and Electronics | 2022年 / 44卷 / 06期
关键词：
Aircraft power system; Failure mode and effects analysis (FMEA); Risk assessment; Technique for order preference by similarity to an ideal solution (TOPSIS);
D O I：
10.12305/j.issn.1001-506X.2022.06.35
中图分类号：
学科分类号：
摘要：
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. © 2022, Editorial Office of Systems Engineering and Electronics. All right reserved.
引用
收藏
页码：2060 / 2064
页数：4
相关论文
共 18 条
  • [1] WEIMER J P., Present and future of aircraft electrical power systems, Proc.of the 39th Aerospace Sciences Meeting and Exhibit, (2013)
  • [2] WHEELER P., Technology for the more and all electric aircraft of the future, Proc.of the IEEE International Conference on Automatica, (2016)
  • [3] WHEELER P, BOZHKO S., The more electric aircraft: techno-logy and challenges, IEEE Electrification Magazine, 2, 4, pp. 6-12, (2014)
  • [4] ZHANG S F, LI M W, ZHENG H Y, Et al., Aircraft fuel system fuzzy FMEA and FMECA analysis, Proc.of the 1st International Conference on Information Sciences, Machinery, Materials and Energy, pp. 378-382, (2015)
  • [5] JUN L, XU H B., Reliability analysis of aircraft equipment based on FMECA method, Physics Procedia, 25, pp. 1816-1822, (2012)
  • [6] HUANG Z T, WANG Z S, LIU Z B., Fault diagnosis of aircraft power supply based on priority dynamic fault tree, Advanced Materials Research, 443, pp. 229-236, (2012)
  • [7] JAVADI M S, NOBAKHT A, MESKARBASHEE A., Fault tree analysis approach in reliability assessment of power system, International Journal of Multidisciplinary Sciences and Engineering, 2, 6, pp. 46-50, (2011)
  • [8] HE L R, YIN C, PENG W W, Et al., Reliability and risk assessment of aircraft electric systems, Maintenance and Reliability, 16, pp. 497-506, (2014)
  • [9] WU H, ZUO H F., Level of repair analysis non-economic evaluation for aircraft maintenance based on improved AHP, Aircraft Design, 6, pp. 46-49, (2008)
  • [10] JIANG L L., Research on fault diagnosis of aircraft power supply system, (2013)
12