Degradation Reliability Analysis Based on TOPSIS Model Selection Method

doi:10.1007/s12204-019-2067-5

摘要/Abstract

摘要： It is necessary to determine the degradation path model of products at first when using the method based on degradation path model to evaluate the degradation reliability of products. At present, the degradation path model is mainly determined by scatter plots of degradation data. However, this method has strong subjectivity and is liable to cause the evaluation results to be inconsistent with the actual situation. In this paper, a degradation reliability analysis method based on TOPSIS (technique for order preference by similarity to an ideal solution) model selection is proposed, and its implementation process is given. The optimal degradation path model is selected according to the calculated proximity. With the help of TOPSIS method, various degradation path models can be selected and quantified, and the original degradation path method can be improved to avoid the risk of errors in product reliability evaluation caused by inaccurate subjective hypothesis, so as to ensure the objectivity and accuracy in the process of model determination. The validity and practicability of the proposed method are verified by the degradation analysis of the injector of a certain type of diesel engine.

关键词: performance degradation, degradation path, least squares estimation, technique for order preference by similarity to an ideal solution (TOPSIS), reliability

Abstract: It is necessary to determine the degradation path model of products at first when using the method based on degradation path model to evaluate the degradation reliability of products. At present, the degradation path model is mainly determined by scatter plots of degradation data. However, this method has strong subjectivity and is liable to cause the evaluation results to be inconsistent with the actual situation. In this paper, a degradation reliability analysis method based on TOPSIS (technique for order preference by similarity to an ideal solution) model selection is proposed, and its implementation process is given. The optimal degradation path model is selected according to the calculated proximity. With the help of TOPSIS method, various degradation path models can be selected and quantified, and the original degradation path method can be improved to avoid the risk of errors in product reliability evaluation caused by inaccurate subjective hypothesis, so as to ensure the objectivity and accuracy in the process of model determination. The validity and practicability of the proposed method are verified by the degradation analysis of the injector of a certain type of diesel engine.

Key words: performance degradation, degradation path, least squares estimation, technique for order preference by similarity to an ideal solution (TOPSIS), reliability

中图分类号:

TB 114.3

GU Yingkui *(古莹奎), SHEN Yanjun (沈延军), YU Dongping (余东平). Degradation Reliability Analysis Based on TOPSIS Model Selection Method[J]. Journal of Shanghai Jiao Tong University (Science), 2019, 24(3): 351-356.

参考文献 13

[1]	GU Y K. Reliability analysis and risk assessment fordiesel engine [M]. Beijing: Tsinghua University Press,2012 (in Chinese).
[2]	LEE H M, WU J W, LEI C L. Assessing the lifetimeperformance index of exponential products with stepstressaccelerated life-testing data [J]. IEEE Transactionson Reliability, 2013, 62(1): 296-304.
[3]	CHEN J, ZIO E, LI J, et al. Accelerated life test forreliability evaluation of pneumatic cylinders [J]. IEEEAccess, 2018, 6: 75062-75075.
[4]	WANG Y P, PHAM H. Modeling the dependent competingrisks with multiple degradation processes andrandom shock using time-varying copulas [J]. IEEETransactions on Reliability, 2012, 61(1): 13-22.
[5]	JIANG X, LIU H Z, LIU L L, et al. Extremely smallscalesample’s reliability of an electric spindle based ondistribution of false lifetime [J]. Journal of Vibrationand Shock, 2013, 32(19): 80-85 (in Chinese).
[6]	SUN Q, KVAM P H. Multi-cause degradation pathmodel: A case study on rubidium lamp degradation[J]. Quality and Reliability Engineering International,2011, 27(6): 781-793.
[7]	HU Y T, FAN J S, HU C H. Modeling degradationpath using v-support vector regression [J]. Systems Engineeringand Electronics, 2017, 39(1): 231-236 (inChinese).
[8]	DENG A M, CHEN X, ZHANG C H, et al. Reliabilityassessment based on performance degradation data[J]. Journal of Astronautics, 2006, 27(3): 546-552 (inChinese).
[9]	LU C J, MEEKER W O. Using degradation measuresto estimate a time-to-failure distribution [J]. Technometrics,1993, 35(2): 161-174.
[10]	BAGDONAVIˇ CIUS V, HAGHIGHI F, NIKULIN M.Statistical analysis of general degradation path modeland failure time data with multiple failure modes [J].Communications in Statistics - Theory and Methods,2005, 34(8): 1771-1791.
[11]	CHEN Z H, LIU Y S. Ecumenical model of reliabilityevaluation based on performance degradation data [J].Journal of Electronic Measurement and Instrument,2008, 22(Sup. 2): 22-25 (in Chinese).
[12]	BEHZADIAN M, OTAGHSARA S K, YAZDANI M,et al. A state-of the-art survey of TOPSIS applications[J]. Expert Systems with Applications, 2012, 39(17):13051-13069.
[13]	LIN M C, WANG C C, CHEN M S, et al. Using AHPand TOPSIS approaches in customer-driven productdesign process [J]. Computers in Industry, 2008, 59(1):17-31.

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