Remaining useful life estimation based on stochastic deterioration models: A comparative study

被引：193

作者：

Khanh Le Son ^{[1
]}

Fouladirad, Mitra ^{[1
]}

Barros, Anne ^{[1
]}

Levrat, Eric ^{[2
]}

Lung, Benoit ^{[2
]}

机构：

[1] Univ Technol Troyes, Inst Charles Delaunay, CNRS UMR STMR 6279, F-10010 Troyes, France

[2] Univ Henri Poincare, CRAN, CNRS UMR 7039, F-54506 Vandoeuvre Les Nancy, France

来源：

RELIABILITY ENGINEERING & SYSTEM SAFETY | 2013年 / 112卷

关键词：

Deterioration modelling; Principal component analysis; Stochastic process; Wiener process with drift; Prognostic; Remaining useful life time estimation; PROGNOSIS MODEL; DEGRADATION; PREDICTION;

D O I：

10.1016/j.ress.2012.11.022

中图分类号：

T [工业技术];

学科分类号：

08 ;

摘要：

Prognostic of system lifetime is a basic requirement for condition-based maintenance in many application domains where safety, reliability, and availability are considered of first importance. This paper presents a probabilistic method for prognostic applied to the 2008 PHM Conference Challenge data. A stochastic process (Wiener process) combined with a data analysis method (Principal Component Analysis) is proposed to model the deterioration of the components and to estimate the RUL on a case study. The advantages of our probabilistic approach are pointed out and a comparison with existing results on the same data is made. (C) 2012 Elsevier Ltd. All rights reserved.

引用

页码：165 / 175

页数：11

共 41 条

[21] Remaining life estimation of used components in consumer products: Life cycle data analysis by Weibull and artificial neural networks [J].

Mazhar, M. I. ;

Kara, S. ;

Kaebernick, H. .

JOURNAL OF OPERATIONS MANAGEMENT, 2007, 25 (06) :1184-1193

[22]

Moler C. B., 2004, Numerical computing with MATLAB

[23] Formalisation of a new prognosis model for supporting proactive maintenance implementation on industrial system [J].

Muller, Alexandre ;

Suhner, Marie-Christine ;

Lung, Benoit .

RELIABILITY ENGINEERING & SYSTEM SAFETY, 2008, 93 (02) :234-253

[24] Inference from accelerated degradation and failure data based on Gaussian process models [J].

Padgett, WJ ;

Tomlinson, MA .

LIFETIME DATA ANALYSIS, 2004, 10 (02) :191-206

[25]

Palazzolo JJ, 2008, AEROSP CONF PROC, P3683

[26] EVALUATIONS OF BARRIER-CROSSING PROBABILITIES OF WIENER PATHS [J].

PARK, C ;

SCHUURMANN, FJ .

JOURNAL OF APPLIED PROBABILITY, 1976, 13 (02) :267-275

[27]

Peel L, 2008, 2008 INTERNATIONAL CONFERENCE ON PROGNOSTICS AND HEALTH MANAGEMENT (PHM), P65

[28]

Revuz D., 1999, CONTINUOUS MARTINGAL

[29] ON THE 1ST HITTING TIME AND THE LAST EXIT TIME FOR A BROWNIAN-MOTION TO FROM A MOVING BOUNDARY [J].

SALMINEN, P .

ADVANCES IN APPLIED PROBABILITY, 1988, 20 (02) :411-426

[30] Remaining Useful Life Estimation Based on a Nonlinear Diffusion Degradation Process [J].

Si, Xiao-Sheng ;

Wang, Wenbin ;

Hu, Chang-Hua ;

Zhou, Dong-Hua ;

Pecht, Michael G. .

IEEE TRANSACTIONS ON RELIABILITY, 2012, 61 (01) :50-67

← 1 2 3 4 5 →