Ensemble of Models for Fatigue Crack Growth Prognostics

被引：9

作者：

Hoang-Phuong Nguyen ^{[1
]}

Liu, Jie ^{[2
]}

Zio, Enrico ^{[3
,4
,5
]}

机构：

[1] Univ Paris Saclay, Chair Syst Sci & Energet Challenge, Cent Supelec, EDF Fdn, F-91192 Gif Sur Yvette, France

[2] Beihang Univ, Sch Reliabil & Syst Engn, Beijing 10019, Peoples R China

[3] Politecn Milan, Dept Energy, I-20156 Milan, Italy

[4] ParisTech PSL Univ Paris, Ctr Rech Risques & Crises CRC, F-06904 Sophia Antipolis, France

[5] Kyung Hee Univ, Dept Nucl Engn, Seoul 02447, South Korea

来源：

IEEE ACCESS | 2019年 / 7卷

关键词：

Fatigue crack growth; multiple stochastic degradation; prognostics and health management; remaining useful life; particle filter; dynamic ensemble; PERFORMANCE; CHALLENGES;

D O I：

10.1109/ACCESS.2019.2910611

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

Various models of fatigue crack growth in different scenarios have been proposed in the literature. Here, in this paper, we propose a general prognostic framework for tracking crack evolution in equipment undergoing fatigue and predicting the Remaining Useful Life (RUL). The main contribution of this work is to integrate Particle Filtering (PF) and a new ensemble model which combines diverse physical degradation models with respect to their accuracy performance in previous time steps, in order to maximize the overall prediction capability. To validate the effectiveness of the proposed framework, a case study concerning multiple fatigue crack growth degradations is extensively investigated.

引用

页码：49527 / 49537

页数：11

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