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Deep diagnostics and prognostics: An integrated hierarchical learning framework in PHM applications
Lin, Yanhui1; Li, Xudong2; Hu, Yang3
Department空间技术部
Source PublicationAPPLIED SOFT COMPUTING
2018
Volume72Pages:555-564
DOI10.1016/j.asoc.2018.01.036
ISSN1568-4946
Language英语
KeywordFeature learning Auto-encoder Extreme learning machines Prognostics and health management Motor bearing Turbofan engine
AbstractPrognostics and Health Management (PHM) is an integrated technique for improving the availability and efficiency of high-value industry equipment and reducing the maintenance cost. One of the most challenging problems in PHM is how to effectively process the raw monitoring signal into the information-rich features that are readable enough for PHM modeling. In this paper, we propose an integrated hierarchical learning framework, which is capable to perform the unsupervised feature learning, diagnostics and prognostics modeling together. The proposed method is based on Auto-Encoders (trained by considering the Li-norm penalty) and Extreme Learning Machines (trained by considering the L-2-norm penalty). The proposed method is applied on two different case studies considering the diagnostics of motor bearings and prognostics of turbofan engines, also the performances are compared with other commonly applied PHM approaches and machine learning tools. The obtained results demonstrate the superiority of the proposed method, especially the ability of extracting the relevant features from the non-informative and noisy signals and maintaining their efficiencies. (C) 2018 Elsevier B.V. All rights reserved.
Indexed BySCI ; EI
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Document Type期刊论文
Identifierhttp://ir.nssc.ac.cn/handle/122/6558
Collection空间技术部
Affiliation1.School of Reliability and Systems Engineering, Beihang University, Beijing, China;
2.National Space Science Center, Beijing, China;
3.Science and Technology on Complex Aviation System Simulation Laboratory, Beijing,9236, China
Recommended Citation
GB/T 7714
Lin, Yanhui,Li, Xudong,Hu, Yang. Deep diagnostics and prognostics: An integrated hierarchical learning framework in PHM applications[J]. APPLIED SOFT COMPUTING,2018,72:555-564.
APA Lin, Yanhui,Li, Xudong,&Hu, Yang.(2018).Deep diagnostics and prognostics: An integrated hierarchical learning framework in PHM applications.APPLIED SOFT COMPUTING,72,555-564.
MLA Lin, Yanhui,et al."Deep diagnostics and prognostics: An integrated hierarchical learning framework in PHM applications".APPLIED SOFT COMPUTING 72(2018):555-564.
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