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A Novel Prognostic Approach for RUL Estimation with Evolving Joint Prediction of Continuous and Discrete States
Rong-Jing Bao1; Hai-Jun Rong1; Zhixin Yang2; Badong Chen3
2019-01
Source PublicationIEEE Transactions on Industrial Informatics
ISSN1551-3203
Abstract

In this paper, we propose a novel prognostic approach for remaining useful life estimation with evolving joint prediction of continuous and discrete states which represent the signals and health states of systems respectively. The predictors are built with evolving capability of adapting structures and parameters online to capture the dynamic characteristics of systems during runtime. Moreover, the discrete states can be determined dynamically during the construction of the predictors for systems operating under different environments. In the testing phase, the optimum predictor for predicting continuous and discrete states jointly is chosen under the error and distance criteria. The RULs are estimated conveniently once the predicted signals fall into failure mode based on a distance metric. In order to validate the performance of the proposed approach, the widely used turbofan engine datasets are taken into consideration. Experimental results demonstrate the reasonability and superiority of the proposed approach compared to other approaches.

DOIhttp://doi.org/10.1109/TII.2019.2896288
Language英语
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Document TypeJournal article
专题DEPARTMENT OF ELECTRICAL AND COMPUTER ENGINEERING
DEPARTMENT OF ELECTROMECHANICAL ENGINEERING
Corresponding AuthorRong-Jing Bao; Hai-Jun Rong; Zhixin Yang; Badong Chen
Affiliation1.State Key Laboratory for Strength and Vibration of Mechanical Structures, Shaanxi Key Laboratory of Environment and Control for Flight Vehicle, School of Aerospace, Xi’an Jiaotong University, Xi’an 710049, China
2.State Key Laboratory of Internet of Things for Smart City, Department of Electromechanical Engineering, Faculty of Science and Technology, University of Macau, Macao SAR 999078, China
3.Institute of Artificial Intelligence and Robotics, School of Electronic and Information Engineering, Xi’an Jiaotong University, Xi’an 710049, China
Corresponding Author AffilicationFaculty of Science and Technology
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Rong-Jing Bao,Hai-Jun Rong,Zhixin Yang,et al. A Novel Prognostic Approach for RUL Estimation with Evolving Joint Prediction of Continuous and Discrete States[J]. IEEE Transactions on Industrial Informatics,2019.
APA Rong-Jing Bao,Hai-Jun Rong,Zhixin Yang,&Badong Chen.(2019).A Novel Prognostic Approach for RUL Estimation with Evolving Joint Prediction of Continuous and Discrete States.IEEE Transactions on Industrial Informatics.
MLA Rong-Jing Bao,et al."A Novel Prognostic Approach for RUL Estimation with Evolving Joint Prediction of Continuous and Discrete States".IEEE Transactions on Industrial Informatics (2019).
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