journal article·2020-02-18Open access

A Hybrid Degradation Modeling and Prognostic Method for the Multi-Modal System

Jun Peng, Shengnan Wang, Dianzhu Gao, Xiaoyong Zhang, Bin Chen, Yijun Cheng, Yingze Yang, Wentao Yu, Zhiwu Huang

Applied Sciences· Volume 10· Issue 4

Abstract

Engineering systems typically go through complicated degradation processes, partially due to their multiple operating modes. Therefore, how to accurately estimate their remaining useful life is a critical issue. To address this challenge, a hybrid degradation modeling and prognostic method for the multi-modal system is proposed. Firstly, the cumulative dynamic differential health indicator is constructed for the multi-modal switching system using a multi-objective optimization approach. The long-term cumulative degradation assessment model is constructed based on the gated recurrent unit. Then, considering that the damage in the latest stage has a significant impact on the remaining useful life, the time window is used to extract local features of the sequence, including energy features and statistical features. The latest stage degradation is predicted based on the light gradient boosting machine. Finally, model averaging is used to integrate the two predicted results, which is expected to improve the prognostic robustness. The proposed model is evaluated with synthetic analysis and NASA turbofan aero-engine datasets. Extensive experimental results demonstrate the proposed method provides a better characterization of the degradation status of the system and provides a higher estimation accuracy than existing methods.
Source: crossref · Quality: baseline

Research context

OpenAlex topics: Reliability and Maintenance Optimization · Machine Fault Diagnosis Techniques · Risk and Safety Analysis

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

Affiliations

School of Computer Science and Engineering, Central South University, Changsha 410075, China

School of Automation, Central South University, Changsha 410075, China

College of Computer and Information Engineering, Central South University of Forestry and Technology, Changsha 410004, China

Funding

National Natural Science Foundation of China · Fundamental Research Funds for Central Universities of the Central South University

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