Adaptive deep learning-based remaining useful life prediction framework for systems with multiple failure patterns

Jiawei Xiong, Jian Zhou, Yizhong Ma, Fengxia Zhang and Chenglong Lin

Reliability Engineering and System Safety, 2023, vol. 235, issue C

Abstract: Recent advances in multivariate data fusion technology have promoted the applications of neural network-based models for remaining useful life (RUL) prediction. However, the interpretability of these models is usually poor since they are developed in a black-box manner. It is difficult to use them in engineering systems with multiple failure modes (FMs) under various operation conditions (OCs). This work proposes an adaptive deep learning-based RUL prediction framework with FM recognition. First, a FM recognizer fusing physics-informed FM classifier with deep convolutional neural networks (DCNN) is developed, which improves the interpretability and the accuracy of the recognition model. Then, a framework which can adaptively train models and select them for RUL prediction according to FM recognition results is presented. An OC-based smoothing technique is proposed to improve the RUL prediction accuracy and robustness. Extensive experiments based on turbofan datasets are conducted to validate the effectiveness of the proposed framework. The results show that the RUL prediction accuracy is improved by 7% under the proposed framework when compared with other methods. It proves the performance gains of the proposed framework by incorporating prior FM recognition with RUL prediction. It also provides insights for RUL prognostics subject to distinct FMs and OCs.

Keywords: Remaining useful life; Failure mode recognition; Deep learning; Prediction model (search for similar items in EconPapers)
Date: 2023
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (9)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S095183202300159X
Full text for ScienceDirect subscribers only

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:reensy:v:235:y:2023:i:c:s095183202300159x

DOI: 10.1016/j.ress.2023.109244

Access Statistics for this article

Reliability Engineering and System Safety is currently edited by Carlos Guedes Soares

More articles in Reliability Engineering and System Safety from Elsevier
Bibliographic data for series maintained by Catherine Liu ().