Prediction of remaining useful life based on bidirectional gated recurrent unit with temporal self-attention mechanism

Jiusi Zhang, Yuchen Jiang, Shimeng Wu, Xiang Li, Hao Luo and Shen Yin

Reliability Engineering and System Safety, 2022, vol. 221, issue C

Abstract: Prediction of remaining useful life (RUL) is of vital significance in the prognostics health management (PHM) tasks. To deal with the reverse time series and to reflect the difference in RUL prediction results at different time instances, this paper proposes a novel bidirectional gated recurrent unit with temporal self-attention mechanism (BiGRU-TSAM) to predict RUL. Specifically, a novel approach is proposed where each of the considered time instance is assigned a self-learned weight according to the degree of significance. Furthermore, the parameter update process of the TSAM is obtained with solid theoretical foundation, and as a sign of interpretability, it is shown that the assigned weights can remain consistency over several independent training processes. On this basis, the BiGRU-TSAM is applied to predict RUL online. An aircraft turbofan engine dataset and a milling dataset are applied to verify the proposed RUL prediction approach. The experimental results show the superiority of the proposed approach over the existing ones based on machine learning and deep learning.

Keywords: Prognostics health management; Remaining useful life; Temporal self-attention mechanism; Bidirectional gated recurrent unit; Prediction (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (29)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:reensy:v:221:y:2022:i:c:s0951832021007687

DOI: 10.1016/j.ress.2021.108297

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