Hybrid remaining useful life prediction method. A case study on railway D-cables

Yu Zang, Wei Shangguan, Baigen Cai, Huasheng Wang and Michael. G. Pecht

Reliability Engineering and System Safety, 2021, vol. 213, issue C

Abstract: This paper develops a hybrid remaining useful life (RUL) prediction method and explores the feasibility for complex system equipment, using one of transmission equipment D-cables in high-speed railways as an example. RUL prediction is a promising way to reduce high maintenance costs for high-speed railways. However, there is no sufficient actual life-cycle data due to the lack of sensors, and no mature physics-of-failure model of the equipment in high-speed railways, which make it difficult to predict RUL. To solving this problem, firstly the failure modes, mechanisms, and effects of the D-cables are first analyzed, and accelerated life tests are run under different thermal stresses in Ansys to obtain the life-cycle data. Based on the life-cycle data, particle filtering (PF) method predicts the RUL based on Paris-Law model, meanwhile feedforward neural network (FNN) predicts the RUL under the same thermal stress with PF method, finally a hybrid RUL prediction method that combines model-based and data-driven methods is developed. The results are verified using simulation.

Keywords: Remaining useful life; Model-based method; Data-driven method; Hybrid method; High-speed railway; D-cable (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (14)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:reensy:v:213:y:2021:i:c:s0951832021002775

DOI: 10.1016/j.ress.2021.107746

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