Two-stage physics-based Wiener process models for online RUL prediction in field vibration data

•We propose the two-stage physics-based Wiener process models.•An online stage division principle is developed to detect the change point.•An online remaining useful life prediction framework is constructed.•A dataset of wheel tread vibration demonstrates the superiority of the proposed method. Due...

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Veröffentlicht in:Mechanical systems and signal processing Jg. 152; S. 107378
Hauptverfasser: Yan, Bingxin, Ma, Xiaobing, Huang, Guifa, Zhao, Yu
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Berlin Elsevier Ltd 01.05.2021
Elsevier BV
Schlagworte:
Accuracy
Crack propagation
Degradation
Failure mechanisms
Fatigue crack and spall
Fatigue failure
Fracture mechanics
Mathematical models
Nonlinear systems
Online RUL prediction
Parameter estimation
Rotating machinery
Statistical inference
Treads
Two-stage physics-based models
Vibration
Wheel tread vibration
Wiener process model
Working conditions
Online RUL prediction
Wiener process model
Two-stage physics-based models
Wheel tread vibration
Fatigue crack and spall
ISSN:0888-3270, 1096-1216
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Zusammenfassung:•We propose the two-stage physics-based Wiener process models.•An online stage division principle is developed to detect the change point.•An online remaining useful life prediction framework is constructed.•A dataset of wheel tread vibration demonstrates the superiority of the proposed method. Due to most failure mechanisms, such as fatigue crack growth and fatigue spall, the degradation process of rotating machinery commonly exhibits two-stage features in engineering practice. Other minor factors are also the key issues affecting the health evolution process, including the component structure, assembly accuracy, and working environment. Ignoring such a mechanism may lead to imprecise in degradation modeling, life prognostic, and ultimately lead to safety risk. Besides, achieving high accuracy of prognostic emphasizes the influence of random effect in the degradation process. The contribution of this study lies in addressing this issue by proposing two-stage physics-based Wiener process models integrating: (a) fatigue crack mechanism and crack growth law, and (b) other minor factors. A general prognostic framework is formulated by jointly employing the online change point detection, parameter estimation, and remaining useful life (RUL) prediction, which has good statistic inference and applicability in two general nonlinear systems, i.e., power-law and exponential-law. A joint implement of offline two-step parameter estimation method and the online Bayesian update method is executed, making full advantage of historical and in-service data, based on which the RUL prediction transcends into an imperative PHM module. A practical case study on the vibration dataset of wheel treads demonstrates the practically implement ability of the proposed method in achieving high accuracy of RUL prediction.
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ISSN:0888-3270
1096-1216
DOI:10.1016/j.ymssp.2020.107378