A Microscopic Approach for Generic Degradation Modeling

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Published Nov 13, 2020
Farhang Momeni Xiaoning Jin Jun Ni

Abstract

One of the main challenges in prognostics is degradation modeling for which there are no straightforward methods compared with system governing equations modeling (e.g., Newton`s law, Euler`s law, thermodynamics conservation laws, fluid dynamics laws, and so forth). Once both governing equations and degradation equations are generated, then the RUL or EOL can be easily estimated by using a filtering technique like Kalman filter. This paper presents a new approach for generic degradation modeling which can be engaged in (1) complex engineering systems, and (2) the structures which are fabricated by the new manufacturing processes such as 4D printing that in both cases the physical knowledge is not adequate to model the degradation equations. In the existing approaches for parametric degradation modeling, there are always possibilities that a specific degradation phenomenon of a new system is ignored. This deficiency arises from the assumption made in the previous studies that degradation phenomenon is equivalently represented by degradation mechanism such as crack, wear, corrosion, erosion, and so forth. Here we relax this assumption and provide a more general approach for parametric degradation modeling. This research first, quantifies the concepts of governing equations and degradation equations in prognostics in a general view, second provides a generic approach for deriving the governing equations by using techniques of system identification, third, it digs into the concepts of degradation and provides a microscopic approach for generic degradation modeling, and finally it combines and incorporates the governing equations and degradation equations in a way that the generality is conserved. In addition, this paper opens the door of degradation modeling in 4D printing by starting from the conceptual point of view to the final generic methodology.

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Keywords

PHM, Data-driven prognostics, system-level prognostics, physics-based prognostics, Degradation Mechanisms, microscopic degradation modeling, Degradation phenomenoa, 4D printing

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Section
Communications