LAUSR.org creates dashboard-style pages of related content for over 1.5 million academic articles. Sign Up to like articles & get recommendations!

Model-based prognosis using an explicit degradation model and Inverse FORM for uncertainty propagation

Photo by heftiba from unsplash

Abstract In this paper, an analytical method issued from the field of reliability analysis is used for prognosis. The inverse first-order reliability method (Inverse FORM) is an uncertainty propagation method… Click to show full abstract

Abstract In this paper, an analytical method issued from the field of reliability analysis is used for prognosis. The inverse first-order reliability method (Inverse FORM) is an uncertainty propagation method that can be adapted to remaining useful life (RUL) calculation. An extended Kalman filter (EKF) is first applied to estimate the current degradation state of the system, then the Inverse FORM allows to compute the probability density function (pdf) of the RUL. In the proposed Inverse FORM methodology, an analytical or numerical solution to the differential equation that describes the evolution of the system degradation is required to calculate the RUL model. In this work, the method is applied to a Paris fatigue crack growth model, and then compared to filter-based methods such as EKF and particle filter using performance evaluation metrics (precision, accuracy and timeliness). The main advantage of the Inverse FORM is its ability to compute the pdf of the RUL at a lower computational cost.

Keywords: degradation; inverse form; form uncertainty; model; uncertainty propagation

Journal Title: IFAC-PapersOnLine
Year Published: 2017

Link to full text (if available)


Share on Social Media:                               Sign Up to like & get
recommendations!

Related content

More Information              News              Social Media              Video              Recommended



                Click one of the above tabs to view related content.