Multiple Model Moving Horizon Estimation Approach to Prognostics in Coupled Systems

被引：0

作者：

Pattipati, Bharath ^{[1
]}

Sankavaram, Chaitanya ^{[1
]}

Pattipati, Krishna ^{[1
]}

Zhang, Yilu ^{[2
]}

Howell, Mark ^{[2
]}

Salman, Mutasim ^{[2
]}

机构：

[1] Univ Connecticut, Dept Elect & Comp Engn, 371 Fairfield Rd,U-2157, Storrs, CT 06269 USA

[2] GM Global R&D, Gen Motor Co, Warren, MI 48090 USA

来源：

IEEE AUTOTESTCON 2011: SYSTEMS READINESS TECHNOLOGY CONFERENCE | 2011年

基金：

美国国家科学基金会;

关键词：

multiple model moving horizon estimation (MM-MHE); model predictive control (MPC); electronic throttle control (ETC) system; survival function estimation; proportional hazard model (PHM); nonlinear programming;

D O I：

暂无

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

The key objectives of this paper are to analyze and implement a novel moving horizon model predictive estimation scheme based on constrained nonlinear optimization techniques for inferring the survival functions and residual useful life (RUL) of components in coupled systems. The approach employs a data-driven prognostics framework that combines failure time data, static and dynamic (time-series) parametric data, and the Multiple Model Moving Horizon Estimation (MM-MHE) algorithm for predicting the survival functions of components based on their usage profiles. Validation of the approach has been provided based on data from an electronic throttle control (ETC) system. The proposed prognostic approach is modular and has the potential to be applicable to a wide variety of systems, ranging from automobiles to aerospace.

引用

页码：149 / 157

页数：9

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