Incipient fault diagnosis of dynamical systems using online approximators

Author

Demetriou, Michael A. ; Polycarpou, Marios M.

Author_Institution

Dept. of Mech. Eng., Worcester Polytech. Inst., MA, USA

Volume

43

Issue

11

fYear

1998

fDate

11/1/1998 12:00:00 AM

Firstpage

1612

Lastpage

1617

Abstract

Detection of incipient (slowly developing) faults is crucial in automated maintenance problems where early detection of worn equipment is required. In this paper, a general framework for model-based fault detection and diagnosis of a class of incipient faults is developed. The changes in the system dynamics due to the fault are modeled as nonlinear functions of the state and input variables, while the time profile of the failure is assumed to be exponentially developing. An automated fault diagnosis architecture using nonlinear online approximators with an adaptation scheme is designed and analyzed. A simulation example of a simple nonlinear mass-spring system is used to illustrate the results

Keywords

approximation theory; fault diagnosis; maintenance engineering; nonlinear systems; automated fault diagnosis architecture; automated maintenance problems; dynamical systems; exponentially developing time profile; incipient fault diagnosis; model-based fault detection; nonlinear functions; nonlinear mass-spring system; nonlinear online approximators; online approximators; system dynamics; worn equipment detection; Algorithm design and analysis; Automatic control; Control systems; Delay lines; Delay systems; Fault detection; Fault diagnosis; Linear systems; Riccati equations; Robust stability;

fLanguage

English

Journal_Title

Automatic Control, IEEE Transactions on

Publisher

ieee

ISSN

0018-9286

Type

jour

DOI

10.1109/9.728881

Filename

728881