Annual Conference of Prognostics and Health Management Society, 2012.

Prognostics Method for Analog Electronic Circuits

Arvind Sai Sarathi Vasan¹, Student Member, IEEE, Bing Long² and Michael Pecht¹, Fellow, IEEE

¹Center for Advanced Life Cycle Engineering (CALCE)
University of Maryland, College Park, MD 20742, USA
Arvind88@calce.umd.edu
pecht@calce.umd.edu

²School of Automation Engineering,
University of Electronic Science and Technology of China, Chengdu, China

Abstract:

Analog electronic circuits are an integral part of many industrial systems. Failure in such analog circuits during field operation can have severe economic implications. The presence of an expert system that can provide advance warnings on circuit failures can minimize the downtime and improve the reliability of electrical systems. Through successive refinement of circuit's response to a sweep signal, features are extracted for fault prognosis. From the extracted features, a fault indicator is developed. An empirical model is developed based on the degradation trend exhibited by the fault indicator. Particle filtering approach is used for model adaptation and remaining useful performance estimation. This framework is completely automated and has the merit of implementation simplicity. The proposed framework is demonstrated on two analog filter circuits.

Full text: CALCE Consortium members, Publisher

CALCE | University of Maryland. All Rights Reserved.