Prognostics of Analog Filters Based on Particle Filters Using Frequency Features

Authors:
Min Li;Weiming Xian;Bing Long;Houjun Wang
Affiliations:
School of Automation, University of Electronic Science and Technology of China, Chengdu, China 611731;School of Automation, University of Electronic Science and Technology of China, Chengdu, China 611731;School of Automation, University of Electronic Science and Technology of China, Chengdu, China 611731;School of Automation, University of Electronic Science and Technology of China, Chengdu, China 611731
Venue:
Journal of Electronic Testing: Theory and Applications
Year:
2013

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Abstract

Analog circuits play an important role in ensuring the availability of electronic systems. Unexpected circuit failures can lead to severe economic implications, and hence, prevention of circuit failures is imperative and highly desired. However, few methods have been suggested for predicting the remaining time till circuit failure. To address this challenge, a novel method for predicting the remaining useful performance (RUP) of analog filters is proposed. By analyzing the circuit's response to a sweep signal, frequency features such as the center frequency, the lower pass-band limit, the upper pass-band limit, and the maximum frequency response, are extracted. Based on the extracted features, a fault indicator (FI) monitoring the degradation trend of the analog filters is developed for failure prognosis. Moreover, a model is developed based on the degradation trend exhibited by the FI. Particle filters approach is applied to model adaption and RUP prediction. Case studies demonstrating this approach are presented. The studies' results show that (1) the proposed FI based on the frequency features can well characterize the degradation trend of the analog filters; and (2) the proposed prognostic approach can predict the RUP of analog filters with small error.