A Novel Prediction Method about Single Components of Analog Circuits Based on Complex Field Modeling

Few researches pay attention to prediction about analog circuits. The few methods lack the correlation with circuit analysis during extracting and calculating features so that FI (fault indicator) calculation often lack rationality, thus affecting prognostic performance. To solve the above problem,...

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Main Authors: Jingyu Zhou, Shulin Tian, Chenglin Yang
Format: Article
Language:English
Published: Wiley 2014-01-01
Series:The Scientific World Journal
Online Access:http://dx.doi.org/10.1155/2014/530942
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author Jingyu Zhou
Shulin Tian
Chenglin Yang
author_facet Jingyu Zhou
Shulin Tian
Chenglin Yang
author_sort Jingyu Zhou
collection DOAJ
description Few researches pay attention to prediction about analog circuits. The few methods lack the correlation with circuit analysis during extracting and calculating features so that FI (fault indicator) calculation often lack rationality, thus affecting prognostic performance. To solve the above problem, this paper proposes a novel prediction method about single components of analog circuits based on complex field modeling. Aiming at the feature that faults of single components hold the largest number in analog circuits, the method starts with circuit structure, analyzes transfer function of circuits, and implements complex field modeling. Then, by an established parameter scanning model related to complex field, it analyzes the relationship between parameter variation and degeneration of single components in the model in order to obtain a more reasonable FI feature set via calculation. According to the obtained FI feature set, it establishes a novel model about degeneration trend of analog circuits’ single components. At last, it uses particle filter (PF) to update parameters for the model and predicts remaining useful performance (RUP) of analog circuits’ single components. Since calculation about the FI feature set is more reasonable, accuracy of prediction is improved to some extent. Finally, the foregoing conclusions are verified by experiments.
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institution Kabale University
issn 2356-6140
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publisher Wiley
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spelling doaj-art-97442423752a445c8fd6455fef5432372025-08-20T03:37:09ZengWileyThe Scientific World Journal2356-61401537-744X2014-01-01201410.1155/2014/530942530942A Novel Prediction Method about Single Components of Analog Circuits Based on Complex Field ModelingJingyu Zhou0Shulin Tian1Chenglin Yang2School of Automation Engineering, University of Electronic Science and Technology of China, Chengdu 611731, ChinaSchool of Automation Engineering, University of Electronic Science and Technology of China, Chengdu 611731, ChinaSchool of Automation Engineering, University of Electronic Science and Technology of China, Chengdu 611731, ChinaFew researches pay attention to prediction about analog circuits. The few methods lack the correlation with circuit analysis during extracting and calculating features so that FI (fault indicator) calculation often lack rationality, thus affecting prognostic performance. To solve the above problem, this paper proposes a novel prediction method about single components of analog circuits based on complex field modeling. Aiming at the feature that faults of single components hold the largest number in analog circuits, the method starts with circuit structure, analyzes transfer function of circuits, and implements complex field modeling. Then, by an established parameter scanning model related to complex field, it analyzes the relationship between parameter variation and degeneration of single components in the model in order to obtain a more reasonable FI feature set via calculation. According to the obtained FI feature set, it establishes a novel model about degeneration trend of analog circuits’ single components. At last, it uses particle filter (PF) to update parameters for the model and predicts remaining useful performance (RUP) of analog circuits’ single components. Since calculation about the FI feature set is more reasonable, accuracy of prediction is improved to some extent. Finally, the foregoing conclusions are verified by experiments.http://dx.doi.org/10.1155/2014/530942
spellingShingle Jingyu Zhou
Shulin Tian
Chenglin Yang
A Novel Prediction Method about Single Components of Analog Circuits Based on Complex Field Modeling
The Scientific World Journal
title A Novel Prediction Method about Single Components of Analog Circuits Based on Complex Field Modeling
title_full A Novel Prediction Method about Single Components of Analog Circuits Based on Complex Field Modeling
title_fullStr A Novel Prediction Method about Single Components of Analog Circuits Based on Complex Field Modeling
title_full_unstemmed A Novel Prediction Method about Single Components of Analog Circuits Based on Complex Field Modeling
title_short A Novel Prediction Method about Single Components of Analog Circuits Based on Complex Field Modeling
title_sort novel prediction method about single components of analog circuits based on complex field modeling
url http://dx.doi.org/10.1155/2014/530942
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