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A Fault Diagnosis Method of Modular Analog Circuit Based on SVDD and D–S Evidence Theory

In the actual fault diagnosis process of an analog circuit, there is often a problem due to the lack of fault samples, leading to the low-accuracy of diagnostic models. Therefore, using positive samples that are easy to obtain to establish diagnostic models became a research hotspot in the field of...

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Autores principales: Sun, Peng, Yang, Zhiming, Jiang, Yueming, Jia, Shaohua, Peng, Xiyuan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8539104/
https://www.ncbi.nlm.nih.gov/pubmed/34696102
http://dx.doi.org/10.3390/s21206889
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author Sun, Peng
Yang, Zhiming
Jiang, Yueming
Jia, Shaohua
Peng, Xiyuan
author_facet Sun, Peng
Yang, Zhiming
Jiang, Yueming
Jia, Shaohua
Peng, Xiyuan
author_sort Sun, Peng
collection PubMed
description In the actual fault diagnosis process of an analog circuit, there is often a problem due to the lack of fault samples, leading to the low-accuracy of diagnostic models. Therefore, using positive samples that are easy to obtain to establish diagnostic models became a research hotspot in the field of analog circuit fault diagnosis. This paper proposes a method based on Support Vector Data Description (SVDD) and Dempster–Shafer evidence theory (D–S evidence theory) for fault diagnosis of modular analog circuit. Firstly, the principle of circuit module partition is proposed to divide the analog circuit under test, and the output port of each module is selected as test point. Secondly, the paper extracts the feature of the time-domain and frequency-domain output signals of the circuit module through Principal Component Analysis (PCA). Thirdly, four state detection models based on SVDD are established to judge the working state of each circuit module, including TSG, TSP, FSG, and FSP state detection model. Finally, the D–S theory is introduced to integrate the test results of each model for locating fault circuit module. To verify the effectiveness of the proposed method, the dual bandpass filter circuit is selected for simulation and hardware experiment. The results show that the proposed method can locate the analog fault effectively and has a higher diagnosis accuracy.
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spelling pubmed-85391042021-10-24 A Fault Diagnosis Method of Modular Analog Circuit Based on SVDD and D–S Evidence Theory Sun, Peng Yang, Zhiming Jiang, Yueming Jia, Shaohua Peng, Xiyuan Sensors (Basel) Article In the actual fault diagnosis process of an analog circuit, there is often a problem due to the lack of fault samples, leading to the low-accuracy of diagnostic models. Therefore, using positive samples that are easy to obtain to establish diagnostic models became a research hotspot in the field of analog circuit fault diagnosis. This paper proposes a method based on Support Vector Data Description (SVDD) and Dempster–Shafer evidence theory (D–S evidence theory) for fault diagnosis of modular analog circuit. Firstly, the principle of circuit module partition is proposed to divide the analog circuit under test, and the output port of each module is selected as test point. Secondly, the paper extracts the feature of the time-domain and frequency-domain output signals of the circuit module through Principal Component Analysis (PCA). Thirdly, four state detection models based on SVDD are established to judge the working state of each circuit module, including TSG, TSP, FSG, and FSP state detection model. Finally, the D–S theory is introduced to integrate the test results of each model for locating fault circuit module. To verify the effectiveness of the proposed method, the dual bandpass filter circuit is selected for simulation and hardware experiment. The results show that the proposed method can locate the analog fault effectively and has a higher diagnosis accuracy. MDPI 2021-10-18 /pmc/articles/PMC8539104/ /pubmed/34696102 http://dx.doi.org/10.3390/s21206889 Text en © 2021 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Sun, Peng
Yang, Zhiming
Jiang, Yueming
Jia, Shaohua
Peng, Xiyuan
A Fault Diagnosis Method of Modular Analog Circuit Based on SVDD and D–S Evidence Theory
title A Fault Diagnosis Method of Modular Analog Circuit Based on SVDD and D–S Evidence Theory
title_full A Fault Diagnosis Method of Modular Analog Circuit Based on SVDD and D–S Evidence Theory
title_fullStr A Fault Diagnosis Method of Modular Analog Circuit Based on SVDD and D–S Evidence Theory
title_full_unstemmed A Fault Diagnosis Method of Modular Analog Circuit Based on SVDD and D–S Evidence Theory
title_short A Fault Diagnosis Method of Modular Analog Circuit Based on SVDD and D–S Evidence Theory
title_sort fault diagnosis method of modular analog circuit based on svdd and d–s evidence theory
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8539104/
https://www.ncbi.nlm.nih.gov/pubmed/34696102
http://dx.doi.org/10.3390/s21206889
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