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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...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2021
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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. |
format | Online Article Text |
id | pubmed-8539104 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
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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