Analog Circuit Soft Fault Diagnosis Based on Sparse Random Projections and K-Nearest Neighbor

Analog circuit fault diagnosis is a key problem in theory of circuit networks and has been investigated by many researchers in recent years. An approach based on sparse random projections (SRPs) and K-nearest neighbor (KNN) to the realization of analog circuit soft fault diagnosis has been presented...

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Autores principales:	Jian Sun, Guobin Hu, Chenghua Wang
Formato:	article
Lenguaje:	EN
Publicado:	Hindawi Limited 2021
Materias:	Computer software QA76.75-76.765
Acceso en línea:	https://doaj.org/article/0ea199d2c1144b64a19b49e0a2bd0630
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spelling	oai:doaj.org-article:0ea199d2c1144b64a19b49e0a2bd06302021-11-15T01:20:10ZAnalog Circuit Soft Fault Diagnosis Based on Sparse Random Projections and K-Nearest Neighbor1875-919X10.1155/2021/8040140https://doaj.org/article/0ea199d2c1144b64a19b49e0a2bd06302021-01-01T00:00:00Zhttp://dx.doi.org/10.1155/2021/8040140https://doaj.org/toc/1875-919XAnalog circuit fault diagnosis is a key problem in theory of circuit networks and has been investigated by many researchers in recent years. An approach based on sparse random projections (SRPs) and K-nearest neighbor (KNN) to the realization of analog circuit soft fault diagnosis has been presented in this paper. The proposed method uses the wavelet packet energy spectrum and sparse random projections to preprocess the time response for feature extraction. Then, the variables of the fault features are constructed, which are used to form the observation sequences of K-nearest neighbor classifier. K-nearest neighbor classifier is used to accomplish the fault diagnosis of analog circuit. In this paper, four-opamp biquad high-pass filter has been used as simulation example to verify the effectiveness of the proposed method. The simulations show that the proposed method offers higher correct fault location rate in analog circuit soft fault diagnosis application as compared with the other methods.Jian SunGuobin HuChenghua WangHindawi LimitedarticleComputer softwareQA76.75-76.765ENScientific Programming, Vol 2021 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Computer software QA76.75-76.765
spellingShingle	Computer software QA76.75-76.765 Jian Sun Guobin Hu Chenghua Wang Analog Circuit Soft Fault Diagnosis Based on Sparse Random Projections and K-Nearest Neighbor
description	Analog circuit fault diagnosis is a key problem in theory of circuit networks and has been investigated by many researchers in recent years. An approach based on sparse random projections (SRPs) and K-nearest neighbor (KNN) to the realization of analog circuit soft fault diagnosis has been presented in this paper. The proposed method uses the wavelet packet energy spectrum and sparse random projections to preprocess the time response for feature extraction. Then, the variables of the fault features are constructed, which are used to form the observation sequences of K-nearest neighbor classifier. K-nearest neighbor classifier is used to accomplish the fault diagnosis of analog circuit. In this paper, four-opamp biquad high-pass filter has been used as simulation example to verify the effectiveness of the proposed method. The simulations show that the proposed method offers higher correct fault location rate in analog circuit soft fault diagnosis application as compared with the other methods.
format	article
author	Jian Sun Guobin Hu Chenghua Wang
author_facet	Jian Sun Guobin Hu Chenghua Wang
author_sort	Jian Sun
title	Analog Circuit Soft Fault Diagnosis Based on Sparse Random Projections and K-Nearest Neighbor
title_short	Analog Circuit Soft Fault Diagnosis Based on Sparse Random Projections and K-Nearest Neighbor
title_full	Analog Circuit Soft Fault Diagnosis Based on Sparse Random Projections and K-Nearest Neighbor
title_fullStr	Analog Circuit Soft Fault Diagnosis Based on Sparse Random Projections and K-Nearest Neighbor
title_full_unstemmed	Analog Circuit Soft Fault Diagnosis Based on Sparse Random Projections and K-Nearest Neighbor
title_sort	analog circuit soft fault diagnosis based on sparse random projections and k-nearest neighbor
publisher	Hindawi Limited
publishDate	2021
url	https://doaj.org/article/0ea199d2c1144b64a19b49e0a2bd0630
work_keys_str_mv	AT jiansun analogcircuitsoftfaultdiagnosisbasedonsparserandomprojectionsandknearestneighbor AT guobinhu analogcircuitsoftfaultdiagnosisbasedonsparserandomprojectionsandknearestneighbor AT chenghuawang analogcircuitsoftfaultdiagnosisbasedonsparserandomprojectionsandknearestneighbor
_version_	1718428905760620544

Analog Circuit Soft Fault Diagnosis Based on Sparse Random Projections and K-Nearest Neighbor

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