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Short-Circuit Fault Diagnosis Based on Rough Sets Theory for a Single-Phase Inverter
The short-circuit (SC) fault diagnosis in inverters is an important procedure for the continuity of the performance and the extension of its useful life. The methods of diagnosis of SC failures produce good results, however, they present unfavorable aspects: they detect only one of the faults of SC,...
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Published in: | IEEE transactions on power electronics 2019-05, Vol.34 (5), p.4747-4764 |
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creator | de Mello Oliveira, Andre Barros Moreno, Robson Luiz Ribeiro, Enio Roberto |
description | The short-circuit (SC) fault diagnosis in inverters is an important procedure for the continuity of the performance and the extension of its useful life. The methods of diagnosis of SC failures produce good results, however, they present unfavorable aspects: they detect only one of the faults of SC, that is to say, the hard switch fault (HSF) or the fault under load (FUL); depend on switch parameters; and use artificial intelligence (AI) techniques in their algorithms, which are executed simultaneously with the inverter operation. This article presents a method of diagnosing SC faults performed with a digital circuit. The proposed method identifies short-circuit faults: HSF and FUL; can be used with any switch, regardless of its parameters; and does not use AI algorithms and techniques concurrently with inverter operation. The digital diagnostic circuit is obtained with the use of rough sets theory (RST), which optimizes and defines a minimum set of variables necessary to diagnose faults. Applying RST to the variables obtains a set of diagnostic rules. These rules are performed with basic logic functions and, for this reason, a digital diagnostic circuit is obtained. The diagnostic variables are the command signals and the voltage source inverter switches currents. The simulation and experimental results validate the shown diagnostic method. |
doi_str_mv | 10.1109/TPEL.2018.2861564 |
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The methods of diagnosis of SC failures produce good results, however, they present unfavorable aspects: they detect only one of the faults of SC, that is to say, the hard switch fault (HSF) or the fault under load (FUL); depend on switch parameters; and use artificial intelligence (AI) techniques in their algorithms, which are executed simultaneously with the inverter operation. This article presents a method of diagnosing SC faults performed with a digital circuit. The proposed method identifies short-circuit faults: HSF and FUL; can be used with any switch, regardless of its parameters; and does not use AI algorithms and techniques concurrently with inverter operation. The digital diagnostic circuit is obtained with the use of rough sets theory (RST), which optimizes and defines a minimum set of variables necessary to diagnose faults. Applying RST to the variables obtains a set of diagnostic rules. These rules are performed with basic logic functions and, for this reason, a digital diagnostic circuit is obtained. The diagnostic variables are the command signals and the voltage source inverter switches currents. The simulation and experimental results validate the shown diagnostic method.</description><identifier>ISSN: 0885-8993</identifier><identifier>EISSN: 1941-0107</identifier><identifier>DOI: 10.1109/TPEL.2018.2861564</identifier><identifier>CODEN: ITPEE8</identifier><language>eng</language><publisher>New York: IEEE</publisher><subject>Algorithms ; Artificial intelligence ; Circuit faults ; Computer simulation ; Current measurement ; Diagnostic systems ; Digital electronics ; Digital fault diagnosis circuit ; Fault detection ; fault detection and location ; Fault diagnosis ; fault diagnosis method ; Inverters ; Logic gates ; Parameters ; rough sets theory (RST) ; Short circuits ; short-circuit (SC) fault diagnosis ; single-phase voltage source inverter ; Switches ; Voltage measurement</subject><ispartof>IEEE transactions on power electronics, 2019-05, Vol.34 (5), p.4747-4764</ispartof><rights>Copyright The Institute of Electrical and Electronics Engineers, Inc. (IEEE) 2019</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c293t-498c57d7427c0edf071be4cf2cf40cdcd5eebf083b55ee3cac595c9483d28cc43</citedby><cites>FETCH-LOGICAL-c293t-498c57d7427c0edf071be4cf2cf40cdcd5eebf083b55ee3cac595c9483d28cc43</cites><orcidid>0000-0002-1938-7685 ; 0000-0002-5797-0759 ; 0000-0003-0347-0991</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://ieeexplore.ieee.org/document/8423507$$EHTML$$P50$$Gieee$$H</linktohtml><link.rule.ids>314,776,780,27901,27902,54771</link.rule.ids></links><search><creatorcontrib>de Mello Oliveira, Andre Barros</creatorcontrib><creatorcontrib>Moreno, Robson Luiz</creatorcontrib><creatorcontrib>Ribeiro, Enio Roberto</creatorcontrib><title>Short-Circuit Fault Diagnosis Based on Rough Sets Theory for a Single-Phase Inverter</title><title>IEEE transactions on power electronics</title><addtitle>TPEL</addtitle><description>The short-circuit (SC) fault diagnosis in inverters is an important procedure for the continuity of the performance and the extension of its useful life. The methods of diagnosis of SC failures produce good results, however, they present unfavorable aspects: they detect only one of the faults of SC, that is to say, the hard switch fault (HSF) or the fault under load (FUL); depend on switch parameters; and use artificial intelligence (AI) techniques in their algorithms, which are executed simultaneously with the inverter operation. This article presents a method of diagnosing SC faults performed with a digital circuit. The proposed method identifies short-circuit faults: HSF and FUL; can be used with any switch, regardless of its parameters; and does not use AI algorithms and techniques concurrently with inverter operation. The digital diagnostic circuit is obtained with the use of rough sets theory (RST), which optimizes and defines a minimum set of variables necessary to diagnose faults. Applying RST to the variables obtains a set of diagnostic rules. These rules are performed with basic logic functions and, for this reason, a digital diagnostic circuit is obtained. The diagnostic variables are the command signals and the voltage source inverter switches currents. The simulation and experimental results validate the shown diagnostic method.</description><subject>Algorithms</subject><subject>Artificial intelligence</subject><subject>Circuit faults</subject><subject>Computer simulation</subject><subject>Current measurement</subject><subject>Diagnostic systems</subject><subject>Digital electronics</subject><subject>Digital fault diagnosis circuit</subject><subject>Fault detection</subject><subject>fault detection and location</subject><subject>Fault diagnosis</subject><subject>fault diagnosis method</subject><subject>Inverters</subject><subject>Logic gates</subject><subject>Parameters</subject><subject>rough sets theory (RST)</subject><subject>Short circuits</subject><subject>short-circuit (SC) fault diagnosis</subject><subject>single-phase voltage source inverter</subject><subject>Switches</subject><subject>Voltage measurement</subject><issn>0885-8993</issn><issn>1941-0107</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2019</creationdate><recordtype>article</recordtype><recordid>eNo9kE1PwkAURSdGExH9AcbNJK6Lb77ozFIRlIREInU9KdNXWoIdnGlN-PeWQFy9uzj3vuQQcs9gxBiYp2w5XYw4MD3ieszUWF6QATOSJcAgvSQD0Fol2hhxTW5i3AIwqYANSLaqfGiTSR1cV7d0lne7lr7W-abxsY70JY9YUN_QT99tKrrCNtKsQh8OtPSB5nRVN5sdJsuqB-m8-cXQYrglV2W-i3h3vkPyNZtmk_dk8fE2nzwvEseNaBNptFNpkUqeOsCihJStUbqSu1KCK1yhENclaLFWfRIud8ooZ6QWBdfOSTEkj6fdffA_HcbWbn0Xmv6l5RyE7HVw1VPsRLngYwxY2n2ov_NwsAzsUZ49yrNHefYsr-88nDo1Iv7zWnKhIBV_1rBrHw</recordid><startdate>20190501</startdate><enddate>20190501</enddate><creator>de Mello Oliveira, Andre Barros</creator><creator>Moreno, Robson Luiz</creator><creator>Ribeiro, Enio Roberto</creator><general>IEEE</general><general>The Institute of Electrical and Electronics Engineers, Inc. (IEEE)</general><scope>97E</scope><scope>RIA</scope><scope>RIE</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7SP</scope><scope>7TB</scope><scope>8FD</scope><scope>FR3</scope><scope>JQ2</scope><scope>KR7</scope><scope>L7M</scope><orcidid>https://orcid.org/0000-0002-1938-7685</orcidid><orcidid>https://orcid.org/0000-0002-5797-0759</orcidid><orcidid>https://orcid.org/0000-0003-0347-0991</orcidid></search><sort><creationdate>20190501</creationdate><title>Short-Circuit Fault Diagnosis Based on Rough Sets Theory for a Single-Phase Inverter</title><author>de Mello Oliveira, Andre Barros ; Moreno, Robson Luiz ; Ribeiro, Enio Roberto</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c293t-498c57d7427c0edf071be4cf2cf40cdcd5eebf083b55ee3cac595c9483d28cc43</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2019</creationdate><topic>Algorithms</topic><topic>Artificial intelligence</topic><topic>Circuit faults</topic><topic>Computer simulation</topic><topic>Current measurement</topic><topic>Diagnostic systems</topic><topic>Digital electronics</topic><topic>Digital fault diagnosis circuit</topic><topic>Fault detection</topic><topic>fault detection and location</topic><topic>Fault diagnosis</topic><topic>fault diagnosis method</topic><topic>Inverters</topic><topic>Logic gates</topic><topic>Parameters</topic><topic>rough sets theory (RST)</topic><topic>Short circuits</topic><topic>short-circuit (SC) fault diagnosis</topic><topic>single-phase voltage source inverter</topic><topic>Switches</topic><topic>Voltage measurement</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>de Mello Oliveira, Andre Barros</creatorcontrib><creatorcontrib>Moreno, Robson Luiz</creatorcontrib><creatorcontrib>Ribeiro, Enio Roberto</creatorcontrib><collection>IEEE All-Society Periodicals Package (ASPP) 2005-present</collection><collection>IEEE All-Society Periodicals Package (ASPP) 1998–Present</collection><collection>IEEE/IET Electronic Library (IEL)</collection><collection>CrossRef</collection><collection>Electronics & Communications Abstracts</collection><collection>Mechanical & Transportation Engineering Abstracts</collection><collection>Technology Research Database</collection><collection>Engineering Research Database</collection><collection>ProQuest Computer Science Collection</collection><collection>Civil Engineering Abstracts</collection><collection>Advanced Technologies Database with Aerospace</collection><jtitle>IEEE transactions on power electronics</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>de Mello Oliveira, Andre Barros</au><au>Moreno, Robson Luiz</au><au>Ribeiro, Enio Roberto</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Short-Circuit Fault Diagnosis Based on Rough Sets Theory for a Single-Phase Inverter</atitle><jtitle>IEEE transactions on power electronics</jtitle><stitle>TPEL</stitle><date>2019-05-01</date><risdate>2019</risdate><volume>34</volume><issue>5</issue><spage>4747</spage><epage>4764</epage><pages>4747-4764</pages><issn>0885-8993</issn><eissn>1941-0107</eissn><coden>ITPEE8</coden><abstract>The short-circuit (SC) fault diagnosis in inverters is an important procedure for the continuity of the performance and the extension of its useful life. The methods of diagnosis of SC failures produce good results, however, they present unfavorable aspects: they detect only one of the faults of SC, that is to say, the hard switch fault (HSF) or the fault under load (FUL); depend on switch parameters; and use artificial intelligence (AI) techniques in their algorithms, which are executed simultaneously with the inverter operation. This article presents a method of diagnosing SC faults performed with a digital circuit. The proposed method identifies short-circuit faults: HSF and FUL; can be used with any switch, regardless of its parameters; and does not use AI algorithms and techniques concurrently with inverter operation. The digital diagnostic circuit is obtained with the use of rough sets theory (RST), which optimizes and defines a minimum set of variables necessary to diagnose faults. Applying RST to the variables obtains a set of diagnostic rules. 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subjects | Algorithms Artificial intelligence Circuit faults Computer simulation Current measurement Diagnostic systems Digital electronics Digital fault diagnosis circuit Fault detection fault detection and location Fault diagnosis fault diagnosis method Inverters Logic gates Parameters rough sets theory (RST) Short circuits short-circuit (SC) fault diagnosis single-phase voltage source inverter Switches Voltage measurement |
title | Short-Circuit Fault Diagnosis Based on Rough Sets Theory for a Single-Phase Inverter |
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