Current-Residual-Based Stator Interturn Fault Detection in Permanent Magnet Machines
Interturn short-circuit fault, also known as turn fault, is a common fault in electric machines, which can cause severe damages if no prompt detection and mitigation are conducted. This article proposes a turn fault detection method for permanent magnet machines based on current residual. After the...
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Veröffentlicht in: | IEEE transactions on industrial electronics (1982) 2021-01, Vol.68 (1), p.59-69 |
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description | Interturn short-circuit fault, also known as turn fault, is a common fault in electric machines, which can cause severe damages if no prompt detection and mitigation are conducted. This article proposes a turn fault detection method for permanent magnet machines based on current residual. After the impact of the turn fault is first analyzed on a simplified mathematical machine model to assess the fault signature, a finite-element model is developed to obtain healthy machine behavior. The residual between the measured and estimated currents by the model with the same applied voltages contains mainly the fault features. The quality of the fault detection can be improved because the fault signatures are enhanced, and the impact of the current controller bandwidth on fault signature is minimized. The dc components in the negative-sequence current residuals are extracted through angular integration, and their magnitude is defined as the fault indicator. The robustness of the fault detection against transient states is achieved. The effectiveness of the proposed method is validated on a triple redundant fault-tolerant permanent-magnet-assisted synchronous reluctance machine. |
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This article proposes a turn fault detection method for permanent magnet machines based on current residual. After the impact of the turn fault is first analyzed on a simplified mathematical machine model to assess the fault signature, a finite-element model is developed to obtain healthy machine behavior. The residual between the measured and estimated currents by the model with the same applied voltages contains mainly the fault features. The quality of the fault detection can be improved because the fault signatures are enhanced, and the impact of the current controller bandwidth on fault signature is minimized. The dc components in the negative-sequence current residuals are extracted through angular integration, and their magnitude is defined as the fault indicator. The robustness of the fault detection against transient states is achieved. The effectiveness of the proposed method is validated on a triple redundant fault-tolerant permanent-magnet-assisted synchronous reluctance machine.</description><identifier>ISSN: 0278-0046</identifier><identifier>EISSN: 1557-9948</identifier><identifier>DOI: 10.1109/TIE.2020.2965500</identifier><identifier>CODEN: ITIED6</identifier><language>eng</language><publisher>New York: IEEE</publisher><subject>Analytical models ; Circuit faults ; Current residual ; Damage detection ; dc component extraction ; Fault detection ; Fault tolerance ; Finite element method ; Harmonic analysis ; Insulation ; Mathematical model ; Mathematical models ; negative sequence ; permanent magnet machine ; Permanent magnets ; Reluctance machinery ; Robustness (mathematics) ; Short circuits ; Transient analysis ; turn fault detection</subject><ispartof>IEEE transactions on industrial electronics (1982), 2021-01, Vol.68 (1), p.59-69</ispartof><rights>Copyright The Institute of Electrical and Electronics Engineers, Inc. (IEEE) 2021</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c333t-1a6797edf84009c0c4ec8e436a67b5ffa11a52bd20fda27c33db1833b53b50343</citedby><cites>FETCH-LOGICAL-c333t-1a6797edf84009c0c4ec8e436a67b5ffa11a52bd20fda27c33db1833b53b50343</cites><orcidid>0000-0003-0057-0743 ; 0000-0002-6798-5284 ; 0000-0003-4870-3744</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://ieeexplore.ieee.org/document/8960656$$EHTML$$P50$$Gieee$$H</linktohtml><link.rule.ids>314,776,780,792,27901,27902,54733</link.rule.ids><linktorsrc>$$Uhttps://ieeexplore.ieee.org/document/8960656$$EView_record_in_IEEE$$FView_record_in_$$GIEEE</linktorsrc></links><search><creatorcontrib>Hu, Rongguang</creatorcontrib><creatorcontrib>Wang, Jiabin</creatorcontrib><creatorcontrib>Mills, Andrew R.</creatorcontrib><creatorcontrib>Chong, Ellis</creatorcontrib><creatorcontrib>Sun, Zhigang</creatorcontrib><title>Current-Residual-Based Stator Interturn Fault Detection in Permanent Magnet Machines</title><title>IEEE transactions on industrial electronics (1982)</title><addtitle>TIE</addtitle><description>Interturn short-circuit fault, also known as turn fault, is a common fault in electric machines, which can cause severe damages if no prompt detection and mitigation are conducted. This article proposes a turn fault detection method for permanent magnet machines based on current residual. After the impact of the turn fault is first analyzed on a simplified mathematical machine model to assess the fault signature, a finite-element model is developed to obtain healthy machine behavior. The residual between the measured and estimated currents by the model with the same applied voltages contains mainly the fault features. The quality of the fault detection can be improved because the fault signatures are enhanced, and the impact of the current controller bandwidth on fault signature is minimized. The dc components in the negative-sequence current residuals are extracted through angular integration, and their magnitude is defined as the fault indicator. The robustness of the fault detection against transient states is achieved. The effectiveness of the proposed method is validated on a triple redundant fault-tolerant permanent-magnet-assisted synchronous reluctance machine.</description><subject>Analytical models</subject><subject>Circuit faults</subject><subject>Current residual</subject><subject>Damage detection</subject><subject>dc component extraction</subject><subject>Fault detection</subject><subject>Fault tolerance</subject><subject>Finite element method</subject><subject>Harmonic analysis</subject><subject>Insulation</subject><subject>Mathematical model</subject><subject>Mathematical models</subject><subject>negative sequence</subject><subject>permanent magnet machine</subject><subject>Permanent magnets</subject><subject>Reluctance machinery</subject><subject>Robustness (mathematics)</subject><subject>Short circuits</subject><subject>Transient analysis</subject><subject>turn fault detection</subject><issn>0278-0046</issn><issn>1557-9948</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2021</creationdate><recordtype>article</recordtype><sourceid>RIE</sourceid><recordid>eNo9kE1Lw0AQhhdRsFbvgpeA59TZzyRHra0GKorW87JJJprSburu5uC_d0OLMDAwvM_M8BByTWFGKRR363IxY8BgxgolJcAJmVAps7QoRH5KJsCyPAUQ6pxceL8BoEJSOSHr-eAc2pC-o--awWzTB-OxST6CCb1LShvQhcHZZGmGbUgeMWAdut4mnU3e0O2MjXDyYr4sjq3-7iz6S3LWmq3Hq2Ofks_lYj1_TlevT-X8fpXWnPOQUqOyIsOmzQVAUUMtsM5RcBXnlWxbQ6mRrGoYtI1hWYSaiuacVzIWcMGn5Pawd-_6nwF90Js-_hpPaiakEBnwfEzBIVW73nuHrd67bmfcr6agR3c6utOjO310F5GbA9Ih4n88LxQoqfgfO3FqRg</recordid><startdate>202101</startdate><enddate>202101</enddate><creator>Hu, Rongguang</creator><creator>Wang, Jiabin</creator><creator>Mills, Andrew R.</creator><creator>Chong, Ellis</creator><creator>Sun, Zhigang</creator><general>IEEE</general><general>The Institute of Electrical and Electronics Engineers, Inc. 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subjects | Analytical models Circuit faults Current residual Damage detection dc component extraction Fault detection Fault tolerance Finite element method Harmonic analysis Insulation Mathematical model Mathematical models negative sequence permanent magnet machine Permanent magnets Reluctance machinery Robustness (mathematics) Short circuits Transient analysis turn fault detection |
title | Current-Residual-Based Stator Interturn Fault Detection in Permanent Magnet Machines |
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