A Detection Method for Fast Electrical Impedance Imaging of Grounding Grid Based on Optimized Differential-Multigrid-Homotopy Algorithm
Efficient electrical impedance imaging fault detection in grounding grid is necessary. In this article, we propose an optimized differential-multigrid-homotopy (MG-HT) algorithm for grounding grid impedance imaging. To enhance the iteration speed, we introduced an optimized differential algorithm to...
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| Veröffentlicht in: | IEEE transactions on instrumentation and measurement 2023, Vol.72, p.1-14 |
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| creator | Yan, Xiaoheng Huang, Shangfei Smolik, Waldemar Tomasz Chen, Weihua Yang, Songhan |
| description | Efficient electrical impedance imaging fault detection in grounding grid is necessary. In this article, we propose an optimized differential-multigrid-homotopy (MG-HT) algorithm for grounding grid impedance imaging. To enhance the iteration speed, we introduced an optimized differential algorithm to obtain the Jacobian matrix and derive calculation methods for the 2-D constraint operator and interpolation operator. Moreover, we utilize multigrid fast iteration and HT methods simultaneously to improve the rapidity and ill-posedness of the inverse problem. We validate the proposed algorithm through numerical simulations and experimental studies. First, we verify the time and convergence of the optimized differential algorithm for solving the Jacobian matrix. Second, we investigate the CPU time and convergence of image reconstruction based on the Tikhonov algorithm, HT algorithm, and MG-HT algorithm under different ground grid fault scenarios and noise levels. The simulation and experimental results show that the optimized differential-MG-HT algorithm has better robustness and convergence. |
| doi_str_mv | 10.1109/TIM.2023.3311059 |
| format | Article |
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In this article, we propose an optimized differential-multigrid-homotopy (MG-HT) algorithm for grounding grid impedance imaging. To enhance the iteration speed, we introduced an optimized differential algorithm to obtain the Jacobian matrix and derive calculation methods for the 2-D constraint operator and interpolation operator. Moreover, we utilize multigrid fast iteration and HT methods simultaneously to improve the rapidity and ill-posedness of the inverse problem. We validate the proposed algorithm through numerical simulations and experimental studies. First, we verify the time and convergence of the optimized differential algorithm for solving the Jacobian matrix. Second, we investigate the CPU time and convergence of image reconstruction based on the Tikhonov algorithm, HT algorithm, and MG-HT algorithm under different ground grid fault scenarios and noise levels. The simulation and experimental results show that the optimized differential-MG-HT algorithm has better robustness and convergence.</description><identifier>ISSN: 0018-9456</identifier><identifier>EISSN: 1557-9662</identifier><identifier>DOI: 10.1109/TIM.2023.3311059</identifier><identifier>CODEN: IEIMAO</identifier><language>eng</language><publisher>New York: IEEE</publisher><subject>Algorithms ; Computer simulation ; Conductivity ; Convergence ; Electrical grounding ; Electrical impedance ; Electrical impedance imaging ; Electrical impedance tomography ; Fault detection ; Finite element analysis ; Grounding ; grounding grid ; Image reconstruction ; Imaging ; Impedance ; Interpolation ; Inverse problems ; Iterative methods ; Jacobi matrix method ; Jacobian matrix ; Multigrid methods ; multigrid-homotopy (MG-HT) algorithm ; Noise levels ; Operators (mathematics) ; optimized differential algorithm ; Robustness (mathematics)</subject><ispartof>IEEE transactions on instrumentation and measurement, 2023, Vol.72, p.1-14</ispartof><rights>Copyright The Institute of Electrical and Electronics Engineers, Inc. (IEEE) 2023</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c292t-b3d659130eb2a88baacaf78fbaf7d6fc872d8d0a275d5d2d8e37b411e59c802b3</citedby><cites>FETCH-LOGICAL-c292t-b3d659130eb2a88baacaf78fbaf7d6fc872d8d0a275d5d2d8e37b411e59c802b3</cites><orcidid>0000-0002-7481-1610 ; 0009-0002-1095-9277 ; 0000-0002-1524-5049 ; 0000-0002-9048-9035 ; 0009-0009-7564-4197</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://ieeexplore.ieee.org/document/10237265$$EHTML$$P50$$Gieee$$H</linktohtml><link.rule.ids>314,777,781,793,4010,27904,27905,27906,54739</link.rule.ids><linktorsrc>$$Uhttps://ieeexplore.ieee.org/document/10237265$$EView_record_in_IEEE$$FView_record_in_$$GIEEE</linktorsrc></links><search><creatorcontrib>Yan, Xiaoheng</creatorcontrib><creatorcontrib>Huang, Shangfei</creatorcontrib><creatorcontrib>Smolik, Waldemar Tomasz</creatorcontrib><creatorcontrib>Chen, Weihua</creatorcontrib><creatorcontrib>Yang, Songhan</creatorcontrib><title>A Detection Method for Fast Electrical Impedance Imaging of Grounding Grid Based on Optimized Differential-Multigrid-Homotopy Algorithm</title><title>IEEE transactions on instrumentation and measurement</title><addtitle>TIM</addtitle><description>Efficient electrical impedance imaging fault detection in grounding grid is necessary. In this article, we propose an optimized differential-multigrid-homotopy (MG-HT) algorithm for grounding grid impedance imaging. To enhance the iteration speed, we introduced an optimized differential algorithm to obtain the Jacobian matrix and derive calculation methods for the 2-D constraint operator and interpolation operator. Moreover, we utilize multigrid fast iteration and HT methods simultaneously to improve the rapidity and ill-posedness of the inverse problem. We validate the proposed algorithm through numerical simulations and experimental studies. First, we verify the time and convergence of the optimized differential algorithm for solving the Jacobian matrix. Second, we investigate the CPU time and convergence of image reconstruction based on the Tikhonov algorithm, HT algorithm, and MG-HT algorithm under different ground grid fault scenarios and noise levels. The simulation and experimental results show that the optimized differential-MG-HT algorithm has better robustness and convergence.</description><subject>Algorithms</subject><subject>Computer simulation</subject><subject>Conductivity</subject><subject>Convergence</subject><subject>Electrical grounding</subject><subject>Electrical impedance</subject><subject>Electrical impedance imaging</subject><subject>Electrical impedance tomography</subject><subject>Fault detection</subject><subject>Finite element analysis</subject><subject>Grounding</subject><subject>grounding grid</subject><subject>Image reconstruction</subject><subject>Imaging</subject><subject>Impedance</subject><subject>Interpolation</subject><subject>Inverse problems</subject><subject>Iterative methods</subject><subject>Jacobi matrix method</subject><subject>Jacobian matrix</subject><subject>Multigrid methods</subject><subject>multigrid-homotopy (MG-HT) algorithm</subject><subject>Noise levels</subject><subject>Operators (mathematics)</subject><subject>optimized differential algorithm</subject><subject>Robustness (mathematics)</subject><issn>0018-9456</issn><issn>1557-9662</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2023</creationdate><recordtype>article</recordtype><sourceid>RIE</sourceid><recordid>eNpNkD1PwzAQhi0EEqWwMzBYYk7xR5yPsfRbatWlzJETn1tXSRwcdyh_gL-Nq3ZgubtX99570oPQKyUjSkn-sVttRowwPuI8aJHfoQEVIo3yJGH3aEAIzaI8Fskjeur7IyEkTeJ0gH7HeAoeKm9sizfgD1ZhbR2ey97jWR0WzlSyxqumAyXbCsIk96bdY6vxwtlTqy5i4YzCn7IHhUPOtvOmMT9BTI3W4KD1RtbR5lR7sw_OaGkb6213xuN6b53xh-YZPWhZ9_By60P0NZ_tJstovV2sJuN1VLGc-ajkKhE55QRKJrOslLKSOs10GapKdJWlTGWKSJYKJVSYgadlTCmIvMoIK_kQvV9zO2e_T9D74mhPrg0vC5YlMY8v0IKLXF2Vs33vQBedM41054KS4oK7CLiLC-7ihjucvF1PDAD8szOeskTwP5vefdk</recordid><startdate>2023</startdate><enddate>2023</enddate><creator>Yan, Xiaoheng</creator><creator>Huang, Shangfei</creator><creator>Smolik, Waldemar Tomasz</creator><creator>Chen, Weihua</creator><creator>Yang, Songhan</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>7U5</scope><scope>8FD</scope><scope>L7M</scope><orcidid>https://orcid.org/0000-0002-7481-1610</orcidid><orcidid>https://orcid.org/0009-0002-1095-9277</orcidid><orcidid>https://orcid.org/0000-0002-1524-5049</orcidid><orcidid>https://orcid.org/0000-0002-9048-9035</orcidid><orcidid>https://orcid.org/0009-0009-7564-4197</orcidid></search><sort><creationdate>2023</creationdate><title>A Detection Method for Fast Electrical Impedance Imaging of Grounding Grid Based on Optimized Differential-Multigrid-Homotopy Algorithm</title><author>Yan, Xiaoheng ; Huang, Shangfei ; Smolik, Waldemar Tomasz ; Chen, Weihua ; Yang, Songhan</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c292t-b3d659130eb2a88baacaf78fbaf7d6fc872d8d0a275d5d2d8e37b411e59c802b3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2023</creationdate><topic>Algorithms</topic><topic>Computer simulation</topic><topic>Conductivity</topic><topic>Convergence</topic><topic>Electrical grounding</topic><topic>Electrical impedance</topic><topic>Electrical impedance imaging</topic><topic>Electrical impedance tomography</topic><topic>Fault detection</topic><topic>Finite element analysis</topic><topic>Grounding</topic><topic>grounding grid</topic><topic>Image reconstruction</topic><topic>Imaging</topic><topic>Impedance</topic><topic>Interpolation</topic><topic>Inverse problems</topic><topic>Iterative methods</topic><topic>Jacobi matrix method</topic><topic>Jacobian matrix</topic><topic>Multigrid methods</topic><topic>multigrid-homotopy (MG-HT) algorithm</topic><topic>Noise levels</topic><topic>Operators (mathematics)</topic><topic>optimized differential algorithm</topic><topic>Robustness (mathematics)</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Yan, Xiaoheng</creatorcontrib><creatorcontrib>Huang, Shangfei</creatorcontrib><creatorcontrib>Smolik, Waldemar Tomasz</creatorcontrib><creatorcontrib>Chen, Weihua</creatorcontrib><creatorcontrib>Yang, Songhan</creatorcontrib><collection>IEEE All-Society Periodicals Package (ASPP) 2005-present</collection><collection>IEEE All-Society Periodicals Package (ASPP) 1998-Present</collection><collection>IEEE Electronic Library (IEL)</collection><collection>CrossRef</collection><collection>Electronics & Communications Abstracts</collection><collection>Solid State and Superconductivity Abstracts</collection><collection>Technology Research Database</collection><collection>Advanced Technologies Database with Aerospace</collection><jtitle>IEEE transactions on instrumentation and measurement</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Yan, Xiaoheng</au><au>Huang, Shangfei</au><au>Smolik, Waldemar Tomasz</au><au>Chen, Weihua</au><au>Yang, Songhan</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>A Detection Method for Fast Electrical Impedance Imaging of Grounding Grid Based on Optimized Differential-Multigrid-Homotopy Algorithm</atitle><jtitle>IEEE transactions on instrumentation and measurement</jtitle><stitle>TIM</stitle><date>2023</date><risdate>2023</risdate><volume>72</volume><spage>1</spage><epage>14</epage><pages>1-14</pages><issn>0018-9456</issn><eissn>1557-9662</eissn><coden>IEIMAO</coden><abstract>Efficient electrical impedance imaging fault detection in grounding grid is necessary. In this article, we propose an optimized differential-multigrid-homotopy (MG-HT) algorithm for grounding grid impedance imaging. To enhance the iteration speed, we introduced an optimized differential algorithm to obtain the Jacobian matrix and derive calculation methods for the 2-D constraint operator and interpolation operator. Moreover, we utilize multigrid fast iteration and HT methods simultaneously to improve the rapidity and ill-posedness of the inverse problem. We validate the proposed algorithm through numerical simulations and experimental studies. First, we verify the time and convergence of the optimized differential algorithm for solving the Jacobian matrix. Second, we investigate the CPU time and convergence of image reconstruction based on the Tikhonov algorithm, HT algorithm, and MG-HT algorithm under different ground grid fault scenarios and noise levels. 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| subjects | Algorithms Computer simulation Conductivity Convergence Electrical grounding Electrical impedance Electrical impedance imaging Electrical impedance tomography Fault detection Finite element analysis Grounding grounding grid Image reconstruction Imaging Impedance Interpolation Inverse problems Iterative methods Jacobi matrix method Jacobian matrix Multigrid methods multigrid-homotopy (MG-HT) algorithm Noise levels Operators (mathematics) optimized differential algorithm Robustness (mathematics) |
| title | A Detection Method for Fast Electrical Impedance Imaging of Grounding Grid Based on Optimized Differential-Multigrid-Homotopy Algorithm |
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