Artificial Neural Network Algorithm for Condition Monitoring of DC-link Capacitors Based on Capacitance Estimation
In power electronic converters, reliability of DC-link capacitors is one of the critical issues. The estimation of their health status as an application of condition monitoring have been an attractive subject for industrial field and hence for the academic research filed as well. More reliable solut...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Academy Publishing Center
2015-12-01
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| Series: | Renewable Energy and Sustainable Development |
| Subjects: | |
| Online Access: | http://apc.aast.edu/ojs/index.php/RESD/article/view/100 |
| _version_ | 1797258845187211264 |
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| author | Hammam Abdelaal Hammam Soliman Huai Wang Brwene Salah Abdelkarim Gadalla Frede Blaabjerg |
| author_facet | Hammam Abdelaal Hammam Soliman Huai Wang Brwene Salah Abdelkarim Gadalla Frede Blaabjerg |
| author_sort | Hammam Abdelaal Hammam Soliman |
| collection | DOAJ |
| description | In power electronic converters, reliability of DC-link capacitors is one of the critical issues. The estimation of their health status as an application of condition monitoring have been an attractive subject for industrial field and hence for the academic research filed as well. More reliable solutions are required to be adopted by the industry applications in which usage of extra hardware, increased cost, and low estimation accuracy are the main challenges. Therefore, development of new condition monitoring methods based on software solutions could be the new era that covers the aforementioned challenges. A capacitance estimation method based on Artificial Neural Network (ANN) algorithm is therefore proposed in this paper. The implemented ANN estimated the capacitance of the DC-link capacitor in a back-toback converter. Analysis of the error of the capacitance estimation is also given. The presented method enables a pure software based approach with high parameter estimation accuracy. |
| first_indexed | 2024-03-12T01:40:51Z |
| format | Article |
| id | doaj.art-ffe179a401b34a6a926a7fb3ef5842aa |
| institution | Directory Open Access Journal |
| issn | 2356-8518 2356-8569 |
| language | English |
| last_indexed | 2024-04-24T23:00:00Z |
| publishDate | 2015-12-01 |
| publisher | Academy Publishing Center |
| record_format | Article |
| series | Renewable Energy and Sustainable Development |
| spelling | doaj.art-ffe179a401b34a6a926a7fb3ef5842aa2024-03-17T15:35:46ZengAcademy Publishing CenterRenewable Energy and Sustainable Development2356-85182356-85692015-12-011229429910.21622/resd.2015.01.2.29455Artificial Neural Network Algorithm for Condition Monitoring of DC-link Capacitors Based on Capacitance EstimationHammam Abdelaal Hammam Soliman0Huai Wang1Brwene Salah Abdelkarim Gadalla2Frede Blaabjerg3Aalborg University, DenmarkAalborg University, DenmarkAalborg University, DenmarkAalborg University, DenmarkIn power electronic converters, reliability of DC-link capacitors is one of the critical issues. The estimation of their health status as an application of condition monitoring have been an attractive subject for industrial field and hence for the academic research filed as well. More reliable solutions are required to be adopted by the industry applications in which usage of extra hardware, increased cost, and low estimation accuracy are the main challenges. Therefore, development of new condition monitoring methods based on software solutions could be the new era that covers the aforementioned challenges. A capacitance estimation method based on Artificial Neural Network (ANN) algorithm is therefore proposed in this paper. The implemented ANN estimated the capacitance of the DC-link capacitor in a back-toback converter. Analysis of the error of the capacitance estimation is also given. The presented method enables a pure software based approach with high parameter estimation accuracy.http://apc.aast.edu/ojs/index.php/RESD/article/view/100capacitor condition monitoringcapacitor health statuscapacitance estimation. |
| spellingShingle | Hammam Abdelaal Hammam Soliman Huai Wang Brwene Salah Abdelkarim Gadalla Frede Blaabjerg Artificial Neural Network Algorithm for Condition Monitoring of DC-link Capacitors Based on Capacitance Estimation Renewable Energy and Sustainable Development capacitor condition monitoring capacitor health status capacitance estimation. |
| title | Artificial Neural Network Algorithm for Condition Monitoring of DC-link Capacitors Based on Capacitance Estimation |
| title_full | Artificial Neural Network Algorithm for Condition Monitoring of DC-link Capacitors Based on Capacitance Estimation |
| title_fullStr | Artificial Neural Network Algorithm for Condition Monitoring of DC-link Capacitors Based on Capacitance Estimation |
| title_full_unstemmed | Artificial Neural Network Algorithm for Condition Monitoring of DC-link Capacitors Based on Capacitance Estimation |
| title_short | Artificial Neural Network Algorithm for Condition Monitoring of DC-link Capacitors Based on Capacitance Estimation |
| title_sort | artificial neural network algorithm for condition monitoring of dc link capacitors based on capacitance estimation |
| topic | capacitor condition monitoring capacitor health status capacitance estimation. |
| url | http://apc.aast.edu/ojs/index.php/RESD/article/view/100 |
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