Neural Network Based Fault Detection and Diagnosis System for Three-Phase Inverter in Variable Speed Drive with Induction Motor
Recently, electrical drives generally associate inverter and induction machine. Therefore, inverter must be taken into consideration along with induction motor in order to provide a relevant and efficient diagnosis of these systems. Various faults in inverter may influence the system operation by un...
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| Format: | Article |
| Language: | English |
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Wiley
2016-01-01
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| Series: | Journal of Control Science and Engineering |
| Online Access: | http://dx.doi.org/10.1155/2016/1286318 |
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| _version_ | 1849467552878559232 |
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| author | Furqan Asghar Muhammad Talha Sung Ho Kim |
| author_facet | Furqan Asghar Muhammad Talha Sung Ho Kim |
| author_sort | Furqan Asghar |
| collection | DOAJ |
| description | Recently, electrical drives generally associate inverter and induction machine. Therefore, inverter must be taken into consideration along with induction motor in order to provide a relevant and efficient diagnosis of these systems. Various faults in inverter may influence the system operation by unexpected maintenance, which increases the cost factor and reduces overall efficiency. In this paper, fault detection and diagnosis based on features extraction and neural network technique for three-phase inverter is presented. Basic purpose of this fault detection and diagnosis system is to detect single or multiple faults efficiently. Several features are extracted from the Clarke transformed output current and used in neural network as input for fault detection and diagnosis. Hence, some simulation study as well as hardware implementation and experimentation is carried out to verify the feasibility of the proposed scheme. Results show that the designed system not only detects faults easily, but also can effectively differentiate between multiple faults. These results prove the credibility and show the satisfactory performance of designed system. Results prove the supremacy of designed system over previous feature extraction fault systems as it can detect and diagnose faults in a single cycle as compared to previous multicycles detection with high accuracy. |
| format | Article |
| id | doaj-art-e78052d783e440f9b585cb0e7caaf3d1 |
| institution | Kabale University |
| issn | 1687-5249 1687-5257 |
| language | English |
| publishDate | 2016-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Journal of Control Science and Engineering |
| spelling | doaj-art-e78052d783e440f9b585cb0e7caaf3d12025-08-20T03:26:10ZengWileyJournal of Control Science and Engineering1687-52491687-52572016-01-01201610.1155/2016/12863181286318Neural Network Based Fault Detection and Diagnosis System for Three-Phase Inverter in Variable Speed Drive with Induction MotorFurqan Asghar0Muhammad Talha1Sung Ho Kim2Kunsan National University, Saemangeum Campus, Room No. 202/203, Osikdo-Dong, Gunsan-Si, Jeollabuk-Do 573-540, Republic of KoreaSchool of Electronics and Information Engineering, Kunsan National University, Kunsan, Republic of KoreaDepartment of Control and Robotics Engineering, Kunsan National University, Kunsan, Republic of KoreaRecently, electrical drives generally associate inverter and induction machine. Therefore, inverter must be taken into consideration along with induction motor in order to provide a relevant and efficient diagnosis of these systems. Various faults in inverter may influence the system operation by unexpected maintenance, which increases the cost factor and reduces overall efficiency. In this paper, fault detection and diagnosis based on features extraction and neural network technique for three-phase inverter is presented. Basic purpose of this fault detection and diagnosis system is to detect single or multiple faults efficiently. Several features are extracted from the Clarke transformed output current and used in neural network as input for fault detection and diagnosis. Hence, some simulation study as well as hardware implementation and experimentation is carried out to verify the feasibility of the proposed scheme. Results show that the designed system not only detects faults easily, but also can effectively differentiate between multiple faults. These results prove the credibility and show the satisfactory performance of designed system. Results prove the supremacy of designed system over previous feature extraction fault systems as it can detect and diagnose faults in a single cycle as compared to previous multicycles detection with high accuracy.http://dx.doi.org/10.1155/2016/1286318 |
| spellingShingle | Furqan Asghar Muhammad Talha Sung Ho Kim Neural Network Based Fault Detection and Diagnosis System for Three-Phase Inverter in Variable Speed Drive with Induction Motor Journal of Control Science and Engineering |
| title | Neural Network Based Fault Detection and Diagnosis System for Three-Phase Inverter in Variable Speed Drive with Induction Motor |
| title_full | Neural Network Based Fault Detection and Diagnosis System for Three-Phase Inverter in Variable Speed Drive with Induction Motor |
| title_fullStr | Neural Network Based Fault Detection and Diagnosis System for Three-Phase Inverter in Variable Speed Drive with Induction Motor |
| title_full_unstemmed | Neural Network Based Fault Detection and Diagnosis System for Three-Phase Inverter in Variable Speed Drive with Induction Motor |
| title_short | Neural Network Based Fault Detection and Diagnosis System for Three-Phase Inverter in Variable Speed Drive with Induction Motor |
| title_sort | neural network based fault detection and diagnosis system for three phase inverter in variable speed drive with induction motor |
| url | http://dx.doi.org/10.1155/2016/1286318 |
| work_keys_str_mv | AT furqanasghar neuralnetworkbasedfaultdetectionanddiagnosissystemforthreephaseinverterinvariablespeeddrivewithinductionmotor AT muhammadtalha neuralnetworkbasedfaultdetectionanddiagnosissystemforthreephaseinverterinvariablespeeddrivewithinductionmotor AT sunghokim neuralnetworkbasedfaultdetectionanddiagnosissystemforthreephaseinverterinvariablespeeddrivewithinductionmotor |