Combined Diagnosis of PD Based on the Multidimensional Parameters
This paper presents a comprehensive multiparameter diagnosis method based on multiple partial discharge (PD) signals which include high-frequency current (HFC), ultrasound, and ultrahigh frequency (UHF). The HFC, ultrasound, and UHF PD are calculated under different types of faults. Therefor the cha...
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| Format: | Article |
| Language: | English |
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Wiley
2016-01-01
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| Series: | Modelling and Simulation in Engineering |
| Online Access: | http://dx.doi.org/10.1155/2016/5949140 |
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| _version_ | 1832558353256022016 |
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| author | Mohammad Heidari |
| author_facet | Mohammad Heidari |
| author_sort | Mohammad Heidari |
| collection | DOAJ |
| description | This paper presents a comprehensive multiparameter diagnosis method based on multiple partial discharge (PD) signals which include high-frequency current (HFC), ultrasound, and ultrahigh frequency (UHF). The HFC, ultrasound, and UHF PD are calculated under different types of faults. Therefor the characteristic values, as nine basic characteristic parameters, eight phase characteristic parameters, and the like are calculated. Diagnose signals are found with the method based on information fusion and semisupervised learning for HFC PD, adaptive mutation parameters of particle entropy for ultrasonic signals, and IIA-ART2A neural network for UHF signals. In addition, integrate the diagnostic results, which are the probability of fault of various defects and matrix, of different PD diagnosis signals, and analysis with Sugeno fuzzy integral to get the final diagnosis. |
| format | Article |
| id | doaj-art-eecfffe73c934dd48459f145765a0371 |
| institution | Kabale University |
| issn | 1687-5591 1687-5605 |
| language | English |
| publishDate | 2016-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Modelling and Simulation in Engineering |
| spelling | doaj-art-eecfffe73c934dd48459f145765a03712025-02-03T01:32:35ZengWileyModelling and Simulation in Engineering1687-55911687-56052016-01-01201610.1155/2016/59491405949140Combined Diagnosis of PD Based on the Multidimensional ParametersMohammad Heidari0Department of Mechanical Engineering, Abadan Branch, Islamic Azad University, Abadan, IranThis paper presents a comprehensive multiparameter diagnosis method based on multiple partial discharge (PD) signals which include high-frequency current (HFC), ultrasound, and ultrahigh frequency (UHF). The HFC, ultrasound, and UHF PD are calculated under different types of faults. Therefor the characteristic values, as nine basic characteristic parameters, eight phase characteristic parameters, and the like are calculated. Diagnose signals are found with the method based on information fusion and semisupervised learning for HFC PD, adaptive mutation parameters of particle entropy for ultrasonic signals, and IIA-ART2A neural network for UHF signals. In addition, integrate the diagnostic results, which are the probability of fault of various defects and matrix, of different PD diagnosis signals, and analysis with Sugeno fuzzy integral to get the final diagnosis.http://dx.doi.org/10.1155/2016/5949140 |
| spellingShingle | Mohammad Heidari Combined Diagnosis of PD Based on the Multidimensional Parameters Modelling and Simulation in Engineering |
| title | Combined Diagnosis of PD Based on the Multidimensional Parameters |
| title_full | Combined Diagnosis of PD Based on the Multidimensional Parameters |
| title_fullStr | Combined Diagnosis of PD Based on the Multidimensional Parameters |
| title_full_unstemmed | Combined Diagnosis of PD Based on the Multidimensional Parameters |
| title_short | Combined Diagnosis of PD Based on the Multidimensional Parameters |
| title_sort | combined diagnosis of pd based on the multidimensional parameters |
| url | http://dx.doi.org/10.1155/2016/5949140 |
| work_keys_str_mv | AT mohammadheidari combineddiagnosisofpdbasedonthemultidimensionalparameters |