An Intelligent Fault Diagnosis Method Based-on Extension Theory for DC-AC Converters

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Title:	An Intelligent Fault Diagnosis Method Based-on Extension Theory for DC-AC Converters
Authors:	Kuei-Hsiang Chao, Pi-Yun Chen
Contributors:	圖書館
Keywords:	Extension algorithm Fault diagnosis DC–AC converter Characteristic spectrum
Date:	2015-03
Issue Date:	2016-10-17
Abstract:	In this paper, an extension evaluation method was proposed to diagnose the fault of a DC–AC converter in a motor drive system. First, the PSIM software package was used to construct a three-level neutral point clamped (NPC) DC–AC converter for simulating the occurrence of the fault of any power transistor in the NPC DC–AC converter. Simultaneously, the fast Fourier transform was adopted to transcribe the waveform of phase voltage in time domain into the spectrum in frequency domain, looking for the corresponding characteristic spectrum during the fault of the power transistor in a DC–AC converter. Then, we establish the relationship between the fault type and the specific spectrum as the characteristics of the extension evaluation method, building up a fault diagnosis system for a DC–AC converter. Finally, the simulation results are made to demonstrate the feasibility of the proposed intelligent fault diagnosis system.
Relation:	International Journal of Fuzzy Systems
Appears in Collections:	[Department of Electrical Engineering] 【電機工程系所】期刊論文

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