Journal
COMPUTERS & ELECTRICAL ENGINEERING
Volume 96, Issue -, Pages -Publisher
PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.compeleceng.2021.107481
Keywords
Fault detection; Fault classification; Support vector machine; Entropy of wavelet packet; Open circuit fault; IGBTs; Multilevel converter; Two-sample algorithm
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Funding
- Department of Electrical Engineering, Indian Institute of Technology (Banaras Hindu University), Varanasi, India
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This paper introduces a fast fault detection algorithm based on the two samples technique and a fault localization algorithm using the Entropy of Wavelet Packets as a feature, which can effectively classify and localize Open Circuit faults in Multilevel Converters.
The Open Circuit (OC) faults occurring in switches of Multilevel Converters (MLC) may lead to undesirable operation of the converter. Therefore, fault detection and its localization in minimum time are necessary. This paper focuses on the fast fault detection algorithm based on the two samples technique and the fault localization algorithm using the Entropy of Wavelet Packets (EWP) as a feature. The EWP feature is used to classify and localize the OC faults in Insulated Gate Bipolar Transistors (IGBTs) of three-phase, three-level inverter using Support Vector Machine (SVM) based fault classification algorithm. The proposed technique can detect the fault in single IGBT and multiple IGBTs in a lesser time range of microseconds to 0.33 ms. It gives better performance and accuracy (99.70%) than previously proposed SVM algorithms, as the EWP-based feature extraction process used in this paper is simple and accurate with a less computational burden.
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