A data-driven method for IGBT open-circuit fault diagnosis based on hybrid ensemble learning and sliding-window classification

• المؤلفون الرئيسيون: Xia, Yang, Xu, Yan, Gou, Bin
• مؤلفون آخرون: School of Electrical and Electronic Engineering
• التنسيق: مقال
• اللغة: English
• منشور في: 2022
• الموضوعات: Engineering::Electrical and electronic engineering; Hybrid Ensemble Learning; Multiobjective Optimization Programming
• الوصول للمادة أونلاين: https://hdl.handle.net/10356/155302

In this article, a novel data-driven method is proposed for open-circuit fault diagnosis of insulated gate bipolar transistor used in three-phase pulsewidth modulation converter. Based on the sampled three-phase current signals, fast Fourier transform and ReliefF algorithm are used to select most co...