全球能源互联网（英文）2024，Vol.7Issue(2)：155-165,11.DOI:10.1016/j.gloei.2024.04.004
基于FrFT-Mel的高灵敏变频电机匝绝缘状态感知方法
High-sensitive state perception method for inverter-fed machine turn insulation based on FrFT-Mel
摘要
Abstract
Amidst the swift advancement of new power systems and electric vehicles,inverter-fed machines have progressively materialized as a pivotal apparatus for efficient energy conversion.Stator winding turn insulation failure is the root cause of inverter-fed machine breakdown.The online monitoring of turn insulation health can detect potential safety risks promptly,but faces the challenge of weak characteristics of turn insulation degradation.This study proposes an innovative method to evaluate the turn insulation state of inverter-fed machines by utilizing the fractional Fourier transform with a Mel filter(FrFT-Mel).First,the sensitivity of the high-frequency(HF)switching oscillation current to variations in turn insulation was analyzed within the fractional domain.Subsequently,an improved Mel filter is introduced,and its structure and parameters are specifically designed based on the features intrinsic to the common-mode impedance resonance point of the electrical machine.Finally,an evaluation index was proposed for the turn insulation state of inverter-fed machines.Experimental results on a 3kW permanent magnet synchronous machine(PMSM)demonstrate that the proposed FrFT-Mel method significantly enhances the sensitivity of turn insulation state perception by approximately five times,compared to the traditional Fourier transform method.关键词
状态感知/匝绝缘/开关振荡/分数阶傅里叶变换/梅尔滤波器Key words
State perception/Turn insulation/Switching oscillation/Fractional Fourier transform/Mel filter引用本文复制引用
范瑞天,雷兴,贾涛,秦梦龙,李豪,向大为..基于FrFT-Mel的高灵敏变频电机匝绝缘状态感知方法[J].全球能源互联网（英文）,2024,7(2):155-165,11.基金项目
This work was supported in part by the National Natural Science Foundation of China under Grant 51907116,in part sponsored by Natural Science Foundation of Shanghai 22ZR1425400 and sponsored by Shanghai Rising-Star Program 23QA1404000. （）
