首页|基于FrFT-Mel的高灵敏变频电机匝绝缘状态感知方法

基于FrFT-Mel的高灵敏变频电机匝绝缘状态感知方法

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  • 国家科技期刊平台
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  • NSTL
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随着新型电力系统和电动汽车的迅速发展，变频电机已逐渐成为高效能源转换的关键设备。定子绕组匝绝缘故障是导致变频电机故障的根本原因之一。对匝绝缘健康状况的在线监测可以及时发现潜在的安全风险，但面临着匝绝缘劣化特性较弱的挑战。本研究提出了一种利用分数阶傅里叶变换和改进型梅尔滤波器（FrFT-Mel）来评估变频电机匝绝缘状态的新方法。首先，在分数域内分析了高频开关振荡电流对匝绝缘变化的灵敏性。随后，设计了一种改进型梅尔滤波器，并根据电机共模阻抗谐振点的固有特征专门设计了其结构和参数。最后，提出了变频电机匝绝缘状态的评估指标。在一台3千瓦永磁同步电机（PMSM）上的实验结果表明，与传统的傅立叶变换方法相比，所提出的FrFT-Mel方法显著提高了匝绝缘状态感知的灵敏度，提高了约五倍。
High-sensitive state perception method for inverter-fed machine turn insulation based on FrFT-Mel
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.

State perceptionTurn insulationSwitching oscillationFractional Fourier transformMel filter

范瑞天、雷兴、贾涛、秦梦龙、李豪、向大为

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College of Electrical Power Engineering,Shanghai University of Electric Power,Shanghai 200090,P.R.China

State Grid Shanghai Municipal Electric Power Company,Shanghai 200437,P.R.China

State Grid Technology College,Shandong 250002,P.R.China

College of Electronics and Information Engineering,Tongji University,Shanghai 201804,P.R.China

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状态感知 匝绝缘 开关振荡 分数阶傅里叶变换 梅尔滤波器

National Natural Science Foundation of ChinaNatural Science Foundation of ShanghaiShanghai Rising-Star Program

5190711622ZR142540023QA1404000

2024

10.1016/j.gloei.2024.04.004

全球能源互联网(英文)

全球能源互联网(英文)

CSTPCDEI
ISSN：2096-5117
年,卷(期)：2024.7(2)
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