IFRA Technique to Detect Stator Winding High Impedance Earth Faults During Startup in Salient-Pole Synchronous Generators

IF 7.2 1区 工程技术 Q1 AUTOMATION & CONTROL SYSTEMS IEEE Transactions on Industrial Electronics Pub Date : 2024-12-30 DOI:10.1109/TIE.2024.3519635
Mohammad Zamani;Farhad Haghjoo;Mohammad Reza Haseli;Sérgio M. A. Cruz
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Abstract

This article introduces an impulse frequency response analysis (IFRA) technique to detect stator winding earth faults in salient-pole synchronous generators during startup. The proposed technique involves injecting a square pulse with an appropriate frequency spectrum into the neutral point of the stator winding, which is grounded through a resistance. The transmitted signals from the three phases are captured through high-pass filters installed at the machine terminals. These signals are decomposed in the time-frequency domain using the stationary wavelet transform (SWT). By analyzing and comparing the similarity/dissimilarity of these signals at an appropriate frequency band, a numerical index is defined to detect earth faults. Experimental results on a laboratory salient-pole synchronous generator demonstrate that this technique can detect high-impedance earth faults, even in the vicinity of the neutral point, with high sensitivity. Additionally, the defective phase can be identified using this method.
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在盐极同步发电机启动期间检测定子绕组高阻抗接地故障的 IFRA 技术
介绍了一种利用脉冲频率响应分析(IFRA)技术检测凸极同步发电机启动时定子绕组接地故障的方法。所提出的技术包括在定子绕组的中性点注入一个具有适当频谱的方脉冲,该中性点通过电阻接地。通过安装在机器终端上的高通滤波器捕获来自三个相位的传输信号。利用平稳小波变换(SWT)对这些信号进行时频分解。通过分析和比较这些信号在适当频段的相同点和不同点,定义了一个数字指标来检测接地故障。在实验室显著极同步发电机上的实验结果表明,该方法可以检测出高阻抗接地故障,即使是在中性点附近,也具有较高的灵敏度。此外,缺陷相可以用这种方法来识别。
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来源期刊
IEEE Transactions on Industrial Electronics
IEEE Transactions on Industrial Electronics 工程技术-工程:电子与电气
CiteScore
16.80
自引率
9.10%
发文量
1396
审稿时长
6.3 months
期刊介绍: Journal Name: IEEE Transactions on Industrial Electronics Publication Frequency: Monthly Scope: The scope of IEEE Transactions on Industrial Electronics encompasses the following areas: Applications of electronics, controls, and communications in industrial and manufacturing systems and processes. Power electronics and drive control techniques. System control and signal processing. Fault detection and diagnosis. Power systems. Instrumentation, measurement, and testing. Modeling and simulation. Motion control. Robotics. Sensors and actuators. Implementation of neural networks, fuzzy logic, and artificial intelligence in industrial systems. Factory automation. Communication and computer networks.
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