In this paper, performance analysis of power system network is carried out by injecting the inter-turn fault at the power transformer. The injection of inter-turn fault generates the inrush current in the network. The power system network consists of transformer, current transformer, potential transformer, circuit breaker, isolator, resistance, inductance, loads, and generating source. The fault detection and termination related to inrush current has some drawbacks and limitations such as slow convergence rate, less stability and more distortion with the existing methods. These drawbacks motivate the researchers to overcome the drawbacks with new proposed methods using wavelet transformation with sample data control and fuzzy logic controller. The wavelet transformation is used to diagnose the fault type but contribute lesser for fault termination; due to that, sample data of different signals are collected at different frequencies. Further, the analysis of collected sample data is assessed by using Z-transformation and fuzzy logic controller for fault termination. The stability, total harmonic distortion and convergence rate of collected sample data among all three methods (wavelet transformation, Z-transformation and fuzzy logic controller) are compared for fault termination by using linear regression analysis. The complete performance of fault diagnosis along with fault termination has been analyzed on Simulink. It is observed that after fault injection at power transformer, fault recovers faster under fuzzy logic controller in comparison with Z-transformation followed by wavelet transformation due to higher stability, less total harmonic distortion and faster convergence.

本文通过在电力变压器中注入匝间故障来进行电力系统网络的性能分析。匝间故障的注入会在网络中产生浪涌电流。电力系统网络包括变压器，电流互感器，电压互感器，断路器，隔离器，电阻，电感，负载和发电源。与涌入电流有关的故障检测和终止具有一些缺点和局限性，例如现有方法收敛速度慢，稳定性差和失真大。这些缺点促使研究人员通过采用小波变换，样本数据控制和模糊逻辑控制器的新方法来克服这些缺点。小波变换用于诊断故障类型，但对故障终止的贡献较小。因此，以不同的频率收集不同信号的样本数据。此外，通过使用Z变换和模糊逻辑控制器评估收集的样本数据的分析以进行故障终止。通过线性回归分析比较了三种方法（小波变换，Z变换和模糊逻辑控制器）之间的稳定性，总谐波失真和所收集样本数据的收敛速度，以进行故障终止。已在Simulink上分析了故障诊断和故障终止的完整性能。可以看出，在变压器上注入故障之后，由于具有更高的稳定性，更少的总谐波失真和更快的收敛性，与Z变换和小波变换相比，在模糊逻辑控制器下故障恢复得更快。不同信号的采样数据以不同的频率收集。此外，通过使用Z变换和模糊逻辑控制器评估收集的样本数据的分析以进行故障终止。通过线性回归分析比较了三种方法（小波变换，Z变换和模糊逻辑控制器）之间的稳定性，总谐波失真和所收集样本数据的收敛速度，以进行故障终止。已在Simulink上分析了故障诊断和故障终止的完整性能。可以看出，在变压器上注入故障之后，由于具有更高的稳定性，更少的总谐波失真和更快的收敛性，与Z变换和小波变换相比，在模糊逻辑控制器下故障恢复得更快。不同信号的采样数据以不同的频率收集。此外，通过使用Z变换和模糊逻辑控制器评估收集的样本数据的分析，以进行故障终止。通过线性回归分析比较了三种方法（小波变换，Z变换和模糊逻辑控制器）之间的稳定性，总谐波失真和所收集样本数据的收敛速度，以进行故障终止。已在Simulink上分析了故障诊断和故障终止的完整性能。可以看出，在变压器上注入故障之后，由于具有更高的稳定性，更少的总谐波失真和更快的收敛性，与Z变换和小波变换相比，在模糊逻辑控制器下故障恢复得更快。