The accurate time-frequency (TF) positioning of power quality (PQ) disturbances is the basis of dealing with PQ problems in power systems. To accurately detect PQ disturbances, this article proposes a Kaiser window-based S-transform (KST) that provides better time resolution at fundamental frequency to detect the amplitude information for voltage swell, sag, interrupt, flicker, and better frequency resolution at higher frequencies to detect the frequency of time-varying harmonics and oscillatory transient. Based on short-time Fourier transform and S-transform, KST uses a Kaiser window with the characteristic of inherent optimal energy concentration as the kernel function. The Kaiser window can be adjusted adaptively according to the detection demand of PQ disturbances by the designed control function. This allows KST to easily accommodate different detection requirements at different frequencies. The utilization of Fourier transform ensures that KST can be realized quickly. The complex TF matrix is generated after a signal is transformed by KST, where the column vector is expressed as the distribution of amplitude and phase with time at a certain frequency, and the row vector represents the distribution of amplitude and phase with frequency at a certain sampling time. Experimental results demonstrate that the proposed KST significantly outperforms the state-of-the-art techniques in TF analysis of PQ signals, especially for the energy concentration and the detection of fundamental wave.

中文翻译：

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用于电能质量信号时频分析的基于 Kaiser 窗的 S 变换


电能质量(PQ)扰动的准确时频(TF)定位是处理电力系统PQ问题的基础。为了准确检测 PQ 扰动，本文提出了基于 Kaiser 窗口的 S 变换 (KST)，它在基频下提供更好的时间分辨率，以检测电压骤升、骤降、中断、闪烁的幅度信息，并在较高频率下提供更好的频率分辨率检测时变谐波和振荡瞬态的频率。 KST基于短时傅里叶变换和S变换，采用具有固有的最优能量集中特性的Kaiser窗作为核函数。通过设计的控制函数，可以根据PQ扰动的检测需求自适应地调整Kaiser窗。这使得 KST 能够轻松适应不同频率下的不同检测要求。傅里叶变换的利用保证了KST的快速实现。信号经过KST变换后生成复TF矩阵，其中列向量表示某一频率下幅度和相位随时间的分布，行向量表示某一频率下幅度和相位随频率的分布采样时间。实验结果表明，所提出的 KST 在 PQ 信号的 TF 分析中显着优于最先进的技术，特别是在能量集中和基波检测方面。