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Nonstationary waveform detection in power quality signals using multisynchrosqueezing transform
International Transactions on Electrical Energy Systems ( IF 1.9 ) Pub Date : 2021-07-06 , DOI: 10.1002/2050-7038.13013
Gupteswar Sahu 1 , Sonali Dash 2
Affiliation  

Time-frequency (TF) analysis (TFA) is widely used as a reliable signal-processing tool for the detection and identification of time-varying waveforms in power quality (PQ) signals. However, the effectiveness of a TFA method is limited by Heisenberg uncertainty principle. The presence of cross terms is also a significant issue in TF analysis of real-time signals. In PQ signal analysis, it is highly necessary to apply a suitable TFA technique with higher clarity and fewer cross-term problems. This paper introduces a newly developed TFA method known as multisynchrosqueezing transform (MSST) to detect the presence of nonstationary waveforms in PQ disturbance signals. The MSST is a high-resolution TFA method, which is similar to synchrosqueezing transform (SST) but has an iterative reassignment process to enhance the energy concentration of the TF representation. We apply the MSST to various types of single and combined PQ disturbance signals and show its potential application to PQ disturbance signal analysis. Results show that MSST provides higher TF resolution compared to other contemporary methods.

中文翻译:

基于多同步压缩变换的电能质量信号非平稳波形检测

时频 (TF) 分析 (TFA) 被广泛用作可靠的信号处理工具,用于检测和识别电能质量 (PQ) 信号中的时变波形。然而,TFA 方法的有效性受到海森堡不确定性原理的限制。交叉项的存在也是实时信号的 TF 分析中的一个重要问题。在 PQ 信号分析中,非常有必要应用合适的 TFA 技术,该技术具有更高的清晰度和更少的交叉项问题。本文介绍了一种新开发的 TFA 方法,称为多同步压缩变换 (MSST),用于检测 PQ 干扰信号中是否存在非平稳波形。MSST 是一种高分辨率的 TFA 方法,它类似于同步压缩变换 (SST),但具有迭代重新分配过程以增强 TF 表示的能量集中度。我们将 MSST 应用于各种类型的单一和组合 PQ 扰动信号,并展示其在 PQ 扰动信号分析中的潜在应用。结果表明,与其他当代方法相比,MSST 提供了更高的 TF 分辨率。
更新日期:2021-07-06
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