Nonstationary waveform detection in power quality signals using multisynchrosqueezing transform. (6th July 2021)

• Record Type: Journal Article
• Authors: Sahu, Gupteswar; Dash, Sonali
• Is Part Of: International transactions on electrical energy systems. Volume 31:Number 9(2021)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2021-07-06
• Subjects: multi synchrosqueezing transform -- power quality -- synchrosqueezing transform -- time‐frequency analysis; Electric power -- Periodicals; Electric power systems -- Periodicals; Electrical engineering -- Periodicals; 621.3
• DOI: 10.1002/2050-7038.13013
• Languages: English
• ISSNs: 2050-7038

Abstract

Summary: 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. Abstract : TFA method is commonly regarded as a powerful signal analysis tool for the detection and characterization of nonstationary signals. The TFA with high time and frequency resolution is of great importance for real‐time signal analysis. In this paper, we have introduced a new TF analysis approach using MSST for the analysis of PQ disturbance signals.