Electric energy quality monitoring and distinguishing method and electric energy quality monitoring and distinguishing system based on dual-tree complex wavelet transform

Abstract

The invention discloses an electric energy quality monitoring and distinguishing method based on dual-tree complex wavelet transform and relates to the technical field of data acquisition, signal processing and mode distinguishing. The monitoring system controls a data acquisition state machine in an on-site programmable logic controller through a digital signal processor, a high-precision 8-channel 16-bit symmetrical analog to digital (AD) converter is controlled through the data acquisition state machine in the programmable logic controller so as to complete synchronous acquisition of electric energy quality signals, the digital signal processor reads acquired electric energy liquid data from a first in first out (FIFO) memory in the programmable logic controller, the dual-tree complex wavelet transform is performed on the acquired electric energy liquid data, wavelet coefficient Shannon entropy of the acquired electric energy liquid data is calculated, and finally a wavelet support vector machine classifier based on a binary tree is used for classifying and distinguishing disturbing signals so as to achieve continuous real-time accurate electric energy quality monitoring of three-phase voltage and current. In addition, the invention further provides an electric energy quality monitoring and distinguishing system.

Description

technical field [0001] The invention belongs to the technical field of power quality monitoring and identification, specifically relates to data collection, signal processing and pattern recognition technologies, in particular to a power quality monitoring and identification method based on dual-tree complex wavelet transform, and also relates to a system. Background technique [0002] In recent years, the power quality problem has become one of the important issues that the power sector and users generally pay attention to. Detecting and analyzing the power quality is a prerequisite for discovering power quality problems and then controlling and improving them. The short-term disturbance analysis of power quality plays an important role in power quality analysis, and its classification and identification is a complicated subject, because it contains many complex disturbance types, and various disturbance signals themselves have great irregularities. [0003] Feature extrac...

AI Technical Summary

Problems solved by technology

Because the existing methods cannot achieve real-time continuous monitoring of power quality, and the recognition rate of power quality disturbance signals is not high

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