Novel efficient power quality disturbance image feature extraction and recognition method

Abstract

The invention discloses a novel efficient power quality disturbance image feature extraction and recognition method. The method comprises the following steps: converting an electric energy quality signal into a gray level image, enhancing disturbance characteristics by using three methods of gamma correction, edge detection and peak-valley detection to obtain a binary image, and extracting nine characteristics of area, Euler number, angle second moment, contrast ratio, correlation, mean value, variance, inverse difference moment and entropy to construct an original characteristic set; carryingout sorting on the basis of the feature Gini importance degree, and determining the feature with the maximum influence on classification; and comprehensively considering the classification precisionand efficiency, determining the number of trees in the random forest, and constructing a random forest classifier by using the optimal feature subset to identify the power quality disturbance signal.According to the invention, 8 types of common power quality disturbance signals of voltage sag, voltage sag, voltage interruption, flickering, transient oscillation, harmonic waves, voltage cutting marks and voltage peaks under different noise environments can be identified efficiently and accurately, and the feature extraction efficiency of the disturbance signals is improved.

Description

technical field

[0001] The disclosure relates to the field of electric technology, in particular, it is a new method for feature extraction and identification of high-efficiency power quality disturbance images. Background technique

[0002] With the extensive application of various power electronic devices and nonlinear loads in modern power systems, the problem of power quality in power systems is becoming more and more serious. In addition, new energy sources such as distributed photovoltaics and wind power with intermittent and random output characteristics are connected to the grid, which further affects power quality. Power quality problems have brought huge losses to the national economy and seriously affected industrial production and residents' lives. Therefore, the governance of power quality problems is urgent. There are many types of power quality disturbances and frequent occurrences. Accurate identification of various common power disturbance types for target...

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