Study of Fast Identification Edge Detection Method for Electrical Equipment

Abstract

In view of the current method for load of user side electric equipment in edge detection performance problems, based on the study of threshold detection algorithm (TDA), transient energy startup algorithm (TEA) method of differential operator algorithm (MDA) and the fitting process algorithm, a method of edge Gauss filter and industrial detection based on cumulative sum (CUSUM) algorithm were proposed, which solve the problem of single and low precision of traditional algorithm. The method adopt the adaptive Gaussian filter to filter the noise effectively, while retaining the characteristics of the mutated point information, and the accuracy of the detection is improved by detecting the fluctuation of the mutation point after denoising. Combined with CUSUM algorithm, the detection speed and accuracy of the device mode are improved. Through the construction of non-invasive load identification platform, the proposed method was simulated and verified, and the proposed method can effectively improve the detection speed and accuracy of the electrical equipment.