Partial discharge ultrahigh frequency signal blind source separation denoising method based on principal component analysis

Abstract

The invention discloses a partial discharge ultrahigh-frequency signal blind source separation and denoising method based on principal component analysis. The method comprises the following implementation steps of: performing partial discharge detection on gas insulated switchgear by using an ultrahigh-frequency detection method to obtain original partial discharge ultrahigh-frequency signals; performing ensemble empirical mode decomposition on single-channel ultrahigh frequency signals to obtain limited intrinsic mode function components; performing spatial transformation on a matrix formed by the intrinsic mode function components by utilizing principal component analysis to obtain eigenvalues of the intrinsic mode function components, and arranging the eigenvalues from large to small; determining the number of source signals and constructing multi-channel detection signals in a new feature space by analyzing the variation trend of the eigenvalues; and carrying out blind source separation by using a FastICA algorithm based on independent component analysis, and obtaining denoised ultrahigh frequency signals. According to the method, environmental white noise and periodic communication noise can be effectively removed, the denoised signals are closer to noise-free source signals, the calculation amount is small, and the diagnosis accuracy is improved.

Description

technical field [0001] The invention belongs to the technical field of state monitoring and fault diagnosis of electric equipment, and in particular relates to a method for blind source separation and denoising of partial discharge UHF signals based on principal component analysis. Background technique [0002] With the development of power system and technological progress of power equipment, gas insulated switchgear (GIS) has been widely used due to its advantages of compact structure, small footprint and high reliability. According to statistics, insulation faults account for nearly one-half of GIS faults, while other types of faults are often related to insulation aging. When there are insulation defects in GIS, the local electric field near the defects will be distorted and partial discharge will occur, and the insulation aging will be further aggravated. Therefore, it is of great significance to detect partial discharge in GIS. [0003] The UHF method is currently the...

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Problems solved by technology

Due to the complex environment of GIS operation site and the rapid development of communication technology, the obtained UHF signal contains a large amount of environmental white noise, periodic communication noise and random pulse interference noise caused by the action of switching devices, which seriously affects the detection effect and status. Accuracy of recognition

In the existing UHF signal denoising methods, filter methods such as fast Fourier transform, threshold filter and adaptive filter have the problem of denoising signal distortion and loss of important features, and wavelet transform methods have the problem of wavelet Difficult to determine the basis function, the number of decomposition layers, etc., the empirical mode decomposition method has the modal aliasing effect that affects the time-frequency distribution of the signal, and the sparse matrix method has the problem of excessive calculation caused by a large number of matrix operations

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