Partial discharge wavelet denoising method based on hybrid particle swarm

A technology of mixed particle swarm and partial discharge, applied in the direction of testing dielectric strength, etc., which can solve the problems of reduced reliability of results and subsequent processing of unfavorable signals.

Inactive Publication Date: 2016-11-09
SHANDONG UNIV
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Problems solved by technology

Therefore, the reliability of the obtained results decreases, which is not conducive to the subsequent processing of the signal. Therefore, a partial discharge denoising algorithm that can effectively remove white noise while retaining the PD signal to the maximum extent and has high denoising reliability is needed.

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  • Partial discharge wavelet denoising method based on hybrid particle swarm
  • Partial discharge wavelet denoising method based on hybrid particle swarm
  • Partial discharge wavelet denoising method based on hybrid particle swarm

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Embodiment Construction

[0052] The present invention will be further described below in conjunction with the accompanying drawings and embodiments.

[0053] Such as figure 1 As shown, a partial discharge wavelet denoising method based on mixed particle swarm, the specific method is:

[0054] S1. Input a noisy partial discharge signal;

[0055] S2. Perform wavelet decomposition on the noisy partial discharge signal to obtain wavelet coefficients at each wavelet scale;

[0056] The number of decomposition layers is set to 6-8 layers; the wavelet coefficients on each scale after decomposition are obtained through wavelet decomposition; these coefficients are used as the initial parameters of the iteration after calculation of the original data.

[0057] S3, select the second-order derivable Sigmoid-like threshold function and the hybrid particle swarm adaptive threshold selection method, carry out adaptive threshold selection and processing on the wavelet coefficients obtained in S2, eliminate the noi...

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Abstract

The invention discloses a partial discharge wavelet denoising method based on a hybrid particle swarm. The method comprises the steps that step S1, wavelet decomposition is performed on noised partial discharge signals so that the wavelet coefficient under each wavelet scale is obtained; step S2, self-adaptive threshold selection and processing are performed on the wavelet coefficients obtained in the step S1 by using a second-order differentiable class Sigmoid threshold function and a hybrid particle swarm self-adaptive threshold selection method so that effective values are maintained and noise components are eliminated, and the results after threshold processing are saved as new wavelet components; and step S3, signal reconstruction is performed by using the obtained wavelet coefficients so that the denoised partial discharge signals are obtained. The applied threshold function is the class Sigmoid function. Compared with the common soft threshold function, the function is second-order differentiable and adaptive to an iterative algorithm based on gradient descent so that wavelet coefficient threshold self-adaptive selection based on the minimum mean square error can be realized.

Description

technical field [0001] The invention relates to the technical field of electrical equipment insulation state operation monitoring, in particular to the technical field of equipment early fault diagnosis; in particular, it relates to a partial discharge wavelet denoising method based on mixed particle swarms. Background technique [0002] With the rapid growth of my country's electricity consumption, the scale of the power grid is increasing, and the voltage level is gradually increasing. Ensuring the insulation safety of electrical equipment is an important prerequisite for maintaining the stable operation of the power grid. Partial discharge on-line monitoring of power equipment is an important means to evaluate the insulation status of equipment, and it is also an effective measure to discover latent faults of equipment, and finally realize fault warning and avoid fault occurrence. It is of great significance to ensure the safe operation of equipment. The partial discharg...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G01R31/12
CPCG01R31/12
Inventor 李清泉秦冰阳李斯盟司雯史瑞楠
Owner SHANDONG UNIV
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