Feature value extraction method applied to ultrasonic partial discharge detection

An extraction method and partial discharge detection technology, applied in the ultrasonic field, can solve the problems of inaccurate signal analysis results, limited wavelet base length, and inability to judge signals, so as to solve false IMF components, solve modal aliasing, and improve accuracy Effect

Active Publication Date: 2019-08-27
HANGZHOU DIANZI UNIV
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Problems solved by technology

For example, the Fourier transform analysis method loses the time information during the transformation, and cannot judge when a specific signal occurs; although the wavelet transform can better analyze the time-frequency characteristics of partial discharge signals, it relies too much on the wavelet basis. The selection of the wavelet base is limited, and the energy leakage will occur during processing, so it i...

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  • Feature value extraction method applied to ultrasonic partial discharge detection
  • Feature value extraction method applied to ultrasonic partial discharge detection
  • Feature value extraction method applied to ultrasonic partial discharge detection

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Embodiment Construction

[0037] Such as figure 2 As shown, a eigenvalue extraction method applied to ultrasonic partial discharge detection, the method specifically includes the following steps:

[0038] Step 1 Wavelet packet decomposition and reconstruction

[0039] The compactly supported wavelet Daubechies3 (db3) wavelet base is used to decompose and reconstruct the three-layer wavelet packet of the signal, and obtain 8 narrow-band signals of different frequency bands.

[0040] The structure diagram of the three-layer wavelet packet decomposition is as follows figure 1 As shown, let the original signal S be the (0, 0) node, and (1, 0) represent the low-frequency coefficient S of the first layer of wavelet packet decomposition 10 , (1, 1) represents the high-frequency coefficient S of the first layer of wavelet packet decomposition 11 , (2, 0) represents the low-frequency coefficient S of the second layer wavelet packet decomposition 20 , (2, 1) represents the high-frequency coefficient S of th...

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Abstract

The invention discloses a feature value extraction method applied to ultrasonic partial discharge detection. According to the invention, a wavelet packet decomposition and mutual information amount-based IMF component screening method is adopted. Firstly, wavelet packet decomposition is performed. Preliminary frequency division is carried out on the signal. The IMF component of the single-frequency component is obtained. The initial bandwidth of the EMD decomposition signal is reduced. The ultrasonic signal is decomposed more accurately, the problems of modal aliasing and false IMF componentsexisting in EMD decomposition are effectively solved by applying a mutual information amount method, the accuracy of time-frequency analysis is improved, waveform characteristics are extracted more effectively, and finally, the ultrasonic partial discharge signal is classified by applying a neural network.

Description

technical field [0001] The invention belongs to the field of ultrasonic technology, in particular to a feature value extraction method applied to ultrasonic partial discharge detection. Background technique [0002] With the continuous development of modern power grids, people have put forward higher standards for the safety and reliability of power grid operation. Partial discharge detection, as an effective live detection method without damaging the equipment itself, has attracted more and more attention. and favored. [0003] When the insulation part of electrical equipment deteriorates due to various reasons, it will cause partial discharge in severe cases, and even insulation breakdown and damage, of which more than 70% are caused by partial discharge. Carrying out partial discharge live detection is a need for the safety of the power system. It is convenient for electric power workers to grasp the insulation status of the substation operating equipment in a timely man...

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Application Information

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IPC IPC(8): G06K9/00G01R31/12
CPCG01R31/1209G06F2218/12G06F2218/08
Inventor 娄雨靖孔亚广陈张平
Owner HANGZHOU DIANZI UNIV
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