Power equipment partial discharge identification method, system and equipment and storage medium

A technology for partial discharge and power equipment, applied in the field of signal identification, can solve the problems of partial discharge signal annihilation, low work efficiency and convergence accuracy, and achieve the effect of avoiding signal loss

Pending Publication Date: 2022-04-12
CHINA ELECTRIC POWER RES INST
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Problems solved by technology

[0013] In order to solve the problem that the electromagnetic interference existing in the prior art is easy to annihilate the partial discharge signal, and the neural network algorithm for identifying and classifying the partial discharge signal in the prior art has low work efficiency and convergence accuracy, the present invention provides a A method for identifying partial discharge of electric power equipment, comprising:

Method used

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  • Power equipment partial discharge identification method, system and equipment and storage medium
  • Power equipment partial discharge identification method, system and equipment and storage medium
  • Power equipment partial discharge identification method, system and equipment and storage medium

Examples

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Embodiment 1

[0079] A method for identifying partial discharge of power equipment, such as figure 2 shown, including:

[0080] I: Use broadband high-speed sampling to collect sampling data of power equipment within a certain period of time;

[0081] II: converting the sampling data into a PRPD spectrum, and performing feature extraction and classification on the PRPD spectrum;

[0082] III: Bring the signal features extracted from the PRPD spectrogram of each type into the pre-trained partial discharge identification model corresponding to the type, and obtain whether there is a partial discharge in the electric equipment within the certain period of time and whether it belongs to type of partial discharge;

[0083] Wherein, the trained partial discharge identification model is obtained by training the statistical features extracted from each type of PRPD spectrogram and the type of discharge to which the statistical features belong, using a neural network.

[0084] The training of the...

Embodiment 2

[0144] The present application also provides a partial discharge identification system for power equipment, including:

[0145] The data acquisition module is used to collect the sampling data of the power equipment within a certain period of time by means of broadband high-speed sampling;

[0146] Separation and classification module for converting the sampling data into PRPD spectrograms, and performing signal feature extraction and classification on the PRPD spectrograms;

[0147] The partial discharge identification module is used to bring the statistical features in the signal features extracted from the PRPD spectrogram of each type into the pre-trained partial discharge identification model corresponding to the type, and obtain the power equipment in the Whether there is partial discharge within a certain period of time and the type of partial discharge it belongs to;

[0148] Wherein, the partial discharge identification model is obtained by training the statistical f...

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Abstract

The invention discloses a power equipment partial discharge identification method, system and equipment and a storage medium. The method comprises the following steps: acquiring sampling data of power equipment within a certain time by adopting a broadband high-speed sampling mode; the sampling data are converted into a PRPD spectrogram, and signal feature extraction and classification are carried out on the PRPD spectrogram; statistical features in the signal features extracted from each type of PRPD spectrogram are substituted into a pre-trained partial discharge identification model corresponding to the type, and whether partial discharge exists in the power equipment or not and the partial discharge type to which the power equipment belongs are obtained; the partial discharge identification model is obtained by training the statistical characteristics extracted from each type of PRPD spectrogram and the discharge type to which the statistical characteristics belong by using a neural network. Broadband high-speed sampling is adopted to collect sampling data, complete partial discharge waveforms are obtained, signal feature extraction and classification are carried out on the PRPD spectrogram, and the pre-trained partial discharge identification model is adopted to carry out partial discharge identification, so that the equipment partial discharge monitoring precision is improved, and false alarms and missing alarms are reduced.

Description

technical field [0001] The invention relates to the field of signal identification, in particular to a method, system, equipment and storage medium for identifying partial discharge of electric equipment. Background technique [0002] Partial Discharge (PD): It means that only a local area of ​​the insulation system discharges without breakdown, that is, the discharge does not penetrate between the conductors to which the voltage is applied. Partial discharges can occur inside an insulator, at the interface between an insulator and a conductor, and on the surface of an insulator. When the conductor is surrounded by gas, the PD at the edge of the conductor is also called corona. [0003] With the development of social science and technology, the economic level continues to improve, and the demand for electricity continues to increase. As the last link in the power network, the distribution network is directly oriented to end users, and is directly related to the reliability...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G01R31/12
Inventor 盛万兴周莉梅尚宇炜解芳孟晓丽范闻博王金丽王冠璎
Owner CHINA ELECTRIC POWER RES INST
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