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Cable fault distance measurement method and system based on discharge waveform intelligent identification

A cable fault and intelligent identification technology, applied in the direction of fault location, etc., can solve the problems of relying on subjective judgment, difficult to teach and inherit, and long training time, so as to improve the level of automation and intelligence, reduce the distance measurement error, and improve the positioning accuracy Effect

Active Publication Date: 2022-03-22
SHANDONG UNIV +1
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

At present, at home and abroad, it is mainly to manually identify the breakdown discharge waveform and manually calibrate the reflected pulse, which requires the operator to have rich testing experience, and the training cost and long training time required to accumulate experience are high.
The experience and skills of manually identifying fault information and deriving the fault distance are difficult to pass on and inherit without the on-site environment, and there are limitations of relying on subjective judgment and low efficiency

Method used

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  • Cable fault distance measurement method and system based on discharge waveform intelligent identification
  • Cable fault distance measurement method and system based on discharge waveform intelligent identification
  • Cable fault distance measurement method and system based on discharge waveform intelligent identification

Examples

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Embodiment 1

[0059] This embodiment provides a cable fault location method based on intelligent identification of discharge waveforms, which integrates fault information in the time-frequency domain, calls the GS-SVM algorithm to accurately identify the breakdown discharge waveforms of the pulse current method and the secondary pulse method, and uses the wavelet model The maximum value point and the correlation coefficient calibrate the fault click through the discharge pulse, automatically calculate the fault distance, and get rid of the restriction of relying on manual identification and judgment for cable fault detection, which not only improves the efficiency of positioning, but also improves the accuracy of positioning.

[0060] Such as Figure 16 As shown, a cable fault location method based on intelligent identification of discharge waveforms, specifically includes the following steps:

[0061] Step 1: Acquire cable fault discharge waveform data.

[0062] In this embodiment, differ...

Embodiment 2

[0130] This embodiment provides a cable fault location system based on intelligent identification of discharge waveforms, which specifically includes the following modules:

[0131] A data acquisition module, which is used to collect cable fault discharge waveforms with a pulse current method or a secondary pulse method;

[0132] A feature extraction module, which is used to extract the time-frequency domain characteristics of the discharge waveform and construct the identification feature quantity;

[0133] GS-SVM training module, which is used to train known samples, establish a mapping relationship between input feature quantities and output recognition results, and construct a GS-SVM recognition model;

[0134] The GS-SVM identification module is used to call the trained GS-SVM model to identify the unknown discharge waveform, give a judgment on whether it is a breakdown discharge waveform, and save the correctly identified breakdown discharge waveform;

[0135] The autom...

Embodiment 3

[0139] This embodiment provides a computer-readable storage medium, on which a computer program is stored. When the program is executed by a processor, the steps in the method for locating a cable fault based on intelligent identification of discharge waveforms as described in Embodiment 1 are implemented.

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Abstract

The invention provides a cable fault distance measurement method and system based on discharge waveform intelligent identification. The method comprises the following steps: acquiring cable fault discharge waveform data; decomposing the discharge waveform data, and extracting time-frequency domain feature information; based on the time-frequency domain feature information, recognizing a breakdown discharge waveform by using a support vector machine recognition model optimized by a pre-trained grid search method; and the identified disruptive discharge waveform is calibrated, a fault point disruptive discharge pulse is determined, and a fault distance is calculated based on the disruptive discharge pulse. According to the invention, an artificial intelligence algorithm is combined with a fault positioning method with mature technology, machine learning and an intelligent algorithm are introduced to effectively extract fault features, a fault waveform is automatically distinguished, a fault distance is accurately calculated, and automation and intelligence levels of cable fault positioning are effectively improved.

Description

technical field [0001] The invention belongs to the technical field of power cable fault detection, and in particular relates to a cable fault ranging method and system based on intelligent identification of discharge waveforms. Background technique [0002] The statements in this section merely provide background information related to the present invention and do not necessarily constitute prior art. [0003] As an important part of the distribution network, power cables are widely used in power engineering construction due to their high power supply reliability, little influence from the external environment, and no ground corridors. The number of uses is increasing day by day, and the location distribution It's getting more complicated. However, once the cables laid underground fail due to potential problems such as mechanical damage, damp insulation, and insulation aging, it will not only cause huge losses to the power company, but also bring serious chaos to people's ...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G01R31/08
CPCG01R31/08Y04S10/52
Inventor 邹贵彬张金亮徐丙垠李峰单超魏秀燕
Owner SHANDONG UNIV
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