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Partial discharge diagnosis method based on data mining

A technology of partial discharge and diagnostic methods, applied in the field of electrical signal detection, can solve problems such as low efficiency, poor interpretability, and low recognition rate, and achieve good interpretability, fast recognition speed, and avoid the limitations of determining weights.

Inactive Publication Date: 2014-02-19
STATE GRID CORP OF CHINA +2
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Problems solved by technology

[0005] It can be seen that when using the above existing methods for partial discharge type identification, there are many deficiencies such as poor interpretation, low efficiency and low recognition rate.

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  • Partial discharge diagnosis method based on data mining
  • Partial discharge diagnosis method based on data mining
  • Partial discharge diagnosis method based on data mining

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Embodiment Construction

[0035] The method for diagnosing partial discharge based on data mining in the present invention will be further explained and described below in conjunction with the accompanying drawings and specific embodiments.

[0036] Such as figure 1 As shown, adopt Matlab development language to provide the partial discharge diagnosis method based on data mining in the present embodiment, it comprises the following steps:

[0037] (1) Acquisition signal: Use the sensor to sense the partial discharge signal of the power equipment, amplify the partial discharge signal and perform analog-to-digital conversion to convert it into a digital signal, and continuously collect the digital signal. The continuous collection time of the signal is two power frequencies Period (2×20=40 milliseconds).

[0038] (2) Pre-processing: pre-processing such as amplification and denoising of the collected digital signals, using FIR filtering and wavelet methods to suppress narrow-band noise and white noise in...

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Abstract

The invention discloses a partial discharge diagnosis method based on data mining. The method comprises the steps of 1) acquiring a partial discharge signal of power equipment; 2) extracting characteristic parameters from the partial discharge signal; 3) implementing interval division in a competitive gathering method according to the extracted characteristic parameters, mining a training database of partial discharge types after interval division via an association rule mining algorithm, obtaining a classification rule according to a set minimal confidence and a set minimal support degree, and according to the classification rule, calculating the subordination degrees of the to-be-classified partial discharge signal to the partial discharge types in a fuzzy inference method; and 4) according to the calculated subordination degrees, determining the possibility that the to-be-classified partial discharge signal represents a certain partial discharge type. The partial discharge diagnosis method disclosed by the invention is high in recognition rate and recognition speed.

Description

technical field [0001] The invention relates to an electrical signal detection method, in particular to a partial discharge diagnosis method. Background technique [0002] For large-scale power equipment that has been in operation for a certain period of time, its insulation problems will become more and more significant with the increase of service life. At the same time, harsh environmental factors and local defects of the power equipment itself will greatly shorten the service life of the power equipment, resulting in serious insulation aging and frequent failures. [0003] As an important parameter reflecting the insulation status of large-scale power equipment, partial discharge is closely related to the insulation status of power equipment. The characteristics of partial discharge signals generated by different defects are different, and different types of partial discharges have different damage degrees to the insulation of power equipment. Therefore, the diagnosis o...

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Application Information

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IPC IPC(8): G01R31/12
Inventor 陈晓红钱勇袁冰靳方元刘宗杰刘长征徐辉丁清鹏盛戈皞江秀臣
Owner STATE GRID CORP OF CHINA
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