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Partial discharge phase distribution detection method based on NSCT photoelectric fusion map

A photoelectric fusion and phase distribution technology, which is applied to computer parts, instruments, characters and pattern recognition, etc., can solve the problems of incomplete feature information and reduce the accuracy of pattern recognition, so as to ensure safe and stable operation and improve the accuracy of pattern recognition Efficiency, conducive to the effect of operation and maintenance

Active Publication Date: 2020-05-19
SHANGHAI JIAO TONG UNIV +1
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Problems solved by technology

Therefore, in the process of performing PD pattern recognition on the two types of detection patterns, this signal omission phenomenon will lead to incomplete characteristic information of the partial discharge phase distribution (hereinafter referred to as PRPD) pattern, thereby reducing the accuracy of pattern recognition. Accuracy

Method used

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  • Partial discharge phase distribution detection method based on NSCT photoelectric fusion map
  • Partial discharge phase distribution detection method based on NSCT photoelectric fusion map
  • Partial discharge phase distribution detection method based on NSCT photoelectric fusion map

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Embodiment Construction

[0063] See first figure 1 , figure 1 It is the overall flow chart of the partial discharge phase distribution detection method based on the NSCT photoelectric fusion map of the present invention. It can be seen from the figure that the present invention is based on the NSCT photoelectric fusion map. The method includes the following steps:

[0064] a. Collect partial discharge atlas

[0065] Based on the photoelectric combined partial discharge detection experimental platform, the partial discharge signals of various discharge defects are collected, and the corresponding optical PRPD patterns and UHF PRPD patterns are obtained, such as figure 2 Shown (take the tip defect as an example).

[0066] b. Perform NSCT decomposition

[0067] The optical PRPD atlas and the UHF PRPD atlas are grayed out and NSCT is decomposed to obtain the high frequency and low frequency sub-images of the corresponding source atlas.

[0068] NSCT decomposition can be composed of two parts: Non-Subsampled Pyra...

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Abstract

The invention discloses a partial discharge phase distribution detection method based on an NSCT photoelectric fusion map. The method comprises the following steps: collecting a partial discharge map,carrying out graying processing and NSCT decomposition, NSCT fusion and NSCT inverse transformation on an optical PRPD map and an ultrahigh frequency PRPD map, reconstructing a photoelectric fusion image F, and carrying out pattern recognition on the photoelectric fusion PRPD map. Experimental results show that the method can improve the accuracy of mode recognition of single optical detection and single ultrahigh frequency detection at the present stage, has a good recognition effect and high practicability, facilitates the operation and maintenance of power equipment, and guarantees the safe and stable operation of a power grid.

Description

Technical field [0001] The present invention belongs to partial discharge fault diagnosis of gas insulated equipment, in particular to a partial discharge phase distribution detection method based on NSCT photoelectric fusion map. The diagnosis method can improve the pattern recognition accuracy of single optical detection and single UHF detection at this stage, It is conducive to the operation, maintenance and repair of power equipment, and ensures the safe and stable operation of the power grid. Background technique [0002] In recent years, due to the characteristics of large capacity, high stability, and resistance to environmental impact, gas insulated equipment has been widely used in the operation of substations and the transmission of electrical energy. With the large-scale application of gas-insulated equipment, the deterioration of its equipment insulation performance has gradually become the focus of power grid security. Because partial discharge is one of the key fac...

Claims

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Application Information

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IPC IPC(8): G06K9/62
CPCG06F18/213G06F18/25G06F18/241
Inventor 臧奕茗钱勇陈孝信王辉舒博李泽盛戈皞江秀臣
Owner SHANGHAI JIAO TONG UNIV
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