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Research on partial discharge propagation characteristics of transformer and optimization of monitoring points
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Youhua JIANG1, Xingsen SHANG1, Xiangwei JIANG2, Wenji WANG3
Insulating Materials | 2024, 57(5) : 116 - 124
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Insulating Materials | 2024, 57(5): 116-124
Special Issue on High-performance Transformer Insulation
Research on partial discharge propagation characteristics of transformer and optimization of monitoring points
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Youhua JIANG1, Xingsen SHANG1, Xiangwei JIANG2, Wenji WANG3
Affiliations
  • 1Shanghai University of Electric Power, Shanghai 200120, China
  • 2Anqing Power Supply Company, State Grid Anhui Province Electric Power Co., Ltd., Anqing 246000, China
  • 3State Grid Wuhan Hannan District Power Supply Company, Wuhan 430090, China
Published: 2024-05-20 doi: 10.16790/j.cnki.1009-9239.im.2024.05.017
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The partial discharge ultrasonic signal attenuates severely on power transformer equipment shell, resulting in larger differences in the partial discharge signals received by different positions of sensors, which greatly affects its measurement accuracy and detection efficiency in field application. In this paper, a partition model of oil-immersed power transformer was built using finite element simulation software, the partitioning rule of partial discharge ultrasonic signal on the main surface of oil tank was obtained, and the transformer spatial sound pressure and partition sound pressure distribution maps were formed. On the basis of monitoring point optimization method of Pearson correlation coefficient and K-means clustering, the monitoring points with the best sensitivity of spatial sound pressure and partition sound pressure were preferably selected and compared. The results show that the average detection efficiency of the A-level monitoring points is 86.0%, which realizes the efficient detection of transformer partial discharge and provides a new method for selecting the placement points of ultrasonic sensors.

transformer  /  partial discharge ultrasonic signal  /  finite element simulation  /  Pearson correlation coefficient  /  K-means clustering
Youhua JIANG, Xingsen SHANG, Xiangwei JIANG, Wenji WANG. Research on partial discharge propagation characteristics of transformer and optimization of monitoring points[J]. Insulating Materials, 2024 , 57 (5) : 116 -124 . DOI: 10.16790/j.cnki.1009-9239.im.2024.05.017
Year 2024 volume 57 Issue 5
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Article Info
doi: 10.16790/j.cnki.1009-9239.im.2024.05.017
  • Receive Date:2023-06-05
  • Online Date:2025-12-22
  • Published:2024-05-20
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History
  • Received:2023-06-05
  • Revised:2023-08-24
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Affiliations
    1Shanghai University of Electric Power, Shanghai 200120, China
    2Anqing Power Supply Company, State Grid Anhui Province Electric Power Co., Ltd., Anqing 246000, China
    3State Grid Wuhan Hannan District Power Supply Company, Wuhan 430090, China
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表12种不同金属材料的力学参数

Family
属数
Number of
genus
种数
Number of
species
占总种数比例
Percentage of
total species (%)

Genus
种数
Number of
species
占总种数比例
Percentage of total
species (%)
鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
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