Key Method of Wiring Diagram Recognition with Artificial Intelligence for Power Plant and Substation

被引：0
|
作者：
Wang Z. [1 ,2 ]
Luo Q. [1 ,2 ]
Xiao W. [1 ,2 ]
Wang Y. [1 ,2 ]
Yu T. [1 ,2 ]
机构：
[1] College of Electric Power, South China University of Technology, Guangzhou
[2] Guangdong Provincial Key Laboratory of Intelligent Measurement and Advanced Metering of Power Grid, Guangzhou
来源：
Dianli Xitong Zidonghua/Automation of Electric Power Systems | 2023年 / 47卷 / 02期
基金：
中国国家自然科学基金;
关键词：
artificial intelligence; graphic element recognition; knowledge fusion; text recognition; transfer learning; wiring diagram of power plant and substation; wiring recognition;
D O I：
10.7500/AEPS20220223008
中图分类号：
学科分类号：
摘要：
Vectorized wiring diagram for power plants and substations needs to be manually drawn and imported by dispatching operation and maintenance personnel with reference to design drawings, which is labor intensive and error prone. Aiming at the three core recognition problems, i.e., graphic element, text and wiring relationship of the wiring diagram for power plants and substations, a complete method of wiring diagram recognition for power plants and substations based on artificial intelligence is proposed to significantly improve the efficiency and accuracy of recognition. Through the combination of overlapping sliding window mechanism of hierarchical preprocessing and YOLOv4 algorithm, the problem of“large image and small graphic element detection”of the wiring diagram recognition for power plants and substations is solved. Through the combination of transfer learning and convolutional recurrent neural network, the recognition rate of Chinese electrical texts is improved. Embedded with the electrical domain knowledge and rules, the accuracy of wiring recognition is improved. Finally, according to the obtained electrical component information, text information, connection line information, other downstream tasks are completed. Using the data set of grid wiring diagram derived from the actual dispatching system, the comparison experiments of graphic element, text and wiring recognition are designed to verify the effectiveness of the proposed method. © 2023 Automation of Electric Power Systems Press. All rights reserved.
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页码：115 / 124
页数：9
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