基于多阶段协同的电网厂站接线图智能识别

Intelligent Recognition of Power Grid Station Wiring Diagrams Based on Multi-stage Collaboration

电网厂站接线图作为电力系统网络结构的重要数据,承载着电力设备运行的关键信息,在电网调度控制应用中具有重要作用。针对调度运维人员手动绘制方式导致工作繁琐、任务量大的问题,提出基于多阶段协同的电网厂站接线图智能识别方法,实现机器代人绘图。首先,采用切割检测增强对图元小目标的检测能力,通过形态特征提取及模糊比对处理实现图元方向识别;其次,基于随机粘贴原理增强文字识别模型的鲁棒性,基于知识融合技术提升图元文本匹配准确性;最后,基于连通域检测识别连接线,采用遍历筛选匹配图元与主接线的连接关系。实验结果表明,该方法对电网厂站接线图整体识别准确率在88%以上,将其应用变电站监控系统、换流站运行人员控制系统中,极大提升了作业人员构图建模效率。

Power grid station wiring diagrams,as important data of the power system network structure,carry the key information of power equipment operation and play an important role in the application of power grid dispatch and control.A multi-stage collaborative intelligent recognition method for power grid station wiring diagrams is proposed to address the problem of dispatch and operation personnel manually drawing,which leads to tedious work and a large task volume.This method achieves machine-assisted drawing.Firstly,cutting detection and line fitting are used to enhance the generalization ability of graphic targets and graphic direction recognition is achieved through structural feature extraction and fuzzy comparison processing.Secondly,based on the principle of random pasting,the robustness of the text recognition model is enhanced,and the accuracy of graphic text matching is improved through knowledge fusion technology.Finally,based on connected domain detection and identification of connecting lines,traversal filtering is used to match the connection relationship between the entity and the main wiring.The experimental results show that the overall recognition accuracy of the method for the factory station wiring diagram is over 88%.When applied to the substation monitoring system and converter station operator control system,it greatly improves the efficiency of personnel composition modeling.