电力系统厂站接线图拓扑关系检测技术

厂站接线图中电气元件的拓扑关系是厂站接线图自动生成技术所需的核心数据。目前，已知的厂站接线图自动生成技术仍然依靠人工获取图中的拓扑关系。通过利用基于深度学习的目标检测技术与传统的计算机图像处理技术相结合的方式，能够实现厂站接线图拓扑关系检测。首先，利用基于深度学习的目标检测方法对电气元件进行识别，并利用计算机图像处理技术对标量格式接线图进行预处理，完成电气元件与连接线的分割。然后，利用轮廓跟踪算法对连接线连通区域进行检测标记。最后，根据获取的电气元件信息与连接线信息获取图纸的拓扑关系。采用国家电网有限公司提供的数据集，并设计了对比实验，验证了所提方法的有效性。 

Topological relation detection technology of substation wiring diagram in electric power system

Topological relation of electrical components is the core-data required by substation wiring diagram automatic generation technology. At present, known technologies still rely much on artificial access to topological relations. By the combination of deep learning based object detection technology and traditional computer image processing technology, topological relation can be detected automatically. Firstly, to segment the electrical components and connection lines, deep learning based object detection technology was used to identify the electrical components, and the image processing technology was used to preprocess the scalar-format wiring diagram of power plants. Secondly, a contour tracking algorithm was adopted to detect and mark the connected area of the connection lines. Finally, the topological relation of the drawing was acquired according to the obtained information of electrical components and connection lines. Comparative experiments based on a dataset released by the State Grid Corporation of China indicate the effectiveness of the proposed method.