面向变电站安全监控的视频智能终端布点优化

人工智能视频监控技术在变电站安全监控与管理工作方面具有广阔应用前景。为提高智能变电站的视频监控系统中摄像头终端的利用效率，研究了智能摄像头终端的优化布点模型和算法。首先，基于栅格化思想对变电站平面图进行区域划分，提出采用监控区域重要度矩阵来描述区域和设备的重要程度。然后，建立了摄像头终端监控范围的清晰度离散模型。据此引入监控乘子函数建立以平均监控距离最小为目标，考虑摄像头选型选址和购置成本约束的变电站监控摄像头终端布点优化模型。并采用遗传算法求解该模型得到其优化布点方案。最后，通过仿真算例验证了模型在减少监控盲区数量的有效性和实用性，具有较高的工程应用价值。

Layout optimization of video intelligent terminal for substation safety monitoring

Artificial intelligence video surveillance technology has broad application prospects in substation safety monitoring and management. In order to improve the utilization efficiency of the camera terminal in the video surveillance system of smart substation, the optimization layout model and algorithm of the smart camera terminal are studied. Firstly, based on the idea of rasterization, the plan of the substation is divided into regions. And the importance matrix of monitoring area is proposed to describe the importance of regions and equipment. Then, a definition discrete model of camera monitoring range is established. Based on this, the monitoring multiplier function is introduced to establish the layout optimization model for substation surveillance cameras terminals. This model takes the minimum average monitoring distance as the optimization goal, taking into account the constraints of camera selection and site selection and acquisition cost. And then the genetic algorithm is used to solve the model to get the optimal layout of the cameras. Finally, the validity and practicability of the model in reducing the number of monitoring blind spots are verified by simulation example, which has high engineering application value. This work is supported by Science and Technology Project of Guangdong Power Grid Ltd. (No. 031800KK52160013) and Natural Science Foundation of Guangdong Province (No. 2017A030313304).