摘要
220 kV变电站承担着将高压电能分配给下级电网的重要任务。若变电站的运行设备出现发热异常故障,则不仅会影响本级电网的正常运行,还可能会对下级电网乃至整个电网的稳定运行造成威胁,故提出220 kV变电站运行设备发热异常自动监测方法的研究。应用红外成像仪获取运行设备红外图像,采用中值滤波算法与非线性拉伸算法增强处理红外图像,以此为基础,提取运行设备温度特征--局部平均温度、温度梯度与温度标准差,基于支持向量机构造运行设备发热异常判定决策函数,从而获取运行设备发热异常监测结果。应用设计方法后获得的温度标准差提取结果与实际温度标准差趋于一致,运行设备发热异常监测结果与实际运行设备发热状态相同。
220 kV substations undertake the critical task of distributing high-voltage electrical energy to lower-level power grids.If abnormal heating faults occur in the operating equipment of substations,not only will the normal operation of the local power grid be affected,but the stability of downstream grids and even the entire power system may also be threatened.Therefore,a study on automatic monitoring methods for abnormal heating in operating equipment of 220 kV substations is proposed.Infrared images of the operating equipment are acquired using an infrared imager.The infrared images are enhanced through median filtering and nonlinear stretching algorithms.Based on the processed images,temperature characteristics of the operating equipment power grid local average temperature,temperature gradient,and temperature standard deviations are enhanced through median filtering and nonlinear stretching algorithms.Based on the processed images,temperature characteristics of the operating equipment power grid results for abnormal heating.The extracted temperature standard deviation values obtained using the proposed method are consistent with the actual temperature standard deviations.Additionally,the monitoring results for abnormal heating in the operating equipment align with the actual thermal states of the equipment.
作者
杜献雷
DU Xianlei(Shanxi Electric Power Construction Third Co.,Ltd.,China Energy Engineering Group,Taiyuan,Shanxi 030006,China)
出处
《自动化应用》
2025年第15期201-203,210,共4页
Automation Application
关键词
运行设备
自动监测
红外图像
发热异常
220
kV变电站
operating equipment
automatic monitoring
infrared image
abnormal heating
220 kV substations
