基于红外检测的变电站设备热状态诊断

提出了一种基于红外检测的变电站设备热状态诊断方案。首先基于变电站设备的红外图像，采用局部方差映射函数和遗传算法阈值提取了变电站设备的热状态数据，以用于对异常区域进行分割。然后构建了红外图像灰度数与变电站设备温度两者之间的关系。最后采用改进的相对温差法达到了对设备热状态进行分类和诊断的目标，并捕获定位了变电站设备的热状态异常区域。实验结果表明，该方法提高了异常热区提取的精度和效率，提升了变电站设备热状态诊断的容错能力，进一步保证了变电站和整个电力系统的运行稳定性。

Thermal State Diagnosis of Substation Equipment Based on Infrared Detection

The thermal state diagnosis scheme for substation equipment is proposed based on infrared detection. Firstly， the local variance mapping function and genetic algorithm threshold are used to extract the thermal state data of the substation equipment which is used to segment the abnormal area based on the infrared image. Then the relationship between the gray scale of the infrared image and the temperature of the substation equipment is constructed. Finally， the improved relative temperature difference method is used to achieve the goal of classifying and diagnosing the thermal state of the equipment，and to capture and locate the abnormal thermal state area of the substation equipment. Experimental results show that this method improves the accuracy and efficiency of abnormal hot zone extraction，improves the fault tolerance of the thermal state diagnosis of substation equipment，and further ensures the operational stability of the substation and the entire power system.