基于全景温度场的电力设备在线自动识别与诊断

Online Automatic Recognition and Diagnosis of Electrical Devices via Thermal Panorama

为了解决在线自动识别电力设备并进行相应热故障诊断问题,提出一种基于全景温度场的变电站设备在线自动识别与诊断方法。首先,离线采集若干变电站的红外热像,通过基于SIFT特征的图像拼接方法对这些热像进行拼接,构建变电站全景温度场,并手动标注全景温度场中的设备。其次,对于一幅在线的包含特定设备的热红外热像,在已构建的全景温度场中通过特征匹配的方式自动定位该设备,进而有效地对设备进行识别,然后依据设备类型自动诊断热故障的发生。最后,在真实的变电站场景中进行实验,验证了本文方法的有效性和实用性。

Aiming at solving the problem of online automatic recognition and thermal diagnosis of electrical devices, this paper proposes an online automatic device recognition and diagnosis method based on the stitched thermal panorama. Firstly, we collect some thermal infrared images of the scene and stitch them based on SIFT to construct the thermal panorama in an offline fashion. The categories of devices in the scene are further manually annotated. Secondly, given a thermal image captured online, we locate and identify the devices of this thermal image by utilizing the feature matching algorithm, and then effectively diagnose these devices based on their categories. Finally, experiments on the real substation scenarios demonstrate the effectiveness and practica- bility of the proposed approach.