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An automatic diagnostic method of abnormal heat defect in transmission lines based on infrared video

机译:基于红外视频的传输线异常热缺损自动诊断方法

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Infrared videos from transmission line inspection of UAV have a large amount of data with low SNR (Signal to Noise Ratio). Identifying heat defects automatically using infrared videos is difficult and inefficient. In this paper, an advanced method is proposed. Firstly, points with excessive value of the component regions according to conductors are analyzed in their neighbors to obtain defect points. Then, the heat region of each defect points is segmented, and defect type of which is distinguished automatically by target accounting, skeleton, convex defects, position of lead wire, LBP feature vector. To solve the problem of low efficiency, an infrared video is divided into segments encompassing tower (SETs) and segments don't encompassing tower (SNETs). Heat defects of clamps, lead wire joints, insulators are processed using SETs. Experiment shows that defect locating accuracy is 91.4%, false alarm rate is 12.3%. Classification accuracy of the located defects is 82.3%. Then, this method is effectiveness and robustness.
机译:从传输线路检查UAV的红外视频都有大量数据,具有低SNR(信噪比)。使用红外视频自动识别热缺陷是困难且效率低下的。在本文中,提出了一种先进的方法。首先,在其邻居中分析了根据导体的部件区域的过度值的点,以获得缺陷点。然后,将每个缺陷点的热区域进行分段,并且其缺陷类型由目标计费,骨架,凸缺陷,引线的位置,LBP特征向量自动区分。为了解决效率低的问题,红外视频被分成包含塔(套件)的区段,并且段不包括塔(SCET)。使用组处理夹具,引线接头,绝缘体的热缺陷。实验表明,缺陷定位精度为91.4 %,误报率为12.3 %。定位缺陷的分类准确性为82.3%。然后,这种方法是有效性和鲁棒性。

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