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Intelligent Video Surveillance for Detecting Snow and Ice Coverage on Electrical Insulators of Power Transmission Lines

机译:输电线路绝缘子冰雪覆盖检测智能视频监控

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One of the problems for electrical power delivery through power lines in northern countries is when snow or ice accumulates on electrical insulators. This could lead to snow or ice-induced outages and voltage collapse, causing huge economic loss. This paper proposes a novel real-time intelligent surveillance and image analysis system for detecting and estimating the snow and ice coverage on electric insulators using images captured from an outdoor 420 kV power transmission line. In addition, the swing angle of insulators is estimated, as large swing angles due to wind cause short circuits. Hybrid techniques by combining histogram, edges, boundaries and cross-correlations are employed for handling a broad range of scenarios caused by changing weather and lighting conditions. Experiments have been conducted on the captured images over several month periods. Results have shown that the proposed system has provided valuable estimation results. For image pixels related to snows on the insulator, the current system has yielded an average detection rate of 93% for good quality images, and 67.6% for images containing large amount of poor quality ones, and the corresponding average false alarm ranges from 9% to 18.1%. Further improvement may be achieved by using video-based analysis and improved camera settings.
机译:在北方国家,通过电力线输送电力的问题之一是积雪或冰块积聚在电绝缘体上时。这可能导致冰雪引起的停电和电压崩溃,从而造成巨大的经济损失。本文提出了一种新颖的实时智能监控和图像分析系统,该系统使用从室外420 kV输电线路捕获的图像来检测和估算电绝缘子的积雪和冰覆盖。另外,估计绝缘子的摆动角度,因为风引起的较大摆动角度会导致短路。通过组合直方图,边缘,边界和互相关的混合技术,可以处理由于天气和光照条件变化而导致的各种情况。已经对捕获的图像进行了几个月的实验。结果表明,所提出的系统提供了有价值的估计结果。对于绝缘子上与雪相关的图像像素,当前系统对高质量图像的平均检测率为93%,对于包含大量劣质图像的图像的平均检测率为67.6%,相应的平均误报范围为9%至18.1%。通过使用基于视频的分析和改进的相机设置,可以实现进一步的改进。

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