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输电导线在运行中可能发生损伤、断股现象,对其进行及时检测和诊断对于保证电网的安全运行具有重要意义。现代输电线路状态检修一般采用直升机或者巡线机器人搭载视频检测装置的方式。文中提出应用Gabor滤波器对输电导线视频图像数据进行处理,实现输电导线断股的图像检测,即通过计算完好导线图像与滤波器卷积能量的输出响应、应用小生境遗传算法寻找最优的Gabor滤波器参数和分割阈值,最后通过检测图像的滤波和能量的二值化处理得到检测结果。实验结果表明,该算法能够较好地提取输电导线断股处的故障信息,具有适用性广、识别能力强、检测速度快等优点。
Transmission line in operation may damage, broken stock phenomenon, its timely detection and diagnosis for the safe operation of the grid is of great significance. State-of-the-art transmission line condition maintenance generally adopts a helicopter or patrol line robot equipped with a video detection device. In this paper, Gabor filter is proposed to process the video data of power transmission line to detect the image of transmission line broken. By calculating the output response of the perfect wire image and the filter convolution energy, niche genetic algorithm is used to find the optimal Gabor Filter parameters and segmentation threshold, and finally through the detection of image filtering and energy binarization to get the test results. The experimental results show that the algorithm can extract the fault information of the transmission line strand well and has the advantages of wide applicability, strong recognition ability and fast detection speed.