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The aluminum strands break and surface damage will gradually develop into irreversible destruction to the conductors and the whole transmission lines, and even lead to serious power outages. In order to find out the potential strands break and damage faults and prevent its further deterioration, a recognition method of conductor break and surface defects in transmission lines’ unmanned aerial vehicle (UAV) inspection is presented in this paper. First, a conductor image is obtained by the UAV image acquisition system, and then, the conductor region is extracted by the adaptive threshold segmentation after the enhancement processing by the gray variance normalization method (GVN). Second, the conductor break is detected by the square wave transformation (SWT) of its grayscale distribution curves, which is simple and effective. Meanwhile, the conductor surface defects are identified by the projection algorithm of the GVN image of the conductor region. Finally, calculating the number of broken strands and filtering the suspect defects, the final fault diagnosis results can be obtained. We analyze the performance of the technology by a series of experiments, and the results demonstrate that the proposed method can measure the conductor break and surface defects faults with the average accuracy of 90.45% and 92.05%, respectively. The health condition of the conductor can be monitored based on the method presented in this paper, by which the safe operation of transmission lines can be guaranteed.

A Recognition Technology of Transmission Lines Conductor Break and Surface Damage Based on Aerial Image