Recognition algorithm for fault jumper connection plate of transmission network based on UAV

Jumper connecting plate is an important part of electricity supply network. Jumper connecting plate’s status has a significant impact on electricity supply network’s proper operation. However, all the existing algorithms identify the fault of electricity supply network with a unified approach, so we have no specific approach on various types of transmission equipment failure and it will result in low recognition rate of jumper connecting plate. In order to recognize the fault jumper connecting plate efficiently, we use improved OTSU method for infrared image segmentation and use flood fill method to separate each segmentation area. Secondly, we delete small areas and fill holes through dilation and hole filling algorithm, then get connected area’s skeleton by the skeleton extraction algorithm. Thirdly, we find Harris corner point n skeleton image, and calculate USFPF feature. Finally, through the slope value recognition we can discern jumper connecting plate’s fault. As a result, the successful recognition rate for jumper connecting plate’s fault is 85. 71 %, themiss rate is 1 4. 28%, and themistake rate is 2. 8%. Experimental results show that the method has good results.