In view of the problem that the image details are lost and the edges are blurred in the intelligent patrol inspection of electric power, resulting in the wrong target detection and recognition, a super-resolution method based on per-pixel selt-paced adversarial network （PSPA） is proposed. This method is based on the generation of adversarial network, adds multiple attention mechanisms, and restores the detailed texture through pixel by pixel comparison.The experimental results show that the super-resolution images generated by this method are not only superior to the existing algorithms in human visual system, but also 6.2 and 0.099 3 times higher than the existing algorithms in PSRN and SSIM. Then Yolov3 is applied on the super-resolution images recovered by different algorithms in the UAV transmission line insulator dataset and the power construction helmet wearing dataset. The experimental results demonstrate that the proposed method could not only decreases the residual error rate, but also improves the detection confidence as high as the high-resolution images