The norm of opereation in electric power maintenance is related to the personal safety of the staff, and is very im-portant to the development of electric power industry. In order to detect the illegal operation behavior of power maintenance workers from the perspective of computer vision, a multi-tasking and multi-branch illegal behavior detection algorithm was designed based on the Mask RCNN algorithm. It integrates target detection, key point detection and instance segmentation tasks, and performs parallel target detection. Detect and obtain the frame coordinates, keypoints, and mask information of the target. The experimental result demonstrates that this algorithm has significantly improved the precision in instance segmentation and key point detection, has higher accuracy and robustness compared with Mask RCNN. And it meets the accuracy requirements of actual deployment in power maintenance violation detection.