With the development of computer vision in recent years, more and more attention is paid to the practical application of artificial intelligence algorithms in power security systems. In this paper, aiming at the safety belt specification of power maintenance workers, based on the Mask R-CNN algorithm, we propose a new detection algorithm of safety belts hanging lower than the operator position during aerial work, which can complete the detection of safety belt violation in real-time and efficiently. Furthermore, we propose a new detection method of safety belt violation for aerial work, i.e., Mask-Keypoints R-CNN, which is applicable to the combination of safety belt detection and human key point information. The algorithm cuts the useful safety belt data set from the key parts of human bodies based on the positioning and detection module of the key points of human bodies and judges the violation of operators by combining with the safety belt detection module. In conclusion, the proposed algorithm has strong practicability and high efficiency and has achieved high accuracy.