At present, significant breakthrough has been made in the detection of significant objects of transmission lines, but there are still limitations in predicting the "integrity" of significant areas, and it is difficult to fully identify and locate the defects of insulator strings on transmission lines. In this paper, integrity awareness network is used to detect insulator strings on transmission lines. First, feature aggregation module is used to extract features at different levels. Second, integrity enhancement module is used to highlight significant target channels and suppress other interference channels. Finally, part whole inspection module is used to determine whether there is a strong consistency between parts and the whole of target features, which can improve the recognition accuracy of defective insulator strings. Through subjective and objective comparison between the algorithm in this paper and the three popular algorithms currently disclosed, it is found that the algorithm in this paper has more advantages in the significance detection when the insulator string and background are highly integrated.