In order to reduce a high operation cost of maintenance and recondition, as well as improving the security capability, we employed an improved YoloX-s detection method for the fault of closure detectors. By elevating the PANet path fusion network of the proposed model, a fusion with shallow feature layer is further strengthened; In addition, we added the CA(Coordinate Attention) attention mechanism to the model for the more detailed information in the target area. Moreover, the CIoU loss function is selected to enhance a positioning accuracy, which is aimed at the overlapping area, the center point distance and the aspect ratio between a target frame and a detection frame. After various tests, the experimental results showed that the presented model has a better comprehensive performance compared with the existing YoloX-s model. Furthermore, an average accuracy of moving contact reached 97.73%, an average accuracy of static contact reached 98.83%, and an average accuracy reached 98.28%.