The nut on the transmission tower is the medium connecting two or more transmission tower components, and the pin is an important guarantee to ensure that the nut does not fall off. The lack of pins will lead to potential safety hazards at the joints between various components. This study combines the federated learning and target detection algorithm to upload the local model and generate the fusion model through the central node without any data exchange among regions. The detection algorithm Faster RCNN and the classification network are used to detect and classify nuts, respectively. The experimental results show that compared with local models, the fusion model based on federated learning improves the mAP of detection tasks by 3%–6% and the accuracy of classification tasks by 2%–3%.