Bolt Detection on Railway Rails Using ResNet-50 V1 with SSD Framework

One of the parts of a railroad track is a bolt. The role of bolts is significant in railway tracks, namely as a fastener between rails. Considering the importance of bolts on railway tracks, every morning, an officer would be assigned to go to the railway tracks to check the bolts. This inspection is done manually on foot or by driving along the railway tracks. Inspection performed manually has the possibility of errors in recognizing the condition of the bolt. In addition, if performed manually, there will be no record of the condition of the bolt. This data will be used to consider whether the condition of the bolt is still suitable for use or needs to be replaced. The formulation of the problem of the research conducted is how to detect bolts on railroad tracks using deep learning, with the purpose of this study to use a model to recognize and be able to detect bolts on railroad tracks. This study uses deep learning with the deep learning method used SSD Resnet 50 V1. The first step that must be taken in the study is to identify the object of the bolt located on the railway tracks. Further research can be carried out. This research has successfully detected bolts on railway tracks. This study used a dataset of 200 datasets in the first experiment and 300 datasets in the second experiment. The model used in the study is the Resnet 50 V1 SSD model, where using 2,000 steps, the precision value is 92.64%, and the Recall value is 64.87%.