Sprocket Defect Detection using Deep Learning

The detection and recognition of sprockets and springs play an important role in ensuring the optimal functionality and safety of various mechanical systems. This abstract gives an overview of the methodologies and advancements in automated sprocket and spring detection. The significance of sprockets and springs in mechanical assemblies, highlighting their ubiquitous presence across diverse industries, ranging from automotive to aerospace. Manual inspection methods have challenges including time consumption and susceptibility to human error. To overcome the problems, this sprocket defect detection system is developed. Our custom dataset is used in this project. Presence of springs/holes are identified using deep learning methods. This system will be usseful in automated identification, localization, and classification of sprockets within complex and dynamic manufacturing environments, facilitating tasks such as assembly, inspection, and maintenance.