Modeling and Experimental Analysis for Screw Loosening Detection Using a High-Speed Robotic Hand

Abstract

High-speed robotic hands are capable of agile movements and short-cycle control and can perform a variety of actions that are not possible with ordinary robotic hands. In this study, this characteristic is focused on and verified for the construction of an algorithm to detect screw loosening from force sensor data acquired when an object is vibrated at high-speeds. First, a simple model of the system was developed by applying vibrations to a part connected by a screw to a robotic hand. Based on the constructed model, simulations were performed to confirm weather the presence or absence of screw loosening influenced force data. Subsequently, experiments were conducted using a robotic hand and models to verify the differences caused by screw loosening. These results confirmed the differences in the force data available for detecting screw loosening. Furthermore, to confirm the reliability of the constructed model and consider the inspection method, the grasping position of the inspected object was added as a condition for verification. This additional experiment confirmed that there were significant changes in the force data depending on the grasping position. Additionally, the optimal grasping conditions for the inspection method were discussed, and the validity of the method was confirmed based on simple discrimination results. In the future, simulations using models with extended degrees of freedom, along with further experimental verification, will be conducted to develop more accurate inspection methods.