Estimation of contact force from grinding sound based on frequency analysis and machine learning

Abstract

It is important to obtain the contact force during polishing or grinding processes using a robot to achieve high quality processing. The frequency of the machining sound was correlated with the contact force. In this paper, we propose a method for estimating the contact force based on the sound using a convolutional neural network. Microphones are superior to force sensors in that they reduce the risk of failure and are less expensive. Mel spectrogram was used for frequency analysis of the sound. The results of the experiment showed that the contact force was estimated from the sound. When the contact state was kept constant, the accuracy of the sound-based estimation was better than that of the force sensor-based.