Estimating Operating States of Numerical Control Milling Machines Using Wi-Fi Sensing and Channel State Information

This study investigates whether wi-fi sensing, through channel state information (CSI), can estimate the operating state and the material machined by a numerical control (NC) milling machine without contact sensors. The research aims to develop a predictive system that detects machine tool failures by analyzing fluctuations in wi-fi radio waves and assesses the state of the machine based on changes in wi-fi radio waves. If a machine tool vibrates differently from usual, the system predicts a fault based on historical vibration data. To achieve this, a novel approach is required to predict the operating state of a machine tool using wi-fi sensing. Thus, this study conducted a preliminary evaluation to determine the possibility of estimating the operating state of a machine tool using wi-fi sensing. The experiment involved controlling the NC machine tool to alter its operational state during material processing and measuring the processing state using CSI obtained from a wi-fi module. Results indicated that CSI can estimate the operating and machining states of the milling machine.