A Hybrid Deep Learning Model as the Digital Twin of Ultra-Precision Diamond Cutting for In-Process Prediction of Cutting-Tool Wear

Diamond cutting-tool wear has a direct impact on the processing accuracy of machined surface in ultra-precision diamond cutting. It is difficult to monitor tool’s condition because slight amount. This paper proposed hybrid deep learning model for tool state prediction The cutting force was accurately estimated and predicted by using with motion displacement, velocity, other signals machining process. By carrying out experiments, this method can classify diamond-tool an more than 85%. Meanwhile, effectiveness verified comparing it variety machine models.