Application of a wavelet-based signal analysis for evaluating the tool state in cutting operations

Manufacturing within a flexible production environment rises high demands on a sensor based monitoring of process and tool state. Frequently changing machining conditions in one-off and small batch size production require intelligent and flexible process monitoring systems. Signal analysis and disturbance identification strategies must be able to reliably separate signal pattern caused by the occurrence of tool wear from signal variations in the regular cutting process. Finish milling of sculptured surfaces is characterised by permanently changing engagement conditions between the ball end milling tool and the workpiece surface. The paper describes developments for tool wear monitoring in this complex machining process. The combination of the wavelet based signal parameters and an engagement dependent monitoring strategy allows a reliable determination of the tool state