Abstract: The present disclosure relates to a method for online monitoring defect of a milling tool, comprising the steps of: 1) installing a vibration sensor module on a machine tool spindle; 2) acquiring initial sample data; 3) setting a threshold value ?S0 with a time interval of T; 4) measuring vibration signals of n blades in x, y and z directions in each period T0; 5) shaping to obtain n strong vibration cutting wave data respectively formed by n blades in x and y directions in each period T0; 6) analyzing and processing the strong vibration cutting wave data to obtain the difference ?S0/ between the cutting strong vibration wave areas formed by each blade in each period T0; 7) outputting a blade wear or defect signal to a display alarm module according to the constraint conditions by a data comparing and analyzing module, and giving an alarm by a display alarm module.

Abstract: The present disclosure relates to a method for online monitoring defect of a milling tool, comprising the steps of: 1) installing a vibration sensor module on a machine tool spindle; 2) acquiring initial sample data; 3) setting a threshold value ?S0 with a time interval of T; 4) measuring vibration signals of n blades in x, y and z directions in each period T0; 5) shaping to obtain n strong vibration cutting wave data respectively formed by n blades in x and y directions in each period T0; 6) analyzing and processing the strong vibration cutting wave data to obtain the difference ?S0/ between the cutting strong vibration wave areas formed by each blade in each period T0; 7) outputting a blade wear or defect signal to a display alarm module according to the constraint conditions by a data comparing and analyzing module, and giving an alarm by a display alarm module.