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UBC Theses and Dissertations

Prediction of cutting forces at the tool tip using drive current for five-axis machines Tuysuz, Tugce


The current trend in industry is to achieve intelligent, Computer Numerical Controlled (CNC) machine tools which can monitor its performance and take corrective actions automatically during machining operations. Cutting forces are the most accepted indicators of the tool condition, load on the machine and part, and abnormalities in the machining operations. The objective of this thesis is to predict the cutting forces from the current drawn by each drive during five axis machining operations. The cutting forces generated at the tool–workpiece contact zone are transmitted to the three translational and two rotary drive motors through ball screws and gear boxes. The torque received by individual motors is transformed as disturbance current by the motor amplifiers. The cutting force transmitted to each feed drive acts as a disturbance to the closed loop servo controller, which reacts by supplying torque command in addition to the torque required to overcome the friction and inertial motions. The accurate prediction of cutting forces from the motor current measurements requires the separation of the effects of cutting and inertial motion forces from the total motor current values. The transfer function between the applied force at the tool tip and motor current is identified at each drive. The effects of structural modes are canceled through extended Kalman Filter designed for each drive. Both Coulomb and Viscous Friction forces have been identified, and their effects are also removed from the state measurements of all drives. The cutting forces at the tool tip are predicted by applying extended Kalman Filter on motor current signals, and transmitting them to the tool tip through forward kinematic model of the machine, the contributions are proven using machining tests conducted on a five axis machining center.

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