Thermal Error Measurement Research Articles

Thermal error measurement and modelling techniques for the five-degree-of-freedom spindle drifts in computer numerically controlled machine tools

Thermally induced errors have been significant factors affecting machine tool accuracy. In this paper, the spindle thermal error is examined, where thermal error components with five degrees of freedom (DOFs) are considered. An effective measurement system has been devised for five-DOF thermal errors, consisting of gap sensors and thermocouples around the microcomputer-interfaced environment. Several thermal error modelling techniques are also implemented for the thermal error prediction: multiple linear regression, neural network, system identification methods, etc. The performance of the thermal error modelling techniques is evaluated and compared, giving the system identification method as the optimum model having the least deviation. The developed system for the thermal error measurement and modelling has been practically applied to a computer numerically controlled machining centre, and the spindle thermal errors are effectively compensated using the microcomputer-machine tool interfaced networks. The machine tool accuracy has been improved about four to five times typically.

Thermal Error Measurement and Modeling Techniques for the 5 Degree of Freedom(DOF) Spindle Unit Drifts in CNC Machine Tools

Thermally induced errors have been significant factors affecting the machine tool accuracy. In this paper, the spindle thermal error has been focused, where the 5 degree of freedom thermal error components are considered. An effective measurement system has been devised for the 5 DOF thermal errors, consisting of gap sensors and thermocouples around the micro-computer interfaced environment. Several thermal error modeling techniques are also implemented for the thermal error prediction: multiple linear regression, neural network and system identification methods, etc. The performance of the thermal error modeling techniques is evaluated and compared, giving the system identification method as the optimum model having the least deviation. The developed system for the thermal error measurement and modeling was practically applied to a CNC machining center, and the spindle thermal errors were effectively compensated around the micro computer-machine tool interfaced networks. The machine tool accuracy was improved about 4-5 times typically.

Quick testing and modeling of thermally-induced errors of CNC machine tools

This research is concerned with enhancing the accuracy of a machining center through compensating for the thermally induced errors of the spindle and leadscrews using software. A quick set-up and multiple degree of freedom measurement system consisting of an on-machine probe and artifacts has been developed to accelerate and simplify the thermal error measurement. An artificial neural network based technique which correlates the thermal error field to the machine temperature field is then developed to model the measured multiple thermal errors all together. Test results show that the ANN can not only fit the highly nonlinear thermal errors well, but has also predicted thermal errors well even under varying or new cutting conditions with a precision of more than 85%. A PC based error compensation scheme has also been developed to upgrade a FANUC CNC controller for real-time thermal error compensation. Test results on a vertical machining center show that a 70–90% reduction of thermal errors has been gained after compensation.