The Research For Detecting Techniques Of NC Device's Technical Specifications

The performance of CNC device technical specifications directly affects the efficiency and precision of machining parts. It is of great significance to investigate and improve the separate detection method of technical specifications,contribute to narrow the gap with foreign high-end CNC device.Currently, separate detection methods for technical specifications of NC device are scarce. Processing test parts on the actual machine or using high precision measuring instrument such as circular grating meter to detection, the test results include comprehensive evaluation of NC devices, servo systems, and machine tool drive mechanism. It's not accurate to evaluate the specifications by the results. Detection platform is set up by building the models of servo systems and machine tool drive mechanism to realize objective detection.The function of electromechanical system simulation module is fulfilled by building multi-axis electromechanical system model and RTW technology. Model parameters validation is realized by VC and Matlab cross programming. Meanwhile, real-time specifications are detected by the support of Linux+RTAI/LXRT.Backlash compensation performances are detected by setting up machine backlash model. The model can simulate backlash error compensation ability of NC device for detection. Position and speed commands are collected to calculate the contour error, tracking error and speed fluctuation for evaluating of the position control performance. Based on time division interpolation principle, detection platform directly receives position data to reverse calculate the value of interpolation cycle. Finally, platform detects Nurbs spline interpolation functions and performances.By detecting the backlash error compensation performances of NC device and analyzing the detection results, a multi-cycles comprehensive backlash error compensation algorithm is put forward to improve compensation ability by using the detection platform. The "test driven improvement" function of the detection platform is illustrated by the above example.