Using Power Spectral Density Analysis of Accelerometer-Measured Signals to Adjust CNC Machine Tool Cornering Motion Control Parameters

The dominant frequency peak value (PV) of the power spectral density of accelerometer-measured signals is used to discuss the computer numerical control (CNC) machine tool controller cornering motion control parameters, and then a systematic parameter adjustment procedure is designed to balance the cornering error and cornering speed of the machine tool cornering motions. Because the dominant frequency PV of the power spectral density distribution of the accelerometer-measured signals changes owing to the acceleration and deceleration status of the machine tool cornering motion, this study uses the dominant frequency PV as a reference indicator to adjust and design the control parameters. The Taguchi method and analysis of variance are employed to determine the effects of the control parameters on the machine tool cornering motions, and then power spectral density analysis is used to build the mathematical model of the control parameters for designing the best-fitted control parameters. A CNC machine tool is applied to validate the feasibility of the proposed design and the adjustment method for the control parameters. The results show that the difference in the cornering error of the test path is 7%, and the difference in the motion time is 43%; thus, the control parameter setting values can be used to balance the cornering accuracy and cornering speed of the test path.