Abstract
The temperature-sensitive point is the input variable of the thermal error compensation model of computer numerical control (CNC) machine tools. At present, the most commonly used selection method is to measure the multipoint temperature and thermal error of the machine tool synchronously and select several temperature measurement points with the highest thermal error correlation as temperature-sensitive points according to the measurement data. This study reveals that this method sometimes has obvious mis-selection and causes the model to fail. The reason is that the weak correlation temperature measurement point away from the machine tool heat source amplifies the volatility of the correlation evaluation result, owing to the small overall change. If the calculated result exceeds the true strong correlation temperature measurement point, it will be incorrectly selected as the temperature-sensitive point. This scenario has been termed herein as the pseudocorrelation problem. With the gradual popularization of thermal error compensation technology for CNC machine tools, pseudocorrelation will seriously affect the mass production pass rate. Therefore, the study analyzes and rigorously proves the mathematical mechanism of this problem, and the temperature measurement point preselection algorithm based on the correlation coefficient volatility determination factor (CCVDF) is proposed to eliminate potential pseudocorrelation temperature points before selecting temperature-sensitive points. After 1000 random simulation experiments, the failure rate of Z-direction thermal error modeling after preselection decreased from 5.1% to 0.5%, and the Y-direction error decreased from 33.7% to 1.5%. This algorithm can greatly improve the qualification rate of large-scale equipment of thermal error compensation technology.
Highlights
The thermal error of computer numerical control (CNC) is the displacement between the spindle and the worktable caused by the thermal deformation of the mechanical structure
This study proposes that before the temperature sensitivity point is formally selected, the primary selection according to the correlation coefficient volatility determination factor (CCVDF) can be used, and the temperature measurement point with less effective variation is eliminated in advance to reduce the probability of mis-selection of temperature sensitive points
SUMMARY In this study, the production mechanism of iineffective thermal error modeling caused by pseudocorrelation temperature measurement points is examined in depth
Summary
The thermal error of computer numerical control (CNC) is the displacement between the spindle and the worktable caused by the thermal deformation of the mechanical structure. B. RESEARCH OF THIS STUDY in a large-scale thermal error experiment, it has been found that the selection of temperature-sensitive points based on the correlation coefficient sometimes leads to mis-selection in the strong robust thermal error modeling algorithm in this study, twice in 15 batches of experiments. RESEARCH OF THIS STUDY in a large-scale thermal error experiment, it has been found that the selection of temperature-sensitive points based on the correlation coefficient sometimes leads to mis-selection in the strong robust thermal error modeling algorithm in this study, twice in 15 batches of experiments This error is not high, the increase in application requirements in the future is likely to lead to a serious hidden danger that the qualification rate of large-scale equipment of thermal error compensation technology declines.
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