Geometric accuracy long-term continuous monitoring using strain gauges for CNC machine tools

Wang, Y.-Q.; Wu, Jiakun; Liu, H.-B.; Kang, Kaixuan; Liu, Kai

doi:10.1007/s00170-018-2337-7

Cited by 7 publications

(10 citation statements)

References 24 publications

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“…Machine tool accuracy retentivity is defined as the ability of each accuracy index of the machine tool to remain within the required range for a long time under normal operation [29,37]. e accuracy indexes of machine tools are comparatively steady over short times and show a nonlinearly decreasing tendency over a long period of time.…”

Section: Accuracy Retentivity Modelmentioning

confidence: 99%

“…Sensitivity analysis may also be included within the model training process of embedded feature extraction [28]. e concept of accuracy retentivity of the machine tool was quantitatively defined by Wang et al [29], and an analysis model of the spatial position accuracy of a three-axis machine tool based on multibody theory was established. According to the definition of accuracy retentivity of CNC machine tools, the accuracy retentivity of machine tools is evaluated in the time domain when the accuracy indexes of machine tools are kept within the required range [29,30].…”

Section: Introductionmentioning

confidence: 99%

“…e concept of accuracy retentivity of the machine tool was quantitatively defined by Wang et al [29], and an analysis model of the spatial position accuracy of a three-axis machine tool based on multibody theory was established. According to the definition of accuracy retentivity of CNC machine tools, the accuracy retentivity of machine tools is evaluated in the time domain when the accuracy indexes of machine tools are kept within the required range [29,30]. e longer the time is, the better the accuracy retentivity of the machine tool is, and the opposite case also holds.…”

Section: Introductionmentioning

confidence: 99%

“…e longer the time is, the better the accuracy retentivity of the machine tool is, and the opposite case also holds. However, aiming at the problems of the accuracy variations of machine tools, most studies have focused on the accuracy degradation and accuracy reliability evaluation caused by the wearing of guideways, bolt relaxation, and stress relaxation-induced deformation of machine bodies [29,[31][32][33]. It is obvious that all of these factors reduce the geometric accuracy gradually, which affects the geometric accuracy retentivity in an essential way [34].…”

Section: Introductionmentioning

confidence: 99%

“…It is obvious that all of these factors reduce the geometric accuracy gradually, which affects the geometric accuracy retentivity in an essential way [34]. e main difference between accuracy reliability and accuracy retentivity is that the reliability of CNC machine tools is generally characterized by the fault possibility of functional components, while accuracy retentivity research mainly studies the accuracy variations of a machine tool in the time domain [29,30]. e performance degradation of functional components is characterized by high nonlinearity, long periods, and various modes and is influenced by the processing method, lubrication method, pretightening force, and installation type.…”

Section: Introductionmentioning

confidence: 99%

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A Recognition Methodology for the Key Geometric Errors of a Multi‐Axis Machine Tool Based on Accuracy Retentivity Analysis

2019

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This paper proposes a recognition methodology for key geometric errors using the feature extraction method and accuracy retentivity analysis and presents the approach of optimization compensation of the geometric error of a multiaxis machine tool. The universal kinematics relations of the multiaxis machine tool are first modelled mathematically based on screw theory. Then, the retentivity of geometric accuracy with respect to the geometric error is defined based on the mapping between the constitutive geometric errors and the time domain. The results show that the variation in the spatial error vector is nonlinear while considering the operation time of the machine tool and the position of the motion axes. Based on this aspect, key factors are extracted that simultaneously consider the correlation, similarity, and sensitivity of the geometric error terms, and the results reveal that the effect of the position-independent geometric errors (PIGEs) on the error vectors of the position and orientation is greater than that of the position-dependent geometric errors (PDGEs) of the linear and rotary axes. Then, the fruit fly optimization algorithm (FOA) is adopted to determine the compensation values through multiobjective tradeoffs between accuracy retentivity and fluctuation in the geometric errors. Finally, an experiment on a four-axis horizontal boring machine tool is used to validate the effectiveness of the proposed approach. The experimental results show that the variations in the precision of each test piece are lower than 25.0%, and the maximum variance in the detection indexes between the finished test pieces is 0.002 mm when the optimized parameters are used for error compensation. This method not only recognizes the key geometric errors but also compensates for the geometric error of the machine tool based on the accuracy retentivity analysis results. The results show that the proposed methodology can effectively enhance the machining accuracy.

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Section: Accuracy Retentivity Modelmentioning

confidence: 99%