A Review of Geometric Error Modeling and Error Detection for CNC Machine Tool

Han, Zhen; Jin, Hong; Liu, Yu Long; Fu, Hong

doi:10.4028/www.scientific.net/amm.303-306.627

Cited by 16 publications

(3 citation statements)

References 15 publications

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“…9 A review of different instruments to measure machine tools had been discussed. 10 Linear displacement accuracy showed improvement for computer numerical control (CNC) machine by applying positive and negative direction pitch error compensation. 11 Linear displacement error of CNC Lathe, CNC milling center and deep drilling machine had been measured.…”

Section: Introductionmentioning

confidence: 99%

Measurement of error in computer numerical control machines and optimization using teaching–learning-based optimization algorithm

Ravichandran¹,

Natarajan²

2019

Measurement and Control

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The accuracy of computer numerical control machine tools can be improved by identifying error sources affecting the overall position error and orientation errors. Because of their inevitable nature, the position errors cannot be entirely eliminated from the machinery, but they can be identified, measured and compensated during the manufacturing process of the components by developing and using a mathematical model. In this present work, different mathematical models have been developed for the errors measured by laser interferometer at different nominal positions of X, Y and Z axes both in forward and reverse direction movement as per VDI 3441 Germany standard. Using Akaike information criterion, the best model is selected for each axis and later the best model’s coefficients have been optimized by considering both minimizing sum square errors and maximizing R2 values using teaching–learning-based optimization algorithm. Technique for Order Preference by Similarity to the Ideal Solution method has been adopted to convert the dual objectives into a single objective. An improvement of 1%–71% in R2 values was reported to prove the effectiveness of the proposed optimization algorithm, Teaching–Learning-Based Optimization algorithm, with the same sum square error values.

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Section: Introductionmentioning

confidence: 99%

Measurement of error in computer numerical control machines and optimization using teaching–learning-based optimization algorithm

Ravichandran¹,

Natarajan²

2019

Measurement and Control

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“…Hence, error avoidance is not a widely used or cost-effective method for enhancing machining accuracy. Error compensation is a "soft technique" that aims to create an opposite error to eliminate the original thermal error (Han et al 2013). The thermal error compensation method has advantages of diverse applications and lower cost.…”

Section: Introductionmentioning

confidence: 99%

Comprehensive compensation method for thermal error of vertical drilling center

Kang

Zhao

et al. 2019

Transactions of the Canadian Society for Mechanical Engineering

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To eliminate the influence of thermally induced error from a machine tool on machining accuracy, a comprehensive error compensation method for thermal displacement of the screw shaft and spindle is put forward. Based on a heat transfer mechanism and experimental analysis, a model of screw thermal expansion error is built. Modeling of spindle thermal growth that depends on speed variations is also proposed. Thermal tests for studying thermal behavior of the spindle and screw axis are carried out on the vertical drilling center TC500R. Finally, the compensation effect of the robust model is validated via experimental tests and machining. Experimental results show that thermal displacement variations are controlled within 2 μm when the compensation system is activated. The suggested model can achieve high accuracy and good applicability in different moving states. Machining results indicate that dimensional accuracy of the workpiece is significantly improved after implementation of compensation. Feasibility of the thermal error compensation system is satisfactory in applications for drilling operations.

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“…Learning capability of the neural networks is employed to compensate the effects of the nonlinear friction. 15 Generally, friction can cause geometric and thermal errors, the volumetric error modeling and compensation method considering the thermal effect on five-axis machine tools is proposed in Zhang et al 16 Geometric and thermal error compensation for CNC milling machines based on Newton interpolation method is proposed in Wang et al 17 The total differential methods based universal post processing algorithm considering geometric error for multi-axis NC machine tool is proposed in Peng et al 18 Geometric error modeling and error detection for CNC machine tool is reviewed in Han et al 19 Software compensation technology model for the geometric error is designed in Han et al 20 and the new methods for geometric errors identification in machining center are established in Yang and Lin. 21 In the aforementioned literature, most researches use a specific friction model during the whole control process.…”

Section: Introductionmentioning

confidence: 99%

Robust control of the A-axis with friction variation and parameters uncertainty in five-axis CNC machine tools

Zhao

Shi

2014

Proceedings of the Institution of Mechanical Engineers, Part C:

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A-axis is an essential assembly in the five-axis CNC machine tools, and its positioning precision directly affects the machining accuracy and surface quality of the parts. Considering the influence of parameters perturbation and uncertain cutting force on the control precision of the A-axis, a nonlinear dynamics model of the A-axis system is established, which reveals the relationships among the drive torque, the load torque, the motion direction and the system parameters. Then, two adaptive sliding mode controllers (ASMC) are designed. The first one is based on the bipolar sigmoid function, which can adjust the switching gain and the boundary layer thickness adaptively, then, equilibrium between the tracking error and the chattering can be achieved. The second one is a compound adaptive controller constituted by the traditional sliding mode controller (TSMC) and an internal controller that is based on the hyperbolic tangent function. When the state trajectory comes into the boundary layer, the TSMC will be replaced by the internal controller, thus, the adaptive controller can continuously switch between these two controllers, which can effectively eliminate the high-frequency chattering in the TSMC. Stability of these two controllers is guaranteed by the Lyapunov theory. Experimental results demonstrate the effectiveness and feasibility of the proposed ASMC, which can smooth the input chattering and reduce the tracking error by 16.62% and 21.44%, respectively.

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A Review of Geometric Error Modeling and Error Detection for CNC Machine Tool

Cited by 16 publications

References 15 publications

Measurement of error in computer numerical control machines and optimization using teaching–learning-based optimization algorithm

Measurement of error in computer numerical control machines and optimization using teaching–learning-based optimization algorithm

Comprehensive compensation method for thermal error of vertical drilling center

Robust control of the A-axis with friction variation and parameters uncertainty in five-axis CNC machine tools

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