Piecewise compensation of thermal errors of a ball screw driven CNC axis

Zapłata, J.; Pajor, M.

doi:10.1016/j.precisioneng.2019.07.011

Cited by 37 publications

(15 citation statements)

References 12 publications

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“…According to Ramesh et al [ 18 , 19 ], the thermal factors account for 40–70% of the total dimensional and shape errors in machine tools. Much scientific research has been performed to analyze, model, and compensate the influence of thermal positioning error in manually or computer-numerical-control (CNC) machines [ 20 , 21 , 22 , 23 , 24 , 25 , 26 , 27 , 28 ]. The majority of this research analyzes only the machine tool structure, considering that the used measurement system is not the source of the error by itself [ 29 ].…”

Section: Introductionmentioning

confidence: 99%

Thermal and Geometric Error Compensation Approach for an Optical Linear Encoder

Gurauskis

Kilikevičius

Kasparaitis

2021

Sensors

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Linear displacement measuring systems, like optical encoders, are widely used in various precise positioning applications to form a full closed-loop control system. Thus, the performance of the machine and the quality of its technological process are highly dependent on the accuracy of the linear encoder used. Thermoelastic deformation caused by a various thermal sources and the changing ambient temperature are important factors that introduce errors in an encoder reading. This work presents an experimental realization of the real-time geometric and thermal error compensation of the optical linear encoder. The implemented compensation model is based on the approximation of the tested encoder error by a simple parametric function and calculation of a linear nature error component according to an ambient temperature variation. The calculation of a two-dimensional compensation function and the real-time correction of the investigated linear encoder position readings are realized by using a field programmable gate array (FPGA) computing platform. The results of the performed experimental research verified that the final positioning error could be reduced up to 98%.

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Section: Introductionmentioning

confidence: 99%

Thermal and Geometric Error Compensation Approach for an Optical Linear Encoder

Gurauskis

Kilikevičius

Kasparaitis

2021

Sensors

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“…For this method, the temperature sensitive point must be determined and establish the mathematical model between the temperature sensitive point and the thermal error. The way to find temperature sensitive point include cluster analysis [6], Lasso [7], fuzzy c-means clustering [8], correlation analysis [9], Gaussian integration method [10], etc. The related modeling methods include Elman neural network [11], adaptive support vector machine [12], dynamic model [13], etc.…”

Section: Introductionmentioning

confidence: 99%

“…JacekZapłata calculated the heat output of nuts and bearings at different speed, then found the mapping relation between heat sources and speed. At last, the change rules of thermal characteristic parameters at different speed was obtained [15]. Liu Kuo proposed the heat value and heat conduction coefficient of the nut through optimization theory, then input these parameters into DBN model to evaluate the reliability of thermal error parameters [16].…”

Section: Introductionmentioning

confidence: 99%

Screw thermal characteristics analysis and error prediction considering the two-dimensional heat transfer structure

Chen¹,

Chen²

2021

Preprint

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Thermal error is a common problem in machine tool processing. It is usually proposed to take the screw as one-dimensional rod heat transfer system to solve the thermal error of screw by establishing thermal characteristic equation. This method regards the temperature on the nut as the temperature of the screw contact surface without considering the heat transfer distance between screw and the mounting point on the nut. To solve this problem, this paper takes the screw-nut feed system as a two-dimensional heat transfer structure considering both screw and nut. In addition, to solve the low convergence speed and easy fall into local optimum problem in optimal parameter identification. The improved particle swarm optimization algorithm (IPSOA) is proposed to identify the boundary parameters of thermal characteristics equations. Finally, the temperature and thermal error of the screw-nut feed system is calculated by the identified results. Experiments under different working condition show that the maximum prediction residual error of the two-dimensional method (TDM) is less than 7.2 um and the simulating prediction accuracy can reach 86.2%. Besides, compared with one-dimensional model (ODM), TDM has a higher predict accuracy which verifies the effectiveness of the proposed method.

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“…For many companies, the cost of hiring a qualified operator is too high and the time needed for training is too long. Therefore, the control systems of machine tools are extended with operator support systems, such as: compensation of temperature errors of ball screws [ 14 ] or 3D (three-dimensional) scanning vision system for positioning the workpiece [ 15 ]. More extensive CNC systems have additional built-in options, which include extensive graphical interfaces to facilitate the generation and analysis of G-code i.e., Siemens: Shopturn/ShopMill, Fanuc: Manual Guide.…”

Section: Introductionmentioning

confidence: 99%

Remanufacturing System with Chatter Suppression for CNC Turning

Miądlicki

Jasiewicz

Gołaszewski

et al. 2020

Sensors

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The paper presents the concept of a support system for the manufacture of machine spare parts. The operation of the system is based on a reverse engineering module enabling feature recognition based on a 3D parts scan. Then, a CAD geometrical model is generated, on the basis of which a machining strategy using the CAM system is developed. In parallel, based on the geometric model, a finite element model is built, which facilitates defining technological parameters, allowing one to minimize the risk of vibrations during machining. These parameters constitute input information to the CAM module. The operation of the described system is presented on the example of machining parts of the shaft class. The result is a replacement part, the accuracy of which was compared by means of the iterative closest point algorithm obtaining the RMSE at the level of scanner accuracy.

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Piecewise compensation of thermal errors of a ball screw driven CNC axis

Cited by 37 publications

References 12 publications

Thermal and Geometric Error Compensation Approach for an Optical Linear Encoder

Thermal and Geometric Error Compensation Approach for an Optical Linear Encoder

Screw thermal characteristics analysis and error prediction considering the two-dimensional heat transfer structure

Remanufacturing System with Chatter Suppression for CNC Turning

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