• 한국기계가공학회지
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• 제6권4호
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• pp.57-64
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• 2007

In the recent years, development of machine tool with high speed feeding system have brought a rapid increase in productivity. Practically, thermal deformation problem due to high speed is, however, become a large obstacle to realize high precision machining. In this study, therefore, the construction of automatic error compensation system to control thermal deformation in high speed feeding system with real time is proposed. To attain this purpose, high speed feeding system with feeding speed 60mm/min is developed and experimental equation for relationship between thermal deformation and temperature of ball screw shaft using multiple regression analysis is established. Furthermore, in order to analyze thermal deformation error, compensation coefficient is determined and thermal deformation experiments is carried out. From obtained results, it is confirmed that automatic error compensation system constructed in this study is able to control thermal deformation error within $15{\sim}20{\mu}m$.

• 한국기계가공학회지
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• 제16권2호
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• pp.88-93
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• 2017

Due to the requirement of the development of the precision manufacturing industry, the accuracy of machine tools has become a key issue in this field. A critical factor that affects the accuracy of machine tools is the feed system, which is generally driven by a ball screw. Basically, to improve the performance of the feed drive system, which will be thermally extended lengthwise by continuous usage, a thermal error compensation system that is highly dependent on the feedback temperature or positioning data is employed in the machine tool system. Due to the overdependence on measuring technology, the cost of the compensation system and low productivity level are inevitable problems in the machine tool industry. This paper presents a novel feed drive thermal error compensation system method that could compensate for thermal error without positioning or temperature feedback. Regarding this thermal error compensation system, the heat generation of components, principal of compensation, thermal model, mathematic model, and calculation method are discussed. As a result, the test data confirm the correctness of the developed feed drive thermal error compensation system very well.

• 한국공작기계학회:학술대회논문집
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• 한국공작기계학회 2001년도 춘계학술대회 논문집(한국공작기계학회)
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• pp.453-457
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• 2001

One of the major limitations of productivity and quality in metal cutting is the machining accuracy of machine tools. The machining accuracy is affected by geometric and thermal errors of the machine tools. In this study, the compensation device is manufactured in order to compensate thermal error of machine tools under the real-time. This paper models of the thermal errors for error analysis and develops on-the-machine measurement system by which the volumetric error are measured and compensated. The thermal error is modeled by means of angularity errors of a column and thermal drift error of the spindle unit which are measured by the touch probe unit with a star type styluses, a designed spherical ball artifact, and five gap sensors. In order to compensate thermal characteristics under several operating conditions, experiments performed with five gap sensors and manufactured compensation device on the horizontal machining center.

• 한국공작기계학회:학술대회논문집
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• 한국공작기계학회 2002년도 추계학술대회 논문집
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• pp.417-422
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• 2002

One of the major limitations of productivity and quality in metal cutting is the machining accuracy of machine tools. The machining accuracy is affected by geometric errors, thermally-induced errors, and the deterioration of the machine tools. Geometric and thermal errors of machine tools should be measured and compensated to manufacture high quality products. In metal cutting, the machining accuracy is more affected by thermal errors than by geometric errors. In this study, the compensation device and temperature-based algorithm have been implemented on the machining center in order to compensate thermal error of machine tools under the real-time. The thermal errors are predicted using the neural network and multi-regression modeling methods. In order to compensate thermal characteristics under several operating conditions, experiments performed with five gap sensors and manufactured compensation device on the horizontal machining center.

• 한국정밀공학회지
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• 제16권3호통권96호
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• pp.215-221
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• 1999

The object of the thermal error compensation system in machine tools is improving the accuracy of a machine tool through real time error compensation. The accuracy of the machine tool totally depends on the accuracy of thermal error model. A thermal error model can be obtained by appropriate combination of temperature variables. The proposed method for optimal variable selection in the thermal error model is based on correlation grouping and successive regression analysis. Collinearity matter is improved with the correlation grouping and the judgment function which minimizes residual mean square is used. The linear model is more robust against measurement noises than an engineering judgement model that includes the higher order terms of variables. The proposed method is more effective for the applications in real time error compensation because of the reduction in computational time, sufficient model accuracy, and the robustness.

• 한국정밀공학회지
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• 제14권11호
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• pp.154-162
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• 1997

A real time error compensation system was developed to improve the quasistatic volumetric accuracy of a machining center by using sensing, metrology, modeling, and computer control techniques. Including thermal errors, 32 error components are formulated in the time-space domain. Fifteen thermal sensors are used to characterize the temperature field of the machine. A compensation controller based on the IBM/PC has been linked with a CNC controller to compensate for machine errors in real time. The maximum linear displacement error in 4 body diagonals were reduced from 140 ${\mu}m$ to 34.5${\mu}m$ with this compensation system, and the spindle thermal drift in space was reduced from 147.3 ${\mu}m$ to 16.8 ${\mu}m$.

• 한국정밀공학회지
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• 제17권4호
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• pp.135-141
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• 2000

The major role of temperature sensors in thermal error compensation system of machine tools is improving machining accuracy by supplying reliable temperature data on the machine structure. This paper presents a new method for fault diagnosis of temperature sensors and recovery of faulted data to establish the reliability of thermal error compensation system. The detection of fault and its location is based on the correlation coefficients among temperature data from the sensors. The multiple linear regression model which is prepared using complete normal data is also used fur the recovery of faulted data. The effectiveness of this method was tested by comparing the computer simulation results and measured data in a CNC machining center.

• Journal of Mechanical Science and Technology
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• 제15권11호
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• pp.1482-1489
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• 2001

Thermally-induced errors originating from machine tool errors have received significant attention recently because high speed and precise machining is now the principal trend in manufacturing proce sses using CNC machine tools. Since the thermal error model is generally a function of temperature, the thermal error compensation system contains temperature sensors with the same number of temperature variables. The minimization of the number of variables in the thermal error model can affect the economical efficiency and the possibility of unexpected sensor fault in a error compensation system. This paper presents a thermal error model with minimum number of variables using a fuzzy logic strategy. The proposed method using a fuzzy logic strategy does not require any information about the characteristics of the plant contrary to numerical analysis techniques, but the developed thermal error model guarantees good prediction performance. The proposed modeling method can also be applied to any type of CNC machine tool if a combination of the possible input variables is determined because the error model parameters are only calculated mathematically-based on the number of temperature variables.

• 제어로봇시스템학회논문지
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• 제18권5호
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• pp.502-508
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• 2012

Heliostat, as a concentrator to reflect the incident solar energy to the receiver, is the most important system in the tower-type solar thermal power plant since it determines the efficiency and ultimately the overall performance of solar thermal power plant. Thus, a good sun tracking ability as well as a good optical property of it are required. Heliostat sun tracking system uses usually an open loop control system. Thus the sun tracking error caused by heliostat's geometrical error, optical error and computational error cannot be compensated. Recently use of sun tracking error model to compensate the sun tracking error has been proposed, where the error model is obtained from the measured ones. This work is a development of heliostat sun tracking error measurement and compensation method using BCS (Beam Characterization System). We first developed an image processing system to measure the sun tracking error optically. Then the measured error is modeled in linear polynomial form and neural network form trained by the extended Kalman filter respectively. Finally error models are used to compensate the sun tracking error. We also developed the necessary image processing algorithms so that the heliostat optical properties such as maximum heat flux intensity, heat flux distribution and total reflected heat energy could be analyzed. Experimentally obtained data shows that the heliostat sun tracking accuracy could be dramatically improved using either linear polynomial type error model or neural network type error model. Neural network type error model is somewhat better in improving the sun tracking performance. Nevertheless, since the difference between two error models in compensation of sun tracking error is small, a linear error model is preferred in actual implementation due to its simplicity.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 2002년도 춘계학술대회 논문집
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• pp.399-404
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• 2002

Improvement of measuring accuracy is an essential part of quality control manufacturing process. The OMM is less than the CMM in measure accuracy but the OMM system is more efficient, easier to use than other measurement system. About 40~70% of the machine tool errors are induced by the thermal errors. Therefore, a key requirement for improving the measuring accuracy is to reduce the geometric and thermal errors. Thermal errors are measured by a ball bar system and predicted by the thermal error modeling. Furthermore, using the pre-defined thermal error map approach compensates the geometric accuracy of the OMM. Appropriate experiments are performed using ball-bar system, temperature measuring devices and touch-type probe. Compensated results are compared with those obtained using CMM to verify the proposed methods.