• Journal of the Korean Society for Precision Engineering
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• v.15 no.8
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• pp.26-32
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• 1998

The grinding force generated during the grinding process causes an elastic deformation of the workpiece, grinding wheel, and machine system. Thus, the true depth of cut is always smaller than the apparent depth of cut. This is known as machining elasticity phenomenon. The machining elasticity parameter is defined as a ratio between the true depth of cut and the apparent depth of cut. It is an important factor to understand the material removal mechanism of the grinding process. To increase productivity, the value of this machining elasticity parameter must be large. Therefore, it is essential to know the characteristics of this parameter. The objective of this research is to study the effect of the major grinding conditions, such as table speed and depth of cut, on this parameter experimentally. Through this research, it is found that this parameter value is increasing when the table speed is decreasing or the depth of cut is increasing. Also, this parameter value depends on the grinding mode (up grinding, down grinding).

• Transactions of the Korean Society of Mechanical Engineers
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• v.17 no.12
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• pp.3115-3123
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• 1993

This paper presents a real-time correction method of the movemont errors of a translatory precision machine axis. This method is a null-balances technique in which two plane mirrors are used to generate an interferometric fringe pattern utilizing the optical principles of TwymanGreen interferometry. One mirror is fixed on a reference frame, while the other is placed on the machine axis being supported by three piezoelectric actuators. From the fringe pattern, one translatory and two rotational error components of the machine axis are simultaneously detected by using CCD camera vision and image processing techniques. These errors are then independently suppressed by activating the peizoelectric actuators by real-time feedback control while the machine axis is moving. Experimental results demonstrate that a machine axis can be controlled with movement errors less than 10 nm in vertical straightness, 0.1 arcsec in pitch, and 0.06 arcsec in roll for 50mm travel by adopting the real-time correction method.

• Journal of the Korean Society of Radiology
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• v.16 no.6
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• pp.673-680
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• 2022

In this study, based on PLA, we analyzed the Hounsfield Unit (HU) of materials containing 20% each of aluminum, wood, copper, carbon, and marble, and tried to analyze how they affect the image. A cylindrical phantom of 5×30×30 ㎣ (thickness×diameter×height) was fabricated using a entry-level 3D printer. The kV was changed to 80, 100 and 120, and the mAs was changed to 100 and 200 mAs, and the phantom in the center of the table was cross-scanned under a total of six conditions. A circular ROI was set using image J program and the quantification value of the material part HU and the quantification value of the peripheral part CNR were obtained. The HU average of the material part increased in the order of [PLA - wood 20%], [PLA - marble 20%], [PLA - carbon 20%], [PLA 100%], [PLA - aluminum 20%], [PLA - copper 20%] (p<0.05) a negative correlation was confirmed with the HU by increasing kV. It was confirmed that the CNR value in the peripheral area increased in the order of [PLA - marble 20%], [PLA - copper 20%], [PLA - carbon 20%], [PLA - wood 20%], [PLA - aluminum 20%], and [PLA - 100%] (p<0.05). Human organs with similar HU values for each material are [PLA - copper 20%] compact bone, [PLA - aluminum 20%] cancellous bone, [PLA 100%] coagulated blood, [PLA - carbon 20%] and [PLA - marble 20%] liver, muscle, spleen and [PLA - wood 20%] had similar values to fat. In addition, we confirmed the blur phenomenon that blurs the image around the filament with all materials, and confirmed that [PLA 100%] especially has the most blur around the filament. Therefore, it is considered desirable to reflect the HU value of the target organ and consider cloudiness around the phantom when selecting materials for medical phantom fabrication, and this research can provide basic data.