• Journal of the Korean Society for Precision Engineering
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• v.30 no.12
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• pp.1303-1312
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• 2013

We report an ultra-precision lathe designed to machine micron-scale features on a large-area roll mold. The lathe can machine rolls up to 600 mm in diameter and 2,500 mm in length. All axes use hydrostatic oil bearings to exploit the high-precision, stiffness, and damping characteristics. The headstock spindle and rotary tooling table are driven by frameless direct drive motors, while coreless linear motors are used for the two linear axes. Finite element method modeling reveals that the effects of structural deformation on the machining accuracy are less than $1{\mu}m$. The results of thermal testing show that the maximum temperature rise at the spindle outer surface is approximately $0.5^{\circ}C$. Finally, performance evaluations of the error motion, micro-positioning capability, and fine-pitch machining demonstrate that the lathe is capable of producing optical-quality surfaces with micron-scale patterns with feature sizes as small as $20{\mu}m$ on a large-area roll mold.

• Journal of Advanced Navigation Technology
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• v.19 no.1
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• pp.74-79
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• 2015

In this paper, in order to improve the error is utilized to location tracking the smart sensor detects a walking information user, RSSI is to provide an indoor position tracking system that is capable of correcting an error in terms weak. The acceleration sensor is able to detect the activity in the user walking and detects the number of step and the moving distance using the same. The Direction sensor is utilized as a digital compass, to detect the moving direction of the user. As a result of detecting the walking information using the sensor, it can be showed that this proposed indoor positioning system has a high degree of accuracy for the number of steps and the movement direction. Therefore, this paper shows that the proposed technique can correct the error of the location information to be problem in the conventional indoor location system which uses the only Wi-Fi APs by estimating the user's movement direction and distance using the sensors in smartphone without an additional equipment and cost.

• Journal of the Korean Society for Precision Engineering
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• v.22 no.10 s.175
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• pp.174-185
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• 2005

This paper presents the design, fabrication, and testing results of a dual stage actuator system for a fine positioning of magnetic heads in magnetic disk drives. A novel rotary microactuator which is electrostatically driven and utilized as a secondary actuator was designed. The stator and rotor electrodes in the microactuator was revised to have the optimal shapes and hence produces much higher rotational torque compared with the conventional comb-shape electrodes. The microactuators were successfully fabricated using SoG(silicon on glass) processing technology, which is known as being cost-effective. The fabricated microactuator has the structural thickness of $45{\mu}m$ with the gap width of approximately $3{\mu}m$. The dynamic characteristic of microactuator/slider assembly was investigated, and its natural frequency and DC gain were measured to be 3.4kHz and 32nm/V, respectively. The microactuator/slider assembly was integrated into a HDD model V10 of Samsung Electronics Co. and a dual servo algorithm was tested to explore the tracking performance of dual stage actuator system where the LDV signals instead of magnetic head signals were used. Experimental results indicate that this system achieves the tracking accuracy of 30nm. This value corresponds to a track density of 85,000 track per inch(TPI), which is about 3 times greater than that of current hard disk drives.

• Smart Structures and Systems
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• v.25 no.1
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• pp.111-122
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• 2020

Researchers up to date have introduced several Structural Health Monitoring (SHM) techniques with varying advantages and drawbacks for each. Satellite positioning systems (GPS, GLONASS and GALILEO) based techniques proved to be promising, especially for high natural period structures. Particularly, the GPS has proved sufficient performance and reasonable accuracy in tracking real time dynamic displacements of flexible structures independent of atmospheric conditions, temperature variations and visibility of the monitored object. Tall structures are particularly sensitive to oscillations produced by different sources of dynamic actions; such as typhoons. Wind forces induce in the structure both longitudinal and perpendicular displacements with respect to the wind direction, resulting in torsional effects, which are usually more complex to be detected. To efficiently track the horizontal rotations of the in-plane sections of such flexible structures, two main issues have to be considered: a suitable sensor topology (i.e., location, installation, and combination of sensors), and the methodology used to process the data recorded by sensors. This paper reports the contributions of the measurements recorded from dual frequency GPS receivers and uni-axial accelerometers in a full-scale experimental campaign. The Canton tower in Guangzhou-China is the case study of this research, which is instrumented with a long-term structural health monitoring system deploying both accelerometers and GPS receivers. The elaboration of combining the obtained rather long records provided by these two types of sensors in detecting the torsional behavior of the tower under ambient vibration condition and during strong wind events is discussed in this paper. Results confirmed the reliability of GPS receivers in obtaining the dynamic characteristics of the system, and its ability to capture the torsional response of the tower when used alone or when they are combined with accelerometers integrated data.

• Nuclear Engineering and Technology
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• v.52 no.10
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• pp.2410-2414
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• 2020

Heavy ions have a high potential for destroying deep tumors that carry the highest dose at the peak of Bragg. The peak caused by a single-energy carbon beam is too narrow, which requires special measures for improvement. Here, carbon-12 (¹²C) ion with different energies has been used as a source for calculating the dose distribution in the water phantom, soft tissue and bone by the code of Monte Carlobased FLUKA code. By increasing the energy of the initial beam, the amount of absorbed dose at Bragg peak in all three targets decreased, but the trend for this reduction was less severe in bone. While the maximum absorbed dose per bone-mass unit in energy of 200 MeV/u was about 30% less than the maximum absorbed dose per unit mass of water or soft tissue, it was merely 2.4% less than soft tissue in 400 MeV/u. The simulation result showed a good agreement with experimental data at GSI Darmstadt facility of biophysics group by 0.15 cm average accuracy in Bragg peak positioning. From 200 to 400 MeV/u incident energy, the Bragg peak location increased about 18 cm in soft tissue. Correspondingly, the bone and soft tissue revealed a reduction dose ratio by 2.9 and 1.9. Induced neutrons did not contribute more than 1.8% to the total energy deposited in the water phantom. Also during ¹²C ion bombardment, secondary fragments showed 76% and 24% of primary 200 and 400 MeV/u, respectively, were present at the Bragg-peak position. The combined treatment of carbon ions with neutron or electron beams may be more effective in local dose delivery and also treating malignant tumors.

• Journal of Cadastre & Land InformatiX
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• v.51 no.2
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• pp.185-198
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• 2021

Researches using UAVs are being actively conducted in the field of quickly constructing 3D spatial information in small areas. In this study, without using ground control points, a stereo camera was mounted on a UAV to collect images and quickly construct three-dimensional positions through image matching, bundle adjustment, and the determination of a scale factor. Through the experiment, when bundle adjustment was performed using stereo constraints, the root mean square error was 1.475m, and when absolute orientation was performed in consideration of a scale, it was found to be 0.029m. Through this, it was found that when using the data processing method of a UAV equipped with a stereo camera proposed in this study, high-accuracy 3D spatial information can be constructed without using ground control points.

• Proceedings of the Korean Society of Near Infrared Spectroscopy Conference
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• 2001.06a
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• pp.1267-1267
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• 2001

The existing fruit sorter has the method of tilting tray and extracting fruits by the action of solenoid or springs. In peaches, the most sort processing is supported by man because the sorter make fatal damage to peaches. In order to sustain commodity and quality of peach non-destructive, non-contact and real time based sorter was needed. This study was performed to develop peach sorter using near-infrared spectroscopy in real time and nondestructively. The prototype was developed to decrease internal and external damage of peach caused by the sorter, which had a way of extracting tray with it. To decrease positioning error of measuring sugar contents in peaches, fiber optic with two direction diverged was developed and attached to the prototype. The program for sorting and operating the prototype was developed using visual basic 6.0 language to measure several quality index such as chlorophyll, some defect, sugar contents. The all sorting result was saved to return farmers for being index of good quality production. Using the prototype, program and MLR(multiple linear regression) model, it was possible to estimate sugar content of peaches with the determination coefficient of 0.71 and SEC of 0.42bx using 16 wavelengths. The developed MLR model had determination coefficient of 0.69, and SEP of 0.49bx, it was better result than single point measurement of 1999's. The peach sweetness grading system based on NIR reflectance method, which consists of photodiode-array sensor, quartz-halogen lamp and fiber optic diverged two bundles for transmitting the light and detecting the reflected light, was developed and evaluated. It was possible to predict the soluble solid contents of peaches in real time and nondestructively using the system which had the accuracy of 91 percentage and the capacity of 7,200 peaches per an hour for grading 2 classes by sugar contents. Draining is one of important factors for production peaches having good qualities. The reason why one farm's product belows others could be estimated for bad draining, over-much nitrogen fertilizer, soil characteristics, etc. After this, the report saved by the peach grading system will have to be good materials to farmers for production high quality peaches. They could share the result or compare with others and diagnose their cultural practice.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.26 no.5D
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• pp.877-884
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• 2006

GPS is an essential tool for applications that be required high positioning precision, for the velocity field estimation of tectonic plates. The three years data of eight GPS permanent station were analyzed to estimate crustal deformation velocities using Gipsy-oasis II software. The velocity vectors of GPS stations are estimated by linear regression method in daily solution time series. The velocities have a standard deviation of less than 0.1mm/yr and the magnitude of velocities given by the Korean GPS permanent stations were very small, ranging from 25.1 to 31.1 mm/yr. The comparison between the final solution and other sources, such as IGS velocity result calculated from SOPAC was accomplished and the results generally show good agreement for magnitude and direction in crustal motion. To evaluate the accuracy of our results, the velocities obtained from six plate motion model was compared with the final solution based on GPS observation.

• Journal of Radiation Protection and Research
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• v.48 no.3
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• pp.162-166
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• 2023

Background: Assessment of the radiation doses to which workers are exposed can differ depending on the placement of dosimeters on the body. In addition, it is affected by whether the placement is under or over a shielding apron. This study aimed to evaluate the actual positioning of personal dosimeters on the body, with or without shielding aprons, among radiation workers in Korea. Materials and Methods: We analyzed the survey data, which included demographic characteristics, such as sex, age, occupation, work history, and placement of the personal dosimeter being worn, from a cohort study of Korean radiation workers. We assessed the use of personal dosimeters among workers, stratified by sex, age, working period, starting year of work, and occupation. Results and Discussion: Overall, high compliance (89.1% to 99.0%) with the wearing of dosimeters on the chest was observed regardless of workers' characteristics, such as age, sex, occupation, and work history. However, the placement of dosimeters, either under or over the shielding aprons, was inconsistent. Overall, 40.1% of workers wore dosimeters under their aprons, while the others wore dosimeters over their aprons. This inconsistency indicates that radiation doses are possibly measured differently under the same exposure conditions solely owing to variations in the placement of worn dosimeters. Conclusion: Although a lack of uniformity in dosimeter placement when wearing a shielding apron may not cause serious harm in radiation dose management for workers, the development of detailed guidelines for dosimeter placement may improve the accuracy of dose assessment.

• The Journal of the Convergence on Culture Technology
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• v.10 no.3
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• pp.801-807
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• 2024

Linear motion robots are devices that perform functions such as transferring parts or positioning devices, and require high precision. In companies that develop linear robot application systems, human workers are in charge of quality control and fault diagnosis of linear robots, and the result and accuracy of a fault diagnosis varies depending on the skill level of the person in charge. Recently, there have been many attempts to utilize artificial intelligence to diagnose faults in industrial devices. In this paper, we present a system that automatically diagnoses linear rail and ball screw misalignment of a linear robot using transfer learning. In industrial systems, it is difficult to obtain a lot of learning data, and this causes a data imbalance problem. In this case, a transfer learning model configured by retraining an established model is widely used. The information obtained by using an acceleration sensor and torque sensor was used, and its usefulness was evaluated for each case. After converting the signal obtained from the sensor into a spectrogram image, the type of abnormality was diagnosed using an image recognition artificial intelligence classifier. It is expected that the proposed method can be used not only for linear robots but also for diagnosing other industrial robots.