• Journal of Navigation and Port Research
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• v.27 no.1
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• pp.97-102
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• 2003

Wire ropes are used in a myriad of various industrial applications such as elevator, mine hoist, construction machinery, lift, and suspension bridge. Especially, the wire rope of crane is important component to container transfer. If it happens wire rope failures during the operation, it may lead to safety accident, economic loss by productivity decline and so on. To solve this problem, we developed remote wire rope fault detecting system, and this system is consisted of 3 parts that portable fault detecting part, signal processing part and remote monitoring part. All detected signal has external noise or disturbance according to circumstances. So, we applied to discrete wavelet transform to extract a signal from noisy data. It is verified that the detecting system by de-noising has good efficiency for inspecting faults of wire ropes in service. As a result, by developing this system, container terminal could reduce expense because of extension fo wire ropes exchange period and could competitive power. Also, this system is possible to apply in several field such as elevator, lift and so on.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.40 no.9
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• pp.835-842
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• 2016

In Korea, urban railway cars are typically maintained using the strategy of predictive maintenance. In an effort to overcome the limitations of the existing strategy, there is increased interest in adopting the condition-based maintenance strategy. In this study, a novel method is proposed to detect faults in the solenoid valves of the braking system in urban railway vehicles. We determined the key component (i.e., solenoid valve) that leads to braking system faults through the analysis of failure modes, effects, and criticality. Then, an equivalent circuit model was developed with the compensation of the temperature effect on solenoid coils. Finally, we presented how to detect faults with the equivalent circuit model and current signal measurements. To demonstrate the performance of the proposed method, we conducted a case study using real solenoid valves taken from urban railway vehicles. In summary, it was shown that the proposed method can be effective to detect faults in solenoid valves. We anticipate the outcome from this study can help secure the safety and reliability of urban railway vehicles.

• The Journal of Engineering Geology
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• v.14 no.1
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• pp.71-80
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• 2004

The failure of cut slopes frequently occurs particularly during the thawing season and the rain season in summer. This study interpreted data collected from site to which a real-monitoring system was applied in order to analyze the causes of ground behaviors and to forecast future slope failure. As for research methods, this study analyzed the size and mechanism of failure by integrating the results of field surveys and measurements. Furthermore, it analyzed data transmitted by the monitoring system installed in the a result, three times of ground displacement occurred as well as a number of partial tension cracks. The cut slope composed of sandstone and siltstone started its initial behavior as a result of torrential downpour and the loss of support of the substructure. For quantitative analysis of the characteristics of ground behavior, this study measured 5 lateral lines. According to the result of the measurement, displacement happened little in the section to which countermeasure had been applied, but displacement of maximum 400mm happened in the section to which countermeasure had not bee applied. The analysis of data on displacement and rainfall suggested a close relationship between ground behavior and rainfall. According to the result of stability interpretation along with the change of ground saturation, stability rate appeared to be less than 1.0 when ground saturation is over 55%. Although the current trend of ground behavior is at a stable stage falling within the range of tolerance, it is considered necessary to continue monitoring and data analysis because ground displacement is highly possible with the change of temperature during the winter.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.41 no.8
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• pp.771-782
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• 2017

This paper describes the development of a wearable robot to assist ankle power for the elderly. Previously developed wearable robots have generally used motors and gears to assist muscle power during walking. However, the combination of motor and reduction gear is heavy and has limitations on the simultaneous control of stiffness and torque due to the friction of the gear reducer unlike human muscles. Therefore, in this study, Mckibben pneumatic muscle, which is lighter, safer, and more powerful than an electric motor with gear, was used to assist ankle joint. Antagonistic actuation using a pair of pneumatic muscles assisted the power of the soleus muscles and tibialis anterior muscles used for the pitching motion of the ankle joint, and the model parameters of the antagonistic actuator were experimentally derived using a muscle test platform. To recognize the wearer's walking intention, foot load and ankle torque were calculated by measuring the pressure and the center of pressure of the foot using force and linear displacement sensors, and the stiffness and the torque of the pneumatic muscle joint were then controlled by the calculated ankle torque and foot load. Finally, the performance of the developed ankle power assistive robot was experimentally verified by measuring EMG signals during walking experiments on a treadmill.

• Journal of the Korean Institute of Intelligent Systems
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• v.21 no.3
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• pp.383-388
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• 2011

This paper presents to study the accuracy improvement of the laser navigation using FIS(fuzzy inference system) and the reliability. As wireless guidance system, the top-mounted laser with the laser navigation can rotate $360^{\circ}$ with phototransistor or other optical sensors that read the return signal from reflectors mounted at the perimeter of the workspace. The type of major existing guidance systems is a wire guidance system. Because they have high accuracy and fast response time, they are used to most industries. However, their installation cost is very expensive and maintenance is very difficult because their sensors are placed approximately 1 inch below the ground or embedded in the floor. To solve those problems, the laser navigation was developed as a wire guidance system. It does not need to reconstruct a floor or ground. And it can reduce costs of installation and maintenance because changing the layout is easy. However, it is difficult to apply to an industrial field because it is easily affected by disturbances which cause loss and damage of data, and has slow respond time. Therefore, we study the accuracy improvement of the laser navigation. The proposed method is a correction method using reliability of the laser navigation. here, reliability is calculated by FIS which is designed with the analyzed characteristics of the laser navigation. For performance comparison, we use original position data form the laser navigation and position data corrected by original reliability from the laser navigation. In experimental result, we verified that the performance of the proposed method compared the others is improved by about 50% or more.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.21 no.5
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• pp.103-111
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• 2021

The purpose of this study is to study a method for preventing collisions of multiple drones in controlled airspace. As a result of the study, it was proved that it is appropriate as a method to control drone collisions after setting accurate information on the ROI (Region of Interest) area estimated based on the expected drone path and time in the control system as a method to avoid drone collision. As a result of the empirical analysis, the diameter of the flight path of the operating drone should be selected to reduce the risk of collision, and the change in the departure time and operating speed of the operating drone did not act as an influencing factor in the collision. In addition, it has been demonstrated that providing flight priority is one of the appropriate methods as a countermeasure to avoid collisions. For collision avoidance methods, not only drone sensor-based collision avoidance, but also collision avoidance can be doubled by monitoring and predicting collisions in the control system and performing real-time control. This study is meaningful in that it provided an idea for a method for preventing collisions of multiple drones in controlled airspace and conducted practical tests. This helps to solve the problem of collisions that occur when multiple drones of different types are operating based on the control system. This study will contribute to the development of related industries by preventing accidents caused by drone collisions and providing a safe drone operation environment.

• Journal of Korean Tunnelling and Underground Space Association
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• v.23 no.4
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• pp.253-263
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• 2021

Concrete structures are damaged by aging and external environmental factors. This type of damage is to appear in the form of cracks, to proceed in the form of spalling. Such concrete damage can act as the main cause of reducing the original design bearing capacity of the structure, and negatively affect the stability of the structure. If such damage continues, it may lead to a safety accident in the future, thus proper repair and reinforcement are required. To this end, an accurate and objective condition inspection of the structure must be performed, and for this inspection, a sensor technology capable of detecting damage area is required. For this reason, we propose a deep learning-based image processing algorithm that can detect spalling. To develop this, 298 spalling images were obtained, of which 253 images were used for training, and the remaining 45 images were used for testing. In addition, an improved loss function and data augmentation technique were applied to improve the detection performance. As a result, the detection performance of concrete spalling showed a mean intersection over union of 80.19%. In conclusion, we developed an algorithm to detect concrete spalling through a deep learning-based image processing technique, with an improved loss function and data augmentation technique. This technology is expected to be utilized for accurate inspection and diagnosis of structures in the future.

• 재활복지
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• v.21 no.3
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• pp.129-146
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• 2017

In an event of an emergency, such as fire in a building, visually impaired and blind people are prone to exposed to a level of danger that is greater than that of normal people, for they cannot be aware of it quickly. Current fire detection methods such as smoke detector is very slow and unreliable because it usually uses chemical sensor based technology to detect fire particles. But by using vision sensor instead, fire can be proven to be detected much faster as we show in our experiments. Previous studies have applied various image processing and machine learning techniques to detect fire, but they usually don't work very well because these techniques require hand-crafted features that do not generalize well to various scenarios. But with the help of recent advancement in the field of deep learning, this research can be conducted to help solve this problem by using deep learning-based object detector that can detect fire using images from security camera. Deep learning based approach can learn features automatically so they can usually generalize well to various scenes. In order to ensure maximum capacity, we applied the latest technologies in the field of computer vision such as YOLO detector in order to solve this task. Considering the trade-off between recall vs. complexity, we introduced two convolutional neural networks with slightly different model's complexity to detect fire at different recall rate. Both models can detect fire at 99% average precision, but one model has 76% recall at 30 FPS while another has 61% recall at 50 FPS. We also compare our model memory consumption with each other and show our models robustness by testing on various real-world scenarios.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2016.10a
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• pp.224-226
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• 2016

With the technical development and rapid increase of private demand, the new market for unmanned vehicle combined with the characteristics of 'unmanned automation' and 'vehicle' is rapidly growing. Even though the pilot driving is currently allowed in some countries, there is no country that has institutionalized the formal driving of self-driving cars. In case of the existing vehicles, safety incidents are frequently happening due to the frequent malfunction of the rear sensor, blind spot of the rear camera, or drivers' carelessness. Once such minor flaws are complemented, the relevant regulations for the commercialization of self-driving car and small drone could be relieved. Contrary to the ultrasonic and laser sensors used for the existing vehicles, this paper aims to attempt the distance measurement by using the depth sensor. A depth camera calculates the distance data based on the TOF method calculating the time difference by lighting laser or infrared light onto an object or area and then receiving the beam coming back. As this camera can obtain the depth data in the pixel unit of CCD camera, it can be used for collecting depth data in real-time. This paper suggests to solve problems mentioned above by using depth data in real-time and also to design the obstacle avoidance system through distance measurement.

• Journal of the Korean Society of Radiology
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• v.13 no.3
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• pp.333-338
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• 2019

In the field of radiotherapy, the Quality Assurance(QA) procedure to verify the safety of treatment is considered to be very important. However, due to various problems of the conventional dosimeters used for the QA, researches on these dosimeters have been actively carried out to replace them. In this study, to maximize the sensitivity by visible light(VL) emitted from phosphors, blended hybrid sensors were fabricated by blending various weight percent(wt%) of $Gd_2O_2S:Tb$ which is a phosphor with excellent fluorescence efficiency into $PbI_2$. Then, the electrical properties to high energy radiation from the blended sensors and the pure $PbI_2$ sensor were compared and evaluated. As a result of the sensitivity evaluation, the sensor of 3wt% showed the highest value with more than 40% difference from the other sensors, and gradual decreasing in sensitivity was observed with increasing wt% except for the sensor of 3wt%. Also, in the reproducibility evaluation, the pure $PbI_2$ sensor exhibited a large variation in coefficient of variation(CV)>0.015, while all the blended sensors showed CV<0.015.