• 한국기계가공학회지
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• 제18권6호
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• pp.98-105
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• 2019

In order to improve the fuel economy and dynamic behavior of automobiles, the weight reduction tendency of automobile parts is obvious. Also, in order to maximize assembly and maintenance convenience, various parts are integrated and modularized. Multi-piece methods require many manufacturing processes and become a factor of lowering the strength of parts. It is advantageous to overcome the disadvantages by integrally manufacturing to reduce the processing steps and ensure the strength of the parts. However, when it is necessary to process in a narrow space inside the part, it is impossible to process with the existing spindle. The angle head spindle is only a component of a machine tool, but it is a core part that requires high technology and is highly utilizable in products requiring high precision machining. Therefore, various and continuous studies needs for angle head spindles in areas such as vibration absorption, operational safety, excellent dimensional stability, and strength. In this paper, we propose an optimal design for angle head spindle by performing structural analysis and shape optimization for angle head spindle gear and case.

• 한국공간구조학회논문집
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• 제19권1호
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• pp.117-126
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• 2019

Micro-Electro-Mechanical Systems (MEMS) sensors have been widely used in Structural Health Monitoring due to their convenience and lower costs in comparison to conventional sensors. Triggered measurements are relevant in events such as earthquakes because unlike continuous measurements, they only record the structural response once an event happens. This is more cost effective and it makes the data more manageable because only the required measurements from the event are recorded. The most common method of triggering is amplitude triggering. However, lower input amplitudes (less than 0.1g) cannot be triggered by using this method. In this paper, sound triggering was introduced to allow triggered measurements for lower input amplitude values. The performance of the sound triggering and amplitude triggering were compared by a series of shaking-table tests. It was seen that sound-triggering method has a wider frequency (0.5~10Hz) and amplitude (0.01~1.0g) range of measurements. In addition, the sound triggering method performs better than the amplitude triggering method at lower amplitudes. The performance of the amplitude triggering, in terms of the triggering being simultaneous improves at higher input amplitudes.

• Tribology and Lubricants
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• 제37권2호
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• pp.71-76
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• 2021

As opposed to using fossil fuels, we need to use eco-friendly resources such as sunlight, raindrops and wind to produce electricity and combat environmental pollution. A triboelectric nanogenerator (TENG) is a device that converts mechanical energy into electricity by inducing repetitive contact and separation of two dissimilar materials. During the contact and separation processes, electron flow occurs owing to a change in electric potential of the contacting surface caused by contact electrification and electrostatic induction mechanisms. A solid-solid contact TENG is widely known, but it is possible to generate electricity via liquid-solid contact. Therefore, by designing a hydrophobic TENG, we can gather electricity from raindrop energy in a feasible manner. To fabricate the superhydrophobic surface of TENGs, we employ a dip coating technique to synthesize an octadecylamine (ODA)- and polydimethylsiloxane (PDMS)-based coating on polyethylene terephthalate (PET). The synthesized coating exhibits superhydrophobicity with a contact angle greater than 150° and generates a current of 2.2 ㎂/L while water droplets fall onto it continuously. Hence, we prepare a box-type TENG, with the ODA/PDMS coating deposited on the inside, and place a 1.5 mL water droplet into it. Resultantly, we confirm that the induced vibration causes continuous impacts between the ODA/PDMS coating and the water, generating approximately 100 pA for each impact.

• 자동차안전학회지
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• 제13권2호
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• pp.35-41
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• 2021

In this study, improved path tracking control algorithm based on pure pursuit algorithm is newly proposed by using improved lane detection algorithm through real time post-processing with interpolation methodology. Since the original pure pursuit works well only at speeds below 20 km/h, the look-ahead distance is implemented as a sigmoid function to work well at an average speed of 45 km/h to improve tracking performance. In addition, a smoothing filter was added to reduce the steering angle vibration of the original algorithm, and the stability of the steering angle was improved. The post-processing algorithm presented has implemented more robust lane recognition system using real-time pre/post processing method with deep learning and estimated interpolation. Real time processing is more cost-effective than the method using lots of computing resources and building abundant datasets for improving the performance of deep learning networks. Therefore, this paper also presents improved lane detection performance by using the final results with naive computer vision codes and pre/post processing. Firstly, the pre-processing was newly designed for real-time processing and robust recognition performance of augmentation. Secondly, the post-processing was designed to detect lanes by receiving the segmentation results based on the estimated interpolation in consideration of the properties of the continuous lanes. Consequently, experimental results by utilizing driving guidance line information from processing parts show that the improved lane detection algorithm is effective to minimize the lateral offset error in the diverse maneuvering roads.

• 대한조선학회논문집
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• 제59권1호
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• pp.39-45
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• 2022

Normal strategy of structure optimization procedure has been minimum cost or weight design. Minimum weight design satisfying an allowable stress has been used for the ship and offshore structure, but minimum cost design could be used for the case of high human cost. Natural frequency analysis and forced vibration one have been used for the strength estimation of marine structures. For the case of high precision experiment facilities in marine field, the structure has normally enough margin in allowable stress aspect and sometimes needs high natural frequency of structure to obtain very high precise experiment results. It is not easy to obtain a structure design with high natural frequency, since the natural frequency depend on the stiffness to mass ratio of the structure and increase of structural stiffness ordinary accompanies the increase of mass. It is further difficult at the grillage structure design using the profiles, because the properties of profiles are not continuous but discrete, and resource of profiles are limited at the design of grillage structure. In this paper, the grillage structure design system under the constraint of high natural frequency is introduced. The design system adopted genetic algorithm to realize optimization procedure and can be used at the design of the experimental facilities of marine field such as a towing carriage, PMM, test frame, measuring frame and rotating arm.

• 터널과지하공간
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• 제32권6호
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• pp.345-352
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• 2022

도심지 터널 건설에서 발파공법은 민원이 제기되는 문제점이 있어 적용에 제약받고 있다. 이에 대한 대안으로 TBM 및 기계굴착 공법 적용이 필수적으로 검토되고 있다. 이 중 쉴드 TBM(Tunnel Boring Machine)은 굴진과 세그먼트 체결이 번갈아 반복되며 굴진하는 공정을 가지고 있는데, 세그먼트 체결 동안 굴진을 멈추게 된다. 이러한 가동 정지시간을 최소화하고자 세그먼트 체결 중에도 가동할 수 있는 연속굴착형 TBM 기술이 개발되고 있다. 나선형 세그먼트의 굴진 반력을 확보하기 위해 추진잭을 개조하고 신뢰성을 확보하는 연구가 진행 중이다. 또한 체결 중 세그먼트를 제외한 나머지 부분의 추진잭을 가동하는 유압제어 및 유압시스템 설계기술이 개발될 예정이다. 본 보고는 연속굴착형 TBM 과제 중 부품개조 및 유압제어 기술에 대한 일부 내용을 소개한다.

• 반도체디스플레이기술학회지
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• 제21권4호
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• pp.65-70
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• 2022

In manufacturing and semiconductor industries, transfer robots increase productivity through accurate and continuous work. Due to the nature of the semiconductor process, there are environments where humans cannot intervene to maintain internal temperature and humidity in a clean room. So, transport robots take responsibility over humans. In such an environment where the manpower of the process is cutting down, the lack of maintenance and management technology of the machine may adversely affect the production, and that's why it is necessary to develop a technology for the machine failure diagnosis system. Therefore, this paper tries to identify various causes of failure of transport robots that are widely used in semiconductor automation, and the Prognostics and Health Management (PHM) method is considered for determining and predicting the process of failures. The robot mainly fails in the driving unit due to long-term repetitive motion, and the core components of the driving unit are motors and gear reducer. A simulation drive unit was manufactured and tested around this component and then applied to 6-axis vertical multi-joint robots used in actual industrial sites. Vibration data was collected for each cause of failure of the robot, and then the collected data was processed through signal processing and frequency analysis. The processed data can determine the fault of the robot by utilizing machine learning algorithms such as SVM (Support Vector Machine) and KNN (K-Nearest Neighbor). As a result, the PHM environment was built based on machine learning algorithms using SVM and KNN, confirming that failure prediction was partially possible.

• 반도체디스플레이기술학회지
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• 제22권4호
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• pp.113-118
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• 2023

Maintenance of semiconductor equipment processes is crucial for the continuous growth of the semiconductor market. The process must always be upheld in optimal condition to ensure a smooth supply of numerous parts. Additionally, it is imperative to monitor the status of the robots that play a central role in the process. Just as many senses of organs judge a person's body condition, robots also have numerous sensors that play a role, and like human joints, they can detect the condition first in the joints, which are the driving parts of the robot. Therefore, a normal state test bed and an abnormal state test bed using an aging reducer were constructed by simulating the joint, which is the driving part of the robot. Various sensors such as vibration, torque, encoder, and temperature were attached to accurately diagnose the robot's failure, and the test bed was built with an integrated system to collect and control data simultaneously in real-time. After configuring the user screen and building a database based on the collected data, the characteristic values of normal and abnormal data were analyzed, and machine learning was performed using the KNN (K-Nearest Neighbors) machine learning algorithm. This approach yielded an impressive 94% accuracy in failure diagnosis, underscoring the reliability of both the test bed and the data it produced.

• Tribology and Lubricants
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• 제40권2호
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• pp.39-46
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• 2024

The Morton effect (ME) is an instability phenomenon occurring in rotating machineries supported by fluid film bearings and is induced by the thermal deformation of the overhung mass, which is a part of the rotating shaft. Herein, we describe the ME during the high-speed balancing test of a 20 MW class steam turbine. Additionally, to predict the rotating speed at which the ME occurs, we apply the sensitivity vector theory for the steam turbine. During the operation of the steam turbine, we observe a continuous increase in vibration and hysteresis near the rated speed, which is typical of the ME. Increasing the temperature of the lubricating oil supplied to the bearings from 40 to 60℃ suppresses the occurrence of the ME. The rotordynamic analysis for the steam turbine suggests the existence of a mode in which the overhung mass undergoes significant deformation near the rated speed, and we presume that such a mode will increase the occurrence of the ME. The predicted rotating speed of ME occurrence, obtained through the sensitivity vector method, correlates with the test results. Moreover, increasing the temperature of the supplied lubricating oil mitigates the occurrence of ME by reducing the sensitivity between the temperature deviation vector and unbalance mass vector.

• 해양환경안전학회지
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• 제30권3호
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• pp.283-290
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• 2024

In this study, a survey on the coexistence of offshore wind farm and fishing activities in Gochang, Gunsan, and Buan's fishermen in the southwest sea of shore wind farm was carried out witn an aim of examining the factors that should be considered when coexisting. A questionnaire was composed after referring to domestic and foreign literature data on examples of coexistence. The questionnaire was issued through direct visits. Frequency analysis and cross-analysis were used for survey response results, and IBM SPSS Statistics ver. 26 was used for statistical processing. As a result of analyzing a total of 84 questionnaires, the perception of the coexistence of offshore wind and fishing activities was the same by 50.0% positive and negative, respectively. As a result of cross-analysis by region, significant differences were found (p <0.039). Gochang fishermen showed a high negative perception of the coexistence of offshore wind and fishing activities at 62.1%, with the main reason being that fishing resources are expected to decrease due to the influence of noise, vibration, and current generated from offshore wind farm facilities. In Gunsan, negative perception of coexistence was high at 57.7%. This was mainly attributed to the impossibility to operate in the offshore wind farm due to the nature of the fishery. On the contrary, in the case of Buan, 69.0% of the positive perception of coexistence was high 'because fishermen were dissatisfied with the current coexistence plan (policy)'. According to previous studies, 91.8% of domestic fishing methods show the possibility of fishing activities in offshore wind under caution, so it is concluded that research should be conducted to coexist with offshore wind and fishing activities as in foreign countries for smooth installation of offshore wind and continuous fishing activities.