• Journal of Korean Tunnelling and Underground Space Association
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• v.25 no.3
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• pp.221-243
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• 2023

The use of roadheaders has been increasing to mitigate the problems of noise and vibration during tunneling operations in urban area. Since lack of experience of roadheader for hard rock, the selection of appropriate machines and the evaluation of cutting rates have been challenging. Currently, empirical models developed overseas are commonly used to evaluate cutting rates, but their effectiveness has not been verified for domestic rocks. In this paper, a comprehensive literature review was conducted to assess the rock cutting force, cutterhead capacity, and cutting rate to select the appropriate machine and evaluate its performance. The cutterhead capacity was reviewed based on the literature results for the site. Furthermore, a new empirical model and simplified method for predicting cutting rates were proposed through data analysis in relation to operation time and rock strength, and compared with those of the conventional model from the manufacturer. The results show good agreement for high strength range upper 80 MPa of uniaxial compressive strength.

• Journal of the Semiconductor & Display Technology
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• v.21 no.4
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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.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.11
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• pp.1586-1591
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• 2022

Kirchhoff-Love plate (KLP) equation is a well established theory for a description of a deformation of a thin plate under certain outer source. Meanwhile, analysis of a vibrating plate in a frequency domain is important in terms of obtaining the main frequency/eigenfunctions and predicting the vibration of plate. Among various modal analysis methods, dynamic mode decomposition (DMD) is one of the efficient data-driven methods. In this work, we carry out DMD based modal analysis for KLP where thin plate is under effects of sine-type outer force. We first construct discrete time series of KLP solutions based on a finite difference method (FDM). Over 720,000 number of FDM-generated solutions, we select only 500 number of solutions for the DMD implementation. We report the resulting DMD-modes for KLP. Also, we show how DMD can be used to predict KLP solutions in an efficient way.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.28 no.1A
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• pp.135-146
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• 2008

In this paper, a hybrid damage monitoring scheme for prestressed concrete (PSC) girder bridges by using sequential acceleration and impedance signatures is newly proposed. Damage types of interest include prestress-loss in tendon and flexural stiffness-loss in a concrete girder. The hybrid scheme mainly consists of three sequential phases: damage alarming, damage classification, and damage estimation. In the first phase, the global occurrence of damage is alarmed by monitoring changes in acceleration features. In the second phase, the type of damage is classified into either prestress-loss or flexural stiffness-loss by recognizing patterns of impedance features. In the third phase, the location and the extent of damage are estimated by using two different ways: a mode shape-based damage detection to detect flexural stiffness-loss and a natural frequency-based prestress prediction to identify prestress-loss. The feasibility of the proposed scheme is evaluated on a laboratory-scaled PSC girder model for which hybrid vibration-impedance signatures were measured for several damage scenarios of prestress-loss and flexural stiffness-loss.

• Journal of Korean Society of Steel Construction
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• v.16 no.2 s.69
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• pp.285-293
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• 2004

As a special infrastructure, it is important that the suspension bridges which were designed by using the cable are carefully maintained and safely inspected after their construction, more than what is done in other cases of bridge structures. However, the structural analysis for their design and maintenance has considered only the simplified geometric shape of the structure. Particularly, it is not easy to make the modeling analyze the bridge structure including detailed steel deck plates. In this paper, we evaluated the structural behaviors and performances of the completed earth-anchored suspension bridge that was in a completed state through both the tension of hanger member and their computational analysis. We considered the frame system and the detailed steel deck plates that were especially added into the modeling to take more precision analysis about it. We also applied hanger tensions converted by the natural frequency and the natural frequency of the bridge when in normal vibration. Results of the vehicle loading test were used in the analysis. We compared the results by using our modeling with the result of the loading test and the hanger tension. Our prediction on the behavior of the structure emulates the behavior of the real structure. In applying the data measured by the typhoon "Maemi" which arrived in-land last year, we confirmed our analysis model for the possibility of applying effectively into the preliminary design and maintenance plan.

• Journal of Korean Tunnelling and Underground Space Association
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• v.16 no.2
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• pp.249-260
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• 2014

When a train enters the tunnel at high speed, the pressure wave occurs. When this pressure wave reaches at the exit of tunnel, some are either emitted to the outside or reflected in tunnel by the form of expansion wave. The wave emitted to the outside forms the impulsive pressure wave. This wave is called 'Micro Pressure Wave'. The micro pressure wave generates noise and vibration around a exit portal of tunnel. When it becomes worse, it causes anxiety for residents and damage to windows. Thus, it requires a counterplan and prediction about the micro pressure wave for high speed railway construction. In this paper, the effects of train head nose and tunnel portal shape were investigated by model test, measurement for the micro pressure wave at the operating tunnel as well as numerical analysis for the gradient of pressure wave in the tunnel. As results, a method for predicting the intensity of the micro pressure wave is suggested and then the intensity of the micro pressure wave is analyzed by the tunnel length and the cross-sectional area.

• Journal of the Korean Wood Science and Technology
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• v.39 no.6
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• pp.538-547
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• 2011

In this study, eco-friendly hybrid composite boards were manufactured from green tea and wood fibers for application as interior materials with various functionalities of green tea and strong strength properties of wood fibers. In this relation, the effect of green tea content on dynamic MOEs (modulus of elasticity) of these green tea and wood fibers composite boards were investigated. The dynamic MOEs of hybrid composite boards were lower than those of control boards without green tea, and the values decreased with the increase of green tea content. Also, the dynamic MOEs appeared to be somewhat different by resin type used for board manufacture. The hybrid composite boards manufactured from $E_1$ grade urea resin, which has higher molar ratio of formaldehyde to urea than that of $E_0$ grade one, were 1.06~1.54 times higher than that manufactured from $E_0$ grade. And, the differences between hybrid composite boards manufactured from both adhesive increased with the increase of green tea content. On the other hand, high correlations were found between dynamic MOE and static bending strength performances, it was concluded that static bending strength performances could be estimated from the dynamic MOE, except for a few hybrid board types with large variations.

• Journal of the Korean Geotechnical Society
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• v.34 no.7
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• pp.39-49
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• 2018

Jacked pile that involves the use of hydraulic jacks to press the piles into the ground is free from noise and vibration, and is possibly installed within a limited construction area. Thus, as an alternative to conventional pile driving methods, pile jacking could become widely accepted for the construction projects in urban area (e.g., reconstruction or remodeling construction projects). Great concern has arisen over the prediction of axially loaded jacked pile behavior. Against this background, a series of pile load tests were hence conducted on a jacked steel pipe pile installed in weathered zone (i.e., weathered soil and weathered rock). From the test results, base resistance and shaft resistance for each test condition were evaluated and compared with the values predicted by the previous driven pile resistance assessment method. Test results showed that the previous driven pile resistance assessment method highly underestimated both the base and shaft resistances of a jacked pile; differences were more obviously observed with the shaft resistance. The reason for this discrepancy is that a driven pile normally experiences a larger number of loading/unloading cycles during installation, and therefore shows significantly degraded stiffness of surrounding soil. Based on the results of the pile load tests, particular attention was given to the modification of the previous driven pile resistance assessment method for investigating the axially loaded jacked pile behavior.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.40 no.12
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• pp.1005-1011
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• 2016

The fundamental reason for gear noise is transmission error. Transmission error occurs because of STE (static transmission error) and DTE (dynamic transmission error), while a pair of gears is meshing. These errors are generated by the deflection of the teeth and the friction on the surface of the teeth. In addition, the vibration generated by transmission error leads to excited bearings. The bearings support the shafts, and the noise is radiated after exciting the gear casing. The analysis of the contact stress in helical gear tooth flanks indicates that it is due to impact loading, such as the sudden engagement and disengagement of a gear. Stress analysis is performed for different roll positions, in order to determine the most critical roll angle. Dynamic analysis is performed on this critical roll position, in order to evaluate variation in stresses and tooth contact force, with respect to time. In this study, transmission error analysis was implemented on a spur and helical gear with involute geometry and a modified geometry profile. In addition, in order to evaluate the intensity of impact due to sudden engagement and significant backlash, the impact factor was calculated using the finite element analysis results of static and dynamic maximum bending stresses.

• Journal of Advanced Navigation Technology
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• v.23 no.1
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• pp.84-89
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• 2019

This is a pilot study of machine learning based structural health monitoring system using flight data of composite aircraft. In this study, the most suitable machine learning algorithm for structural health monitoring was selected and dimensionality reduction method for application on the actual flight data was conducted. For these tasks, impact test on the cantilever beam with added mass, which is the simulation of damage in the aircraft wing structure was conducted and classification model for damage states (damage location and level) was trained. Through vibration test of cantilever beam with fiber bragg grating (FBG) sensor, data of normal and 12 damaged states were acquired, and the most suitable algorithm was selected through comparison between algorithms like tree, discriminant, support vector machine (SVM), kNN, ensemble. Besides, through neighborhood component analysis (NCA) feature selection, dimensionality reduction which is necessary to deal with high dimensional flight data was conducted. As a result, quadratic SVMs performed best with 98.7% for without NCA and 95.9% for with NCA. It is also shown that the application of NCA improved prediction speed, training time, and model memory.