• Journal of Korean Society of Industrial and Systems Engineering
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• v.46 no.2
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• pp.168-175
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• 2023

In the era of the 4th Industrial Revolution, Logistic 4.0 using data-based technologies such as IoT, Bigdata, and AI is a keystone to logistics intelligence. In particular, the AI technology such as prognostics and health management for the maintenance of logistics facilities is being in the spotlight. In order to ensure the reliability of the facilities, Time-Based Maintenance (TBM) can be performed in every certain period of time, but this causes excessive maintenance costs and has limitations in preventing sudden failures and accidents. On the other hand, the predictive maintenance using AI fault diagnosis model can do not only overcome the limitation of TBM by automatically detecting abnormalities in logistics facilities, but also offer more advantages by predicting future failures and allowing proactive measures to ensure stable and reliable system management. In order to train and predict with AI machine learning model, data needs to be collected, processed, and analyzed. In this study, we have develop a system that utilizes an AI detection model that can detect abnormalities of logistics rotational equipment and diagnose their fault types. In the discussion, we will explain the entire experimental processes : experimental design, data collection procedure, signal processing methods, feature analysis methods, and the model development.

• Earthquakes and Structures
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• v.24 no.2
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• pp.127-140
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• 2023

The vibration of microtubule in human cells is the source of electrical field around it and inside cell structure. The induction of electrical field is a direct result of the existence of dipoles on the surface of the microtubules. Measuring the electrical fields could be performed using nano-scale sensors and the data could be transformed to other computers using internet of things (IoT) technology. Processing these data is feasible by artificial intelligence-based methods. However, the first step in analyzing the vibrational behavior is to study the mechanics of microtubules. In this regard, the vibrational behavior of the microtubules is investigated in the present study. A shell model is utilized to represent the microtubules' structure. The displacement field is assumed to obey first order shear deformation theory and classical theory of elasticity for anisotropic homogenous materials is utilized. The governing equations obtained by Hamilton's principle are further solved using analytical method engaging Navier's solution procedure. The results of the analytical solution are used to train, validate and test of the deep neural network. The results of the present study are validated by comparing to other results in the literature. The results indicate that several geometrical and material factors affect the vibrational behavior of microtubules.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.18 no.3
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• pp.562-568
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• 2017

A precast floating slab track with a 5m slab panel and installed with isolators is proposed to solve the noise and vibration problem at existing elevated railway stations. Thus, the construction can be carried out rapidly without interrupting the train operation. However, dynamic instability problems may be caused by repeated discontinuities in track due to the short slab panel length and excessive rail displacement due to the inherent operation mechanism of a floating system in reducing the vibration. Furthermore, the difference of the supporting stiffness at the transition between the floating track and ballast track may raise problems. In this study, the assessment factors to evaluate the dynamic stability of the precast floating slab track are presented and assessed with the vehicle-track interaction analysis. Through the analysis, all values relevant to the stability at the floating track section are found to be acceptable, and the slab panels at the transition section are designed to satisfy the stability.

• Structural Monitoring and Maintenance
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• v.2 no.1
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• pp.77-93
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• 2015

The idea of using measured dynamic characteristics for damage detection is attractive because it allows for a global evaluation of the structural health and condition. However, vibration-based damage detection for complex structures such as long-span cable-supported bridges still remains a challenge. As a suspension or cable-stayed bridge involves in general thousands of structural components, the conventional damage detection methods based on model updating and/or parameter identification might result in ill-conditioning and non-uniqueness in the solution of inverse problems. Alternatively, methods that utilize, to the utmost extent, information from forward problems and avoid direct solution to inverse problems would be more suitable for vibration-based damage detection of long-span cable-supported bridges. The auto-associative neural network (ANN) technique and the probabilistic neural network (PNN) technique, that both eschew inverse problems, have been proposed for identifying and locating damage in suspension and cable-stayed bridges. Without the help of a structural model, ANNs with appropriate configuration can be trained using only the measured modal frequencies from healthy structure under varying environmental conditions, and a new set of modal frequency data acquired from an unknown state of the structure is then fed into the trained ANNs for damage presence identification. With the help of a structural model, PNNs can be configured using the relative changes of modal frequencies before and after damage by assuming damage at different locations, and then the measured modal frequencies from the structure can be presented to locate the damage. However, such formulated ANNs and PNNs may still be incompetent to identify damage occurring at the deck members of a cable-supported bridge because of very low modal sensitivity to the damage. The present study endeavors to enhance the damage identification capability of ANNs and PNNs when being applied for identification of damage incurred at deck members. Effort is first made to construct combined modal parameters which are synthesized from measured modal frequencies and modal shape components to train ANNs for damage alarming. With the purpose of improving identification accuracy, effort is then made to configure PNNs for damage localization by adapting the smoothing parameter in the Bayesian classifier to different values for different pattern classes. The performance of the ANNs with their input being modal frequencies and the combined modal parameters respectively and the PNNs with constant and adaptive smoothing parameters respectively is evaluated through simulation studies of identifying damage inflicted on different deck members of the double-deck suspension Tsing Ma Bridge.

• Journal of the Korean Society for Railway
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• v.18 no.3
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• pp.175-185
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• 2015

Generally, in the train area, switch tracks have required high reliability because this system is directly associated with derailment. Especially, switch tracks of Maglev vehicles must be moved in terms of the whole geometric characteristics, in which the bogies are encased in the switch track. For this reason, switch track was constructed with steel lighter than concrete girders. But, the steel switch track was weak because of structural vibration as well as structural deformation. Therefore, it is important to predict the levitation stability when a vehicle passes over flexible switch track. The aims of this paper are to develop a coupled dynamic model to describe the relationship between a Maglev vehicle and switch track and to predict the levitation stability. In order to develop the coupled dynamic model, a three dimensional vehicle model was developed based on multibody dynamics; a switch model was made using the modal superposition method. And, the developed model was verified using comparison measured data.

• Journal of Korean Tunnelling and Underground Space Association
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• v.25 no.4
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• pp.305-330
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• 2023

Unlike NATM tunnels, Shield TBM tunnels have split linings. Therefore, the stress distribution of the lining is different even if the lining is under the same load. Representative methods for analyzing the stress generated in lining in Shield TBM tunnels include Non-joint Mode that does not consider connections and a 2-ring beam-spring model that considers ring-to-ring joints and segment connections. This study is an analysis method by Break-joint Mode. However, we do not consider the structural role of segment lining connections. The effectiveness of the modeling is verified by analyzing behavioral characteristics against vibration loads by modeling with segment connection interfaces to which vertical stiffness and shear stiffness, which are friction components, are applied. Unlike the Non-joint mode, where the greatest stress occurs on the crown for static loads such as earth pressure, the stress distribution caused by contact between segment lining and friction stiffness produced the smallest stress in the crown key segment where segment connections were concentrated. The stress distribution was clearly distinguished based on segment connections. The results of static analysis by earth pressure, etc., produced up to seven times the stress generated in Non-joint mode compared to the stress generated by Break-joint Mode. This result is consistent with the stress distribution pattern of the 2-ring beam-spring model. However, as for the stress value for the train vibration load, the stress of Break-joint Mode was greater than that of Non-joint mode. This is a different result from the static mechanics concept that a segment ring consisting of a combination of short members is integrated in the circumferential direction, resulting in a smaller stress than Non-joint mode with a relatively longer member length.

• Proceedings of the KSR Conference
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• 2010.06a
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• pp.880-894
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• 2010

The Grout injected precast pile is widely used in rapid-transit railway bridge recently. The existing portland cement of well used filling at injected precast method that with low strength and environmental pollution, unstable in which ground water contamination by cement flow out, ground relaxation by water down, decrease of horizontality resistance and durability and load transfer divide etc. In particular, as in rapid-transit railway bridge need to secure safety from different angle with vibration of high speed train, horizontal force when train stop and earthquake. Works of foundation construction consider to requirements of the times to coal yard green growth. Together, new green foundation method for possible economics and securing of reduce the term of works are material to developments. Therefore, we carried out study that it is using and development new concept environment - friendly filling include durability and earthquake resistance, for secure safety and minimize environment pollution. To achieve this, we carried out difference tests that new green fillings of underwater concrete, high liquidity, high viscosity, early stiffness as compared to existing portland cement fillings. As results, new green filling have outstanding application at precast pile method and micropile construction method with vertical bearing capacity, horizontal bearing capacity and many case. From now on we will be looking forward to development of new environment-friendly foundation method from various further studies.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.12
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• pp.237-246
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• 2019

The Electro-Mechanical Brake (EMB) is the next generation braking system for automobiles and railway vehicles. Current brake systems for high-speed trains generate a braking force using a pneumatic cylinder, but EMB systems produce that force through a combination of an electric motor and a gear. In this study, an EMB operation mechanism capable of generating a high braking force was proposed, and structural and vibration analyses of the gears and shafts, which are the core parts of the mechanisms, were performed. Dynamic structural analysis confirmed that the maximum stress in the analysis model was within the yield strength of the material. In addition, the design that maximizes the diameter of the motor shaft was found to be advantageous in strength, and large shear stress could be generated in the bolt fixing the gear and eccentric shaft. In addition, a test apparatus that can reproduce the mechanism of the analytical model was fabricated to measure the strain of the fixed bolt part, which is the most vulnerable part. The strain measurement results showed that the error between the analysis and measurement was within 10%, which could verify the accuracy of the analytical model.

• Journal of the Korea institute for structural maintenance and inspection
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• v.16 no.3
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• pp.31-40
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• 2012

The irregularity of railway track affects not only the comfort of ride such as noise or vibration but also the safety of train operation. For this reason, it is an interesting research area to design a reliable and sustainable railway track system and to analyze the train movement mechanism based on systematic approaches considering reasons of track irregularity possible in a specific local environment. Irregularity data inspected by EM-120, an railway inspection system in Korea includes unavoidable incomplete and erratic information, so it is encountered lots of problem to analyse those data without appropriate pre-data-refining processes. In this research, for the efficient management and maintenance of railway system, progress rate of standard deviation of irregularity is quantified. During the computation, some important components of railways such as rail joint, ballast, roadbed, and fastener have been considered. Probabilistic distributions of irregularity growth with respect to time are computed to predict the remaining service life of railway track and to be adapted for the safety assessment.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.18 no.2
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• pp.576-582
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• 2017

The switching system in a maglev train is an indispensable element for distributing train routes, and it should be designed to ensure safe operation. Unlike conventional wheels on rails, the switching track in EMS-type maglev is supported by a group of 3 to 4 steel girders. When the vehicle changes its route, the segmented track allows the girders to change from a straight position to a curved one with a small radius of curvature. Hence, the structural characteristics of the segmented switching system may affect the levitation stability of the maglev vehicle. This study experimentally evaluates the dynamic interaction between maglev vehicles and a segmented switching system. The results may be helpful for improving the switching system. The measured levitation and lateral air gaps were evaluated at a vehicle speed of 25 km/h, and the ride quality of the Maglev vehicle was determined to be "comfortable" according to the UIC 513 standard.