• Smart Structures and Systems
• /
• v.30 no.1
• /
• pp.35-47
• /
• 2022

Data-driven engineering is crucial for information delivery between design, fabrication, assembly, and maintenance of prefabricated structures. Design for manufacturing and assembly (DfMA) is a critical methodology for prefabricated bridge structures. In this study, a novel concept of digital engineering model that combined existing knowledge of DfMA with object-oriented parametric modeling technologies was developed. Three-dimensional (3D) geometry models and their data models for each phase of a construction project were defined for information delivery. Digital design models were used for conceptual design, including aesthetic consideration and possible variation during fabrication and assembly. The seismic performance of a bridge pier was evaluated by linking the design parameters to the calculated moment-curvature curves. Control parameters were selected to consider the tolerance control and revision of the digital models. Digitalized fabrication of the prefabricated members was realized using the digital fabrication model with G-code for a concrete printer or a robot. The fabrication error was evaluated and the design digital models were updated. The revised fabrication models were used in the preassembly simulation to guarantee constructability. For the maintenance of the bridge, the as-built information was defined for the prefabricated bridge piers. The results of this process revealed that data-driven information delivery is crucial for lifecycle management of prefabricated bridge piers.

• Tribology and Lubricants
• /
• v.37 no.6
• /
• pp.213-223
• /
• 2021

Electrochemical mechanical planarization (ECMP) was developed to overcome the shortcomings of conventional chemical mechanical planarization (CMP). Because ECMP technology utilizes electrochemical reactions, it can have a higher efficiency than CMP even under low pressure conditions. Therefore, there is an advantage in that it is possible to reduce dicing and erosions, which are physical defects in semiconductor CMP. This paper summarizes the papers on ECMP published from 2003 to 2021 and analyzes research trends in ECMP technology. First, the material removal mechanisms and the configuration of the ECMP machine are dealt with, and then ECMP research trends are reviewed. For ECMP research trends, electrolyte, processing variables and pads, tribology, modeling, and application studies are investigated. In the past, research on ECMP was focused on basic research for the development of electrolytes, but it has recently developed into research on tribology and process variables and on new processing systems and applications. However, there is still a need to increase the processing efficiency, and to this end, the development of a hybrid ECMP processing method using another energy source is required. In addition, ECMP systems that can respond to the developing metal 3D printing technology must be researched, and ECMP equipment technology using CNC and robot technology must be developed.

• Journal of the Korean Society of Industry Convergence
• /
• v.27 no.1
• /
• pp.25-37
• /
• 2024

The objective of this study was to create intelligent rail robots that are optimized for facility management and implement digital twin systems for smart road tunnel management. An autonomous surveillance system is formed by combining the sensing platform consisting of railing robots, fixed cameras and environmental detection sensors with the digital twin data platform technology for tunnel monitoring and early fire suppression. In order to develop mobile rail robots for fire extinguishing, we also designed and manufactured robots for extinguishing & monitoring and fire extinguishing devices, and then we examined the optimization of all parts. Our next step was to build a digital twin for road tunnel management by developing continuous image display system and implementing 3D modeling. After constructing prototypes, we attempted simulations by configuring abnormal symptom scenarios, such as vehicles fires. This study's proposal proposes high-accuracy risk prediction services that will enable intelligent management of risks in the tunnel with early response at each stage, using the data collected from the intelligent rail robots and digital twin systems.

• The Journal of the Acoustical Society of Korea
• /
• v.39 no.2
• /
• pp.120-130
• /
• 2020

This paper solves the problem in underdetermined convolutive mixture by improving the disadvantages of the multichannel nonnegative matrix factorization technique widely used in blind source separation. In conventional researches based on Spatial Covariance Matrix (SCM), each element composed of values such as power gain of single channel and correlation tends to degrade the quality of the separated sources due to high variance. In this paper, level and frequency normalization is performed to effectively cluster the estimated sources. Therefore, we propose a novel SCM and an effective distance function for cluster pairs. In this paper, the proposed SCM is used for the initialization of the spatial model and used for hierarchical agglomerative clustering in the bottom-up approach. The proposed algorithm was experimented using the 'Signal Separation Evaluation Campaign 2008 development dataset'. As a result, the improvement in most of the performance indicators was confirmed by utilizing the 'Blind Source Separation Eval toolbox', an objective source separation quality verification tool, and especially the performance superiority of the typical SDR of 1 dB to 3.5 dB was verified.

• KIPS Transactions on Software and Data Engineering
• /
• v.11 no.3
• /
• pp.141-148
• /
• 2022

Recently, reinforcement learning combined with deep neural network technology has achieved remarkable success in various fields such as board games such as Go and chess, computer games such as Atari and StartCraft, and robot object manipulation tasks. However, such deep reinforcement learning describes states, actions, and policies in vector representation. Therefore, the existing deep reinforcement learning has some limitations in generality and interpretability of the learned policy, and it is difficult to effectively incorporate domain knowledge into policy learning. On the other hand, dNL-RRL, a new relational reinforcement learning framework proposed to solve these problems, uses a kind of vector representation for sensor input data and lower-level motion control as in the existing deep reinforcement learning. However, for states, actions, and learned policies, It uses a relational representation with logic predicates and rules. In this paper, we present dNL-RRL-based policy learning for transportation mobile robots in a manufacturing environment. In particular, this study proposes a effective method to utilize the prior domain knowledge of human experts to improve the efficiency of relational reinforcement learning. Through various experiments, we demonstrate the performance improvement of the relational reinforcement learning by using domain knowledge as proposed in this paper.

• Journal of the Korea Society for Simulation
• /
• v.19 no.3
• /
• pp.37-43
• /
• 2010

In field, one can observe without difficulties that two flocks are intersected or combined with each other. For example, a fish flock in a stream separates into two part by obstacles (e.g. stone) and rejoins behind the obstacles. The dynamics of two flocks guided by their leader were studied in the situation where the flocks cross each other with a crossing angle, ${\theta}$, between their moving directions. Each leader is unaffected by its flock members whereas each member is influenced by its leader and other members. To understand the dynamics, I investigated the order parameter, ${\phi}$, defined by the absolute value of the average unit velocity of the flocks' members. When the two flocks were encountered, the first peak in ${\phi}$ was appeared due to the breaking of the flocks' momentum balance. When the flocks began to separate, the second peak in ${\phi}$ was observed. Subsequently, erratic peaks were emerged by some individuals that were delayed to rejoin their flock. The amplitude of the two peaks, $d_1$ (first) and $d_2$ (second), were measured. Interestingly, they exhibited a synchronized behavior for different ${\theta}$. This simulation model can be a useful tool to explore animal behavior and to develop multi-agent robot systems.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
• /
• v.27 no.5
• /
• pp.555-563
• /
• 2009

When a mobile mapping system or a robot is equipped with only a GPS (Global Positioning System) and multiple stereo camera system, a transformation from a local camera coordinate system to GPS coordinate system is required to link camera poses and 3D data by V-SLAM (Vision based Simultaneous Localization And Mapping) to GIS data or remove the accumulation error of those camera poses. In order to satisfy the requirements, this paper proposed a novel method that calculates a camera rotation in the GPS coordinate system using the three pairs of camera positions by GPS and V-SLAM, respectively. The propose method is composed of four simple steps; 1) calculate a quaternion for two plane's normal vectors based on each three camera positions to be parallel, 2) transfer the three camera positions by V-SLAM with the calculated quaternion 3) calculate an additional quaternion for mapping the second or third point among the transferred positions to a camera position by GPS, and 4) determine a final quaternion by multiplying the two quaternions. The final quaternion can directly transfer from a local camera coordinate system to the GPS coordinate system. Additionally, an update of the 3D data of captured objects based on view angles from the object to cameras is proposed. This paper demonstrated the proposed method through a simulation and an experiment.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
• /
• v.2
• /
• pp.203-208
• /
• 2006

The main research conducted previously on GPS ionosphere in China is first introduced. Besides, the current investigations include as follows: (1) GPS-based spatial environmental, especially the ionosphere, monitoring, modeling and analysis, including ground/space-based GPS ionosphere electron density (IED) through occultation/tomography technologies with GPS data from global/regional network, development of a GNSS-based platform for imaging ionosphere and atmosphere (GPFIIA), and preliminary test results through performing the first 3D imaging for the IED over China, (2) The atmospheric and ionospheric modeling for GPS-based surveying, navigation and orbit determination, involving high precisely ionospheric TEC modeling for phase-based long/median range network RTK system for achieving CM-level real time positioning, next generation GNSS broadcast ionospheric time-delay algorithm required for higher correction accuracy, and orbit determination for Low-Earth-orbiter satellites using single frequency GPS receivers, and (3) Research products in applications for national significant projects: GPS-based ionospheric effects modeling for precise positioning and orbit determination applied to China's manned space-engineering, including spatial robot navigation and control and international space station intersection and docking required for related national significant projects.

• Transactions of the Korean Society of Mechanical Engineers B
• /
• v.35 no.3
• /
• pp.331-336
• /
• 2011

The three-dimensional complex curvature of the airfoil complicates the manufacture and repair of gas-turbine components. As a result of the developments in computer technology since the early 1990s, CNC-based technologies for machine tools and related programs have been increasingly applied in the gas turbine industry. In particular, fiveaxis simultaneous machines with adaptive functions have proven its excellent flexibility and productivity due to the capability in determining the 3D data from the unknown curvature. A well-organized robot system with eight-axis simultaneous control can lead to powerful standardization and high productivity. We summarize and review CNC technologies and their applications in the gas turbine industry, with a discussion of the manufacture and repair of gas turbine parts.

• Journal of the Korean Institute of Intelligent Systems
• /
• v.25 no.1
• /
• pp.78-84
• /
• 2015

Depth estimation is often required for robot vision, 3D modeling, and motion control. Previous method is based on the focus measures which are calculated for a series of image by a single camera at different distance between and object. This method, however, has disadvantage of taking a long time for calculating the focus measure since the mask operation is performed for every pixel in the image. In this paper, we estimates the depth by using the focus measure of the boundary pixels located between the objects in order to minimize the depth estimate time. To detect the boundary of an object consisting of a straight line and a circle, we use the Hough transform and estimate the depth by using the focus measure. We performed various experiments for PCB images and obtained more effective depth estimation results than previous ones.