• International conference on construction engineering and project management
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• 2009.05a
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• pp.1060-1067
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• 2009

The selection and operation of tower cranes at construction sites are dependent on the personal experience of engineers in charge of lifting work. It often causes to overestimate the safety factor resulting in increase of construction cost, or underestimate it resulting in disastrous accident. Therefore, selection of tower cranes needs to consider cost, safety and maximum lifting condition. This study, for resolving such problems, was intended to propose the algorithm designed for even the inexperienced person to select the optimal lifting equipment in timely manner. The algorithm presented herein is an optimization algorithm that enables automatic arrangement of tower crane and minimization of costs by analyzing such conditions as vertical height and lifting load, etc.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2002.11a
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• pp.113-119
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• 2002

Recently, an automatic crane control system is required with high speed and rapid transportation. During the operation of crane system in container yard it is necessary to control the crane trolley position and loop length so that the swing of the hanging container is minimized We can do development of unmanned automation control system using automation travel control technique and anti-sway technique in crane system. Therefore, we designed a controller for Automation travel control to control the transfer crane system. Analyzed crane system through simulation, and proved excellency of control performance than other conventional controllers.

• 제어로봇시스템학회:학술대회논문집
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• 1989.10a
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• pp.260-265
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• 1989

The micro-computer based automatic control of the overhead crane system is designed. Two control methodologies were suggested; the one is the anti-swing controller which improves poor damping characteristics of the crane and the other is the stop-position controller which minimizes the transportation position error. The input speed profile is automatically determined by the pre-programmed digital control algorithm. The experimental results show that these proposed controllers have excellent control performance as compared with those of the uncontrolled crane system.

• 연구논문집
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• s.25
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• pp.99-104
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• 1995

At present, a lot of researches on AS/RS(Automatic Storage and Retrival System) are being performed and also applied to realization of FA, FMS and CIM. Especially facility management and diagnosis of stacker crane that is major equipment of AS/RS, is recognized more importantly. In this paper, Case Base is designed for manager that is non-expert and it is implemented according to possible trouble case for the purpose of trouble diagnosis and maintenance of stacker crane.

• Journal of Power System Engineering
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• v.10 no.3
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• pp.88-96
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• 2006

While the crane system operate in port, one of main objective is to transport containers to the goal position as soon as possible. Because this is one of the biggest problem in terms of productivity of port, the container crane is operated by an expert operator until now. However recently an automatic control system with high performance is required to improve the performance of the crane system and to make high productivity. Therefore we developed an optimal controller based on Humoral Immune Algorithm with PID controller. The proposed system has a real time structure and can improve the performance such as anti-sway problem. Some computer simulations are implemented to assess the characteristics of the proposed controller.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.142-142
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• 2000

During the operation of crane system in container yard, it is necessary to control the crane trolley position so that the swing of the hanging container is minimized. Recently an automatic control system with high speed and rapid transportation is required. Therefore, we designed a controller to control the crane system with disturbances. In this paper, Ive present the neural network two degree of freedom PID controller to control the swing motion and trolley position. Then we executed the computer simulation to verify the performance of the proposed controller and compared the performance of the neural network PID controller with our proposed controller in terms of the rope swing and the precision of position control . Computer simulation results show that the proposed controller has better performances than neural network PID with disturbances.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2002.03a
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• pp.219-227
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• 2002

In this paper, we designed neural network predictive PID controller to control sway happened in transfer of trolley for automatic travel control system. We include dynamic character of nonlinear system, and mathematical expression veny simple used neural network. When various establishment location and surrounding disturbance were approved based on mathematical modelling of crane, controller designed to become effective control location error and vibration angle of two control variables that simultaneously can predictive control. Neural network predictive PID controller produced parameter of PID controller using neural network self-tuner. Neural network self-tuner's input used crane's output and neural network predictive output. Neural network self-tuner using error back propagation algorithm. We analyzed control performance comparison through computer simulation when applied disturbance about sway of location and angle in transfer of crane. The results show that the proposed neural network predictive PID controller has better performances than general PID controller, neural network PID controller.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1998.10a
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• pp.397-402
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• 1998

PID controller has been used very widely in the industrial applications. But it is difficult tune the PID gains. In this paper, we present a design of optimal 2-DOF PID controller for control of container crane which has to control swing motion and trolley position. For tuning of the 2-DOF PID control gains, we used hybrid evolution program(EP). During operate the crane system in yard, the goal is transporting the load to a goal position as quick as possible without rope oscillation. The crane is generally operated by an expert operator, but recently an automatic control system with high accuracy and rapid transportation is required. However, we developed an optimal controller which has to control the crane system with disturbance.

• International conference on construction engineering and project management
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• 2009.05a
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• pp.250-256
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• 2009

This paper presents a robotic tower-crane system using encoder and gyroscope sensors as path tracking devices. Tower crane work is often associated with falling accidents and industrial disasters. Such problems often incur a loss of time and money for the contractor. For this reason, many studies have been done on an automatic tower crane. As a part of 5-year 23-million-dollar research project in Korea, we are developing a robotic tower crane which aims to improve the safety level and productivity. We selected a luffing tower crane, which is commonly used in urban construction projects today, as a platform for the robotic tower crane system. This system comprises two modules: the automated path planning module and the path tracking module. The automated path planning system uses the 3D Cartesian coordinates. When the robotic tower crane lifts construction material, the algorithm creates a line, which represents a lifting path, in virtual space. This algorithm seeks and generates the best route to lift construction material while avoiding known obstacles from real construction site. The path tracking system detects the location of a lifted material in terms of the 3D coordinate values using various types of sensors including adopts encoder and gyroscope sensors. We are testing various sensors as a candidate for the path tracking device. This specific study focuses on how to employ encoder and gyroscope sensors in the robotic crane These sensors measure a movement and rotary motion of the robotic tower crane. Finally, the movement of the robotic tower crane is displayed in a virtual space that synthesizes the data from two modules: the automatically planned path and the tracked paths. We are currently field-testing the feasibility of the proposed system using an actual tower crane. In the next step, the robotic tower crane will be applied to actual construction sites with a following analysis of the crane's productivity in order to ascertain its economic efficiency.

• International conference on construction engineering and project management
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• 2020.12a
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• pp.399-408
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• 2020

The construction industry is suffering from aging workers, frequent accidents, as well as low productivity. With the rapid development of information technologies in recent years, automatic construction, especially automatic cranes, is regarded as a promising solution for the above problems and attracting more and more attention. However, in practice, limited by the complexity and dynamics of construction environment, manual inspection which is time-consuming and error-prone is still the only way to recognize the search object for the operation of crane. To solve this problem, an image-processing-based automated object recognition approach is proposed in this paper, which is a fusion of Convolutional-Neutral-Network (CNN)-based and traditional object detections. The search object is firstly extracted from the background by the trained Faster R-CNN. And then through a series of image processing including Canny, Hough and Endpoints clustering analysis, the vertices of the search object can be determined to locate it in 3D space uniquely. Finally, the features (e.g., centroid coordinate, size, and color) of the search object are extracted for further recognition. The approach presented in this paper was implemented in OpenCV, and the prototype was written in Microsoft Visual C++. This proposed approach shows great potential for the automatic operation of crane. Further researches and more extensive field experiments will follow in the future.