• Journal of the Korea Academia-Industrial cooperation Society
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• v.18 no.5
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• pp.716-722
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• 2017

The present study numerically investigates the effect of obstacles located in the trajectory of fire plume flow on heat flow characteristics by using Fire Dynamics Simulation (FDS) software in an underground combined cycle power plant (CCPP). Fire size is taken as 10 MW and two different locations of fire source are selected depending on the presence of an obstacle. As the results, when the obstacle is in the trajectory of fire plume, hot plume arrives at the ceiling about 5 times slower in the upper of the fire in comparison to the results without obstacle. In addition, the average propagation time of ceiling jet increases by about 70 % with the distance from the ceiling in the upper of the fire, and it increases mainly about 4 times at the distance of 10 m. Consequently, it is noted that the analysis of heat flow characteristics in the underground CCPP considering fire scenarios is essential to develop the fire detection system for initial response on evacuation and disaster management.

• Nuclear Engineering and Technology
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• v.46 no.3
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• pp.439-446
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• 2014

An amphibious inspection robot system (hereafter AIROS) is being developed to visually inspect the in-containment refueling storage water tank (hereafter IRWST) strainer in APR1400 instead of a human diver. Four IRWST strainers are located in the IRWST, which is filled with boric acid water. Each strainer has 108 sub-assembly strainer fin modules that should be inspected with the VT-3 method according to Reg. guide 1.82 and the operation manual. AIROS has 6 thrusters for submarine voyage and 4 legs for walking on the top of the strainer. An inverse kinematic algorithm was implemented in the robot controller for exact walking on the top of the IRWST strainer. The IRWST strainer has several top cross braces that are extruded on the top of the strainer, which can be obstacles of walking on the strainer, to maintain the frame of the strainer. Therefore, a robot leg should arrive at the position beside the top cross brace. For this reason, we used an image processing technique to find the top cross brace in the sole camera image. The sole camera image is processed to find the existence of the top cross brace using the cross edge detection algorithm in real time. A 5-DOF robot arm that has multiple camera modules for simultaneous inspection of both sides can penetrate narrow gaps. For intuitive presentation of inspection results and for management of inspection data, inspection images are stored in the control PC with camera angles and positions to synthesize and merge the images. The synthesized images are then mapped in a 3D CAD model of the IRWST strainer with the location information. An IRWST strainer mock-up was fabricated to teach the robot arm scanning and gaiting. It is important to arrive at the designated position for inserting the robot arm into all of the gaps. Exact position control without anchor under the water is not easy. Therefore, we designed the multi leg robot for the role of anchoring and positioning. Quadruped robot design of installing sole cameras was a new approach for the exact and stable position control on the IRWST strainer, unlike a traditional robot for underwater facility inspection. The developed robot will be practically used to enhance the efficiency and reliability of the inspection of nuclear power plant components.

• Journal of Korea Spatial Information System Society
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• v.4 no.2 s.8
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• pp.55-64
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• 2002

VEfficient generation of road data is one of the most important issues in GIS (Geographic Information System). In this paper, we propose a hybrid approach for automatic generation of road data by combining mobile mapping and image processing techniques. Mobile mapping systems have a form of vehicle equipped with CCD camera, GPS, and INS. They can calculate absolute position of objects that appear in acquired image by photogrammetry, but it is labor-intensive and time-consuming. Automatic road detection methods have been studied also by image processing technology. However, the methods are likely to fail because of obstacles and exceptive conditions in the real world. To overcome the problems, we suggest a hybrid method for automatic road generation, by exploiting both GPS/INS data acquired by mobile mapping system and image processing algorithms. We design an estimator to estimate 3-D coordinates of road line and corresponding location in an image. The estimation process reduces complicated image processing operations that find road line. The missing coordinates of road line due to failure of estimation are obtained by cubic spline interpolation. The interpolation is done piecewise, separated by rapid change such as road intersection. We present experimental results of the suggested estimation and interpolation methods with image sequences acquired by mobile mapping system, and show that the methods are effective in generation of road data.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.12 no.1
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• pp.29-36
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• 2012

In Wireless Sensor Network(WSN)s, the detection of precise location of each node is essential for utilizing sensing data acquired from sensor nodes effectively. Among various location methods, the received signal strength(RSS) based localization scheme is mostly preferable in many applications because it can be easily implemented without any additional hardware cost. Since a RSS-based localization scheme is mainly affected by radio channel or obstacles such as building and mountain between two nodes, the localization error can be inevitable. To enhance the accuracy of localization in RSS-based localization scheme, a number of RSS measurements are needed, which results in the energy consumption. In this paper, a RSS based localization using Bayesian Compressive Sensing(BSS) with path-loss exponent estimation is proposed to improve the accuracy of localization in the energy-efficient way. In the propose scheme, we can increase the adaptative, reliability and accuracy of localization by estimating the path-loss exponents between nodes, and further we can enhance the energy efficiency by the compressive sensing. Through the simulation, it is shown that the proposed scheme can enhance the location accuracy of multiple unknown nodes with fewer RSS measurements and is robust against the channel variation.

• Journal of the Korea Society for Simulation
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• v.20 no.4
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• pp.105-114
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• 2011

The roadmap-based planning is a path planning method which is used widely for a goal-directed movement in Robotics and has been applied to the world of computer animation such as computer games. However it is unnatural for computer characters to follow the path planned by the roadmap method as it is performed in Robotics. Flocking which is used for realistic and natural movements in computer animation enables character's movement by using a few simple rules without planning unlike the roadmap method. However it is impossible to achieve a goal-directed movement with flocking only because it does not keep states. In this paper we propose a simulation method which combines planning based on the road map with reactive actions for natural movements along the path planned. We define and implement steering behaviors for a leader which are needed to follow the trajectory naturally by analysing characteristics of roadmap-based paths and for the rest of members which follow the leader in various manners by detecting obstacles. The simulations are performed and demonstrated by using the implemented steering behaviors on every possible combination of roadmap-based path planning methods and models of configuration spaces. We also show that the detection of obstacle-collisions can be done effectively because paths are planned in the configuration space in which a moving object is reduced to a point.

• International Journal of Railway
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• v.1 no.4
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• pp.149-156
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• 2008

During maintenance or construction works in or at the tracks of railways, high risks for passengers and railway staff, especially for the workers on the construction site exist. The high risks result out of the movement of rail vehicles, like trains or construction vehicles, which must be faced by using any available technical and operational technologies for securing them against the environment. Therefore, it is necessary to evaluate the level of protection continuously and to identify new and innovative methods and technologies for the protection of the gang (construction worker, machines and material). Especially on construction sites at line sections with two or more parallel tracks but also with single tracks, there are still a lot of incidents and accidents mostly with seriously injured persons or fatalities. These were mainly gang members that breach the railway-loading gage. By using proper warning or protection systems, the avoidance of such accidents must be achieved. The latest developments. in gang protection systems concern on the one hand fixed barriers in the middle between the construction site and the operated track and on the other hand construction vehicles equipped with automatic warning systems. The disadvantage of such protection methods is that the gang can be warned against an approaching train but a monitoring of the gang members cannot be performed. Only one part of a potential dangerous situation will be detected. If the gang members will overhear the acoustic warning signal of the security staff and the workers will not leave the danger zone in the track, the driver of the approaching train had no chance to react to the dangerous situation. An accident is often inevitable. While the detection of acoustic warning signals by the gang members working on a construction site is very difficult, the acoustical planning of an automatic warning system has to be designed for an acoustic short range level of one meter besides the construction vehicle. The decision about the use of today's technical warning system (fixed systems, automatic warning systems, etc.) must be geared to the technical feasibility and the level of safety which is needed. Criteria for decision guidance to block a track should be developed by danger estimation and economical variables. To realize the actual jurisdiction and to minimize the hazards of railway operations by the use of construction vehicles near the tracks further developments are needed. This means, that the warning systems have to be enhanced to systems for protection, which monitor the realization of the warning signal as a precondition for giving a movement authority to a train. This method can protect against accidents caused by predictable wrongdoing. The actual state of the art technique of using a collective warning combined with additional security staff is no longer acceptable. Therefore, the Institute of Transportation System of the German Aerospace Center in Braunschweig (Germany) will develop a gang warning and protection system based upon imaging methods, with optical sensors such as video in visible and invisible ranges, radar, laser, and other. The advantage of such a system based on the possibility to monitor both the gang itself and the railway-loading gauge either of the parallel track or of the same track still in use. By monitoring both situations, the system will be able to generate a warning message for the approaching train, that there are obstacles in the track, so that the train can be stopped to prevent an accident. And also the gang workers will be warned, while they breach their area.

• Journal of the Korean Society of Marine Environment & Safety
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• v.28 no.2
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• pp.370-376
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• 2022

Smart ships related studies are being conducted in various fields owing to the development of technology, and an engine room patrol robot that can patrol the unmanned engine room is one such study. A patrol robot moves around the engine room based on the information learned through artificial intelligence and checks the machine normality and occurrence of abnormalities such as water leakage, oil leakage, and fire. Study on engine room patrol robots is mainly conducted on machine detection using artificial intelligence, however study on movement and control is insufficient. This causes a problem in that even if a patrol robot detects an object, there is no way to move to the detected object. To secure maneuverability to quickly identify the presence of abnormality in the engine room, this study experimented with whether a patrol robot can determine the shortest path by applying the A* algorithm. Data were obtained by driving a small car equipped with LiDAR in the ship engine room and creating a map by mapping the obtained data with SLAM(Simultaneous Localization And Mapping). The starting point and arrival point of the patrol robot were set on the map, and the A* algorithm was applied to determine whether the shortest path from the starting point to the arrival point was found. Simulation confirmed that the shortest route was well searched while avoiding obstacles from the starting point to the arrival point on the map. Applying this to the engine room patrol robot is believed to help improve ship safety.

• Journal of the Korean Association of Geographic Information Studies
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• v.26 no.3
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• pp.85-96
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• 2023

This study developed and evaluated a safe route guidance service for electric personal assistive mobility device used mainly by the mobility impaired people to improve their mobility. Thirteen underlying factors affecting the mobility of electric personal assistive mobility device have been derived through a survey with the mobility impaired people and employees in related organizations in Busan Metropolitan City. After assigning safety scores to individual factors and identifying the relevant factors along routes of interest with an object detection AI model, the safe route for electric personal assistive mobility device was provided through an optimal path-finding algorithm. As a result of comparing the general route of T-map and the recommended route of this study for the identical routes, the latter had relatively fewer obstacles and the gentler slope than the former, implicating that the recommended route is safer than the general one. As future works, it is necessary to enhance the function of a route guidance service based on the real-time location of users and to conduct spot investigations to evaluate and verify its social acceptability.

• Journal of Platform Technology
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• v.11 no.2
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• pp.26-38
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• 2023

This paper is a study on a transport robot capable of autonomously driving to a destination using a QR code in an indoor environment. The transport robot was designed and manufactured by attaching a lidar sensor so that the robot can maintain a certain distance during movement by detecting the distance between the camera for recognizing the QR code and the left and right walls. For the location information of the delivery robot, the QR code image was enlarged with Lanczos resampling interpolation, then binarized with Otsu Algorithm, and detection and analysis were performed using the Zbar library. The QR code recognition experiment was performed while changing the size of the QR code and the traveling speed of the transport robot while the camera position of the transport robot and the height of the QR code were fixed at 192cm. When the QR code size was 9cm × 9cm The recognition rate was 99.7% and almost 100% when the traveling speed of the transport robot was less than about 0.5m/s. Based on the QR code recognition rate, an experiment was conducted on the case where the destination is only going straight and the destination is going straight and turning in the absence of obstacles for autonomous driving to the destination. When the destination was only going straight, it was possible to reach the destination quickly because there was little need for position correction. However, when the destination included a turn, the time to arrive at the destination was relatively delayed due to the need for position correction. As a result of the experiment, it was found that the delivery robot arrived at the destination relatively accurately, although a slight positional error occurred while driving, and the applicability of the QR code-based destination self-driving delivery robot was confirmed.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.7
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• pp.1951-1975
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• 2023

Recent advances in Cognitive Radio Networks (CRN) have elevated them to the status of a critical instrument for overcoming spectrum limits and achieving severe future wireless communication requirements. Collaborative spectrum sensing is presented for efficient channel selection because spectrum sensing is an essential part of CRNs. This study presents an innovative cooperative spectrum sensing (CSS) model that is built on the Firefly Algorithm (FA), as well as machine learning artificial neural networks (ANN). This system makes use of user grouping strategies to improve detection performance dramatically while lowering collaboration costs. Cooperative sensing wasn't used until after cognitive radio users had been correctly identified using energy data samples and an ANN model. Cooperative sensing strategies produce a user base that is either secure, requires less effort, or is faultless. The suggested method's purpose is to choose the best transmission channel. Clustering is utilized by the suggested ANN-FA model to reduce spectrum sensing inaccuracy. The transmission channel that has the highest weight is chosen by employing the method that has been provided for computing channel weight. The proposed ANN-FA model computes channel weight based on three sets of input parameters: PU utilization, CR count, and channel capacity. Using an improved evolutionary algorithm, the key principles of the ANN-FA scheme are optimized to boost the overall efficiency of the CRN channel selection technique. This study proposes the Artificial Neural Network with Firefly Algorithm (ANN-FA) for cognitive radio networks to overcome the obstacles. This proposed work focuses primarily on sensing the optimal secondary user channel and reducing the spectrum handoff delay in wireless networks. Several benchmark functions are utilized We analyze the efficacy of this innovative strategy by evaluating its performance. The performance of ANN-FA is 22.72 percent more robust and effective than that of the other metaheuristic algorithm, according to experimental findings. The proposed ANN-FA model is simulated using the NS2 simulator, The results are evaluated in terms of average interference ratio, spectrum opportunity utilization, three metrics are measured: packet delivery ratio (PDR), end-to-end delay, and end-to-average throughput for a variety of different CRs found in the network.