• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.49 no.5
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• pp.383-388
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• 2021

Air-breathing engines used in aircraft have a performance limit as the altitude increases, and this determines the service and absolute ceiling altitude. The method of maintaining altitude and speed in a fixed-wing aircraft in level flight using classical control method is generally using thrust for speed increase/deceleration and pitch attitude for altitude increase/decrease. If this method is used near the service ceiling altitude, increasing the pitch to reduce the altitude error results in a speed reduction. Therefore, it is necessary to use a control method that maintains the speed first using the pitch attitude. Especially in the case of unmanned aerial vehicles, these two methods should be automatically available at the right time. In this paper, we propose a method of switching the speed and altitude maintenance algorithm near service ceiling altitude.

• Journal of the Korean Society of Safety
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• v.36 no.5
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• pp.71-78
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• 2021

There are regularly planned overhaul periods in thermal power plants, which involve the maintenance of the boiler of the power plants. However, thermal power plants workers are always exposed to risk during overhaul periods owing to the narrow space and significant dust inside the boiler. Therefore, it is essential to develop a safety monitoring system that is suitable for operating in this type of environment. In this study, we developed not only a worker three-dimensional (3D)-location monitoring system that can monitor and record the entry/exit of workers, their 3D-location, and fall accidents but also a method to secure the working environment and operation efficiency. This system comprises of a worker tag, which was equipped with an inertial measurement unit, a barometric pressure sensor, and a Bluetooth low energy (BLE), and the tags were given to each worker. In addition, the location of workers inside the boiler was measured using a pedestrian dead reckoning (PDR) method and BLE beacons. The location data of the workers tag were transmitted to the integrated database (DB) server through a gateway, and to the administrator monitoring system. The performance of the system was demonstrated inside an actual thermal power plant boiler, and the accuracy and reliability of the system were verified through a number of repeated tests. These results provide insights on designing a new system for monitoring enclosed spaces.

• Journal of Korean Society on Water Environment
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• v.36 no.6
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• pp.500-507
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• 2020

This study examined the wastewater at a livestock farm, and found that the dairy wastewater from the milking parlor had a lower concentration than the piggery wastewater, and that it was produced at a rate under 1.3 ㎥/day in a single farmhouse. The amount of dairy wastewater was determined based on the performance of the milking machine, the maintenance method of the milking parlor, and the amount of milk production allocated for each farmhouse, not by the area. The results confirmed that both dairy wastewater treatment processes, specifically those using Hanged Bio-Compactor (HBC) and Sequencing Batch Reactor (SBR), can fully satisfy the water quality standards of discharge. The dairy wastewater has a lower amount and concentration than piggery wastewater, meaning it is less valuable as liquid fertilizer, but it can be easily degraded using the conventional activated sludge process in a public sewage treatment plant. Therefore, discharging the dairy wastewater after individual treatment was expected to be a more reasonable method than consigning it to the centralized wastewater treatment plant. The effluent after the SBR process showed a lower degree of color than the HBC effluent, which was attributed to biological adsorption. In the case of the milking parlor in the livestock farm, the concentrations of the effluents obtained after HBC and SBR treatments both satisfied water quality standards for the discharge of public livestock wastewater treatment plants at 99% confidence intervals, and the concentrations of total nitrogen and phosphorous in untreated wastewater were even lower than the water quality standards of discharge. Therefore, we need to discuss strengthening the water quality standards to reduce environmental pollution.

• Journal of the Architectural Institute of Korea Structure & Construction
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• v.35 no.9
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• pp.199-206
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• 2019

Experimental study on the durability characteristics to examine the feasibility of concrete with high water-tightness and self-healing performance to minimize maintenance of concrete for artificial ground is as follows. 1) When blending agent, swelling agents, and curing accelerator were added on the ternary system cement with blast-furnace slag fine particles and fly ash to give a self-healing property, higher blending strengths by 82% at design standard strength of 24MPa and by 74% at design strength of 30MPa, respectively could be obtained. 2) The permeability test for the specimens having high water-tightness and no shrinkage showed that the permeability was reduced at maximum of 98%. However, the permeability was decreased as the design strength was increased, showing the reduction rate of 87% at the design strength of 50MPa. 3) The depth of carbonation of blast-furnace slag and fly ash was increased in all the specimens compared with those of OPC only. However, as the material age was increased, carbonation penetration depth was decreased compared with the reference blend. 4) Compared with the reference blending using only OPC, the freeze-thaw resistance was higher in the case of blending with 40% of blast-furnace slag and 10% of fly ash at the design standard strength of 50MPa. In addition, the freeze-thaw resistance in general was superior in the design standard strength of 50MPa with the lower water-binder ratio (W/B) as compared with the design standard strength of 24MPa and 30MPa with the high water-binder ratios.

• Journal of the Korean Society of Safety
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• v.36 no.1
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• pp.18-25
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• 2021

In many developed countries, such as South Korea, efficiently maintaining the aging infrastructures is an important issue. Currently, inspectors visually inspect the infrastructure for maintenance needs, but this method is inefficient due to its high costs, long logistic times, and hazards to the inspectors. Thus, in this paper, a novel crack inspection approach for concrete bridges is proposed using integrated image processing techniques. The proposed approach consists of four steps: (1) training a deep learning model to automatically detect cracks on concrete bridges, (2) acquiring in-situ images using a drone, (3) generating orthomosaic images based on 3D modeling, and (4) detecting cracks on the orthmosaic image using the trained deep learning model. Cascade Mask R-CNN, a state-of-the-art instance segmentation deep learning model, was trained with 3235 crack images that included 2415 hard negative images. We selected the Tancheon overpass, located in Seoul, South Korea, as a testbed for the proposed approach, and we captured images of pier 34-37 and slab 34-36 using a commercial drone. Agisoft Metashape was utilized as a 3D model generation program to generate an orthomosaic of the captured images. We applied the proposed approach to four orthomosaic images that displayed the front, back, left, and right sides of pier 37. Using pixel-level precision referencing visual inspection of the captured images, we evaluated the trained Cascade Mask R-CNN's crack detection performance. At the coping of the front side of pier 37, the model obtained its best precision: 94.34%. It achieved an average precision of 72.93% for the orthomosaics of the four sides of the pier. The test results show that this proposed approach for crack detection can be a suitable alternative to the conventional visual inspection method.

• Journal of the Korea Society of Computer and Information
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• v.27 no.1
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• pp.1-8
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• 2022

In this paper, we propose a fire detection system based on CCTV images using an object tracking technology with YOLOv4 model capable of real-time object detection and a DeepSORT algorithm. The fire detection model was learned from 10800 pieces of learning data and verified through 1,000 separate test sets. Subsequently, the fire detection rate in a single image and fire detection maintenance performance in the image were increased by tracking the detected fire area through the DeepSORT algorithm. It is verified that a fire detection rate for one frame in video data or single image could be detected in real time within 0.1 second. In this paper, our AI fire detection system is more stable and faster than the existing fire accident detection system.

• The Journal of the Convergence on Culture Technology
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• v.7 no.4
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• pp.727-734
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• 2021

The purpose of this study is to analyze the perception of the residents of the new city by examining the consciousness of the occupants to understand the characteristics of the residents of the city of Bundang. As a result of evaluating and analyzing the durability by visual inspection and some equipment tests at the site of the on-site investigation, it was found that there is a problem with the quality, and continuous maintenance is required to improve the durability and usability of the apartment house. In particular, many cracks appearing in the rapidly deteriorated part should be repaired promptly, and a systematic plan should be formulated and carried out. In the apartment housing perception survey of Bundang new city residents, about 93.4% showed above-average satisfaction, and 43.4% showed a favorable preference toward the residential area.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.20 no.6
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• pp.1-13
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• 2021

In this study, a time series analysis technique was applied to calibrate and predict traffic data for various purposes, such as planning, design, maintenance, and research. Existing algorithms have limitations in application to data such as traffic data because they show strong periodicity and seasonality or irregular data. To overcome and supplement these limitations, we applied the SARIMA model, an analytical technique that combines the autocorrelation model, the Seasonal Auto Regressive(SAR), and the seasonal Moving Average(SMA). According to the analysis, traffic volume prediction using the SARIMA(4,1,3)(4,0,3) 12 model, which is the optimal parameter combination, showed excellent performance of 85% on average. In addition to traffic data, this study is considered to be of great value in that it can contribute significantly to traffic correction and forecast improvement in the event of missing traffic data, and is also applicable to a variety of time series data recently collected.

• Journal of the Korea Society of Computer and Information
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• v.27 no.7
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• pp.83-92
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• 2022

In this paper, we designed an algorithm that can control the state of PM by learning the chain failure pattern of PHM based air conditioning facility. It is an inevitable spread of PM due to the downtime caused by the failure of the air conditioning facility. The algorithm developed by us is to establish a PM management system through PHM, and it is an algorithm that maintains a constant stabilization state through learning the stop/operation pattern of the air conditioner and manages PM based on this. As a result of the simulating at a subway station for the performance qualification of the algorithm, it was verified that the concentration of PM reduces by 30% on average. In the case of stations with many passengers using the subway, the concentration of PM exceeded the Ministry of Environment Standards(100 ㎍/m³), but it was verified that the concentration of PM was improved at all stations where the simulation was conducted. In the future research is to expand the system to comprehensively manage not only PM but also pollutants such as CO₂, CO, and NO₂ in subway stations.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.50 no.8
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• pp.541-550
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• 2022

An effective real time fault diagnosis approach for UAV engine is drawn from IMM filter and GLRT methods. For this purpose based on the linear diagnosis model derived from engine dynamic performance analysis the Kalman filter for residual estimation and each method are applied to the fault diagosis of the actuator for engine control sensors. From the process of the IMM filter application the effective FDI measure is obtained and the state responses due to actuator fault are estimated. Likewise from the GLRT method the fault magnitudes of actuator and sensors are estimated associated with some FDI functionings. The numerical simulations verify the effectiveness of the IMM filter for FDI and the GLRT in estimating the fault magnitudes of each fault mode.