• Korean Journal of Construction Engineering and Management
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• v.12 no.6
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• pp.130-141
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• 2011

The intelligent excavating system(IES), the development in South Korea of which has been underway since 2006, aims for the full-scale automation of the excavation process that includes a series of tasks such as movement, excavation and loading. The core elements to ensure the quality and safety of the automated excavation equipment include 3D modeling of terrain that surrounds the excavating robot and the technology for detecting objects accurately(i.e., for detecting the location of nearby loading trucks and humans as well as of obstacles positioned on the movement paths). Therefore the purpose of this research is to ensure the quality and safety of automated excavation detecting the objects surrounding the excavating robot via a 3D laser scanning system. In this paper, an algorithm for estimating the location, height, width, and shape of objects in the 3D-realized terrain that surrounds the location of the excavator was proposed. The performance of the algorithm was verified via tests in an actual earthwork field.

• Journal of the Korea Society for Simulation
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• v.25 no.4
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• pp.31-42
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• 2016

This study aims to identify the core technology for the automatic impact of the auto-sensing breaker that is one of the construction machinery which do not have a notable development success case yet in Korea. The study has been carried out as follows. Firstly, an analysis model was developed after determining the interconnection of pressure receiving area, opening area and port. And then, a simulation of situation that hard rock and soft rock are mixed was carried out to verify if it is possible to switch between long impact mode and short impact mode continuously. Lastly, the dynamic behavior of automatic control valve induced by the change of impact mode was analyzed based on the analysis result to decipher the core principle of automatic impact control.

• Proceedings of the Korean Institute Of Construction Engineering and Management
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• 2007.11a
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• pp.977-982
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• 2007

There have been many efforts in automatic object recognition using computing technologies. Especially in the development of automated construction equipment, automatic object recognition is very important issue for the proper equipment maneuvering. 3D laser scanning, which uses (time-of-flight) method to construct the 3-dimensional information, is applied to the civil earth work environment for its high accuracy, quick data collection, and object recognition capability that will be developed by the authors in the future. The 3D earth model is also used as a fundamental information for intelligent earth work task planning. This paper presents the analysis of the 3D laser scanner market and selection of the most optimum 3D scanner for the intelligent earth work planning. As well as the hardware configuration for the automated 3D earth modeling is developed but also the software structure and detailed user interface are designed in this research. In addition, it is presented in this paper that the accuracy comparison test between TotalStation(R) which is a traditional survey tool and ScanStation(R). The accuracy test is done by relative distance measurement using known targets.

• Korean Journal of Construction Engineering and Management
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• v.20 no.4
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• pp.69-76
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• 2019

This paper presents a method that identifies the unsafe behaviors at the level of near-misses using image analysis. The method establishes potential collision hazardous area in earthmoving operation. It is implemented using a game engine to reproduce the dangerous events that have been accepted as major difficulty in utilizing computer vision technology to support construction safety management. The method keeps realistically track of the ever-changing hazardous area by reflecting the volatile field conditions. The method opens a way to distinguish unsafe conditions and unsafe behaviors that have been overlooked in previous studies, and reflects the causal relationship which causes an accident. The case study demonstrate how to identify the unsafe behavior of a worker exposed to an unsafe area created by dump trucks at the level of near-misses and to determine the hazardous areas.

• Proceedings of the Korea Water Resources Association Conference
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• 2023.05a
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• pp.154-154
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• 2023

수질모니터링은 수자원 보존과 공중 보건에 있어 매우 중요하다. 기후변화로 인한 이상강우와 산업화 등의 이유로 비점오염물질 및 오염원 배출량이 증가하여 하천과 호소에 영양염류가 증가하게 된다. 영얌염류의 증가로 하천에 부영양화 상태가 지속된다면 녹조발생 등으로 인해 생태계에 부정적 영향을 초래하게 된다. 또한 부영양화는 원수의 유기물량 증가로 인해 처리비용 증가, 이취미 문제 등 인간에게도 직접적인 문제를 유발한다. 특히 우리나라의 경우 하천 취수율이 높은 국가이며, 낙동강 중상류 지역에는 산업시설이 과도하게 밀집되어 있어 하천에 오염물질 유입이 되어 부영양화가 된다면 심각한 문제를 유발하게 된다. TN은 부영양화의 중요한 지표다. 우리나라의 TN 측정은 시료 채수 후 실험실에서 수질오염공정 시험기준에 따라 진행이 된다. 실험실 분석은 TN 농도를 분석하는 일반적인 방법이며, 정확한 검출 및 정량화를 목표로 한다. 하지만 이러한 방식은 정교한 장비를 갖춘 전문 실험실 및 전문 인력을 필요로 한다. 환경부에서 주요 하천에 수질측정망을 설치하여 수질현황에 대한 종합적인 조사를 통해 수질변화 추세를 파악하는 것이 가능하지만, 실시간 TN 농도를 감지하는데 매우 제한적이다. 현재 조사방식은 TN 농도 증가로 인한 문제에 대해 초기대응을 하기에는 한계가 있다. 최근 센서의 발전으로 다양한 항목을 신속하고 지속적으로 모니터링 할 수 있게 되었다. TN에 대한 직접적인 센서 모니터링은 불가능 하지만 여러 측정 항목이 TN과 상관관계가 있는 것이 여러 연구에서 입증되었다. 이러한 결과를 바탕으로 본 연구에서는 오염도가 높은 낙동강을 대상으로 TN 예측에 대한 기초 연구를 진행하였다. 과거 측정된 자료를 활용하여 센서로 측정 가능한 항목을 통해 TN 예측을 진행하며, 실제 활용을 위해 회귀식을 도출하고자 한다. 최근 환경부에서 실시간 수질 현황 및 오염도를 파악하기 위해 자동측정망 지점을 늘리는 추세인데, 본 연구의 결과를 활용한다면 실시간 TN 예측에 대한 기초자료 활용될 수 있을 것으로 판단된다.

• Journal of the Korea institute for structural maintenance and inspection
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• v.27 no.2
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• pp.17-24
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• 2023

A post-processing technique for the measurement signal of a solenoid-type sensor is introduced. The solenoid-type sensor nondestructively evaluates an external tendon of prestressed concrete using the total flux leakage (TFL) method. The TFL solenoid sensor consists of primary and secondary coils. AC electricity, with the shape of a sinusoidal function, is input in the primary coil. The signal proportional to the differential of the input is induced in the secondary coil. Because the amplitude of the induced signal is proportional to the cross-sectional area of the tendon, sectional loss of the tendon caused by ruptures or corrosion can be identified by the induced signal. Therefore, it is important to extract amplitude information from the measurement signal of the TFL sensor. Previously, the amplitude was extracted using local maxima, which is the simplest way to obtain amplitude information. However, because the sampling rate is dramatically decreased by amplitude extraction using the local maxima, the previous method places many restrictions on the direction of TFL sensor development, such as applying additional signal processing and/or artificial intelligence. Meanwhile, the proposed method uses amplitude demodulation to obtain the signal amplitude from the TFL sensor, and the sampling rate of the amplitude information is same to the raw TFL sensor data. The proposed method using amplitude demodulation provides ample freedom for development by eliminating restrictions on the first coil input frequency of the TFL sensor and the speed of applying the sensor to external tension. It also maintains a high measurement sampling rate, providing advantages for utilizing additional signal processing or artificial intelligence. The proposed method was validated through experiments, and the advantages were verified through comparison with the previous method. For example, in this study the amplitudes extracted by amplitude demodulation provided a sampling rate 100 times greater than those of the previous method. There may be differences depending on the given situation and specific equipment settings; however, in most cases, extracting amplitude information using amplitude demodulation yields more satisfactory results than previous methods.