• Journal of Electrical Engineering and Technology
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• 제10권6호
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• pp.2277-2287
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• 2015

In recent times, multilevel inverters are given high priority in many large industrial drive applications. However, the reliability of multilevel inverters are mainly affected by the failure of power electronic switches. In this paper, open-switch and short-switch failure of multilevel inverters and its identification using a high performance diagnostic system is discussed. Experimental and simulation studies were carried out on five level cascaded H-Bridge multilevel inverter and its output voltage waveforms were analyzed at different switch fault cases and at different modulation index values. Salient frequency domain features of the output voltage signal were extracted using the discrete wavelet transform multi resolution signal decomposition technique. Real time application of the proposed fault diagnostic system was implemented through the LabVIEW software. Artificial neural network was trained offline using the Matlab software and the resultant network parameters were transferred to LabVIEW real time system. In the proposed system, it is possible to precisely identify the individual faulty switch (may be due to open-switch (or) short-switch failure) of multilevel inverters.

• Smart Structures and Systems
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• 제6권3호
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• pp.263-275
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• 2010

In the last decade, wireless sensor networks have emerged as a promising technology that could accelerate progress in the field of structural monitoring. The main advantages of wireless sensor networks compared to conventional monitoring technologies are fast deployment, small interference with the surroundings, self-organization, flexibility and scalability. These features could enable mass application of monitoring systems, even on smaller structures. However, since wireless sensor network nodes are battery powered and data communication is the most energy consuming task, transferring all the acquired raw data through the network would dramatically limit system lifetime. Hence, data reduction has to be achieved at the node level in order to meet the system lifetime requirements of real life applications. The objective of this paper is to discuss some general aspects of data processing and management in monitoring systems based on wireless sensor networks, to present a prototype monitoring system for civil engineering structures, and to illustrate long-term field test results.

• 한국철도학회논문집
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• 제17권4호
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• pp.251-259
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• 2014

교량/토공 접속부는 교량에서 토공으로 또는 그 반대방향으로 옮겨가는 구간으로 궤도 하부구조의 지지강성이 급격히 변화하기 때문에 차량 주행안정성에 매우 큰 영향을 미친다. 과거 유도상궤도를 사용할 때에는 접속부에 대한 성능요구조건이 높지 않았으나, 운행속도가 고속화되고 콘크리트궤도가 도입되면서 유지보수와 열차주행안정성에 상당한 영향을 미침에 따라 높은 성능수준을 요구하고 있다. 이에 본 논문에서는 기존의 교량/토공 접속구조의 단점을 보완하고 성능을 개선하기 위한 방안으로 토목섬유와 시멘트처리채움재로 보강된 접속구조를 제안하고 실물가속시험을 통한 성능평가를 수행하였다. 제안된 접속구조는 토목섬유를 이용하여 어프로치블럭을 보강하는 방안으로써 보강토 교대와 유사한 구조를 가지며, 사용재료는 시멘트처리된 흙자갈을 적용함으로써 유용토의 활용을 증대시키고 우수의 침입을 저감시켰다. 실물가속시험항목은 구조별 탄성변위, 누적 침하, 함수비, 교대에 작용하는 수평 및 수직 토압이며, 비교검토를 통해서 장기공용성능의 개선정도를 파악하고자 기존 접속구조와 제안 접속구조에 대한 시험을 동일조건하에서 수행하였다. 실물가속시험 결과, 제안구조가 침하 및 토압경감 측면에서 우수한 성능을 나타내었고 함수비 변동에 대해서도 저항성이 높은 것으로 나타났다.

• Structural Engineering and Mechanics
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• 제72권6호
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• pp.675-687
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• 2019

As the bridges are an integral part of the transportation network, their function as one of the most important vital arteries during an earthquake is fundamental. In a design point of view, the bridges piers, and in particular the wall piers, are considered as effective structural elements in the seismic response of bridge structures due to their cantilever performance. Owing to reduced seismic load during design procedure, the response of these structural components should be ductile. This ductile behavior has a direct and decisive correlation to the development of plastic hinge region at the base of the wall pier. Several international seismic design codes and guidelines have suggested special detailing to assure ductile response in this region. In this paper, the parameters which affect the length of plastic hinge region in the reinforced concrete bridge with wall piers were examined and the sensitivity of these parameters was evaluated on the length of the plastic hinge region. Sensitivity analysis was accomplished by independently variable parameters with one standard deviation away from their means. For this aim, the Monte Carlo simulation, tornado diagram analysis, and first order second moment method were used to determine the uncertainties associated with analysis parameters. The results showed that, among the considered design variables, the aspect ratio of the pier wall (length to width ratio) and axial load level were the most important design parameters in the plastic hinge region, while the yield strength of transverse reinforcements had the least effect on determining the length of this region.

• 동의생리병리학회지
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• 제30권6호
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• pp.376-384
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• 2016

Systems biology is an emerging field aiming at a systems level understanding of living organisms and focusing on the characteristics of the whole network of them. The emergence of systems biology is partly because of the availability of huge amounts of data on organisms and the extensive support of computational technologies as the tools for understanding complex biological systems. The scientific understanding of Korean medicine has been obstructed because of the lack of proper methods examining the complex nature and the unique property of it. However, systems biology could give a chance understanding Korean medicine objectively and scientifically. Pattern classification is a unique tool of Korean medicine to diagnose and treat patients and systems biology would give a useful tool to interpret pattern classification. Various omics technologies has been used to explain the relations between pattern classification and biological factors and then many characteristics of pattern classification in various diseases have been discovered. Therefore, pattern classification could be a bridge to understand the features and differences of western medicine and Korean medicine and it could be a basis to develop pattern-based personalized medicine.

• Structural Engineering and Mechanics
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• 제60권2호
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• pp.237-249
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• 2016

There are constraints on truck weight, axle configurations and size imposed by departments of transportation around the globe due to structural capacity limitations of highway pavements and bridges. In spite of that, freight movers demand some vehicles that surpass the maximum size and legal weight limits to use the transportation network. Oversized trucks serve the purpose of spreading the load on the bridge; thus, reducing the load effect on the superstructure. For such vehicles, often a quick structural analysis of the existing bridges along the traveled route is needed to ensure that the structural capacity is not exceeded. For a wide vehicle having wheel gage larger than the standard 1830 mm, the girder distribution factors in the design specifications cannot be directly used to estimate the live load in the supporting girders. In this study, a simple approach that is based on finite element analysis is developed by modifying the AASHTO LRFD's girder distribution factors for slab-on-steel-girder bridges to overcome this problem. The proposed factors allow for determining the oversized vehicle bending moment and shear force effect in the individual girders as a function of the gage width characteristics. Findings of the study showed that the relationship between the girder distribution factor and gage width is more nonlinear in shear than in flexure. The proposed factors yield reasonable results compared with the finite element analysis with adequate level of conservatism.

• 한국해양공학회지
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• 제32권5호
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• pp.361-366
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• 2018

The present study analyzed the variation factors in inducing a salinity change using the existing observation network in the section between the Nakdong River Estuary Barrage and Changnyeong-Haman Weir, and also examined the seasonal changes in precipitation, salinity, and discharge. Furthermore, this study analyzed the causes of a salinity increase by collecting observational data during a period when abnormal salinity occurred, and further investigated the salinity transfer time in a section of approximately 5.3 km from the Nakdong River Estuary Barrage to Nakdong River Bridge to understand the behavioral characteristics of the salinity moving upstream. The study results would make it possible to control the increase in salinity and block salt water from moving upstream by understanding the salinity variation characteristics according to the discharge amount. This will provide stability in collecting water from various residential, agricultural, and industrial sources through water intake facilities scattered near the Nakdong River Estuary Barrage.

• 한국정보기술학회논문지
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• 제16권12호
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• pp.57-68
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• 2018

도시철도 중 하나인 트램 건설시 노면의 상태를 지속적으로 모니터링 하여 도로의 노면 침화, 싱크 홀, 교량 붕괴 위험, 트램역 주변 온 습도 등 환경정보를 수집과 분석을 통해 재난을 예방하는 시스템이 구축되어야 한다. 본 논문에서는 무가선 트램의 노면, 교량 및 트램역의 위험요인을 사전에 인지하고 위험을 예방할 수 있는 저전력 장거리 통신망(LPWA) 기반 트램 노면의 무선통신망 안전관리 시스템을 제안한다. 제안하는 시스템은 트램 노면의 상태를 감지하는 센서 노드와 센서의 정보를 수집하는 게이트웨이 그리고 트램 노면의 안전 및 환경상황을 모니터링 하는 안전관리 시스템으로 구성되며, 저전력 장거리 통신 기술(LoRa)을 적용하였다. 현장 시험에 제안한 시스템과 LTE를 적용한 시스템을 비교 분석한 결과 모니터링 시스템에서 센서 정보 값과 위험신호 임계값 이상 시 위험 알람 상태에 큰 차이가 없음을 확인하였다.

• 농업과학연구
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• 제47권4호
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• pp.1029-1037
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• 2020

The machine learning algorithm has been widely used in water-related fields such as water resources, water management, hydrology, atmospheric science, water quality, water level prediction, weather forecasting, water discharge prediction, water quality forecasting, etc. However, water quality prediction studies based on the machine learning algorithm are limited compared to other water-related applications because of the limited water quality data. Most of the previous water quality prediction studies have predicted monthly water quality, which is useful information but not enough from a practical aspect. In this study, we predicted the dissolved oxygen (DO) using recurrent neural network with long short-term memory model recurrent neural network long-short term memory (RNN-LSTM) algorithms with hourly- and daily-datasets. Bugok Bridge in Oncheoncheon, located in Busan, where the data was collected in real time, was selected as the target for the DO prediction. The 10-month (temperature, wind speed, and relative humidity) data were used as time prediction inputs, and the 5-year (temperature, wind speed, relative humidity, and rainfall) data were used as the daily forecast inputs. Missing data were filled by linear interpolation. The prediction model was coded based on TensorFlow, an open-source library developed by Google. The performance of the RNN-LSTM algorithm for the hourly- or daily-based water quality prediction was tested and analyzed. Research results showed that the hourly data for the water quality is useful for machine learning, and the RNN-LSTM algorithm has potential to be used for hourly- or daily-based water quality forecasting.

• 한국수자원학회논문집
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• 제54권12호
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• pp.1285-1294
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• 2021

최근 전 세계적으로 기후변화의 영향으로 강우량이 집중되고 강우강도가 커지면서 홍수피해의 규모를 증가시키고 있다. 기존에는 관측되지 않았던 규모의 강우가 내리는가 하면 기록적으로 장기간동안 장마가 지속되기도 한다. 특히, 이러한 피해들은 아세안 국가들에 집중되고 있으며, 최근 해수면 상승, 태풍 및 집중호우로 인해 침수가 빈번히 빌생하는 등 아세안 국가 국민들 중 최소 2,000만 명이 영향을 받고 있다. 우리나라도 각종 ODA사업을 통해 국내의 홍수예경보시스템을 아세안 국가에 지원하고 있지만 통신시설이 불안정하여 중앙제어방식만으로는 한계가 있다. 따라서 본 연구에서는 한 개의 관측소에서 수위, 강우의 관측과, 홍수예측, 경보까지 한번에 가능한 관측소를 개발하기 위한 인공지능기반의 홍수예측모형을 개발하였다. 설마천의 전적비교 관측소의 2009년부터 2020년 까지 10분단위 강우와 수위관측자료를 활용하여 선행예보시간 0.5, 1, 2, 3, 6시간에 대해서 학습, 검증, 시험을 수행하였으며 인공지능알고리즘으로는 LSTM을 적용하였다. 연구결과 모든 선행예보시간에 대해 모형적합도 및 오차에서 우수한 결과를 나타냈다. 설마천과 같이 유역규모가 작고 유역경사가 커서 도달시간이 짧은 경우에는 선행예보시간 1시간은 매우 우수한 예측 결과를 나타낼 것으로 판단되며 유역의 규모나 경사에 따라 더 긴 선행예보시간도 가능할 것으로 예상된다.