• Smart Structures and Systems
• /
• 제10권3호
• /
• pp.271-298
• /
• 2012

Researchers have made significant progress in recent years towards realizing effective structural health monitoring (SHM) utilizing wireless smart sensor networks (WSSNs). These efforts have focused on improving the performance and robustness of such networks to achieve high quality data acquisition and distributed, in-network processing. One of the primary challenges still facing the use of smart sensors for long-term monitoring deployments is their limited power resources. Periodically accessing the sensor nodes to change batteries is not feasible or economical in many deployment cases. While energy harvesting techniques show promise for prolonging unattended network life, low power design and operation are still critically important. This research presents the WiSeMote: a new, fully integrated ultra-low power wireless smart sensor node and a flexible base station, both designed for long-term SHM deployments. The power consumption of the sensor nodes and base station has been minimized through careful hardware selection and the implementation of power-aware network software, without sacrificing flexibility and functionality.

• 해양환경안전학회지
• /
• 제25권7호
• /
• pp.898-905
• /
• 2019

유색 용존 유기물의 빛 흡수와 해빙의 가속화는 수생생태계와 열수지 역동성 간의 양적 피드백에 영향을 줄 수 있으므로 극지 해양에서 유색 용존 유기물의 장기 모니터링이 필요하게 되었다. 그러나 극지 환경에서의 관측은 용이하지 않은 접근성과 거친 기상으로 장기 모니터링이 쉽지 않다. 따라서 유색 용존 유기물의 장기 모니터링 장소로서 남극 세종 기지의 가능성을 확인하기 위해, 마리안 소만과 맥스웰 만에서 유색 용존 유기물의 분포와 외부로부터의 영향을 파악하기 위한 관측을 수행하였다. 맥스웰 만 내의 세종 부두와 세종 곶의 72시간 유색 용존 유기물의 변동성을 관측하고, 외부 영향이 없었던 세종 부두에서 2010년 2월에서 11월까지 10개월간 유색 용존 유기물의 연간 변화와 계절변동을 관측하였다. 세종 부두의 유색 용존 유기물 농도는 가을과 겨울 동안 가장 높고 봄과 여름에 감소하는 뚜렷한 계절 변동성을 보였고, 남극 인근 해역에서 측정된 유색 용존 유기물 농도 자료와 비교하였다. 따라서 우리는 남극해의 열수지에 대한 중요한 요인이자 광화학적 및 생물학적 환경변화에 관한 지시자인 유색 용존 유기물을 장기 모니터링을 위해 적합한 장소로 맥스웰 만의 세종 부두를 제안한다.

• 한국습지학회지
• /
• 제24권4호
• /
• pp.301-311
• /
• 2022

본 연구는 장기 수질모니터링 자료를 이용하여 수질의 계절적 특성을 분석하는 것이 목적이다. 낙동강수계에서 장기 모니터링이 수행되고 있는 34개 지류에서의 모니터링 자료를 이용하여 수질의 계절적 특성을 분석하였고 계절적 분석을 위해 수질의 평균 자료 분석과 변동계수(Coefficient of variation) 분석, 추세분석을 수행하였다. 변동계수 평가결과, 지류가 본류보다 크고 계절적으로는 BOD와 T-P, TOC는 가을철이 크고 T-N은 봄철이 크게 나타났다. 추세분석은 Mann-Kendall과 Sen's Slope를 통해 분석하였으며 BOD와 T-N, T-P는 감소 경향이 많으나 TOC는 증가 경향이 많았다. 또한, 공간적으로는 낙동강 상류보다 하류에서의 증가하는 경향이 많이 나타났다. 본 연구를 통해 장기 수질모니터링 자료의 활용성 평가 및 계절적 특성을 분석할 수 있었고 유역관리를 위해 수질의 안정화 시기, 오염원 증감 변화를 분석할 수 있었다.

• 한국지하수토양환경학회지:지하수토양환경
• /
• 제16권3호
• /
• pp.38-47
• /
• 2011

Groundwater monitoring data from the National Groundwater Monitoring Stations, a total of 320 stations, were analyzed to identify the response of water level and quality to the Odaesan earthquake (M4.9) occurred in January 2007. Among the total of eight stations responded to the earthquake, five wells showed water-level decline, and in three wells, water level rose. In terms of recovery, water levels in four stations had recovered to the original level in five days, but not in the rest four wells. The magnitude of water-level change shows weak relations to the distance between the earthquake epicenter and the groundwater monitoring station. However, the relations to the transmissivities of monitored aquifer in the station with the groundwater change were not significant. To implement the earthquake monitoring system through the groundwater monitoring network, we still need to accumulate the long-term monitoring data and geostatistically analyze those with hydrogeological and tectonic factors.

• 대한조선학회논문집
• /
• 제59권5호
• /
• pp.280-287
• /
• 2022

An open rack vaporizer is a facility that vaporizes liquefied natural gas using sea water. When a vaporization efficiency of the open rack vaporizer decreases, liquefied natural gas can leak, which can cause great damage to the facility. Operators have to monitor the operation state of the facility in real-time to prevent the accident. However, operators have visited the site and have checked the state by looking at the value of sensors installed in the open rack vaporizer through indicators. For the safe operation of the open rack vaporizer, a monitoring system is needed to monitor the operation state of the open rack vaporizer in real-time without the need for operators to visit the site. In this paper, we developed a long term evolution based monitoring system to monitor the operation state of the open rack vaporizer. The developed system can monitor the real-time operation state of the open rack vaporizer at a control center far from the facility. For the system development, data transmission infrastructure using long term evolution was built. Afterwards a software was developed to monitor the operation state of the open rack vaporizer in real-time using the transmitted data. Finally, performance evaluation was conducted to confirm that the developed system operated successfully without data transmission delay or data missing.

• 한국환경과학회지
• /
• 제24권12호
• /
• pp.1691-1703
• /
• 2015

When constructing tunnels, it is important to understand structural, geological and hydrogeological conditions. Geumgeong tunnel that has been constructed in Mt. Geumjeong for the Gyeongbu express railway induced rapid drawdown of groundwater in the tunnel construction area and surroundings. This study aimed to analyze groundwater flow system and baseflow using long-term monitoring and groundwater flow modeling around Geumgeong tunnel. Field hydraulic tests were carried out in order to estimate hydraulic conductivity, transmissivity, and storativity in the study area. Following the formula of Turc and groundwater flow modeling, the annual evapotranspiration and recharge rate including baseflow were estimated as 48% and 23% compared to annual precipitation, respectively. According to the transient modeling for 12 years after tunnel excavation, baseflow was estimated as $9,796-9,402m^3/day$ with a decreasing tendency.

• Structural Monitoring and Maintenance
• /
• 제5권1호
• /
• pp.51-65
• /
• 2018

A number of sensing techniques have been implemented for detecting defects in civil infrastructures instead of onsite human inspections in structural health monitoring. However, the issue of faults in sensors has not received much attention. This issue may lead to incorrect interpretation of data and false alarms. To overcome these challenges, this article presents a deep learning-based method with a new architecture of Stateful Long Short Term Memory Neural Networks (S-LSTM NN) for detecting sensor fault without going into details of the fault features. As LSTMs are capable of learning data features automatically, and the proposed method works without an accurate mathematical model. The detection of four types of sensor faults are studied in this paper. Non-stationary acceleration responses of a three-span continuous bridge when under operational conditions are studied. A deep network model is applied to the measured bridge data with estimation to detect the sensor fault. Another set of sensor output data is used to supervise the network parameters and backpropagation algorithm to fine tune the parameters to establish a deep self-coding network model. The response residuals between the true value and the predicted value of the deep S-LSTM network was statistically analyzed to determine the fault threshold of sensor. Experimental study with a cable-stayed bridge further indicated that the proposed method is robust in the detection of the sensor fault.

• 한국환경과학회지
• /
• 제18권12호
• /
• pp.1399-1410
• /
• 2009

The study on community structure of benthic macroinvertebrates from wetland Woopo was conducted for the long-term ecological monitoring. The wetland Woopo is located in Changnyeong-Gun, Gyeongsangnam - Do of Korea. In 2006, we investigated the seasonal variation of benthic macroinvertebrates with quantitative and qualitative collecting methods. The collection was performed monthly at four surveying region, Woopo, Sajipo, Mokpo and Topyong stream. In this study, 6 classes, 16 orders, 48 families, 95 species were identified on group of benthic macroinvertebrates. The species diversity index and the species richness index were the highest in Topyung region and it was 3.222 and 10.216 respectively. The two species, Cercion calamorum and Cloeon dipterum were quantitatively collected for 9 months. The changes of body lengths of 50 individuals were recorded and the advanced growth on the two species was expected from present study.

• 한국BIM학회 논문집
• /
• 제11권3호
• /
• pp.75-90
• /
• 2021

A smart home system improves the elderly's quality of life by monitoring and analyzing their movements and health conditions with better health-care and social support services. Therefore, there has been an effort to adopt a smart home system for the independently living elderly. However, to the best of our knowledge, no study has investigated the usability of a smart home system on actual independently living elderly housing in long-term settings. Thus, this study aims to demonstrate the usability of a smart home system on independently living elders in living lab conditions. The BLE smart band and the BLE receiver were chosen for the smart home system to monitor the movement of the participants in their homes as well as to monitor the heart rates, step counts, sleep index. Nine independent living elderly from the senior welfare center in Kimjae participated in this living lab demonstration experiment for ten months. This demonstration experiment confirmed the effectiveness of low-cost and easily adoptable IoT-based BLE sensor sets on independent living elders and discussed the troubles and limitations of the experiment. By grasping the pros and cons of IoT-based BLE sensor sets, this study seeks to improve the accessibility and usability of smart home systems for the elderly population in independent living arrangements.

• Smart Structures and Systems
• /
• 제31권1호
• /
• pp.45-56
• /
• 2023

Vibration-based structural health monitoring is used to ensure the safety of structures by installing sensors in structures. The peak picking method, one of the applications of vibration-based structural health monitoring, is a method that analyze the dynamic characteristics of a structure using the peaks of the frequency response function. However, the results may vary depending on the person predicting the peak point; further, the method does not predict the exact peak point in the presence of noise. To overcome the limitations of the existing peak picking methods, this study proposes a new method to automate the modal analysis process by utilizing long short-term memory, a type of recurrent neural network. The method proposed in this study uses the time series data of the frequency response function directly as the input of the LSTM network. In addition, the proposed method improved the accuracy by using the phase as well as amplitude information of the frequency response function. Simulation experiments and lab-scale model experiments are performed to verify the performance of the LSTM network developed in this study. The result reported a modal assurance criterion of 0.8107, and it is expected that the dynamic characteristics of a civil structure can be predicted with high accuracy using data without experts.