• Structural Monitoring and Maintenance
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• v.2 no.2
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• pp.145-164
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• 2015

Bridge scour is the predominant cause of overwater bridge failures in North America and around the world. Several sensing systems have been developed over the years to detect the extent of scour so that preventative actions can be performed in a timely manner. These sensing systems have drawbacks, such as signal inaccuracy and discontinuity, installation difficulty, and high cost. Therefore, attempts to develop more efficient monitoring schemes continue. In this study, the viability of using optical dissolved oxygen (DO) probes for monitoring scour depths was explored. DO levels are very low in streambed sediments, as compared to the standard level of oxygen in flowing water. Therefore, scour depths can be determined by installing sensors to monitor DO levels at various depths along the buried length of a bridge pier or abutment. The measured DO is negligible when a sensor is buried but would increase significantly once scour occurs and exposes the sensor to flowing water. A set of experiments was conducted in which four dissolved oxygen probes were embedded at different soil depths in the vicinity of a mock bridge pier inside a laboratory flume simulating scour conditions. The results confirmed that DO levels jumped drastically when sensors became exposed during scour hole evolution, thereby providing discrete measurements of the maximum scour depth. Moreover, the DO probes could detect any subsequent refilling of the scour hole through the deposition of sediments. The effect of soil permeability on the sensing response time was also investigated.

• Nuclear Engineering and Technology
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• v.33 no.5
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• pp.483-497
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• 2001

In this work, a neuro-fuzzy inference system combined with the wavelet denoising, PCA (principal component analysis) and SPRT (sequential probability ratio test) methods is developed to detect the relevant sensor failure using other sensor signals. The wavelet denoising technique is applied to remove noise components in input signals into the neuro-fuzzy system The PCA is used to reduce the dimension of an input space without losing a significant amount of information. The PCA makes easy the selection of the input signals into the neuro-fuzzy system. Also, a lower dimensional input space usually reduces the time necessary to train a neuro-fuzzy system. The parameters of the neuro-fuzzy inference system which estimates the relevant sensor signal are optimized by a genetic algorithm and a least-squares algorithm. The residuals between the estimated signals and the measured signals are used to detect whether the sensors are failed or not. The SPRT is used in this failure detection algorithm. The proposed sensor-monitoring algorithm was verified through applications to the pressurizer water level and the hot-leg flowrate sensors in pressurized water reactors.

• Journal of IKEEE
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• v.21 no.2
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• pp.158-161
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• 2017

In this paper, we propose Total RMS(Radiation Monitoring System) for nuclear and nuclear medicine. The proposed system can expand and control Stack Monitor, Area Monitor, and Water(Liquid) Monitor into one system, and can monitor the signals measured by each radiation detector in an integrated manner. The proposed system consists of a sensor module that detects the radiation, a display unit that displays the radiation dose near the radiation detection location, an alarm unit that reports the alarm when the detected radiation dose reaches the danger level, A Main Hub for collecting and storing the contents to the remote monitoring system, and an RMS Monitoring Unit for clearly displaying the measured radiation dose at the remote site. In order to evaluate the performance of Total RMS for the proposed nuclear and nuclear medicine field, it is confirmed that the measurement uncertainty is less than 8.5% and it operates normally within ${\pm}15%$ of the international standard.

• Journal of Industrial Technology
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• v.28 no.B
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• pp.39-45
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• 2008

Temperature variation according to space and time on the inner parts of engineering constructions(e.g.: dam, slope) can be a basic information for diagnosing their safety problem. In general, as constructions become superannuated, structural deformation(e.g.: cracks, defects) could be occurred by various factors. Seepage or leakage of water through these cracks or defects in old dams will directly cause temperature anomaly. Groundwater level also can be easily observed by abrupt change of temperature on the level. This study shows that the position of seepage or leakage in dam body can be detected by multi-channel temperature monitoring using thermal line sensor. For this, diverse temperature monitoring experiments for a leakage physical model were performed in the laboratory. In field application of an old earth fill dam, temperature variations for water depth and for inner parts of boreholes located at downstream slope were measured. Temperature monitoring results for a long time at the bottom of downstream slope of the dam showed the possibility that temperature monitoring can provide the synthetic information about flowing path and quantity of seepage of leakage in dam body.

• Proceedings of the KSR Conference
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• 2008.11b
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• pp.789-795
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• 2008

Slope stability is affected by various factors. For safety management of slopes, monitoring systems have been widely constructed along railway lines. The representative data from the systems are variations of ground profile such like ground water level and pore water pressure etc. and direct displacement measured by ground clinometer and tension wire sensor. Slopes are mainly effected by rainfall and rainfall causes the decrease of factor of safety(FOS). Because FOS varies linearly by the variation of ground water level and pore pressure, it has a weak point that could not define the time and proper warning sign to secure the safety of the train. In this study, alternative of FOS such as reliability index and probability of failure is applied to slope stability analysis introducing the reliability concept. FOS, reliability index, probability of failure and velocity of probability of failure of the slopes by variation of ground water level are investigated for setting up the specification of safety management of slopes. By executing case study of a slope(ILLO-IMSUNGLI), it is showed to be applied to specification of safety management.

• 제어로봇시스템학회:학술대회논문집
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• 1988.10b
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• pp.804-809
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• 1988

PRNM(Power Range Neutron Monitoring) of BWR (Boiling Water Reactor) is a system that processes signals from about two hundred LPRM (Local Power Range Monitor) sensors in the nuclear reactor and this system monitors the neutron flux level during the plant operating region. Development has been made by employing a special technique for multiplexing neutron sensor signals and the recent advanced microelectronics technology. It is applicable to the total plant digital control system for a nuclear power plant.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.17 no.11
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• pp.2736-2744
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• 2013

In this paper, we present a Smart Water Treatment Plant using Zigbee USN devices and a real-time monitoring system in K-water Flow Meter Calibration Center Building. For verification, the data of vertical type WTP such as flow rate, pressure, water level and water temperature are obtained by the Zigbee USN devices, operating in 2.45 GHz band, and be wirelessly surveilled by the real-time monitoring system. The received data from the sensor is transmitted to the data processing device, and then the processed data can be monitored on a smart phone. Consequently, the pilot plant based on the low-cost and high-efficiency USN has been developed with the performance analysis for the communication network and remote monitoring system on mobile devices.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.10
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• pp.3275-3298
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• 2022

Cloud-based architectures for precision agriculture are domain-specific controlled and require remote access to process and analyze the collected data over third-party cloud computing platforms. Due to the dynamic changes in agricultural parameters and restrictions in terms of accessing cloud platforms, developing a locally controlled and real-time configured architecture is crucial for efficient water irrigation and farmers management in agricultural fields. Thus, we present a new implementation of an independent sensor-enabled architecture using variety of wireless-based sensors to capture soil moisture level, amount of supplied water, and compute the reference evapotranspiration (ETo). Both parameters of soil moisture content and ETo values was then used to manage the amount of irrigated water in a small-scale agriculture field for 356 days. We collected around 34,200 experimental data samples to evaluate the performance of the architecture under different agriculture parameters and conditions, which have significant influence on realizing real-time monitoring of agricultural fields. In a proof of concept, we provide empirical results that show that our architecture performs favorably against the cloud-based architecture, as evaluated on collected experimental data through different statistical performance models. Experimental results demonstrate that the architecture has potential practical application in a many of farming activities, including water irrigation management and agricultural condition control.

• Journal of the Korean GEO-environmental Society
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• v.16 no.6
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• pp.39-43
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• 2015

This study extends the Distributed Temperature Sensing (DTS) application to delineate the saturated zones in shallow sediment and evaluate the groundwater flow in both downward and upward directions. Dry, partially and fully saturated zones and water level in the subsurface can be recognized from this study. High resolution seepage velocity in vertical direction was estimated from the temperature data in the fully saturated zone. By a single profile, water level can be detected and seepage velocity in saturated zone can be estimated. Furthermore, thermal gradient analysis serves as a new technique to verify unsaturated and saturated zones in the subsurface. The vertical seepage velocity distribution in the recognized saturated zone is then analyzed with improvement of Bredehoeft and Papaopulos' model. This new approach provides promising potential in real-time monitoring of groundwater movement.

• Journal of The Korean Society of Agricultural Engineers
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• v.53 no.6
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• pp.7-16
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• 2011

This study discussed the applicability of satellite SAR (Synthetic Aperture Radar) imagery with regard to reservoir monitoring, and tried the extraction of reservoir storage from multi-temporal C-band RADARSAT-1 SAR backscattering images of Yedang and Goongpyeong agricultural reservoirs, acquired from May to October 2005. SAR technology has been advanced as a complementary and alternative approach to optical remote sensing and in-situ measurement. Water bodies in SAR imagery represent low brightness induced by low backscattering, and reservoir storage can be derived from the backscatter contrast with the level-area-volume relationship of each reservoir. The threshold segmentation over the routine preprocessing of SAR images such as speckle reduction and low-pass filtering concluded a significant correlation between the SAR-derived reservoir storage and the observation record in spite of the considerable disagreement. The result showed up critical limitations for adopting SAR data to reservoir monitoring as follows: the inappropriate specifications of SAR data, the unreliable rating curve of reservoir, the lack of climatic information such as wind and precipitation, the interruption of inside and neighboring land cover, and so on. Furthermore, better accuracy of SAR-based reservoir monitoring could be expected through different alternatives such as multi-sensor image fusion, water level measurement with altimeters or interferometry, etc.