• Proceedings of the Korean Geotechical Society Conference
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• 2008.03a
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• pp.393-398
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• 2008

With the substantial increase of the size of structure, management and monitoring of excavation for the foundation construction becomes more difficult. Therefore, massive collapses which are related to retaining wall recently increase. However, since the study on measuring and monitoring the pre-stressing force of anchor is insufficient, behavior of anchor may not be predicted and monitored appropriately by the existing strain gauge type monitoring system. FBG Sensor, which is smaller than strain gauge and has better durability and does not have a noise from electromagnetic waves, was adapted to develope a smart anchor. A series of pullout tests were performed to verify the feasibility of smart anchor and find out the load transfer mechanism around the steel wire fixed to rock with grout.

• Ocean Systems Engineering
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• v.1 no.1
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• pp.59-72
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• 2011

The objective of this work is to investigate the possibility of using the longitudinal strain on the surface of a pipe to determine the inception of dangerous free spanning. The long term objective is to develop an online monitoring technique to detect the development of dangerous free spanning in subsea pipelines. This work involves experimental study as well as finite element modeling. In the experiments, the strains at four points on a cross section of a pipeline inside the free span zone are measured. Pipes with different boundary conditions and different diameter to length ratios were tested. The pipe is treated as a simple beam with fixed-fixed or simply supported boundary conditions. The variation of the strains as a function of the diameter to length ratio gives a pointer to the inception of dangerous free spanning. The finite element results agree qualitatively with the experiments. The quantitative discrepancy is a result of the difficulty to replicate the exact boundary conditions that is used by the finite element program.

• Journal of Environmental Impact Assessment
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• v.22 no.4
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• pp.389-395
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• 2013

Geostationary Ocean Color Imager(GOCI), the World's first spaceborne ocean color observation satellite operated in geostationary orbit, was successfully launched on May 2010. The main missions of GOCI is the coastal environment monitoring of GOCI in order to meet the necessity of long-term climate change monitoring and research. The GOCI have higher spatial resolution than MODIS, $500m{\times}500m$, and 8 spectral ocean color channels. GOCI have a capability for observation on the coastal environment change, GOCI perform the observation with 8 times a day. In this paper, we presented the more improved results for observation on the coastal environment change than MODIS ocean color sensor and detected the spatial difference of CDOM for monitoring coastal environment change.

• Structural Engineering and Mechanics
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• v.19 no.2
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• pp.123-139
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• 2005

An automatic modal identification program is developed for continuous extraction of modal parameters of three cable-supported bridges in Hong Kong which are instrumented with a long-term monitoring system. The program employs the Complex Modal Indication Function (CMIF) algorithm for identifying modal properties from continuous ambient vibration measurements in an on-line manner. By using the LabVIEW graphical programming language, the software realizes the algorithm in Virtual Instrument (VI) style. The applicability and implementation issues of the developed software are demonstrated by using one-year measurement data acquired from 67 channels of accelerometers permanently installed on the cable-stayed Ting Kau Bridge. With the continuously identified results, variability in modal vectors due to varying environmental conditions and measurement errors is observed. Such an observation is very helpful for selection of appropriate measured modal vectors for structural health monitoring use.

• Earthquakes and Structures
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• v.25 no.1
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• pp.69-78
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• 2023

Life-cycle performance analysis of a reinforced concrete box section bridge was generated. Moreover, Monte Carlo simulation with important sampling (IS) was used to simulate the bridge material and load uncertainties. The bridge deterioration model was generated with the basic probabilistic principles and updated according to the measurement data. A genetic algorithm (GA) with the response surface model (RSM) was used to determine the deterioration rate. The importance of health monitoring systems to sustain the bridge to give services economically and reliably and the advantages of fiber-optic sensors for SHM applications were discussed in detail. This study showed that the most effective loss of strength in reinforced concrete box section bridges is corrosion of the reinforcements. Due to reinforcement corrosion, the use of the bridge, which was examined, could not meet the desired strength performance in 25 years, and the need for reinforcement. In addition, it has been determined that long-term health monitoring systems are an essential approach for bridges to provide safe and economical service. Moreover the use of fiber optic sensors has many advantages because of the ability of the sensors to be resistant to environmental conditions and to make sensitive measurements.

• Clinical Endoscopy
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• v.55 no.4
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• pp.480-488
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• 2022

Endoscopy is vital for diagnosis, assessing treatment response, monitoring and surveillance in patients with inflammatory bowel disease (IBD). With the growing importance of mucosal healing as a treatment target, the assessment of disease activity by endoscopy has been accepted as the standard of care for IBD. There are many endoscopic activity indices for facilitating standardized reporting of the gastrointestinal mucosal appearance in IBD, and each index has its strengths and weaknesses. Although most endoscopic indices do not have a clear-cut validated definition, endoscopic remission or mucosal healing is associated with favorable outcomes, such as a decreased risk of relapse. Therefore, experts suggest utilizing endoscopic indices for monitoring disease activity and optimizing treatment to achieve remission. However, the regular monitoring of endoscopic activity is limited in practice owing to several factors, such as the complexity of the procedure, time consumption, inter-observer variability, and lack of a clear-cut, validated definition of endoscopic response or remission. Although experts have recently suggested consensus-based definitions, further studies are needed to define the values that can predict long-term outcomes.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.28 no.6
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• pp.699-706
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• 2015

This paper presents results of one-year monitoring on prestressing force of a 7-wire steel post-tensioning strand which is installed in a UHPC(ultra high performance concrete) bridge with 11.0 m long, 5.0 m wide, and 0.6 m high by using a FBG-encapsulated 7-wire steel strand. The initial prestressing forces and the prestress changes during a vehicle load test were measured using the FBG-encapsulated strand. The results show that the FBG-encapsulated 7-wire strand is very effective for monitoring the prestress forces even the change in the tension force is very small. Additionally, it was indicated that selection of the thermal expansion coefficient which is used for the temperature correction shall be carefully carried out.

• Smart Structures and Systems
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• v.29 no.1
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• pp.77-91
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• 2022

Various monitoring systems have been implemented in civil infrastructure to ensure structural safety and integrity. In long-term monitoring, these systems generate a large amount of data, where anomalies are not unusual and can pose unique challenges for structural health monitoring applications, such as system identification and damage detection. Therefore, developing efficient techniques is quite essential to recognize the anomalies in monitoring data. In this study, several machine learning techniques are explored and implemented to detect and classify various types of data anomalies. A field dataset, which consists of one month long acceleration data obtained from a long-span cable-stayed bridge in China, is employed to examine the machine learning techniques for automated data anomaly detection. These techniques include the statistic-based pattern recognition network, spectrogram-based convolutional neural network, image-based time history convolutional neural network, image-based time-frequency hybrid convolution neural network (GoogLeNet), and proposed ensemble neural network model. The ensemble model deliberately combines different machine learning models to enhance anomaly classification performance. The results show that all these techniques can successfully detect and classify six types of data anomalies (i.e., missing, minor, outlier, square, trend, drift). Moreover, both image-based time history convolutional neural network and GoogLeNet are further investigated for the capability of autonomous online anomaly classification and found to effectively classify anomalies with decent performance. As seen in comparison with accuracy, the proposed ensemble neural network model outperforms the other three machine learning techniques. This study also evaluates the proposed ensemble neural network model to a blind test dataset. As found in the results, this ensemble model is effective for data anomaly detection and applicable for the signal characteristics changing over time.

• Proceedings of the Korean Geotechical Society Conference
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• 2006.03a
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• pp.171-178
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• 2006

In advanced countries, state-of-the-art temperature monitoring technique is widely used for effective use of geothermal resources. But these kind of modern tools such as Thermal Line Sensor has not been applied to find geothermal characteristics of alluvium and riverbed in domestic area. In this research, state-of-the-art thermal line temperature sensor monitoring was introduced. And long term field test using this type of sensor was performed to find geothermal characteristics of alluvium and riverbed and evaluate the availability for heat energy source. As a result, temperature monitoring technique through thermal line sensor was very effective to obtain basic geothermal information of alluvium deposit and riverbed. Also, it was found that the groundwater temperature phase showed its potential of utilization as a energy source of heat pump. It is estimated that further study shows a specific corelation between temperature monitoring data and its availability as a energy source.

• Corrosion Science and Technology
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• v.15 no.6
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• pp.271-280
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• 2016

An approach to achieving the ambitious goal of cost effectively extending the safe operation life of energy pipeline to 100 years is the application of health monitoring and life prediction tools that are able to provide both long-term remnant pipeline life prediction and in-situ pipeline condition monitoring. A critical step is the enhancement of technological capabilities that are required for understanding and quantifying the effects of key factors influencing buried steel pipeline corrosion and environmentally assisted materials degradation, and the development of condition monitoring technologies that are able to provide in-situ monitoring and site-specific warning of pipeline damage. This paper provides an overview of our current research aimed at developing new sensors and electrochemical cells for monitoring, categorising and quantifying the level and nature of external pipeline and coating damages under the combined effects of various inter-related variables and processes such as localised corrosion, coating cracking and disbondment, cathodic shielding, transit loss of cathodic protection.