• Journal of the Korean Society for Nondestructive Testing
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• v.29 no.5
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• pp.436-441
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• 2009

A fiber optic sensor is prospective to be applied to structural health monitoring. Especially, a fiber Bragg grating(FBG) sensor is one of the most popular sensors for the structural health monitoring. The FBG sensor has several demodulation systems for tracking the shift of the Bragg wavelength. The dynamic bandwidth is dependent on the demodulation system. In this paper, the sensing mechanism is that the slope of the optical spectrum of FBG could be used as its sensitivity when the tunable laser shot the monochromatic laser wavelength at the highest slope point. In this technique, the high sensitivity is guaranteed even though the sensing range is limited. In an example of the application, the composite plate embedding a FBG sensor was manufactured by using an autoclave method and the above sensing mechanism was applied to the composite plate. Firstly, the natural frequencies of the plate were successfully measured by the FBG sensor during the impact hammer test. Secondly, a high-power speaker was used to force the plate to be vibrated at the specific frequency that was one of the natural frequencies. During the shaking, the FBG sensor measures the dynamic characteristics and ESPI was also used to measure the mode shape. From the two dynamic tests, the availability of the FBG sensor system and the ESPI was proven as a technique for measuring the dynamic characteristics of composite structure.

• Structural Monitoring and Maintenance
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• v.2 no.1
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• pp.77-93
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• 2015

The idea of using measured dynamic characteristics for damage detection is attractive because it allows for a global evaluation of the structural health and condition. However, vibration-based damage detection for complex structures such as long-span cable-supported bridges still remains a challenge. As a suspension or cable-stayed bridge involves in general thousands of structural components, the conventional damage detection methods based on model updating and/or parameter identification might result in ill-conditioning and non-uniqueness in the solution of inverse problems. Alternatively, methods that utilize, to the utmost extent, information from forward problems and avoid direct solution to inverse problems would be more suitable for vibration-based damage detection of long-span cable-supported bridges. The auto-associative neural network (ANN) technique and the probabilistic neural network (PNN) technique, that both eschew inverse problems, have been proposed for identifying and locating damage in suspension and cable-stayed bridges. Without the help of a structural model, ANNs with appropriate configuration can be trained using only the measured modal frequencies from healthy structure under varying environmental conditions, and a new set of modal frequency data acquired from an unknown state of the structure is then fed into the trained ANNs for damage presence identification. With the help of a structural model, PNNs can be configured using the relative changes of modal frequencies before and after damage by assuming damage at different locations, and then the measured modal frequencies from the structure can be presented to locate the damage. However, such formulated ANNs and PNNs may still be incompetent to identify damage occurring at the deck members of a cable-supported bridge because of very low modal sensitivity to the damage. The present study endeavors to enhance the damage identification capability of ANNs and PNNs when being applied for identification of damage incurred at deck members. Effort is first made to construct combined modal parameters which are synthesized from measured modal frequencies and modal shape components to train ANNs for damage alarming. With the purpose of improving identification accuracy, effort is then made to configure PNNs for damage localization by adapting the smoothing parameter in the Bayesian classifier to different values for different pattern classes. The performance of the ANNs with their input being modal frequencies and the combined modal parameters respectively and the PNNs with constant and adaptive smoothing parameters respectively is evaluated through simulation studies of identifying damage inflicted on different deck members of the double-deck suspension Tsing Ma Bridge.

• Journal of the Korea institute for structural maintenance and inspection
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• v.26 no.4
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• pp.20-29
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• 2022

The operational modal analysis (OMA) technique, which extracts the modal parameters of a structural system using ambient vibrations, has been actively developed as a field of structural health monitoring of cable-supported bridges. In this paper, the short and long-term modal parameters of a cable-stayed bridge were evaluated using the acceleration data obtained from the two ambient vibration tests (AVTs) and three years of continuous measurements. A total of 27 vertical modes and 1 lateral mode in the range 0.1 ~ 2.5 Hz were extracted from the high-resolution AVTs which were conducted in the 6th and 19th years after its completion. Existing OMA methods such as Peak-Picking (PP), Eigensystem Realization Algorithm with Data Correlation (ERADC), Frequency Domain Decomposition (FDD) and Time Domain Decomposition (TDD) were applied for modal parameters extraction, and it was confirmed that there was no significant difference between the applied methods. From the correlation analysis between long-term natural frequencies and environmental factors, it was confirmed that temperature change is the dominant factor influencing natural frequency fluctuations. It was revealed that the decreased natural frequencies of the bridge were not due to changes in structural performance and integrity, but to the environmental effects caused by the temperature difference between the two AVTs. In addition, when the TDD technique is applied, the accuracy of extracted mode shapes is improved by adding a proposed algorithm that normalizes the sequence so that the autocorrelations at zero lag equal 1.

• Wind and Structures
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• v.21 no.2
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• pp.159-182
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• 2015

This study focuses on the amplitude dependency of damping of tall structures by the random decrement technique (RDT). Many researchers have adopted RDT to establish the amplitude dependency of damping ratios in super-tall buildings under strong wind loads. In this study, a series of simulated examples were analyzed to examine the reliability of this method. Results show that damping ratios increase as vibration amplitudes increase in several cases; however, the damping ratios in the simulated signals were preset as constants. This finding reveals that this method and the derived amplitude-dependent damping ratio characteristics are unreliable. Moreover, this method would obviously yield misleading results if the simulated signals contain Gaussian white noise. Full-scale measurements on a super-tall building were conducted during four typhoons, and the recorded data were analyzed to observe the amplitude dependency of damping ratio. Relatively wide scatter is observed in the resulting damping ratios, and the damping ratios do not appear to have an obvious nonlinear relationship with vibration amplitude. Numerical simulation and field measurement results indicate that the widely-used method for establishing the amplitude-dependent damping characteristics of super-tall buildings and the conclusions derived from it might be questionable at the least. More field-measured data must be collected under strong wind loads, and the damping characteristics of super-tall buildings should be investigated further.

• Proceedings of the Korean Geotechical Society Conference
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• 2004.03b
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• pp.509-516
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• 2004

The measurement of abnormal change of temperature(temperature anomaly) will help determine the safety of various engineering constructions, as the measurement in body often used to diagnose one's health. Temperature anomaly can be occurred in leakage or seepage of water flow in rocks, and in ground water table etc. Grouting materials injected in fractured rocks generate heat during hardening process. The degree of temperature change is associated directly with heat flow characteristics, that is, thermal conductivity, specific heat capacity. density of the surrounding rocks and can afford to assess the grouting efficiency. However, in practice, the use of traditional temperature measuring technique composed of only one single thermal sensor has been fundamentally limited to acquire thermal data sufficient to use for that, partly due to the time-consuming measuring work, partly due to the non-consecutive quality of data. Thus, in this paper, a new concept of temperature measuring technique, what we call, thermal line sensor technique is introduced. In this, the sensors with an accuracy of $0.02^{\circ}$ are inserted at regular intervals in one line cable and addressed by a control device, which enables to fundamentally enhance the capability of data acquisition in time and space. This new technology has been demonstrated on diverse field model experiments. The results were simply meant to be illustrative of a potential to be used for various kinds of temperature measurements encountered in grouting and leakage problems.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.14 no.8
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• pp.1836-1842
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• 2010

Sensor network, which is technology to realize the ubiquitous environment, recently, could apply to the field of Mechanic & electronic Security System, Energy management system, Environment monitoring system, Home automation and health care application. However, feature of wireless networking of sensor network is vulnerable to eavesdropping and falsification about message. Presently, PKC(public key cryptography) technique using ECC(elliptic curve cryptography) is used to build up the secure networking over sensor network. ECC is more suitable to sensor having restricted performance than RSA, because it offers equal strength using small size of key. But, for high computation cost, ECC needs to enhance the performance to implement over sensor. In this paper, we propose the optimizing technique for multiplication, core operation in ECC, to accelerate the speed of ECC.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.28 no.5A
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• pp.631-639
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• 2008

This paper reports the mode shapes of Seohae cable-stayed bridge extracted by TDD technique. In order to record total 72 acceleration points in the vertical direction of the bridge deck, a custom made data acquisition system with LAN communication has been especially developed and a set of ambient vibration tests has been conducted. For the measured acceleration responses, total twenty four mode shapes up to 2Hz has been extracted by TDD technique. The extracted mode shapes include many new modes that have not been identified in the current on-line health monitoring system installed in the bridge. It is confirmed that TDD technique is the most effective in extracting the high resolution mode shapes on a particularly long span bridge.

• Journal of Korean Society for Atmospheric Environment
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• v.34 no.3
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• pp.393-405
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• 2018

Volatile organic compounds (VOCs) are representative air pollutants due to their detrimental effects on human health and their role in formation of secondary organic aerosols. Assessments and monitoring programs of VOCs using periodic grab sampling like Tedlar bags, canisters, and sorbent traps provide limited information, often with delay times of days or weeks. Selected ion flow tube mass spectrometry (SIFT-MS) is an emerging analytical technique for the real-time quantification of VOCs in air. It relies on chemical ionization of the VOCs molecules in air introduced into helium carrier gas using $H_3O^+$, $NO^+$, and $O_2{^+}$ precursor ions. Real-time monitoring method of 60 VOCs in the ambient air was developed using TO-15 standard gas mixture. Calibration curves, method detection limit, and quantitation reproducibility of the target compounds were tested. Dynamic dilution system was used to dilute standard gas from 0.174 ppbv to 100 ppbv, where calibration curves showed good linearity with $r^2$> 0.95 in all target analytes. Limit of detection (LOD) all compounds were sub ppbv, and some halogenated compounds showed pptv levels. Seven consecutive analyses of target compounds showed good repeatability with relative standard deviation of less than 10%. One day monitoring of VOCs in ambient air was conducted in Geoje. Average concentration of target VOCs in Geoje were relatively lower than other regions, among which formaldehyde showed the highest concentration ($15.4{\pm}5.78ppbv$). SIFT-MS provided good temporal resolution data (1 data per 3.2 minute), which can be used for identifying ephemeral short-term event. It is expected that SIFT-MS will be a versatile monitoring platform for VOCs in ambient air.

• Journal of Environmental Health Sciences
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• v.27 no.3
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• pp.71-80
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• 2001

Blood and urine mercury level of three workers were monitored during 60~80 days after high exposure to mercury at the silver refining plant. Mercury was used to form silver-mercury amalgam from plating sludge. Workers were exposed to mercury about 70 days at the several processes, such as hand held weaving, vibration table, and heating from the furnace. mercury was analysed by atomic absorption spectroscopy-vapor generation technique. Recovery from the biological sample was 95.51% and pooled standard deviation was 0.033. At the time of study, there was no work at the workplace. So, airborne mercury concentration was measured with area sampling 5 days after the work, ranged from 0.1459 to 1.2351 mg/㎥(Arithmatic mean 0.4711 mg/㎥, Geometric mean 0.3566 mg/㎥) at the inside of the plant, that is far above the ACGIH's TLV(0.025 mg/㎥) and ranged from 0.0073 to 0.0330 mg/㎥ at the outdoor. Blood mercury levels at the beginning of the monitoring were 4~14 times greater than the American Conference of Governmental Industrial Hygienists Biological Exposure Index(ACGIH BEI, 15 ug/L). Blood mercury levels were decreased logarithmically, that is, rapidly at the high level and slowly at the low level but sustained above the level of the ACGIH BEI 60~80 days after the work. Urine mercury levels at the beginning of the monitoring were 8~16 times greater than the ACGIH BEI(35 ug/g creatinine). Urine mercury levels were decreased logarithmically, but correlation between urine level and off-days were lower than those of blood. Decreasing pattern of blood mercury levels were little affected than that of urine levels when the chelating agent, D-penicillamine, was administered. There was correlation between blood mercury level and urine mercury level(0.81~0.83) but it didn\`t mean that the highest blood mercury level corresponded the highest urine mercury level. In our study, Case 1 always shows the highest level in urine but case 3 always shows the highest level in blood. Creatinine correction represented better correlations between urine mercury levels and blood levels, and between urine levels and off-days rather than by urine volume. Spot urine sampling had a wide variation than that of whole day urine sampling. So, We recommend spot urine sampling for screening and whole day urine sampling for exact diagnosis.

• The Korean Journal of Physiology and Pharmacology
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• v.17 no.4
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• pp.299-306
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• 2013

Deep brain stimulation (DBS) of the subthalamic nucleus (STN) has been widely used as a treatment for the movement disturbances caused by Parkinson's disease (PD). Despite successful application of DBS, its mechanism of therapeutic effect is not clearly understood. Because PD results from the degeneration of dopamine neurons that affect the basal ganglia (BG) network, investigation of neuronal responses of BG neurons during STN DBS can provide informative insights for the understanding of the mechanism of therapeutic effect. However, it is difficult to observe neuronal activity during DBS because of large stimulation artifacts. Here, we report the observation of neuronal activities of the globus pallidus (GP) in normal and PD model rats during electrical stimulation of the STN. A custom artifact removal technique was devised to enable monitoring of neural activity during stimulation. We investigated how GP neurons responded to STN stimulation at various stimulation frequencies (10, 50, 90 and 130 Hz). It was observed that activities of GP neurons were modulated by stimulation frequency of the STN and significantly inhibited by high frequency stimulation above 50 Hz. These findings suggest that GP neuronal activity is effectively modulated by STN stimulation and strongly dependent on the frequency of stimulation.