• Earthquakes and Structures
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• 제22권2호
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• pp.185-201
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• 2022

Structural Health Monitoring (SHM) is used to provide reliable information about the structure's integrity in near realtime following extreme incidents such as earthquakes, considering the inevitable aging and degradation that occurs in operating environments. This paper experimentally investigates an integrated wireless sensor network (Wi-SN) based monitoring technique for damage detection in concrete structures. An effective SHM technique can be used to detect potential structural damage based on post-earthquake data. Two novel methods are proposed for damage detection in reinforced concrete (RC) building structures including: (i) Jerk Energy Method (JEM), which is based on time-domain analysis, and (ii) Modal Contributing Parameter (MCP), which is based on frequency-domain analysis. Wireless accelerometer sensors are installed at each story level to monitor the dynamic responses from the building structure. Prior knowledge of the initial state (immediately after construction) of the structure is not required in these methods. Proposed methods only use responses recorded during ambient vibration state (i.e., operational state) to estimate the damage index. Herein, the experimental studies serve as an illustration of the procedures. In particular, (i) a 3-story shear-type steel frame model is analyzed for several damage scenarios and (ii) 2-story RC scaled down (at 1/6th) building models, simulated and verified under experimental tests on a shaking table. As a result, in addition to the usual benefits like system adaptability, and cost-effectiveness, the proposed sensing system does not require a cluster of sensors. The spatial information in the real-time recorded data is used in global damage identification stage of SHM. Whereas in next stage of SHM, the damage is detected at the story level. Experimental results also show the efficiency and superior performance of the proposed measuring techniques.

• Journal of Ecology and Environment
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• 제38권3호
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• pp.307-318
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• 2015

The objectives of this study were to identify multi-level stressors from blood biomarkers to community-level bioindicators and diagnose the stream ecosystem health in polluted streams. Blood chemistry such as total protein ($T_{Pro}$), blood urea nitrogen ($B_{UN}$), total cholesterol ($T_{Cho}$) and $A_{lb}$umin ($A_{lb}$) were analyzed from sentinel fish tissues; the functions of kidney, gill and liver were significantly decreased in the impacted zone ($I_z$), compared to the control zone ($C_z$). Histopathological analysis showed that fish liver tissues were normal in the $C_z$. Fish liver tissues in the $I_z$, however, showed large cell necrosis and degeneration and also had moderate lobular inflammation and inflammatory cell infiltration of lymphocytic histocytes. Species biotic index (SBI) at species level and stream health assessment (SHA) at community level indicated that chemical impacts were evident in the $I_z$ (ecological health; poor - very poor), and this was matched with the blood tissue analysis and histopathological analysis. The impairments of the streams were supported by water chemistry analysis (nitrogen, phosphorus). Tolerance guild analysis and trophic guild analysis of fish were showed significant differences (P < 0.01) between $C_z$ and $I_z$. Overall, multiple parameter analysis from biomarker level (blood tissues) to bioindicator level (community health) showed significantly greater impacts in the $I_z$ than $C_z$. This approach may be effective as a monitoring tool in identifying the multilateral and forthcoming problems related to chemical pollution and habitat degradation of stream ecosystems.

• Smart Structures and Systems
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• 제15권3호
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• pp.699-715
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• 2015

A modal parameter based damage sensitive feature (DSF) is defined to mimic the relative change in any diagonal element of the stiffness matrix of a model of a structure. The damage assessment is performed in a statistical pattern recognition framework using empirical complementary cumulative distribution functions (ECCDFs) of the DSFs extracted from measured operational vibration response data. Methods are discussed to perform probabilistic structural health assessment with respect to the following questions: (a) "Is there a change in the current state of the structure compared to the baseline state?", (b) "Does the change indicate a localized stiffness reduction or increase?", with the latter representing a situation of retrofitting operations, and (c) "What is the severity of the change in a probabilistic sense?". To identify a range of normal structural variations due to environmental and operational conditions, lower and upper bound ECCDFs are used to define the baseline structural state. Such an approach attempts to decouple "non-damage" related variations from damage induced changes, and account for the unknown environmental/operational conditions of the current state. The damage assessment procedure is discussed using numerical simulations of ambient vibration testing of a bridge deck system, as well as shake table experimental data from a 4-story steel frame.

• Wind and Structures
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• 제37권6호
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• pp.445-460
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• 2023

Accurate estimation of modal parameters (i.e., natural frequency, damping ratio) of tall buildings is of great importance to their structural design, structural health monitoring, vibration control, and state assessment. Based on the combination of variational mode decomposition, smoothed discrete energy separation algorithm-1, and Half-cycle energy operator (VMD-SH), this paper presents a method for structural modal parameter estimation. The variational mode decomposition is proved to be effective and reliable for decomposing the mixed-signal with low frequencies and damping ratios, and the validity of both smoothed discrete energy separation algorithm-1 and Half-cycle energy operator in the modal identification of a single modal system is verified. By incorporating these techniques, the VMD-SH method is able to accurately identify and extract the various modes present in a signal, providing improved insights into its underlying structure and behavior. Subsequently, a numerical study of a four-story frame structure is conducted using the Newmark-β method, and it is found that the relative errors of natural frequency and damping ratio estimated by the presented method are much smaller than those by traditional methods, validating the effectiveness and accuracy of the combined method for the modal identification of the multi-modal system. Furthermore, the presented method is employed to estimate modal parameters of a full-scale tall building utilizing acceleration responses. The identified results verify the applicability and accuracy of the presented VMD-SH method in field measurements. The study demonstrates the effectiveness and robustness of the proposed VMD-SH method in accurately estimating modal parameters of tall buildings from acceleration response data.

• 한국인터넷방송통신학회논문지
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• 제10권5호
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• pp.31-37
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• 2010

본 논문은 홈 케어를 위해 생체 센서 시스템으로 홈 네트워크 시스템을 구성하여 생체 신호가 전달되도록 생체 신호 알고리즘을 구현하였다. 알고리즘의 구성 조건은 입력함수, 주파수 변화 함수, 변위 점 산출 발생 함수, 위치 변동 축 발생 함수, 축 변화 흔들림 변위(Sway Displacement)의 함수에서 변위치의 최대 값과 최소 값을 기준에 조정할 수 있는 단계로 주파수 변동이 0.01 단위로 변화가 있도록 조정하였다. 산출되는 항목은 맥박(Heart Rate), 체온(Temperature), 체중(Weight) 로 구성되고, 파형으로 신체적 균형정도를 확인하고 건강의 상태를 확인하도록 의미를 부여하였다. 본연구의 결과로 홈 네트워크를 통해 헬스 센터 및 건강관리 중앙 시스템에 단말기를 통해 전송된 알고리즘으로 홈 내 건강 관리시스템이 진행되는 결과를 얻을 수 있고, 다양한 신체적 파라메타를 통한 모니터링 기능을 갖춘 시스템관리가 형성 될 것으로 예상된다.

• 한국산학기술학회논문지
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• 제21권6호
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• pp.218-226
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• 2020

해상풍력터빈 하부구조물은 중요한 기능의 수행, 접근성의 제약 등으로 인하여 건전성 모니터링을 통한 효과적 유지관리가 필요하다. 본 연구에서는 해상풍력터빈 트라이포드 하부구조물의 건전성 모니터링을 위한 기저모델개선 및 결함추정 기법을 실험적으로 연구한다. 우선 하부구조물 건전성 모니터링을 위한 절차를 제안한 후 이 과정을 트라이포드 하부구조물 축소모형에 대하여 적용한다. 즉, 축소모형에 대한 초기 기저모델을 수치적으로 수립한 후 모드특성을 추정하고, 건전상태 진동실험 결과로부터 구한 고유주파수와 모드형상을 기준으로 기저모델을 개선하는데, 이때 구조물의 경계조건을 고려하고 신경망기법을 이용한다. 이후, 개선된 기저모델을 이용하여 신경망의 훈련패턴을 생성하고, 손상상태 진동실험 결과로부터 구한 모드특성을 훈련된 신경망에 입력함으로써 결함을 추정한다. 유효고정부 모델을 이용하여, 건전상태에서 측정된 모드특성에 맞추어 합리적으로 기저모델을 수립할 수 있었다. 또한, 축소모형에 대한 손상실험을 수행하였는데, 4가지 손상경우에 대하여 손상을 추정한 결과, 합리적으로 손상위치를 추정할 수 있었으며, 실제 손상정도가 심해질수록 손상정도 추정치도 증가하였다. 그러나 손상정도가 상대적으로 미소한 경우, 해당 손상위치가 판정은 되지만 다른 위치와 비교하여 확실한 손상위치의 식별이 어려웠다. 향후, 이러한 미소손상 추정 및 손상정도 추정치의 강성감소에 대한 정량화 등에 대한 후속연구가 수반된다면, 해상풍력터빈 트라이포드 하부구조물의 건전성 모니터링에 제안 기법을 효과적으로 활용할 수 있을 것으로 판단된다.

• 한국산업보건학회지
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• 제6권2호
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• pp.272-280
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• 1996

This study was to evaluate the associations between urinary S-Phenyl-mercapturic acid(S-PMA) as a new indicator of biological monitoring for low level of exposure to benzene and independent variables such as the air concentration of benzene in the breathing zone of workers, the years of work, and smoking. In this study the subjects were the total of 145 drawn from 53 workers who were occupationally exposed to benzene and 92 workers who were not. The results were as follows: 1. In the workplace geometric mean concentration of benzene in the breathing zone of workers was 0.31 ppm(0.02 - 3.26 ppm) for the spraying workers and 0.25 ppm(0.02 - 3.95 ppm) for the printing workers. 2. The geometric mean of uninary S-PMA for non exposed group was $8.9{\mu}g/g$ creatinine($0.6-72.3{\mu}g/g$ creatinine), 80.3% (74 workers) of the total non-exposed workers indicated less than $20{\mu}g/g$ creatinine of uninary S-PMA. The difference of uninary S-PMA by sex, age, smoking was not significant. 3. The geometric mean of urinary S-PMA for workers who were exposed to benzene was $37.2{\mu}g/g$ creatinine, and was four times higher than that of workers who were not exposed. And 79.3% (42 workers) of the total exposed workers indicated more than $20{\mu}g/g$ creatinine of urinary S-PMA. 4. Regarding the level of benzene in the air, urinary S-PMA was the highest level of $147.9{\mu}g/g$ creatinine in the workers who were exposed to air concentration of 0.5 ppm of benzene and was higher as the level in the air was increased. 5. The correlation coefficient between log urinary S-PMA and log benzene concentration in the breathing zone was 0.80, and the following linear equation was found between urinary log S-PMA and log benzene concentration in the breathing zone : log S-PMA(${\mu}g/g$ creatinine) = 0.564 log benzene in air(ppm) + 0.192 (n=53, r=0.80, p=0.000) In conclusion, the concentration of S-PMA in urine proved to be good parameter for biological monitoring benzene exposure at the workplace even at low level of benzene in air.

• Structural Monitoring and Maintenance
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• 제2권1호
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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.

• Environmental Analysis Health and Toxicology
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• 제20권4호통권51호
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• pp.311-325
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• 2005

A chemical ranking and scoring system, CRS - Korea, has recently been developed and proposed to use to prioritize on a screening level the toxic chemicals for monitoring and risk assessment. As CRS-Korea requires rigorous assessments prior to its wide application, an assessment was conducted in this study by examining the contribution of individual parameter score to the final chemical score or ranking. The sensitivity of the system to the default values for various parameters of missing data was also tested. The chemical ranking/score was round to depend primarily on the score of a single parameter, i. e., the chemical release, while toxicity scores show little correlation with the priority Further analysis indicated that the dominating effect of the chemical release results from i) its multiplicative relationship with the other two exposure parameters (biodegradation and persistent) and ii) the fact that a maximum score of 10 was assigned to the chemical release parameter while 5 was assigned for all others. AE the fraction of the data that are missing exceeded $70\%$ for various toxicity parameters at compared to less than $10\%$ for exposure parameters, the sensitivity of the ranking to the default value was not significant (rank correlation coefficient = 0.98) for toxicity parameters. Bated on this assessment, an improved CRS system (CRS - Korea II) was proposed in which the impact of the chemical release was properly adjusted by changing the multiplicative relationship to additive one and the maximum score to 5. Chemical priority was derived for each of 16 provinces by using CRS-Korea II. The chemical priority was found to significantly vary among the provinces. It was concluded that not only the national chemical priority but the local chemical priority should be taken into account in setting the nationwide chemical monitoring and risk assessment strategy.

• 한국환경보건학회지
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• 제42권4호
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• pp.280-292
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• 2016

Objectives: The objective of this study was to build COD regression models for the Han River and evaluate water quality. Methods: Water quality data sets for the dry season (as of January) during a four-year period (2012-2015) were collected from the database of the Han River automatic water quality monitoring stations. Statistical techniques, including combined genetic algorithm-multiple linear regression (GA-MLR) were used to build five-descriptor COD models. Multivariate statistical techniques such as principal component analysis (PCA) and cluster analysis (CA) are useful tools for extracting meaningful information. Results: The $r^2$ of the best COD models provided significant high values (> 0.8) between 2012 and 2015. Total organic carbon (TOC) was a surrogate indicator for COD (as COD/TOC) with high reliability ($r^2=0.63$ in 2012, $r^2=0.75$ for 2013, $r^2=0.79$ for 2014 and $r^2=0.85$ for 2015). The ratios of COD/TOC were calculated as 2.08 in 2012, 1.79 in 2013, 1.52 and 1.45 in 2015, indicating that biodegradability in the water body of the Han River was being sustained, thereby further improving water quality. The BOD/COD ratio supported these findings. The cluster analysis revealed higher annual levels of microorganisms and phosphorous at stations along the Hangang-Seoul and Hantangang areas. Nevertheless, the overall water quality over the last four years showed an observable trend toward continuous improvement. These findings also suggest that non-point pollution control strategies should consider the influence of upstreams and downstreams to protect water quality in the Han River. Conclusion: This data analysis procedure provided an efficient and comprehensive tool to interpret complex water quality data matrices. Results from a trend analysis provided much important information about sources and parameters for Han River water quality management.