• Proceedings of the Computational Structural Engineering Institute Conference
• /
• 2006.04a
• /
• pp.21-28
• /
• 2006

Structural health monitoring (SHM) is a new technology that will be increasingly applied at the industrial field as a potential approach to improve cost and convenience of structural inspection. Recently, the development of smart sensor is very active for real application. This study has focused on preparation and application study of SAL sensor. In order to detect elastic wave, smart piezoelectric sensor, SAL, is fabricated by using a piezoelectric element, shielding layer and protection layer. This protection layer plays an important role in a patched network of distributed piezoelectric sensor and shielding treatment. Four types of SAL sensor are designed/prepared/tested, and these details will be discussed in the paper. In this study, SAL sensor can be feasibly applied to perform structural health monitoring and to detect damage sources which result in elastic waves.

• Structural Monitoring and Maintenance
• /
• v.1 no.1
• /
• pp.89-110
• /
• 2014

Structural Health Monitoring (SHM) is an effective alternative to conventional inspections which are time-consuming and subjective. SHM can detect damage early and reduce maintenance cost and thereby help reduce the likelihood of catastrophic structural events to infrastructure such as bridges. After reviewing the Damage Index Method (DIM), an Iterative Damage Index Method (IDIM) is proposed to improve the accuracy of damage detection. These two damage detection techniques are compared based on damage on two structures, a simply supported beam and a pedestrian bridge. Compared to the traditional damage detection algorithm, the proposed IDIM is shown to be less arbitrary and more accurate.

• Structural Engineering and Mechanics
• /
• v.31 no.5
• /
• pp.527-544
• /
• 2009

In this study, the periodic seismic performance evaluation scheme is proposed using a structural health monitoring system in terms of seismic fragility. An instrumented highway bridge is used to demonstrate the evaluation procedure involving (1) measuring ambient vibration of a bridge under general vehicle loadings, (2) identifying modal parameters from the measured acceleration data by applying output-only modal identification method, (3) updating a preliminary finite element model (obtained from structural design drawings) with the identified modal parameters using real-coded genetic algorithm, (4) analyzing nonlinear response time histories of the structure under earthquake excitations, and finally (5) developing fragility curves represented by a log-normal distribution function using maximum likelihood estimation. It is found that the seismic fragility of a highway bridge can be updated using extracted modal parameters and can also be monitored further by utilizing the instrumented structural health monitoring system.

• Smart Structures and Systems
• /
• v.12 no.3_4
• /
• pp.271-290
• /
• 2013

The acceleration information is significant for the structural health monitoring, which is the basic measurement to identify structural dynamic characteristics and structural vibration. The efficiency of the accelerometer is subsequently important for the structural health monitoring. In this paper, the distance measure matrix and the support level matrix are constructed firstly and the synthesized support level and the fusion method are given subsequently. Furthermore, the synthesized support level can be served as the determination for diagnosis on accelerometers, while the consensus data fusion method can be used to recover the acceleration information in frequency domain. The acceleration acquisition measurements from the accelerometers located on the real structure National Aquatics Center are used to be the basic simulation data here. By calculating two groups of accelerometers, the validation and stability of diagnosis and recovering on acceleration based on the data fusion are proofed in the paper.

• Proceedings of the Computational Structural Engineering Institute Conference
• /
• 2006.04a
• /
• pp.63-68
• /
• 2006

As a part of efforts to enhance construction technology, it is essential to obtain competitive technology which is future-oriented. In this paper, the current status of structural health monitoring techniques is reviewed. Also, ubiquitous system is expected in its use for further development and applications in construction.

• Journal of the Computational Structural Engineering Institute of Korea
• /
• v.21 no.6
• /
• pp.615-632
• /
• 2008

The bridge health monitoring has become an important research topic in conjunction with damage assessment and safety evaluation of structures owing to the improvement of structural modeling techniques incorporating response measurements and the advancements in signal analysis and information processing capabilities. The bridge monitoring systems are generally composed of hardwares such as sensors, data acquisition equipment, data transmission systems, etc, and softwares such as signal processing, damage assessment, display and management, etc. In this paper, the research and development(R&D) activities on the information processing for structural health monitoring of bridges are reviewed. After a brief introduction to the process of bridge health monitoring, various information processing techniques including various signal processing and damage detection algorithms are introduced in detail. Several challenges addressing critical issues in the current bridge health monitoring system and future R&D activities are discussed.

• Journal of the Korean Dietetic Association
• /
• v.25 no.2
• /
• pp.142-155
• /
• 2019

The aim of this study was to construct and test a structural equation model for the risk factors of metabolic syndrome in Korean adults. The structural equation model hypothesizes that eating alone and feeling depressed is a risk factor for metabolic syndrome. The data of this study were obtained from the Sixth Korea National Health and Nutrition Examination Survey which was cross-sectional data from the representative national survey. A total of 4,013 subjects replied to the survey item of lifestyle and completed the physical examinations among adults aged 19 years or older in South Korea was in 2015. The structural model in this study was composed of four latent variables: eating alone, depression, negative health behavior, and metabolic syndrome. Two variables, the rate of eating alone and depression, were exogenous variables. Negative health behavior was both a mediating variable and endogenous variable, and metabolic syndrome was the final endogenous variable. The data were analyzed using the Maximum Likelihood method and bootstrapping. The structural model was appropriate for the data based on the model fit indices. The results of this study can be summarized as follows: Eating alone is a direct risk factor of metabolic syndrome in Korean women. Depression can mediate metabolic syndrome through negative health behaviors. Negative health behavior had a direct impact on metabolic syndrome in both men and women. This study may be a guideline for interventions and strategies to reduce the incidence of metabolic syndrome in Korean adults.

• Smart Structures and Systems
• /
• v.25 no.3
• /
• pp.285-299
• /
• 2020

Long term structural health monitoring has gained wide attention among civil engineers in recent years due to the scale and severity of infrastructure deterioration. Establishing effective damage indicators and proposing enhanced monitoring methods are of great interests to the engineering practices. In the case of bridge health monitoring, long term structural vibration measurement has been acknowledged to be quite useful and utilized in the planning of maintenance works. Previous researches are majorly concentrated on linear time series models for the measurement, whereas nonlinear dependences among the measurement are not carefully considered. In this paper, a new bridge health monitoring method is proposed based on the use of long term vibration measurement. A combination of the fundamental ARMA model and copula theory is investigated for the first time in detecting bridge structural damages. The concept is applied to a real engineering practice in Japan. The efficiency and accuracy of the copula based damage indicator is analyzed and compared in different window sizes. The performance of the copula based indicator is discussed based on the damage detection rate between the intact structural condition and the damaged structural condition.

• Smart Structures and Systems
• /
• v.15 no.1
• /
• pp.99-117
• /
• 2015

The Stonecutters Bridge (SCB) in Hong Kong is the third-longest cable-stayed bridge in the world with a main span stretching 1,018 m between two 298 m high single-leg tapering composite towers. A Wind and Structural Health Monitoring System (WASHMS) is being implemented on SCB by the Highways Department of The Hong Kong SAR Government, and the SCB-WASHMS is composed of more than 1,300 sensors in 15 types. In order to establish a linkage between structural health monitoring and maintenance management, a Structural Health Rating System (SHRS) with relevant rating tools and indices is devised. On the basis of a 3D space frame finite element model (FEM) of SCB and model updating, this paper presents the development of an SHR-oriented 3D multi-scale FEM for the purpose of load-resistance analysis and damage evaluation in structural element level, including modeling, refinement and validation of the multi-scale FEM. The refined 3D structural segments at deck and towers are established in critical segment positions corresponding to maximum cable forces. The components in the critical segment region are modeled as a full 3D FEM and fitted into the 3D space frame FEM. The boundary conditions between beam and shell elements are performed conforming to equivalent stiffness, effective mass and compatibility of deformation. The 3D multi-scale FEM is verified by the in-situ measured dynamic characteristics and static response. A good agreement between the FEM and measurement results indicates that the 3D multi-scale FEM is precise and efficient for WASHMS and SHRS of SCB. In addition, stress distribution and concentration of the critical segments in the 3D multi-scale FEM under temperature loads, static wind loads and equivalent seismic loads are investigated. Stress concentration elements under equivalent seismic loads exist in the anchor zone in steel/concrete beam and the anchor plate edge in steel anchor box of the towers.

• Research in Community and Public Health Nursing
• /
• v.17 no.2
• /
• pp.153-165
• /
• 2006

Purpose: The purpose of this study was to develop and test a structural model on cardiovascular disease risk factors among male manufacturing workers. Methods: Data were collected through questionnaires and health exams from 201 workers in a local electronic company during September 2004. Data analysis was done with SAS 9.1 for descriptive statistics and PC-LISREL 8.54 for covariance structural analysis Results: The overall fit of the hypothetical model to the data was moderate, it was modified by deleting five paths. The modified model had a better fit to the data($x^2=504.23$(p<001, df: 180), $x^2/df=2.80$, GFI=.95, RMR=.07, NFI=.90, PGFI=.64). Health behaviors and psychosocial distress were found to have significant direct effects on the cardiovascular disease risk factors. Self-concept had direct effect on psychosocial distress or health behaviors. Self-concept, work environment, and work condition had direct effect on social support. Work environment had indirect effect on psychosocial distress. Social support had indirect effect on health behaviors. But work environment and work condition were found to have little direct effect on health behaviors, psychosocial distress or cardiovascular disease risk factors. Conclusion: A cardiovascular health promotion program should therefore include psycho-social factors as well as health behavioral determinants in worksites.