• Smart Structures and Systems
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• v.24 no.3
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• pp.319-332
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• 2019

Structural health monitoring (SHM) is of great importance to super high-rise buildings. The Shanghai Tower is currently the tallest building in China, and a complete SHM system was simultaneously constructed at the beginning of the construction of the tower. Due to the variety of sensor types and the large number of measurement points in the SHM system, an online automatic structural health assessment method with few computations and no manual intervention is needed. This paper introduces a structural health assessment method for the Shanghai Tower that uses the coefficients of an autoregressive (AR) time series model as structural state indicators. An analysis of collected data indicates that the coefficients of the AR model are affected by environmental factors, and the principal component analysis method is used to remove the influence of environmental factors. Finally, the control chart method is used to track the changes in structural state indicators, and a plan for online automatic structure health state evaluation is proposed. This method is applied to long-term acceleration and inclination data from the Shanghai Tower and successfully identifies the changes in the structural state. Overall, the structural state indicators of the Shanghai Tower are stable, and the structure is in a healthy state.

• International Journal of High-Rise Buildings
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• v.4 no.1
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• pp.39-44
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• 2015

This paper presents the structural health monitoring (SHM) of Shanghai Tower. In order to provide useful information for safety evaluation and regular maintenance under construction and in-service condition, a comprehensive structural health monitoring (SHM) system is installed in Shanghai Tower, which is composed of a main monitoring station and eleven substations. Structural responses at different construction stages are measured using this SHM system and presented in this study. Meanwhile, a detailed finite element model (FEM) is created and comparison of results between SHM and FEM is carried out. Results indicate that the time-dependent property of concrete creep is of great importance to structural response and the measured data can be used in FEM updating to obtain more accurate FEM models at different construction stages. Therefore, installation of structural health monitoring system in super-tall buildings could be considered as an effective way to assure structural safety during the construction process.

• Smart Structures and Systems
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• v.18 no.2
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• pp.317-334
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• 2016

Structural Health Monitoring System (SHMS) works as an efficient platform for monitoring the health status and performance deterioration of engineering structures during long-term service periods. The objective of its installation is to provide reasonable suggestions for structural maintenance and management, and therefore ensure the structural safety based on the information extracted from the real-time measured data. In this paper, the SHMS implemented on a world-famous kilometer-level cable-stayed bridge, named as Sutong Cable-stayed Bridge (SCB), is introduced in detail. The composition and core functions of the SHMS on SCB are elaborately presented. The system consists of four main subsystems including sensory subsystem, data acquisition and transmission subsystem, data management and control subsystem and structural health evaluation subsystem. All of the four parts are decomposed to separately describe their own constitutions and connected to illustrate the systematic functions. Accordingly, the main techniques and strategies adopted in the SHMS establishment are presented and some extension researches based on structural health monitoring are discussed. The introduction of the SHMS on SCB is expected to provide references for the establishment of SHMSs on long-span bridges with similar features as well as the implementation of potential researches based on structural health monitoring.

• Smart Structures and Systems
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• v.15 no.1
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• pp.151-167
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• 2015

Instrumentation on structural health monitoring system imposes critical issues for applying the structural monitoring system to real world structures, for which not only on the configuration and geometry, but also aesthetics on the system to be monitored should be considered. To illustrate this point, two real world structural health monitoring systems, the structural health monitoring system of Shenzhen Vanke Center and the structural health monitoring system of Shenzhen Bay Stadium in China, are presented in the paper. The instrumentation on structural health monitoring systems of real world structures is addressed by providing the description of the structure, the purpose of the structural health monitoring system implementation, as well as details of the system integration including the installations on the sensors and acquisition equipment and so on. In addition, an intelligent algorithm on stress identification using measurements from multi-region is presented in the paper. The stress identification method is deployed using the fuzzy pattern recognition and Dempster-Shafer evidence theory, where the measurements of limited strain sensors arranged on structure are the input data of the method. As results, at the critical parts of the structure, the stress distribution evaluated from the measurements has shown close correlation to the numerical simulation results on the steel roof of the Beijing National Aquatics Center in China. The research work in this paper can provide a reference for the design and implementation of both real world structural health monitoring systems and intelligent algorithm to identify stress distribution effectively.

• Smart Structures and Systems
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• v.5 no.4
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• pp.469-482
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• 2009

The emerging sensor-based structural health monitoring (SHM) technology has a potential for cost-effective maintenance of aging civil infrastructure systems. The author proposes to integrate continuous and global monitoring using on-structure sensors with targeted local non-destructive evaluation (NDE). Significant technical challenges arise, however, from the lack of cost-effective sensors for monitoring spatially large structures, as well as reliable methods for interpreting sensor data into structural health conditions. This paper reviews recent efforts and advances made in addressing these challenges, with example sensor hardware and health monitoring software developed in the author's research center. The hardware includes a novel fiber optic accelerometer, a vision-based displacement sensor, a distributed strain sensor, and a microwave imaging NDE device. The health monitoring software includes a number of system identification methods such as the neural networks, extended Kalman filter, and nonlinear damping identificaiton based on structural dynamic response measurement. These methods have been experimentally validated through seismic shaking table tests of a realistic bridge model and tested in a number of instrumented bridges and buildings.

• Journal of Preventive Medicine and Public Health
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• v.28 no.1 s.49
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• pp.187-205
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• 1995

The purpose of this study was to determine the relationships among the health concern, health practice and health status of Koreans. This study utilized the data from Korean National Health Survey (KNHS) in 1992. The data consisted of random sample of 2,799 individuals (1,304 male and 1,495 females) whose ages were between 20 and 59. The data were analyzed using SAS version 6.04 and LISREL version 7.13. The analytic methods for the study were chi-square analysis and covariance structural analysis. The results of the study were as follows. (1) There were significant positive relationships between health concern level and health practice index, and between health practice index and self-perceived health status. (2) There were negative relationships between practice index and chronic illness, and between health practice index and acute illness only in female. (3) Based on the findings, the structural model of the health concern, health practice, health status and socioeconomic variables was established and then the covariance structural analysis was used. The higher educational level and economic status were, the higher the health concern was. And urban residents were much more concerned with their health than rural residents. The more persons were concerned with health, the more they did health practices. And the more the health practice was, the higher the health status was. The younger the persons were and the higher the health status of one's family was, the higher the health status was. In female, the higher the economic status was, the higher the health status was.

• BMB Reports
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• v.45 no.1
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• pp.44-46
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• 2012

Recent advances in high-throughput genotyping technologies have enabled us to conduct a genome-wide association study (GWAS) on a large cohort. However, analyzing millions of single nucleotide polymorphisms (SNPs) is still a difficult task for researchers conducting a GWAS. Several difficulties such as compatibilities and dependencies are often encountered by researchers using analytical tools, during the installation of software. This is a huge obstacle to any research institute without computing facilities and specialists. Therefore, a proper research environment is an urgent need for researchers working on GWAS. We developed BioSMACK to provide a research environment for GWAS that requires no configuration and is easy to use. BioSMACK is based on the Ubuntu Live CD that offers a complete Linux-based operating system environment without installation. Moreover, we provide users with a GWAS manual consisting of a series of guidelines for GWAS and useful examples. BioSMACK is freely available at http://ksnp.cdc.go.kr/biosmack.

• Genomics & Informatics
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• v.14 no.4
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• pp.216-221
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• 2016

Osteoporotic fractures (OFs) are critical hard outcomes of osteoporosis and are characterized by decreased bone strength induced by low bone density and microarchitectural deterioration in bone tissue. Most OFs cause acute pain, hospitalization, immobilization, and slow recovery in patients and are associated with increased mortality. A variety of genetic studies have suggested associations of genetic variants with the risk of OF. Genome-wide association studies have reported various single-nucleotide polymorphisms and copy number variations (CNVs) in European and Asian populations. To identify CNV regions associated with OF risk, we conducted a genome-wide CNV study in a Korean population. We performed logistic regression analyses in 1,537 Korean subjects (299 OF cases and 1,238 healthy controls) and identified a total of 8 CNV regions significantly associated with OF (p < 0.05). Then, one CNV region located on chromosome 20q13.12 was selected for experimental validation. The selected CNV region was experimentally validated by quantitative polymerase chain reaction. The CNV region of chromosome 20q13.12 is positioned upstream of a family of long non-coding RNAs, LINC01260. Our findings could provide new information on the genetic factors associated with the risk of OF.

• Journal of the Korean Society for Nondestructive Testing
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• v.32 no.3
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• pp.241-262
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• 2012

Some applications require structural health monitoring in inaccessible components. This paper presents a technique useful for Structural Health Monitoring of double wall structures, such as double wall steam pipes and double wall pressure vessels separated from an ultrasonic transducer by three layers. Detection has been demonstrated at distances in excess of one meter for a fixed transducer. The case presented here is for one of the layers, the middle layer, being a fluid. For certain transducer configurations the wave propagating in the fluid is a wave with low velocity and attenuation. The paper presents a model based on wave theory and finite element simulation; the experimental set-up and observations, and comparison between theory and experiment. The results provide a description of the technique, understanding of the phenomenon and its possible applications in Structural Health Monitoring.

• International Journal of High-Rise Buildings
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• v.12 no.4
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• pp.321-333
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• 2023

Structural health monitoring is a technology or research field that extends the service life of structures and contributes to the prevention of disaster accidents by continuously evaluating the safety, stability, and serviceability of structures as well as allowing timely and proper maintenance. However, the contact-type sensors used for it require considerable time, cost, and labor for installation and maintenance. As an alternative, computer vision has attracted attention recently. Computer vision has the potential to make quality, deformation, and damage monitoring for structures contactless and automated. In this study, research cases in which computer vision was utilized for structural health monitoring are introduced, and its effects and limitations are summarized. Therefore, the applicability and future research directions of computer vision-based structural health monitoring are discussed.