• Computers and Concrete
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• v.8 no.3
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• pp.293-309
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• 2011

A long-term structural health monitoring (SHM) system comprising over 700 sensors of sixteen types has been implemented on the Guangzhou Television and Sightseeing Tower (GTST) of 610 m high for real-time monitoring of the structure at both construction and service stages. As part of this sophisticated SHM system, 48 temperature sensors have been deployed at 12 cross-sections of the reinforced concrete inner structure of the GTST to provide on-line monitoring via a wireless data transmission system. In this paper, the differential temperature profiles in the reinforced concrete inner structure of the GTST, which are mainly caused by solar radiation, are recognized from the monitoring data with the purpose of understanding the temperature-induced structural internal forces and deformations. After a careful examination of the pre-classified temperature measurement data obtained under sunny days and non-sunny days, common characteristic of the daily temperature variation is observed from the data acquired in sunny days. Making use of 60-day temperature measurement data obtained in sunny days, statistical patterns of the daily rising temperature and daily descending temperature are synthesized, and temperature distribution models of the reinforced concrete inner structure of the GTST are formulated using linear regression analysis. The developed monitoring-based temperature distribution models will serve as a reliable input for numerical prediction of the temperature-induced deformations and provide a robust basis to facilitate the design and construction of similar structures in consideration of thermal effects.

• Journal of the Korea institute for structural maintenance and inspection
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• v.10 no.2
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• pp.191-202
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• 2006

Computer programs for a structure design help the optimum design that considers each condition. however, the findings can not explain accurately a behavior of the real-living structure because each condition of a structure is simplified and generalized. The smart structure is introduced to overcome these problems, and we can understand a behavior of the real-living structure by means of Health Monitoring System. In this study, we compare a behavior by means of the existing structure design with a behavior of the living structure by means of an experiment. As a result, we examine adequacy of a measuring system and developing possibility in the future.

• Journal of the Korean Society for Nondestructive Testing
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• v.32 no.6
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• pp.648-660
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• 2012

Reliable response measurements are extremely important for proper bridge health monitoring but incomplete and unreliable data may be acquired due to sensor problems and environmental effects. In the case of a sensor malfunction, parts of the measured data can be missing so that the structural health condition cannot be monitored reliably. This means that the dynamic characteristics of natural frequencies can change as if the structure is damaged due to environmental effects, such as temperature variations. To overcome these problems, this paper proposes a systematic procedure of data analysis to recover missing data and eliminate the environmental effects from the measured data. It also proposes a health index calculated statistically using revised data to evaluate the health condition of a bridge. The proposed method was examined using numerically simulated data with a truss structure and then applied to a set of field data measured from a cable-stayed bridge.

• Journal of the Korean Society for Railway
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• v.6 no.4
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• pp.232-238
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• 2003

A health monitoring system becomes a very useful tool to obtain information on long term behavior of the important railway structures such as very long span and special type bridges. It can be also used to give a warning signal to the maintenance engineer when the structure shows abnormal behavior. However, due to long term use and temperature changes, the health monitoring system needs to be calibrated periodically. In this study, calibration and gauge factor readjustment process made for the health monitoring system installed in the railroad bridges and tunnel are reviewed and a few findings are updated. Future work will be concentrated on the long-term analysis of the measurement data and on the database structures so that the assessment of the structure is possible

• Structural Monitoring and Maintenance
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• v.3 no.1
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• pp.71-90
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• 2016

The paper reports a wide overview of the scientific activities on Structural Health Monitoring (SHM) in Italy. They are classified on three different conceptual scales: national territory (macro); regional area (medium); single structure (small). In the latter case differences have been pointed out between permanent installation and short-term experimental campaigns. A particular focus has been dedicated to applications devoted to cultural heritage which have an important historic, strategic and economic value for Italy. Two specific cases, the first related to the permanent monitoring of an historical Basilica and the second regarding the dynamic testing of a modern structure, have been presented as a basis for a general discussion.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2016.10a
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• pp.130-131
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• 2016

This study was performed for application of Structural Health Monitoring system of large structures. In order to evaluate damage of a structure, strain data of truss members that are changing with damage are gained by FEM analysis program. These data are used to train Artificial Neural Network(ANN), and this ANN algorithm can be used to analysis strain data for evaluating damage of the truss members.

• Structural Engineering and Mechanics
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• v.30 no.2
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• pp.191-209
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• 2008

A structural monitoring system based on cheap and wireless monitoring system is investigated in this paper. Due to low-cost and low power consumption, micro-electro-mechanical system (MEMS) is suitable for wireless monitoring and the use of MEMS and wireless communication can reduce system cost and simplify the installation for structural health monitoring. For system identification using wireless MEMS, a finite element (FE) model updating method through correlation with the initial analytical model of the structure to the measured one is used. The system identification using wireless MEMS is evaluated experimentally using a three storey frame model. Identification results are compared to ones using data measured from traditional accelerometers and results indicate that the system identification using wireless MEMS estimates system parameters with reasonable accuracy. Another smart sensor considered in this paper for structural health monitoring is Lead Zirconate Titanate (PZT) which is a type of piezoelectric material. PZT patches have been applied for the health monitoring of structures owing to their simultaneous sensing/actuating capability. In this paper, the system identification for building structures by using PZT patches functioning as sensor only is presented. The FE model updating method is applied with the experimental data obtained using PZT patches, and the results are compared to ones obtained using wireless MEMS system. Results indicate that sensing by PZT patches yields reliable system identification results even though limited information is available.

• Smart Structures and Systems
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• v.17 no.1
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• pp.135-147
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• 2016

This paper describes a smart structural system, which uses smart materials for real-time monitoring and active control of bolted-joints in steel structures. The goal of this research is to reduce the possibility of failure and the cost of maintenance of steel structures such as bridges, electricity pylons, steel lattice towers and so on. The concept of the smart structural system combines impedance based health monitoring techniques with a shape memory alloy (SMA) washer to restore the tension of the loosened bolt. The impedance-based structural health monitoring (SHM) techniques were used to detect loosened bolts in bolted-joints. By comparing electrical impedance signatures measured from a potentially damage structure with baseline data obtained from the pristine structure, the bolt loosening damage could be detected. An outlier analysis, using generalized extreme value (GEV) distribution, providing optimal decision boundaries, has been carried out for more systematic damage detection. Once the loosening damage was detected in the bolted joint, the external heater, which was bonded to the SMA washer, actuated the washer. Then, the heated SMA washer expanded axially and adjusted the bolt tension to restore the lost torque. Additionally, temperature variation due to the heater was compensated by applying the effective frequency shift (EFS) algorithm to improve the performance of the diagnostic results. An experimental study was conducted by integrating the piezoelectric material based structural health monitoring and the SMA-based active control function on a bolted joint, after which the performance of the smart 'self-monitoring and self-healing bolted joint system' was demonstrated.

• Smart Structures and Systems
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• v.29 no.4
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• pp.561-576
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• 2022

Heritage timber structures represent the history and culture of a nation. These structures have been inherited from previous generations; however, they inevitably exhibit deterioration over time, potentially leading to structural deficiencies. Structural Health Monitoring (SHM) offers the potential to assess operational anomalies, deterioration, and damage through processing and analysis of data collected from transducers and sensors mounted on the structure. This paper reports on the design and implementation of a long-term SHM system on the Feiyun Wooden Pavilion in China, a three-story timber building built more than 500 years ago. The principles and features of the design and implementation of SHM systems for heritage timber buildings are systematically discussed. In total, 104 sensors of 6 different types are deployed on the structure to monitor the environmental effects and structural responses, including air temperature and humidity, wind speed and direction, structural temperatures, strain, inclination, and acceleration. In addition, integrated data acquisition and transmission subsystem using a newly developed software platform are implemented. Selected preliminary statistical and correlation analysis using one year of monitoring data are presented to demonstrate the condition assessment capability of the system based on the monitoring data.

• Journal of the Society of Disaster Information
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• v.18 no.4
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• pp.847-860
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• 2022

Purpose: The purpose of this paper is to present a basic study on the development of a self-generation infrastructure for monitoring the health of harbour structures. Method: By developing a self-generation system and fiber optic sensors for seawater, the study provides basic research data on port structure health monitoring. Result: Through sunlight simulation analysis, 4-5 hours of sunlight can be secure in the domestic environment. Through this, the optical splitter (Introgate) that collects the raw data from the FBG sensor applicable to seawater, the MCU that calculates it, the IoT module with wireless communication functionality, the monitoring server and the supply system are set up. Conclusion: Monitoring port structures directly with fiber optic probes (FBG) and the possibility of using selfpowered systems were confirmed.