• 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.

• 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.

• 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.

• Proceedings of the KSR Conference
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• 2011.05a
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• pp.470-475
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• 2011

The objective of this study is the developement health & disaster monitoring measurement using ubiquitous active communication digital datalogger system for monitoring measurement of railway construction sites. For the replacement of current passive data communication, ubiquitous active communication digital datalogger system is studied for the first time with in a country. Therefore data communication method and analyzing program of automatic measurement data is developed for the global positioning automatic digital datalogger system. The results of this study will be using both real time automatic monitoring measurement and health & disaster monitoring measurement of railway structures.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.67 no.8
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• pp.1099-1105
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• 2018

Wireless sensor networks have been shown to be an effective method for health monitoring of civil structures. In this paper a wireless strain sensor system which will allow easier collection of accurate strain signals in small sized structures is described. The experiment result shows that the developed wireless sensor system and the proposed network system are fit for health & safety monitoring and control of structures.

• Earthquakes and Structures
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• v.8 no.3
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• pp.541-553
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• 2015

Structural Health Monitoring (SHM) systems can provide valuable information regarding the safety of structures during and after ground motions which can be used by authorities to reduce post-earthquake hazards. Strain gages as a key element play an important role in the success of SHM systems. Reducing the number of required strain gages while keeping the efficiency of SHM system not only can reduce the cost of structural health monitoring but also avoids storage and process of uninformative data. In this study, a method based on performance based seismic design of structures is proposed for ideal placement of stain gages in structures. The robustness and efficiency of the proposed method is demonstrated through installation of strain gages on an Airport Traffic Control (ATC) Tower. The obtained results show that the number of required strain gages decrease significantly.

• Structural Monitoring and Maintenance
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• v.3 no.3
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• pp.259-276
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• 2016

Historically the UK has been a pioneer and early adopter of experimental investigation techniques on new and operation structures, a technology that would now be descried as 'structural health monitoring' (SHM), yet few of these investigations have been enduring or carried out on the long span or tall structures that feature in flagship SHM applications in the Far East.

• Nuclear Engineering and Technology
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• v.55 no.8
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• pp.3039-3045
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• 2023

Fiber-reinforced polymer (FRP) composites are considered suitable candidates for structural materials of spacecrafts due to their excellent properties of high strength, light weight, and corrosion resistance. An online health monitoring method for FRP composites must be applied to space structures. However, the application of existing health monitoring methods to space structures is limited due to the harsh space environment. Here, carbon fiber-reinforced polymer (CFRP) composites embedded with fiber Bragg grating (FBG) sensors were prepared to explore the feasibility of strain monitoring using embedded FBG sensors in γ-radiation environment. The analysis of the influence of radiation on the strain monitoring demonstrated that the embedded FBG can be successfully applied to the health monitoring of FRP composites in radiation environment.

• Smart Structures and Systems
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• v.20 no.2
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• pp.163-173
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• 2017

Structural health monitoring (SHM) of civil infrastructure using fiber Bragg grating sensor networks (FBGSNs) has received significant public attention in recent years. However, there is currently little research on the health-monitoring technology of high-piled wharfs in coastal ports using the fiber Bragg grating (FBG) sensor technique. The benefits of FBG sensors are their small size, light weight, lack of conductivity, resistance corrosion, multiplexing ability and immunity to electromagnetic interference. Based on the properties of high-piled wharfs in coastal ports and servicing seawater environment and the benefits of FBG sensors, the SHM system for a high-piled wharf in the Tianjin Port of China is devised and deployed partly using the FBG sensor technique. In addition, the health-monitoring parameters are proposed. The system can monitor the structural mechanical properties and durability, which provides a state-of-the-art mean to monitor the health conditions of the wharf and display the monitored data with the BIM technique. In total, 289 FBG stain sensors, 87 FBG temperature sensors, 20 FBG obliquity sensors, 16 FBG pressure sensors, 8 FBG acceleration sensors and 4 anode ladders are installed in the components of the back platform and front platform. After the installation of some components in the wharf construction site, the good signal that each sensor measures demonstrates the suitability of the sensor setup methods, and it is proper for the full-scale, continuous, autonomous SHM deployment for the high-piled wharf in the costal port. The South 27# Wharf SHM system constitutes the largest deployment of FBG sensors for wharf structures in costal ports to date. This deployment demonstrates the strong potential of FBGSNs to monitor the health of large-scale coastal wharf structures. This study can provide a reference to the long-term health-monitoring system deployment for high-piled wharf structures in coastal ports.