• Structural Monitoring and Maintenance
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• v.10 no.3
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• pp.261-281
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• 2023

Magnetic flux sensors are commonly used in monitoring the cable force, but the application of the sensors in large diameter non-closed Galfan cables, as those adopted in Yueqing Gymnasium which is located in Yueqing City, Zhejiang Province, China and is the largest span hybrid space structure in the world, is seldom done in engineering. Based on the construction of Yueqing Gymnasium, this paper studies the cable tension monitoring using the magnetic flux method across two stages, namely, the pre-calibration stage before the cable leaves the rigging factory and the field tension formation stage of the cable system. In the pre-calibration stage in the cable factory, a series of 1:1 full-scale comparative tests were carried out to study the feasibility and relability of this kind of monitoring method, and the influence on the monitoring results of charging and discharging voltage, sensor location, cable diameter and fitting method were also studied. Some meaningful conclusions were obtained. On this basis, the real-time cable tension monitoring system of the structure based on the magnetic flux method is established. During the construction process, the monitoring results of the cables are in good agreement with the data of the on-site pressure gauge.The work of this paper will provide a useful reference for cable force monitoring in the construction process of long-span spatial structures.

• Smart Structures and Systems
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• v.8 no.1
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• pp.119-137
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• 2011

A bio-inspired two-mode structural health monitoring (SHM) system based on the Na$\ddot{i}$ve Bayes (NB) classification method is discussed in this paper. To implement the molecular biology based Deoxyribonucleic acid (DNA) array concept in structural health monitoring, which has been demonstrated to be superior in disease detection, two types of array expression data have been proposed for the development of the SHM algorithm. For the micro-vibration mode, a two-tier auto-regression with exogenous (AR-ARX) process is used to extract the expression array from the recorded structural time history while an ARX process is applied for the analysis of the earthquake mode. The health condition of the structure is then determined using the NB classification method. In addition, the union concept in probability is used to improve the accuracy of the system. To verify the performance and reliability of the SHM algorithm, a downscaled eight-storey steel building located at the shaking table of the National Center for Research on Earthquake Engineering (NCREE) was used as the benchmark structure. The structural response from different damage levels and locations was collected and incorporated in the database to aid the structural health monitoring process. Preliminary verification has demonstrated that the structure health condition can be precisely detected by the proposed algorithm. To implement the developed SHM system in a practical application, a SHM prototype consisting of the input sensing module, the transmission module, and the SHM platform was developed. The vibration data were first measured by the deployed sensor, and subsequently the SHM mode corresponding to the desired excitation is chosen automatically to quickly evaluate the health condition of the structure. Test results from the ambient vibration and shaking table test showed that the condition and location of the benchmark structure damage can be successfully detected by the proposed SHM prototype system, and the information is instantaneously transmitted to a remote server to facilitate real-time monitoring. Implementing the bio-inspired two-mode SHM practically has been successfully demonstrated.

• 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.

• IEMEK Journal of Embedded Systems and Applications
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• v.7 no.6
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• pp.331-338
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• 2012

This paper presents a wireless sensor network protocol aimed for artificial structure monitoring. The proposed protocol enables the sensor network to operate at a low duty cycle for reducing power consumption with a high degree of synchronization accuracy. It also enables event-triggered measurement of environmental information with a high sampling rate and the transmission of the measured data with a low latency. The feasibility of the proposed protocol is demonstrated through experiments involving three sensor nodes and a sink node. Though a tunnel health monitoring was considered in the paper, the proposed protocol can be easily adopted in other areas.

• 한국방재학회:학술대회논문집
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• 2007.02a
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• pp.429-432
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• 2007

For smart structure technologies, the interests in wireless sensor networks for structural health monitoring are growing. The wireless sensor networks reduce the installation of the wire embedded in the whole structure and save the costs. But the wireless sensor networks have lots of limits and there are lots of researches and developments of wireless sensor and the network for data process. Most of the researches of wireless sensor network is applying to the civil engineering structure and the researches for the highrise building are required. And strain-based SHM gives the local damage information of the structures which acceleration-based SHM can not. In this paper, concept of wireless sensor network for structural health monitoring of highrise building is suggested. And verifying the feasibility of the strain-based SHM a strain sensor board has developed and tested by experiments.

• Journal of Korea Society of Digital Industry and Information Management
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• v.6 no.2
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• pp.29-38
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• 2010

It often occur to nature disaster that like earthquake, typhoon, etc. around KOREA. A Haiti and Chile also metropolitan area of KOREA occur earthquake. in result, People think of nature disaster. Structures of present age are easily affected by nature disaster. So we are important that warn of dangerous situation as soon as possible. On this study, I introduce Integrated monitoring system that administrator check a event as early. I develop Monitoring System using SMS(Short Message Service). Administrator always monitor structure on real-time using mobile web-page. As Administrator using mobile device like PDA, Administrator always monitor structure. As using this system, Damage of nature disaster is minimized and is prevented post damage.

• Journal of Communications and Networks
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• v.11 no.4
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• pp.350-358
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• 2009

In a wireless sensor network (WSN) setting, this paper presents a distributed decision-making framework and illustrates its application in an online structural health monitoring (SHM) system. The objective is to recover a damage severity vector, which identifies, localizes, and quantifies damages in a structure, via distributive and collaborative decision-making among wireless sensors. Observing the fact that damages are generally scarce in a structure, this paper develops a nonlinear 0-norm minimization formulation to recover the sparse damage severity vector, then relaxes it to a linear and distributively tractable one. An optimal algorithm based on the alternating direction method of multipliers (ADMM) and a heuristic distributed linear programming (DLP) algorithm are proposed to estimate the damage severity vector distributively. By limiting sensors to exchange information among neighboring sensors, the distributed decision-making algorithms reduce communication costs, thus alleviate the channel interference and prolong the network lifetime. Simulation results in monitoring a steel frame structure prove the effectiveness of the proposed algorithms.

• Journal of Ocean Engineering and Technology
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• v.24 no.1
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• pp.90-98
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• 2010

In this paper, vibration-based structural health monitoring methods that are suitable for caisson-type structures are examined by an experimental evaluation. To achieve the objective, four approaches are implemented. First, vibration-based structural health monitoring methods are selected to monitor the structural condition of caisson-type breakwaters. Second, a lab-scaled caisson structure is constructed to verify the selected monitoring methods. Third, the vibration characteristics are numerically analyzed using an FE model due to the change in the rubble mound condition. Finally, experimental vibration tests of the lab-scaled caisson structure are performed to monitor the vibration responses due to changes in rubble mound conditions and the performances of the selected methods are examined from the monitoring results.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.23 no.1
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• pp.18-25
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• 2011

This study presents the damage monitoring method in foundation-structure interface of harbor caisson using vibration-based autoregressive (AR) model. In order to achieve the objective, the following approaches are implemented. Firstly, vibration-based AR model is selected to monitor the damage in foundation-structure interface of caisson structure. Secondly, finite element analysis on a caisson structure model is implemented to evaluate the vibration-based damage monitoring method. Finally, vibration test on a caisson structure model is performed to evaluate applicability of vibration-based AR model method for foundation-structure interface of caisson structure.

• 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.