• 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.

• Structural Monitoring and Maintenance
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• v.1 no.1
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• pp.47-67
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• 2014

This study has been motivated to examine the performance of a wireless sensor system under the typhoons as well as to analyze the effect of the typhoons on the bridge's vibration responses and the variation of cable forces. During the long-term field experiment on a real cable-stayed bridge in years 2011-2012, the bridge had experienced two consecutive typhoons, Bolaven and Tembin, and the wireless sensor system had recorded data of wind speeds and vibration responses from a few survived sensor nodes. In this paper, the wireless structural health monitoring of stay cables under the two consecutive typhoons is presented. Firstly, the wireless monitoring system for cable-stayed bridge is described. Multi-scale vibration sensor nodes are utilized to measure both acceleration and PZT dynamic strain from stay cables. Also, cable forces are estimated by a tension force monitoring software based on vibration properties. Secondly, the cable-stayed bridge with the wireless monitoring system is described and its wireless monitoring capacities for deck and cables are evaluated. Finally, the structural health monitoring of stay cables under the attack of the two typhoons is described. Wind-induced deck vibration, cable vibration and cable force variation are examined based on the field measurements in the cable-stayed bridge under the two consecutive typhoons.

• Smart Structures and Systems
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• v.15 no.6
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• pp.1625-1642
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• 2015

We propose an electrically self-reliant structural health monitoring (SHM) system that is able to wirelessly transmit sensing data using electrical power generated by vibration without the need for additional external power sources. The provision of reliable electricity to wireless SHM systems is a highly important issue that has often been ignored, and to expand the applicability of various wireless SHM innovations, it will be necessary to develop comprehensive wireless SHM devices including stable electricity sources. In light of this need, we propose a new, highly efficient vibration-powered generator based on a tuned-mass-damper (TMD) mechanism that is quite suitable for vibration-based SHM. The charging time of the TMD generator is shorter than that of conventional generators based on the impedance matching method, and the proposed TMD generator can harvest 16 times the amount of energy that a conventional generator can. The charging time of an SHM wireless transmitter is quantitatively formulated. We conduct wireless monitoring experiments to validate a wireless SHM system composed of a self-reliant SHM and a vibration-powered TMD generator.

• Smart Structures and Systems
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• v.6 no.3
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• pp.335-347
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• 2010

Recent advances in hardware and instrumentation technology have allowed the possibility of deploying very large sensor arrays on structures. Exploiting the huge amount of data that can result in order to perform vibration-based structural health monitoring (SHM) is not a trivial task and requires research into a number of specific problems. In terms of pressing problems of interest, this paper discusses: the design and optimisation of appropriate sensor networks, efficient data reduction techniques, efficient and automated feature extraction methods, reliable methods to deal with environmental and operational variability, efficient training of machine learning techniques and multi-scale approaches for dealing with very local damage. The paper is a result of the ESF-S3T Eurocores project "Smart Sensing For Structural Health Monitoring" (S3HM) in which a consortium of academic partners from across Europe are attempting to address issues in the design of automated vibration-based SHM systems for structures.

• Journal of Korean Society of Water and Wastewater
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• v.35 no.5
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• pp.335-349
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• 2021

As the frequency of seismic disasters in Korea has increased rapidly since 2016, interest in systematic maintenance and crisis response technologies for structures has been increasing. A data-based leading management system of Lifeline facilities is important for rapid disaster response. In particular, the water supply network, one of the major Lifeline facilities, must be operated by a systematic maintenance and emergency response system for stable water supply. As one of the methods for this, the importance of the structural health monitoring(SHM) technology has emerged as the recent continuous development of sensor and signal processing technology. Among the various types of SHM, because all machines generate vibration, research and application on the efficiency of a vibration-based SHM are expanding. This paper reviews a vibration-based pipeline SHM system for seismic disaster response of water supply pipelines including types of vibration sensors, the current status of vibration signal processing technology and domestic major research on structural pipeline health monitoring, additionally with application plan for existing pipeline operation system.

• Smart Structures and Systems
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• v.6 no.7
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• pp.811-833
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• 2010

Vibration control and health monitoring of building structures have been actively investigated in recent years but treated separately according to the primary objective pursued. This paper presents a general approach in the time domain for integrating vibration control and health monitoring of a building structure to accommodate various types of control devices and on-line damage detection. The concept of the time-domain approach for integrated vibration control and health monitoring is first introduced. A parameter identification scheme is then developed to identify structural stiffness parameters and update the structural analytical model. Based on the updated analytical model, vibration control of the building using semi-active friction dampers against earthquake excitation is carried out. By assuming that the building suffers certain damage after extreme event or long service and by using the previously identified original structural parameters, a damage detection scheme is finally proposed and used for damage detection. The feasibility of the proposed approach is demonstrated through detailed numerical examples and extensive parameter studies.

• Smart Structures and Systems
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• v.4 no.2
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• pp.195-208
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• 2008

This paper summarizes the experimental vibration-based structural health monitoring study on a historical monument in Jordan. In this work, and within the framework of the European Commission funded project "wide-Range Non-Intrusive Devices Toward Conservation of Historical Monuments in the Mediterranean Area", a seven and a half century old minaret located in Ajloun (73 km north of the capital Amman) is studied. Because of their cultural value, touristic importance and the desire to preserve them for the future, only non-destructive tests were allowed for the experimental investigation of such heritage structures. Therefore, after dimensional measurements and determination of the current state of damage in the selected monument, ambient vibration tests are conducted to measure the accelerations at strategic locations of the system. Output-only modal identification technique is applied to extract the modal parameters such as natural frequencies and mode shapes. A Non-linear version of SAP 2000 computer program is used to develop a three-dimensional finite element model of the minaret. The developed numerical model is then updated according to the modal parameters obtained experimentally by the ambient-vibration test-results and the measured characteristics of old stone and deteriorated mortar. Moreover, a parametric identification method using the N4Sid state space model is employed to model the dynamic behavior of the minaret and to build up a robust, immune and noise tolerant model.

• Journal of the Korean Society for Nondestructive Testing
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• v.26 no.6
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• pp.373-379
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• 2006

Vibration-based structural health monitoring is one of non-destructive evaluation (NDE) techniques for civil infrastructures. This paper presents a novel fiber optic accelerometer system to monitor civil engineering structures and a successful application of the novel sensor system for measuring ambient vibration of a real building structure. This sensor system integrates the Moire fringe phenomenon with fiber optics to achieve accurate and reliable measurements. The sensor system is immune to electromagnetic (EM) interference making it suitable for difficult applications in such environments involving strong EM fields, electrical spark-induced explosion risks, and cabling problems, prohibiting the use of conventional electromagnetic accelerometers. A prototype sensor system has been developed, together with a signal processing software. The experimental studies demonstrated the high-performance of the fiber optic sensor system. Especially, the sensor was successfully used for monitoring a real building on UCI (University of California Irvine, USA).

• Smart Structures and Systems
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• v.30 no.6
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• pp.557-569
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• 2022

Vibration-based structural health monitoring (SHM) is crucial for the dynamic maintenance of civil building structures to protect property security and the lives of the public. Analyzing these vibrations with modern artificial intelligence and deep learning (DL) methods is a new trend. This paper proposed an unsupervised deep learning method based on a convolutional autoencoder (CAE), which can overcome the limitations of conventional supervised deep learning. With the convolutional core applied to the DL network, the method can extract features self-adaptively and efficiently. The effectiveness of the method in detecting damage is then tested using a benchmark model. Thereafter, this method is used to detect damage and instant disaster events in a rubber bearing-isolated gymnasium structure. The results indicate that the method enables the CAE network to learn the intact vibrations, so as to distinguish between different damage states of the benchmark model, and the outcome meets the high-dimensional data distribution characteristics visualized by the t-SNE method. Besides, the CAE-based network trained with daily vibrations of the isolating layer in the gymnasium can precisely recover newly collected vibration and detect the occurrence of the ground motion. The proposed method is effective at identifying nonlinear variations in the dynamic responses and has the potential to be used for structural condition assessment and safety warning.

• 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.