• Smart Structures and Systems
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• v.16 no.2
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• pp.243-262
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• 2015

Optimal sensor placement (OSP) is a critical issue in construction and implementation of a sophisticated structural health monitoring (SHM) system. The uncertainties in the identified structural parameters based on the measured data may dramatically reduce the reliability of the condition evaluation results. In this paper, the information entropy, which provides an uncertainty metric for the identified structural parameters, is adopted as the performance measure for a sensor configuration, and the OSP problem is formulated as the multi-objective optimization problem of extracting the Pareto optimal sensor configurations that simultaneously minimize the appropriately defined information entropy indices. The nondirective movement glowworm swarm optimization (NMGSO) algorithm (based on the basic glowworm swarm optimization (GSO) algorithm) is proposed for identifying the effective Pareto optimal sensor configurations. The one-dimensional binary coding system is introduced to code the glowworms instead of the real vector coding method. The Hamming distance is employed to describe the divergence of different glowworms. The luciferin level of the glowworm is defined as a function of the rank value (RV) and the crowding distance (CD), which are deduced by non-dominated sorting. In addition, nondirective movement is developed to relocate the glowworms. A numerical simulation of a long-span suspension bridge is performed to demonstrate the effectiveness of the NMGSO algorithm. The results indicate that the NMGSO algorithm is capable of capturing the Pareto optimal sensor configurations with high accuracy and efficiency.

• Smart Structures and Systems
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• v.12 no.2
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• pp.97-119
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• 2013

This paper presents numerical and experimental results on the use of guided waves for structural health monitoring (SHM) of crack growth during a fatigue test in a thick steel plate used for civil engineering application. Numerical simulation, analytical modeling, and experimental tests are used to prove that piezoelectric wafer active sensor (PWAS) can perform active SHM using guided wave pitch-catch method and passive SHM using acoustic emission (AE). AE simulation was performed with the multi-physic FEM (MP-FEM) approach. The MP-FEM approach permits that the output variables to be expressed directly in electric terms while the two-ways electromechanical conversion is done internally in the MP-FEM formulation. The AE event was simulated as a pulse of defined duration and amplitude. The electrical signal measured at a PWAS receiver was simulated. Experimental tests were performed with PWAS transducers acting as passive receivers of AE signals. An AE source was simulated using 0.5-mm pencil lead breaks. The PWAS transducers were able to pick up AE signal with good strength. Subsequently, PWAS transducers and traditional AE transducer were applied to a 12.7-mm CT specimen subjected to accelerated fatigue testing. Active sensing in pitch catch mode on the CT specimen was applied between the PWAS transducers pairs. Damage indexes were calculated and correlated with actual crack growth. The paper finishes with conclusions and suggestions for further work.

• Smart Structures and Systems
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• v.31 no.4
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• pp.393-407
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• 2023

To assess structural condition in a non-destructive manner, computer vision-based structural health monitoring (SHM) has become a focus. Compared to traditional contact-type sensors, the advantages of computer vision-based measurement systems include lower installation costs and broader measurement areas. In this study, we propose a novel computer vision-based vibration measurement and coarse-to-fine damage assessment method for truss bridges. First, a deep learning model FairMOT is introduced to track the regions of interest (ROIs) that include joints to enhance the automation performance compared with traditional target tracking algorithms. To calculate the displacement of the tracked ROIs accurately, a normalized cross-correlation method is adopted to fine-tune the offset, while the Harris corner matching is utilized to correct the vibration displacement errors caused by the non-parallel between the truss plane and the image plane. Then, based on the advantages of the stochastic damage locating vector (SDLV) and Bayesian inference-based stochastic model updating (BI-SMU), they are combined to achieve the coarse-to-fine localization of the truss bridge's damaged elements. Finally, the severity quantification of the damaged components is performed by the BI-SMU. The experiment results show that the proposed method can accurately recognize the vibration displacement and evaluate the structural damage.

• Journal of Korean Society of societal Security
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• v.2 no.3
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• pp.47-53
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• 2009

This study performed the construction of test bed for the combination of the health monitoring system In Yongjong grand bridge with the safety management network system in order to explore the feasibility of combining the existing monitoring system with the safety management network system. For this purpose, connection program which consists of DAQ sender server program and DAQ receiver server program has been developed. DAQ sender server program installed in the connection server, which is located on the DMZ zone of the existing monitoring system, plays the role of communicating with the monitoring system. On the other hand, DAQ receiver server program installed in the connection server, which is located on the integrated operation center of the safety management network system, plays the part of gathering real time and tim history data of the existing monitoring system and storing them in the integrated operation server through the communication with the DAQ sender. Test bed demonstrated the feasibility of combining the existing monitoring system with the safety management network system.

• The Journal of the Korea Contents Association
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• v.16 no.3
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• pp.11-21
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• 2016

Recently, structure safety management techniques using cutting-edge technology(Displacement senor, sensor of acceleration) has emerged as an important issue owing to the aging of infrastructure such as bridge and building. In general, the structural monitoring system for structure safety management is based on IT technology and it is expensive to install. In this paper developed an image-based structure dynamic characteristic analysis system prototype to assess the damage of structure in a more cost-effective way than traditional structure health monitoring system. The inspector can take a video of buildings or other structures with digital camera or any other devices that is passible to take video, and then using NCC calculation for image processing technique to get natural frequency. This system is analysis of damage of the structure using a compare between the frequency response ratio and functions when problems are occurs send alarm to administrator. This system is easier to install and remove than previous monitoring sensor in economical way.

• Smart Structures and Systems
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• v.6 no.3
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• pp.197-209
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• 2010

The structural state of a bridge is currently examined by visual inspection or by wired sensor techniques, which are relatively expensive, vulnerable to inclement conditions, and time consuming to undertake. In contrast, wireless sensor networks are easy to deploy and flexible in application so that the network can adjust to the individual structure. Different sensing techniques have been used with such networks, but the acoustic emission technique has rarely been utilized. With the use of acoustic emission (AE) techniques it is possible to detect internal structural damage, from cracks propagating during the routine use of a structure, e.g. breakage of prestressing wires. To date, AE data analysis techniques are not appropriate for the requirements of a wireless network due to the very exact time synchronization needed between multiple sensors, and power consumption issues. To unleash the power of the acoustic emission technique on large, extended structures, recording and local analysis techniques need better algorithms to handle and reduce the immense amount of data generated. Preliminary results from utilizing a new concept called Acoustic Emission Array Processing to locally reduce data to information are presented. Results show that the azimuthal location of a seismic source can be successfully identified, using an array of six to eight poor-quality AE sensors arranged in a circular array approximately 200 mm in diameter. AE beamforming only requires very fine time synchronization of the sensors within a single array, relative timing between sensors of $1{\mu}s$ can easily be performed by a single Mote servicing the array. The method concentrates the essence of six to eight extended waveforms into a single value to be sent through the wireless network, resulting in power savings by avoiding extended radio transmission.

• Journal of the Korea institute for structural maintenance and inspection
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• v.18 no.6
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• pp.105-113
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• 2014

Most operating civil structures measure response data continuously by various types of sensors and evaluate their health conditions. Measurement control criteria for such civil structures are usually defined in the first operating stage by experts working at a construction or engineering company. However, a few studies have been carried to examine the adequacy of these measurement control criteria based on the actual measured data. The paper introduces a systematic way of resetting the measurement control criteria for the measured monitoring data based on the statistical aspects of the measured data. The proposed statistical approach has been examined with actually measured time-history data from a bridge structure.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.23 no.10
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• pp.869-877
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• 2013

Tension force of hanger ropes has been recognized and utilized as an important parameter for health monitoring of suspension bridges. Conventional vibration method based on string theory has been utilized to estimate tension forces of relatively long hanger ropes without any problem, however it is convinced that the vibration method is not applicable for shorter hanger ropes in which the influence of flexural stiffness is not ignorable. Therefore, as an alternative of vibration method, a number of feasibility studies of system identification(SI) technique considering flexural stiffness of the hanger ropes are recently performed. In this study, the influence of support condition of the finite element model utilized for the SI method is investigated with numerical examples. The numerical examples are prepared with the specification of the Kwang-Ahn bridge hanger ropes, and it is revealed that the estimation result of the tension force can be varied from -21.6 % to +35.3 % of the exact value according to the consideration of the support condition of FE model. Therefore, it is concluded that the rotational stiffness of the support spring should be included to the list of the identification parameters of the FE model to improve the result of tension estimation.

• The Transactions of the Korean Institute of Power Electronics
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• v.12 no.5
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• pp.400-408
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• 2007

In this paper, development of the 8kW parallel module converter is presented. For a effective configuration of FB-PWM converter, this paper proposes 4-parallel operation of 2 kw-module. FB converter of 2-kW module is controlled by phase shut PWM and in order to achieve ZVZCS, the simple auxiliary circuit is applied in secondary side. In order to achieve ZCS, control logic for auxiliary circuit operation is designed to reset the primary current during free-wheeling period. For output current sharing of 4-modules, the charge control is employed. The charge control logic is designed with phase shift PWM logic. Voltage controller is implemented by using DSP(TMS320LF2406) with A/D conversion data of the output current and voltage of each module. The developed converter is installed in PCU(Power Conditioning Unit) for HSG(High Speed Generator) in a vehicle and health monitoring system is implemented for vehicle operation test. Finally, performance of the developed converter is proved under practical operation of HSG.

• Structural Engineering and Mechanics
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• v.64 no.4
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• pp.449-459
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• 2017

High-rise buildings are generally sensitive to strong winds. The evaluation of wind loads for the structural design, structural health monitoring (SHM), and vibration control of high-rise buildings is of primary importance. Nevertheless, it is difficult or even infeasible to measure the wind loads on an existing building directly. In this regard, a new inverse method for evaluating wind loads on high-rise buildings is developed in this study based on a discrete-time Kalman filter. The unknown structural responses are identified in conjunction with the wind loads on the basis of limited structural response measurements. The algorithm is applicable for estimating wind loads using different types of wind-induced response. The performance of the method is comprehensively investigated based on wind tunnel testing results of two high-rise buildings with typical external shapes. The stability of the proposed algorithm is evaluated. Furthermore, the effects of crucial factors such as cross-section shapes of building, the wind-induced response type, errors of structural modal parameters, covariance matrix of noise, noise levels in the response measurements and number of vibration modes on the identification accuracy are examined through a detailed parametric study. The research outputs of the proposed study will provide valuable information to enhance our understanding of the effects of wind on high-rise buildings and improve codes of practice.