• Smart Structures and Systems
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• v.25 no.2
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• pp.135-153
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• 2020

There has been a sustained interest towards the non-contact structural displacement measurement by means of videogrammetric technique. On the way forward, one of the major concerns is the spurious image drift induced by temperature variation. This study therefore carries out an investigation into the temperature effect of videogrammetric technique, focusing on the exploration of the mechanism behind the temperature effect and the elimination of the temperature-caused measurement error. 2D videogrammetric measurement tests under monotonic or cyclic temperature variation are first performed. Features of measurement error and the casual relationship between temperature variation and measurement error are then studied. The variation of the temperature of digital camera is identified as the main cause of measurement error. An excellent linear relationship between them is revealed. After that, camera parameters are extracted from the mapping between world coordinates and pixels coordinates of the calibration targets. The coordinates of principle point and focal lengths show variations well correlated with temperature variation. The measurement error is thought to be an outcome mainly attributed to the variation of the coordinates of principle point. An approach for eliminating temperature-caused measurement error is finally proposed. Correlation models between camera parameters and temperature are formulated. Thereby, camera parameters under different temperature conditions can be predicted and the camera projective matrix can be updated accordingly. By reconstructing the world coordinates with the updated camera projective matrix, the temperature-caused measurement error is eliminated. A satisfactory performance has been achieved by the proposed approach in eliminating the temperature-caused measurement error.

• Smart Structures and Systems
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• v.15 no.4
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• pp.1121-1137
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• 2015

This study presents probabilistic-based damage identification technique for highlighting damage in metallic structures. This technique utilizes distributed piezoelectric transducers to generate and monitor the ultrasonic Lamb wave with narrowband frequency. Diagnostic signals were used to define the scatter signals of different paths. The energy of scatter signals till different times were calculated by taking root mean square of the scatter signals. For each pair of parallel paths an error function based on the energy of scatter signals is introduced. The resultant error function then is used to estimate the probability of the presence of damage in the monitoring area. The presented method with an autofocusing feature is applied to aluminum plates for method verification. The results identified using both simulation and experimental Lamb wave signals at different central frequencies agreed well with the actual situations, demonstrating the potential of the presented algorithm for identification of damage in metallic structures. An obvious merit of the presented technique is that in addition to damages located inside the region between transducers; those who are outside this region can also be monitored without any interpretation of signals. This novelty qualifies this method for online structural health monitoring.

• Smart Structures and Systems
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• v.17 no.6
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• pp.995-1015
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• 2016

In the design and condition assessment of bridges, it is usually necessary to take into consideration the extreme conditions which are not expected to occur within a short time period and thus require an extrapolation from observations of limited duration. Long-term structural health monitoring (SHM) provides a rich database to evaluate the extreme conditions. This paper focuses on the extrapolation of extreme traffic load effects on bridges using long-term monitoring data of structural strain. The suspension Tsing Ma Bridge (TMB), which carries both highway and railway traffic and is instrumented with a long-term SHM system, is taken as a testbed for the present study. Two popular extreme value extrapolation methods: the block maxima approach and the peaks-over-threshold approach, are employed to extrapolate the extreme stresses induced by highway traffic and railway traffic, respectively. Characteristic values of the extreme stresses with a return period of 120 years (the design life of the bridge) obtained by the two methods are compared. It is found that the extrapolated extreme stresses are robust to the extrapolation technique. It may owe to the richness and good quality of the long-term strain data acquired. These characteristic extremes are also compared with the design values and found to be much smaller than the design values, indicating conservative design values of traffic loading and a safe traffic-loading condition of the bridge. The results of this study can be used as a reference for the design and condition assessment of similar bridges carrying heavy traffic, analogous to the TMB.

• Transactions of the Korean Society of Pressure Vessels and Piping
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• v.16 no.2
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• pp.1-9
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• 2020

Large-scale industrial facility structures continue to deteriorate due to the effects of operating and environmental conditions. The problems of these industrial facilities are potentially causing economic losses, environmental pollution, casualties, and national losses. Accordingly, in order to prevent disaster accidents of large structures in advance, the necessity of diagnosing structures using non-destructive inspection techniques is being highlighted. The defect occurrence, location and defect type of the structure are important parameters for predicting the remaining life of the structure, so continuous defect observation is very important. Recently, many researchers have been actively researching real-time monitoring technology to solve these problems. Structure Health Monitoring Inspection is a technology that can identify and respond to the occurrence of defects in real time, but there is a limit to check the degree of defects and the direction of growth of defects. In order to compensate for the shortcomings of these technologies, the importance of defect imaging techniques is emerging, and in order to find defects in large structures, a method of inspecting a wide range using guided ultrasonic is effective. The work presented here introduces a calculation for the shape factor for evaluation of the damaged area, as well as a variable β parameter technique to correct a damaged shape. Also, we perform research in modeling simulation and an experiment for comparison with a suggested inspection method and verify its validity. The curved structure image obtained by the advanced RAPID algorithm showed a good match between the defect area and the shape.

• Computers and Concrete
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• v.31 no.5
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• pp.457-468
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• 2023

Buildings, bridges, and dams are examples of civil infrastructure that play an important role in public life. These structures are prone to structural variations over time as a result of external forces that might disrupt the operation of the structures, cause structural integrity issues, and raise safety concerns for the occupants. Therefore, monitoring the state of a structure, also known as structural health monitoring (SHM), is essential. Owing to the emergence of the fourth industrial revolution, next-generation sensors, such as wireless sensors, UAVs, and video cameras, have recently been utilized to improve the quality and efficiency of building forensics. This study presents a method that uses a target-based system to estimate the dynamic displacement and its corresponding dynamic properties of structures using UAV-based video. A laboratory experiment was performed to verify the tracking technique using a shaking table to excite an SDOF specimen and comparing the results between a laser distance sensor, accelerometer, and fixed camera. Then a field test was conducted to validate the proposed framework. One target marker is placed on the specimen, and another marker is attached to the ground, which serves as a stationary reference to account for the undesired UAV movement. The results from the UAV and stationary camera displayed a root mean square (RMS) error of 2.02% for the displacement, and after post-processing the displacement data using an OMA method, the identified natural frequency and damping ratio showed significant accuracy and similarities. The findings illustrate the capabilities and reliabilities of the methodology using UAV to evaluate the dynamic properties of structures.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.24 no.1
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• pp.107-117
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• 2011

In this study, the effect of temperature-induced uncertainty to damage monitoring using acceleration-impedance response features is analyzed for presterssed concrete(PSC) girder bridges. Firstly, a damage monitoring algorithm using global and local vibration features is designed. As global and local features, acceleration and electro-mechanical impedance features are selected respectively. Secondly, the temperature effect on the acceleration and impedance features for a lab-scaled PSC girder is experimentally analyzed. From the experimental results, compensation models for temperature-acceleration features and temperature-impedance features are estimated. Finally, the feasibility of the acceleration-impedance-based damage monitoring technique using the compensation model is evaluated in the PSC girder for which a set of prestress-loss and flexural stiffness loss cases were dynamically tested.

• Smart Structures and Systems
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• v.6 no.3
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• pp.225-238
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• 2010

We report on the development of a new technology for the fabrication of Micro-Electro-Mechanical-System (MEMS) strain sensors to realize a novel type of crackmeter for health monitoring of ageing civil infrastructures. The fabrication of micromachined silicon MEMS sensors based on a Silicon On Insulator (SOI) technology, designed according to a Double Ended Tuning Fork (DETF) geometry is presented, using a novel process which includes a gap narrowing procedure suitable to fabricate sensors with low motional resistance. In order to employ these sensors for crack monitoring, techniques suited for bonding the MEMS sensors on a steel surface ensuring good strain transfer from steel to silicon and a packaging technique for the bonded sensors are proposed, conceived for realizing a low-power crackmeter for ageing infrastructure monitoring. Moreover, the design of a possible crackmeter geometry suited for detection of crack contraction and expansion with a resolution of $10{\mu}m$ and very low power consumption requirements (potentially suitable for wireless operation) is presented. In these sensors, the small crackmeter range for the first field use is related to long-term observation on existing cracks in underground tunnel test sections.

• Journal of the Korea institute for structural maintenance and inspection
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• v.23 no.3
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• pp.92-95
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• 2019

In this paper, a novel laser-based non-contact and non-destructive stress measurement technique is newly proposed for measuring stress in steel structural members. As the demand of stress monitoring in structural members is increased, various non-destructive techniques are being applied to the field of structural health monitoring. Spectroscopic techniques are non-contact technique and widely used for chemical identification of target materials. Especially, piezospectroscopic technique is a residual stress measurement technique in thermal barrier coatings. Although the piezospectroscopic technique has high possibility of measuring structural stress in steel members, the technique has been rarely applied to this field. In this paper, piezospectroscopy-based stress measurement technique is, therefore, proposed for measuring stress in steel structural member. To do that, alumina particles have been coated onto a specimen of a structural steel rod using a thermal spray coating technique. And then, an uniaxial compression test has been conducted to the specimen to collect each fluorescence spectrum under different loading conditions. Finally, the linear relation of spectral shift and applied compressive stress of the specimen has been experimentally established.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.5
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• pp.611-617
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• 2018

The application of health monitoring, including a fault detection technique, is needed to secure the structural safety of large structures. A 2-step crack identification method for detecting the crack location and size of the beam structure is presented. First, a crack occurrence region was estimated using the modified Laplacian operator for the strain mode shape obtained from the distributed local strain data. The crack location and size were then identified based on the natural frequencies obtained from the acceleration data and the neural network technique for the pre-estimated crack occurrence region. The natural frequencies of a cracked beam were calculated based on an equivalent bending stiffness induced by the energy method, and used to generate the training patterns of the neural network. An experimental study was carried out on an aluminum cantilever beam to verify the present method for crack identification. Cracks were produced on the beam, and free vibration tests were performed. A crack occurrence region was estimated using the modified Laplacian operator for the strain mode shape, and the crack location and size were assessed using the natural frequencies and neural network technique. The identified crack occurrence region agrees well with the exact one, and the accuracy of the estimation results for the crack location and size could be enhanced considerably for 3 damage cases. The presented method could be applied effectively to the structural health monitoring of large structures.

• Smart Structures and Systems
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• v.3 no.2
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• pp.201-217
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• 2007

An active damage detection technique is introduced to locate damage in an isotropic plate using Lamb waves. This technique uses a time-domain energy model of Lamb waves in plates that the wave amplitude inversely decays with the propagation distance along a ray direction. Accordingly the damage localization is formulated as a least-squares problem to minimize an error function between the model and the measured data. An active sensing system with integrated actuators/sensors is controlled to excite/receive $A_0$ mode of Lamb waves in the plate. Scattered wave signals from the damage can be obtained by subtracting the baseline signal of the undamaged plate from the recorded signal of the damaged plate. In the experimental study, after collecting the scattered wave signals, a discrete wavelet transform (DWT) is employed to extract the first scattered wave pack from the damage, then an iterative method is derived to solve the least-squares problem for locating the damage. Since this method does not rely on time-of-flight but wave energy measurement, it is more robust, reliable, and noise-tolerant. Both numerical and experimental examples are performed to verify the efficiency and accuracy of the method, and the results demonstrate that the estimated damage position stably converges to the targeted damage.