• Journal of Ocean Engineering and Technology
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• v.23 no.1
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• pp.122-128
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• 2009

In this study, damage detection method using harmony search method and frequency response is proposed. In order to verify this method, the following approaches are implemented. Firstly, damage detection method using harmony search was developed. To detect damage, objective functions that minimize difference with natural frequency and modal strain energy from undamaged and damaged model are used. Secondly, efficiency of developed damage detection method was verified by damage detection of beam structure. And results of harmony search and micro genetic algorithm are compared and evaluated. Thirdly, numerical model was implemented for harbor caisson structure and damage scenario was determined. Lastly, damage detection was performed by proposed method and utility of proposed method is verified.

• Journal of Ocean Engineering and Technology
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• v.29 no.5
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• pp.351-358
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• 2015

This paper presents an effective damage detection method using a meta model. A meta model is an approximation model that uses the relations between the design and response variables. It eliminates the need for repetitive analyses of computationally expensive models during the optimization process. In this study, a response surface model was employed as the meta model. The surface model was estimated using the correlation of the stiffness and natural frequencies of the structures. The locations and values of the damages were identified using a meta model-based damage detection method. Two numerical examples (a cantilever beam and jacket structure) were considered to verify the performance of the proposed method. As a result, the damages to the structures were accurately detected.

• Journal of Advanced Navigation Technology
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• v.22 no.5
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• pp.359-366
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• 2018

In this paper, the noise is removed by using CTLS aircraft installed FBG sensor inside the aircraft wing. We suggest a normal wavelet transform scheme with motion - invariant characteristics for noise reduction. In the case of installing FBG sensors inside the composite material as in CTLS, large and small empty spaces and parts or sections are generated between the adhesive layers, and a signal splitting problem occurs. FBG sensor is not affected by noise. but eletromagnetic, light source, light detector and signal processing device are influeced by noise because these are eletronic components what affected by eletromagnetic wave. because of this, errors are occured. Experimental results show that the noise can be removed using normal wavelet transform and more accurate data detection is possible.

• Journal of the Korean Society for Nondestructive Testing
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• v.31 no.6
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• pp.601-608
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• 2011

This paper presents the damage assessment of a building structure by using a novel optical fiber accelerometer system. Especially, a sub-scaled building model is designed and manufactured to check up the feasibility of the optical fiber accelerometer for structural health monitoring. The novel accelerometer exploits the moir$\acute{e}$ fringe optical phenomenon and two pairs of optical fibers to measure the displacement with a high accuracy, and furthermore a pendulum to convert the displacement into acceleration. A prototype of optical fiber accelerometer system has been successfully developed that consists of a sensor head, a control unit and a signal processing unit. The building model is also designed as a 4-story building with a rectangular shape of $200{\times}300$ mm of edges. Each floor is connected to the next ones by 6 steel columns which are threaded rods. Basically, a random vibration test of the building model is done with a shaker and all of acceleration data is successfully measured at the assigned points by the optical fiber accelerometer. The experiments are repeated in the undamaged state and the damaged state. The comparison of dynamic parameters including the natural frequencies and the eigenvectors is successfully carried out. Finally, the optical fiber accelerometer is proven to be prospective to evaluate dynamic characteristics of a building structure for the damage assessment.

• Smart Structures and Systems
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• v.2 no.3
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• pp.225-235
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• 2006

With the discovery in plants of the proteinaceous forisome crystalloid (Knoblauch, et al. 2003), a novel, non-living, ATP-independent biological material became available to the designer of smart materials for advanced actuating and sensing. The in vitro studies of Knoblauch, et al. show that forisomes (2-4 micron wide and 10-40 micron long) can be repeatedly stimulated to contract and expand anisotropically by shifting either the ambient pH or the ambient calcium ion concentration. Because of their unique abilities to develop and reverse strains greater than 20% in time periods less than one second, forisomes have the potential to outperform current smart materials as advanced, biomimetic, multi-functional, smart sensors or actuators. Probing forisome material properties is an immediate need to lay the foundation for synthesizing forisomebased smart materials for health monitoring of structural integrity in civil infrastructure and for aerospace hardware. Microfluidics is a growing, vibrant technology with increasingly diverse applications. Here, we use microfluidics to study the surface interaction between forisome and substrate and the conformational dynamics of forisomes within a confined geometry to lay the foundation for forisome-based smart materials synthesis in controlled and repeatable environment.

• Korean Journal of Optics and Photonics
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• v.12 no.4
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• pp.294-299
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• 2001

Recently great efforts and investment have been made in order to develop a structural health monitoring technology using fiber optic sensors. Therefore, in this study, we have focused on the development of a fiber optic BOTDA (Brillouin Optical Time Domain Analysis) sensor system in order to measure strains distributed on large structures by an optical fiber. The fiber optic BOTDA sensor was constructed simply, with only two electro-optic modulators. The results of strain measurement tests of an optical fiber showed that the strain can be determined accurately from the Brillouin frequency shift measurement on the strain induced range of 10 m in the total fiber length of 4.8 kIn using 200 averaged signals. Also, the strain sensitivity of Samsung single mode fiber was 4.81 MHz/O.Ol % under the test. test.

• Smart Structures and Systems
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• v.5 no.1
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• pp.43-54
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• 2009

This study introduces a novel approach for locating damage in a structure using wireless sensor system with local level computational capability to alleviate data traffic load on the centralized computation. Smart wireless sensor systems, capable of iterative damage-searching, mimic an optimization process in a decentralized way. The proposed algorithm tries to detect damage in a structure by monitoring abnormal increases in strain measurements from a group of wireless sensors. Initially, this clustering technique provides a reasonably effective sensor placement within a structure. Sensor clustering also assigns a certain number of master sensors in each cluster so that they can constantly monitor the structural health of a structure. By adopting a voting system, a group of wireless sensors iteratively forages for a damage location as they can be activated as needed. Since all of the damage searching process occurs within a small group of wireless sensors, no global control or data traffic to a central system is required. Numerical simulation demonstrates that the newly developed searching algorithm implemented on wireless sensors successfully localizes stiffness damage in a plate through the local level reconfigurable function of smart sensors.

• Nuclear Engineering and Technology
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• v.54 no.4
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• pp.1221-1229
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• 2022

In this work, the guided wave de-bonding area-detecting technique was studied for application to containment liner plates in nuclear power plant areas. To apply this technique, an appropriate Lamb wave mode, symmetric and longitudinal dominance, was verified by the frequency shifting technique. The S0 2.7 MHz mm Lamb wave mode was chosen to realize quantitative experimental results and their visualization. Results of the bulk wave, longitudinal wave mode, and comparison experiments indicate that the wave mode was able to distinguish between the de-bonded and bonded areas. Similar to the bulk wave cases, the bonded region could be distinguished from the de-bonded region using the Lamb wave approach. The Lamb wave technique results showed significant correlation to the de-bonding area. As the de-bonding area increased, the Lamb wave energy attenuation effect decreased, which was a prominent factor in the realization of quantitative tomographic visualization. The feasibility of tomographic visualization was studied via the application of Lamb waves. The reconstruction algorithm for the probabilistic inspection of damage (RAPID) technique was applied to the containment liner plate to verify and visualize the de-bonding condition. The results obtained using the tomography image indicated that the Lamb wave-based RAPID algorithm was capable of delineating debonding areas.

• Smart Structures and Systems
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• v.28 no.6
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• pp.727-735
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• 2021

Recently, non-destructive health monitoring methods such as magnetic flux leakage (MFL) method, have become popular due to their advantages over destructive methods. Currently, numerical study on this field has been limited to simplified studies by only obtaining MFL instead of induced voltage inside coil sensor. In this study, it was proposed to perform a novel numerical simulation of MFL's coil sensor by considering vital parameters including specimen's motion with constant velocity and saturation status of specimen in time domain. A steel-rod specimen with two stepwise cross-sectional changes (i.e., 21% and 16%) was fabricated using low carbon steel. In order to evaluate the results of numerical simulation, an experimental test was also conducted using a magnetic probe, with same size specimen and test parameters, exclusively. According to comparative results of numerical simulation and experimental test, similar signal amplitude and signal pattern were observed. Thus, proposed numerical simulation method can be used as a reliable source to check efficiency of sensor probe when different size specimens with different defects should be inspected.

• Smart Structures and Systems
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• v.30 no.5
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• pp.501-511
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• 2022

Three-dimensional (3D) models have become crucial for improving civil infrastructure analysis, and they can be used for various purposes such as damage detection, risk estimation, resolving potential safety issues, alarm detection, and structural health monitoring. 3D point cloud data is used not only to make visual models but also to analyze the states of structures and to monitor them using semantic data. This study proposes automating the generation of high-quality 3D point cloud data and removing noise using deep learning algorithms. In this study, large-format aerial images of civilian infrastructure, such as cut slopes and dams, which were captured by drones, were used to develop a workflow for automatically generating a 3D point cloud model. Through image cropping, downscaling/upscaling, semantic segmentation, generation of segmentation masks, and implementation of region extraction algorithms, the generation of the point cloud was automated. Compared with the method wherein the point cloud model is generated from raw images, our method could effectively improve the quality of the model, remove noise, and reduce the processing time. The results showed that the size of the 3D point cloud model created using the proposed method was significantly reduced; the number of points was reduced by 20-50%, and distant points were recognized as noise. This method can be applied to the automatic generation of high-quality 3D point cloud models of civil infrastructures using aerial imagery.