• Journal of the Earthquake Engineering Society of Korea
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• v.22 no.3
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• pp.201-210
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• 2018

The improvement in computing systems and sensor technologies devotes to conduct data-driven structural health monitoring algorithms for existing civil infrastructures. Despite of the development of techniques, the uncertainty oriented from the measurement results in the discrepancy to the actual structural parameters and let engineers or decision makers hesitate to adopt such techniques. Many studies have shown that the modal identification results can be affected by the uncertainties due to the applied methods and the types of loading. This paper aims to compare the performance of modal identification methods using Structural Modal Identification Toolsuite (SMIT) which has been developed to facilitate multiple identification methods with a user-friendly designed platform. The data fed into SMIT processes three stages for the comprehensive identification including preprocessing, eigenvalue estimation, and post-processing. The seismic and white noise response for shear frame model was obtained from numerical simulation. The identified modal parameters is compared to the actual modal parameters. In order to improve the quality of coherence in identified modal parameters, several hurdles including modal phase collinearity and extended modal amplitude coherence were introduced. Numerical simulation conducted on the 5 dof shear frame model were used to validate the effectiveness of using these parameters.

• Journal of Ocean Engineering and Technology
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• v.25 no.2
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• pp.1-6
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• 2011

Vibration-based Structural Health Monitoring (SHM) systems use field measurements of operational signals, which are distorted by noise from many sources. Reducing this noise allows a more accurate assessment of the original "clean" signal and improves analysis results. The implementation of a noise reduction methodology for the Modal Distribution Method (MDM) is reported here. The spectral subtraction method is a popular broadband noise reduction technique used in speech signal processing. Its basic principle is to subtract the magnitude of the noise from the total noisy signal in the frequency domain. The underlying assumption of the method is that noise is additive and uncorrelated with the signal. In speech signal processing, noise can be measured when there is no signal. In the MDM, however, the magnitude of the noise profile can be estimated only from the magnitude of the Power Spectral Density (PSD) at higher frequencies than the frequency range of the true signal associated with structural vibrations under the additional assumption of white noise. The implementation of the spectral subtraction method to MDM may decrease the energy of the individual mode. In this work, a modification of the spectral subtraction method is introduced that enables the conservation of the energies of individual modes. The main difference is that any (negative) bars with a height below zero after subtraction are set to the absolute value of their height. Both noise reduction methods are implemented in the MDM, and an application example is presented that demonstrates its effectiveness when used with a signal corrupted by noise.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.15 no.1 s.94
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• pp.53-62
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• 2005

This study presents the NDE (non-destructive evaluation) technique for detecting the loosened bolts on joint steel structures on the basis of TOF (time of flight) and amplitudes of Lamb waves. Probabilistic neural network (PNN) technique which is an effective tool for pattern classification problem was applied to the damage estimation using PZT induced Lamb waves. Two kinds of damages were introduced by dominant damages (DD) which mean loosened bolts within the Lamb waves beam width and minor damages (MD) which mean loosened bolts out of the Lamb waves beam width. They were investigated for the establishment of the optimal decision boundaries which divide each damage class's region including the intact class. In this study, the applicability of the probabilistic neural networks was identified through the test results for the damage cases within and out of wave beam path. It has been found that the present methods are very efficient and reasonable in predicting the loosened bolts on the joint steel structures probabilistically.

• Journal of Institute of Control, Robotics and Systems
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• v.11 no.12
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• pp.1020-1026
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• 2005

In the era of ubiquitous computing, human-friendly man-machine interface is getting more attention due to its possibility to offer convenient services. For this, in this paper, we introduce a 'Half-Mirror Interface System (HMIS)' as a novel type of human-friendly man-machine interfaces. Basically, HMIS consists of half-mirror, USB-Webcam, microphone, 2ch-speaker, and high-speed processing unit. In our HMIS, two principal operation modes are selected by the existence of the user in front of it. The first one, 'mirror-mode', is activated when the user's face is detected via USB-Webcam. In this mode, HMIS provides three basic functions such as 1) make-up assistance by magnifying an interested facial component and TTS (Text-To-Speech) guide for appropriate make-up, 2) Daily weather information provider via WWW service, 3) Health monitoring/diagnosis service using Chinese medicine knowledge. The second one, 'display-mode' is designed to show decorative pictures, family photos, art paintings and so on. This mode is activated when the user's face is not detected for a time being. In display-mode, we also added a 'healing-window' function and 'healing-music player' function for user's psychological comfort and/or relaxation. All these functions are accessible by commercially available voice synthesis/recognition package.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.15 no.7
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• pp.1628-1634
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• 2011

With the advancement of ubiquitous computing technology, u-Healthcare (i.e. ubiquitous health care), is regarded as a key application for information society, which provides health management service at anytime in anywhere. To implement U-Healthcare system, it is essential to monitor stable biological information in daily life. In this paper, we proposed a small size, light weight, patch type real time temperature monitoring system based on wireless sensor network (WSN) technology to monitor patients' body temperature without any inconvenience of activity.

• Smart Structures and Systems
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• v.7 no.2
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• pp.133-152
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• 2011

System identification is a fundamental step towards the application of structural health monitoring and damage detection techniques. On this respect, the development of evolved identification strategies is a priority for obtaining reliable and repeatable baseline modal parameters of an undamaged structure to be adopted as references for future structural health assessments. The paper presents the identification of the modal parameters of the Guangzhou New Television Tower, China, using a data-driven stochastic subspace identification (SSI-data) approach complemented with an appropriate automatic mode selection strategy which proved to be successful in previous literature studies. This well-known approach is based on a clustering technique which is adopted to discriminate structural modes from spurious noise ones. The method is applied to the acceleration measurements made available within the task I of the ANCRiSST benchmark problem, which cover 24 hours of continuous monitoring of the structural response under ambient excitation. These records are then subdivided into a convenient number of data sets and the variability of modal parameter estimates with ambient temperature and mean wind velocity are pointed out. Both 10 minutes and 1 hour long records are considered for this purpose. A comparison with finite element model predictions is finally carried out, using the structural matrices provided within the benchmark, in order to check that all the structural modes contained in the considered frequency interval are effectively identified via SSI-data.

• Smart Structures and Systems
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• v.3 no.3
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• pp.373-384
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• 2007

For structural health monitoring (SHM) of civil infrastructures, displacement is a good descriptor of the structural behavior under all the potential disturbances. However, it is not easy to measure displacement of civil infrastructures, since the conventional sensors need a reference point, and inaccessibility to the reference point is sometimes caused by the geographic conditions, such as a highway or river under a bridge, which makes installation of measuring devices time-consuming and costly, if not impossible. To resolve this issue, a visionbased real-time displacement measurement system using digital image processing techniques is developed. The effectiveness of the proposed system was verified by comparing the load carrying capacities of a steel-plate girder bridge obtained from the conventional sensor and the present system. Further, to simultaneously measure multiple points, a synchronized vision-based system is developed using master/slave system with wireless data communication. For the purpose of verification, the measured displacement by a synchronized vision-based system was compared with the data measured by conventional contact-type sensors, linear variable differential transformers (LVDT) from a laboratory test.

• Structural Engineering and Mechanics
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• v.64 no.6
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• pp.803-817
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• 2017

Structural health monitoring has increasingly been a focus within the civil engineering research community over the last few decades. With increasing application of sensor networks in large structures and infrastructure systems, effective use and development of robust algorithms to analyze large volumes of data and to extract the desired features has become a challenging problem. In this paper, we grasp some precautions and key points of the signal processing approach, wavelet, establish a relative reliable framework, and analyze three problems that require attention when applying wavelet based damage detection approach. The cases studies how to use optimal scales for extracting mode shapes and modal curvatures in a reinforced concrete beam and how to effectively identify damages using maximum curves of wavelet coefficient differences. Moreover, how to make a recognition based on the wavelet multi-resolution analysis, wavelet packet energy, and fuzzy sets is a meaningful topic that has been addressed in this work. The relative systematic work that compasses algorithms, structures and evaluation paves a way to a framework regarding effective structural health monitoring, orientation, decision and action.

• Computers and Concrete
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• v.20 no.5
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• pp.583-593
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• 2017

Applications of fibre-reinforced polymer (FRP) composites for retrofitting, strengthening and repairing concrete structures have been expanded dramatically in the last decade. FRPs have high specific strength and stiffness compared to conventional construction materials, e.g., steel. Ease of preparation and installation, resistance to corrosion, versatile fabrication and adjustable mechanical properties are other advantages of the FRPs. However, there are major concerns about long-term performance, serviceability and durability of FRP applications in concrete structures. Therefore, structural health monitoring (SHM) and damage detection in FRP-retrofitted concrete structures need to be implemented. This paper presents a study on investigating the application of Rayleigh wave for detecting debonding defect in FRP-retrofitted concrete structures. A time-of-flight (ToF) method is proposed to determine the location of a debonding between the FRP and concrete using Rayleigh wave. A series of numerical case studies are carried out to demonstrate the capability of the proposed debonding detection method. In the numerical case studies, a three-dimensional (3D) finite element (FE) model is developed to simulate the Rayleigh wave propagation and scattering at the debonding in the FRP-retrofitted concrete structure. Absorbing layers are employed in the 3D FE model to reduce computational cost in simulating the practical size of the FRP-retrofitted structure. Different debonding sizes and locations are considered in the case studies. The results show that the proposed ToF method is able to accurately determine the location of the debonding in the FRP-retrofitted concrete structure.

• Smart Structures and Systems
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• v.1 no.4
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• pp.385-404
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• 2005

The paper presents a model to calculate reinforcement strain using measured crack width in members under applied tension, flexure, and/or shear stress. Crack mapping using a new type of distributed coaxial cable sensors for health monitoring of large-scale civil engineering infrastructure was recently proposed and developed by the authors. This paper shows the results and performance of such sensors mounted on near surface of two flexural beams and a large scale reinforced concrete box girder that was subjected to cyclic combined shear and torsion. The main objectives of this health monitoring study was to correlate the sensor's response to strain in the member, and show that magnitude of the signal's reflection coefficient is related to increases in applied load, repeated cycles, cracking, and reinforcement yielding. The effect of multiple adjacent cracks, and signal loss was also investigated. The results shown in this paper are an important step in using the sensors for crack mapping and determining reinforcement strain for in-situ structures.