• Structural Monitoring and Maintenance
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• v.5 no.2
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• pp.205-229
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• 2018

Energy induced by minor earthquake and micro vibration cannot be dissipated by traditional buckling-restrained braces (BRBs). To solve this problem, a new type of hybrid passive control device, named as VE-BRB, which is configured by a BRB with high-damping viscoelastic (VE) layers, is developed and studied. Theoretical analysis, performance tests, numerical simulation and case analysis are conducted to study the seismic behavior of VE-BRBs. The results indicate that the combination of hysteretic and damping devices lead to a multi-phased nature and good performance. VE-BRB's working state can be divided into three phases: before yielding of the steel core, VE layers provide sufficient damping ratio to mitigate minor vibrations; after yielding of the steel core, the steel's hysteretic deformations provide supplemental dissipative capacity for structures; after rupture of the steel core, VE layers are still able to work normally and provide multiple security assurance for structures. The simulation results agreed well with the experimental results, validating the finite element analysis method, constitutive models and the identified parameters. The comparison of the time history analysis on a 6-story frame with VE-BRBs and BRBs verified the advantages of VE-BRB for seismic protection of structures compared with traditional BRB. In general, VE-BRB had the potential to provide better control effect on structural displacement and shear in all stages than BRB as expected.

• Wind and Structures
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• v.23 no.4
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• pp.313-350
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• 2016

Taipei 101 Tower, which has 101 stories with height of 508 m, is located in Taipei where typhoons and earthquakes commonly occur. It is currently the second tallest building in the world. Therefore, the dynamic performance of the super-tall building under strong wind actions requires particular attentions. In this study, Large Eddy Simulation (LES) integrated with a new inflow turbulence generator and a new sub-grid scale (SGS) model was conducted to simulate the wind loads on the super-tall building. Three-dimensional finite element model of Taipei 101 Tower was established and used to evaluate the wind-induced responses of the high-rise structure based on the simulated wind forces. The numerical results were found to be consistent with those measured from a vibration monitoring system installed in the building. Furthermore, the equivalent static wind loads on the building, which were computed by the time-domain and frequency-domain analysis, respectively, were in satisfactory agreement with available wind tunnel testing results. It has been demonstrated through the validation studies that the numerical framework presented in this paper, including the recommended SGS model, the inflow turbulence generation technique and associated numerical treatments, is a useful tool for evaluation of the wind loads and wind-induced responses of tall buildings.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.37 no.8C
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• pp.711-720
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• 2012

In this paper, we introduce the implementation of driver fatigue monitering system and its result. Input video device is selected commercially available web-cam camera. Haar transform is used to face detection and adopted illumination normalization is used for arbitrary illumination conditions. Facial image through illumination normalization is extracted using Haar face features easily. Eye candidate area through illumination normalization can be reduced by anthropometric measurement and eye detection is performed by PCA and Circle Mask mixture model. This methods achieve robust eye detection on arbitrary illumination changing conditions. Drowsiness state is determined by the level on illumination normalize eye images by a simple calculation. Our system alarms and operates seatbelt on vibration through controller area network(CAN) when the driver's doze level is detected. Our algorithm is implemented with low computation complexity and high recognition rate. We achieve 97% of correct detection rate through in-car environment experiments.

• Journal of Internet Computing and Services
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• v.21 no.2
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• pp.27-37
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• 2020

Recently, big data is rapidly emerging as a core technology in the 4th industrial revolution. Further, the utilization and the demand of drones are continuously increasing with the development of the 4th industrial revolution. However, as the drones usage increases, the risk of drones falling increases. Drones always have a risk of being able to fall easily even with small problems due to its simple structure. In this paper, in order to predict the risk of drone fall and to prevent the fall, ESC (Electronic Speed Control) is attached integrally with the drone's driving motor and the acceleration sensor is stored to collect the vibration data in real time. By processing and monitoring the data in real time and analyzing the data through big data obtained in such a situation using a Fast Fourier Transform (FFT) algorithm, we proposed a prediction system that minimizes the risk of drone fall by analyzing big data collected from drones.

• Smart Structures and Systems
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• v.11 no.6
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• pp.589-604
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• 2013

Identification of damage has become an evolving area of research over the last few decades with increasing the need of online health monitoring of the large structures. The visual damage detection can be impractical, expensive and ineffective in case of large structures, e.g., offshore platforms, offshore pipelines, multi-storied buildings and bridges. Damage in a system causes a change in the dynamic properties of the system. The structural damage is typically a local phenomenon, which tends to be captured by higher frequency signals. Most of vibration-based damage detection methods require modal properties that are obtained from measured signals through the system identification techniques. However, the modal properties such as natural frequencies and mode shapes are not such good sensitive indication of structural damage. Identification of damaged jacket type offshore platform members, based on wavelet packet transform is presented in this paper. The jacket platform is excited by simple wave load. Response of actual jacket needs to be measured. Dynamic signals are measured by finite element analysis result. It is assumed that this is actual response of the platform measured in the field. The dynamic signals first decomposed into wavelet packet components. Then eliminating some of the component signals (eliminate approximation component of wavelet packet decomposition), component energies of remained signal (detail components) are calculated and used for damage assessment. This method is called Detail Signal Energy Rate Index (DSERI). The results show that reduced wavelet packet component energies are good candidate indices which are sensitive to structural damage. These component energies can be used for damage assessment including identifying damage occurrence and are applicable for finding damages' location.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.45 no.5
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• pp.1-11
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• 2008

Wireless Sensor Networks is applied to improvement of life convenience or service like U-City as well as environment pollution, tunnel and structural health monitoring, storm, and earthquake diagnostic system. To increase the usability of sensor data and applicability, mobile devices and their facilities allow the applications of sensor networks to give mobile users and actuators the results of event detection at anytime and anywhere. In this paper, we present MUSNEMO(Multi-sensor centric Ubiquitous Smart sensor NEtwork using Mobile devices) developed system for providing more efficient and valuable information services with a variety of mobile devices and network camera integrated to WSN. Our system is performed based on IEEE 802.15.4 protocol stack. To validate system usability, we built sensor network environments where were equipped with five application sensors such magnetic, photodiode, microphone, motion and vibration. We also built and tested proposed MUSNEMO to provide a novel model for event detection systems with mobile framework.

• Journal of Navigation and Port Research
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• v.32 no.3
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• pp.215-221
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• 2008

Dynamic characteristics of a structure, i.e., natural frequency and mode shape, have been widely using as an input data in the area of structural integrity or health monitoring which combined with the damage evaluation and structural system identification techniques. It is very difficult, however, to get those information by the conventional modal analysis method from large structures, such as the offshore structure or the long-span bridge, since the source of vibration is not available. In this paper, a method to obtain the frequencies and the mode shapes of a large span truss structure using only acceleration responses is studied. The calculation procedures to obtain acceleration responses and frequency response functions are provided utilizing a numerical model of the truss, and the process to extract natural frequencies and mode shapes from the modal analysis is cleary explained. The extracted mode shapes by proposed method are compared with those from eigenvalue analysis for the estimation of accuracy. The validity of the mode shapes is also demonstrated using an existing damage detection technique for the truss structure by simulated damage cases.

• Journal of the Society of Disaster Information
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• v.16 no.1
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• pp.144-154
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• 2020

Purpose: This paper is a fundamental study on the applicability of the smart bolt developed for monitoring system to detect the leakage of water supply valve. Method: A leak detection experiments were conducted using the smart bolt having embedded strain sensors and accelerometer. The smart bolt used in study meets the allowable criteria of torque and tensile stress for water supply system, and it can be applied to a joint of the water supply valve by behaving well within the allowable limits. Result: As a result of the simulated leak tests, a leak signal at the valve leak point was detected in a band of 60Hz, and the main pipe leaking point was observed to produce a leak signal having much higher frequency than that of the valve leak point. This seems to result in a total coupled vibration under unconfined conditions of the pipes. Conclusion: The smart bolts appeared applicable to detecting a leaking signal from the water supply valve.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.32 no.7
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• pp.43-50
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• 2004

For the simultaneous measurement of strain and damage signal a fiber Bragg grating sensor system with a dual demodulator was proposed. The dual demodulator is composed of a demodulator using a tunable Fabry-Perot filter measuring the low-frequency signal with large magnitude such as strain and the other using a passive Mach-Zehnder interferometer detecting the high-frequency signal with small amplitude such as impact or damage signal. Using the proposed fiber Bragg grating sensor system, both the strain and damage signals of a cross-ply laminated composite beam under tensile loading were simultaneously measured. The strain and damage signals detected by single fiber Bragg grating sensor showed that sudden strain shifts were accompanied with vibration at a maximum frequency of several hundreds of kilohertz at the instant of matrix crack propagation in the 90 degree layer in composite beam.

• Smart Structures and Systems
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• v.15 no.3
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• pp.665-682
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• 2015

Structural identification or St-Id is 'the parametric correlation of structural response characteristics predicted by a mathematical model with analogous characteristics derived from experimental measurements'. This paper describes a St-Id exercise on Humber Bridge that adopted a novel two-stage approach to first calibrate and then validate a mathematical model. This model was then used to predict effects of wind and temperature loads on global static deformation that would be practically impossible to observe. The first stage of the process was an ambient vibration survey in 2008 that used operational modal analysis to estimate a set of modes classified as vertical, torsional or lateral. In the more recent second stage a finite element model (FEM) was developed with an appropriate level of refinement to provide a corresponding set of modal properties. A series of manual adjustments to modal parameters such as cable tension and bearing stiffness resulted in a FEM that produced excellent correspondence for vertical and torsional modes, along with correspondence for the lower frequency lateral modes. In the third stage traffic, wind and temperature data along with deformation measurements from a sparse structural health monitoring system installed in 2011 were compared with equivalent predictions from the partially validated FEM. The match of static response between FEM and SHM data proved good enough for the FEM to be used to predict the un-measurable global deformed shape of the bridge due to vehicle and temperature effects but the FEM had limited capability to reproduce static effects of wind. In addition the FEM was used to show internal forces due to a heavy vehicle to to estimate the worst-case bearing movements under extreme combinations of wind, traffic and temperature loads. The paper shows that in this case, but with limitations, such a two-stage FEM calibration/validation process can be an effective tool for performance prognosis.