• Proceedings of the Computational Structural Engineering Institute Conference
• /
• 2006.04a
• /
• pp.10-14
• /
• 2006

FBG sensors are able to measure the strain of structures more easily and durable than electronic resistance gages and thus many researches are on the way to apply the FBG sensor for response monitering of infrastructures. This study investigates the deflection estimation technique using FBG sensors. Several FBG sensors are multiplexed in single optical fiber and installed. in parallel pairs along the length of the structure. The measured strains at the top and bottom of a cross section can be transferred to the curvature of the section which can be used to calculate its displacement. It has been demonstrated that the estimated deflections using the FBG sensor are compared well with the readings from displacement transducers. The results show that the proposed instrumentation technique is capable of estimating the vertical deflection of the structures for various loading conditions including impact and dynamic loads, which is crucial in the structural health monitoring.

• Journal of Korea Multimedia Society
• /
• v.19 no.12
• /
• pp.1981-1991
• /
• 2016

In recent, the advancement of wearable devices and wireless body area networking technologies motivate researchers to pay attention to remote healthcare system for monitoring patients health and disease progression effectively. However, in order to implement a practical remote healthcare system, we must consider the security and privacy of patient's personal health information transmitted to healthcare servers through the network. Hence, in this paper, we propose a secure health data transmission protocol in remote healthcare monitoring system to protect patient's health information and prevent privacy from eavesdropping on the network. To achieve our security goals, we design an efficient secure protocol based on the identity-based cryptography with key evolution technique, and then confirm the superiority and the efficiency of the proposed protocol as compared with the existing protocol of Yang et al.

• Structural Engineering and Mechanics
• /
• v.43 no.2
• /
• pp.179-197
• /
• 2012

This study presents the findings of the structural health monitoring and the real time system identification of one of the first large scale building instrumentations in Turkey for earthquake safety. Within this context, a thorough review of steps in the instrumentation, monitoring is presented and seismic performance evaluation of structures using both nonlinear pushover and nonlinear dynamic time history analysis is carried out. The sensor locations are determined using the optimal sensor placement techniques used in NASA for on orbit modal identification of large space structures. System identification is carried out via the stochastic subspace technique. The results of the study show that under ambient vibrations, stocky buildings can be substantially stiffer than what is predicted by the finite element models due to the presence of a large number of partitioning walls. However, in a severe earthquake, it will not be safe to rely on this resistance due to the fact that once the partitioning walls crack, the bare frame contributes to the lateral stiffness of the building alone. Consequently, the periods obtained from system identification will be closer to those obtained from the FE analysis. A technique to control the validity of the proportional damping assumption is employed that checks the presence of phase difference in displacements of different stories obtained from band pass filtered records and it is confirmed that the "proportional damping assumption" is valid for this structure. Two different techniques are implemented for identifying the influence of the soil structure interaction. The first technique uses the transfer function between the roof and the basement in both directions. The second technique uses a pre-whitening filter on the data obtained from both the basement and the roof. Subsequently the impulse response function is computed from the scaled cross correlation between the input and the output. The overall results showed that the structure will satisfy the life safety performance level in a future earthquake but some soil structure interaction effects should be expected in the North South direction.

• Safety and Health at Work
• /
• v.9 no.4
• /
• pp.479-485
• /
• 2018

The aim of this study is to validate an integrated air monitoring approach for assessing airborne formaldehyde (FA) in the workplace. An active sampling by silica gel impregnated with 2,4-dinitrophenylhydrazine, a passive solid phase microextraction technique using O-(2,3,4,5,6-pentafluorobenzyl)hydroxylamine as on-fiber derivatization reagent, an electrochemical direct-reading monitor, and an enzyme-based badge were evaluated and tested over a range of 0.020-5.12 ppm, using dynamically generated FA air concentrations. Simple linear regression analysis showed the four methods were suitable for evaluating airborne FA. Personal and area samplings in 12 anatomy pathology departments showed that the international occupational exposure limits in the GESTIS database were frequently exceeded. This monitoring approach would allow a fast, easy-to-use, and economical evaluation of both current work practices and eventual changes made to reduce FA vapor concentrations.

• Smart Structures and Systems
• /
• v.28 no.6
• /
• pp.799-810
• /
• 2021

When monitoring the structural integrity of a bridge using data collected through accelerometers, identifying the profile of the load exerted on the bridge from the vehicles passing over it becomes a crucial task. In this study, the speed and location of vehicles on the deck of a bridge is reconfigured using real-time video to implicitly associate the load applied to the bridge with the response from the bridge sensors to develop an image-based deep learning network model. Instead of directly measuring the load that a moving vehicle exerts on the bridge, the intention in the proposed method is to replace the correlation between the movement of vehicles from CCTV images and the corresponding response by the bridge with a neural network model. Given the framework of an input-output-based system identification, CCTV images secured from the bridge and the acceleration measurements from a cantilevered beam are combined during the process of training the neural network model. Since in reality, structural damage cannot be induced in a bridge, the focus of the study is on identifying local changes in parameters by adding mass to a cantilevered beam in the laboratory. The study successfully identified the change in the material parameters in the beam by using the deep-learning neural network model. Also, the method correctly predicted the acceleration response of the beam. The proposed approach can be extended to the structural health monitoring of actual bridges, and its sensitivity to damage can also be improved through optimization of the network training.

• Journal of the Korea institute for structural maintenance and inspection
• /
• v.2 no.4
• /
• pp.137-147
• /
• 1998

The neural net application was tried to develop the technique for monitoring the health status of a steel truss bridge which was scaled down to 1/15 of the real bridge for the laboratory experiments. The damage scenarios were chosen as 7 cases. The dynamic behavior, which was changed due to the breakage of the members, of the bridge was investigated by finite element analysis. The bridge consists of single spam, and eight (8) main structural subsystems. The loading vehicle, which weighs as 100 kgf, was operated by the servo-motor controller. The accelerometers were bonded on the surface of 7 cross-beams to measure the dynamic behavior induced by the abnormal structural condition. Artificial neural network technique was used to determine the severity of the damage. At first, the neural net was learnt by the results of finite element analysis, and also, the maximum detection error was 3.65 percents. Another neural net was also learnt, and verified by the experimental results, and in this case, the maximum detection error was 1.05 percents. In future study, neural net is necessary to be learnt and verified by various data from the real bridge.

• 한국방재학회:학술대회논문집
• /
• 2007.02a
• /
• pp.53-56
• /
• 2007

It was previously introduced a new displacement measuring technique using terrestrial laser scanning (TLS) that remotely samples the surface of an object using laser pulses and generates the three-dimensional (3D) coordinates of numerous points on the surface. In this paper, for an assessment of the capabilities of the measuring technique about existing structures, the field tests for vertical displacement measurement of an existing long span steel box-girder are experimentally carried out. The performance of the technique is evaluated by comparing the displacements obtained from TLS system and displacements directly measured from linear variable displacement transducer (LVDT).

• Smart Structures and Systems
• /
• v.14 no.5
• /
• pp.811-830
• /
• 2014

A numerical study has been carried out to simulate an innovative monitoring procedure to detect and localize damage in reinforced concrete beams retrofitted with carbon fiber reinforced polymer (CFRP) unidirectional laminates. The main novelty of the present simulation is its ability to conduct the electromechanical admittance monitoring technique by considerably compressing the amount of data required for damage detection and localization. A FEM simulation of electromechanical admittance-based sensing technique was employed by applying lead zirconate titanate (PZT) transducers to acquire impedance spectrum signatures. Response surface methodology (RSM) is finally adopted as a tool for solving inverse problems to estimate the location and size of damaged areas from the relationship between damage and electromechanical admittance changes computed at PZT transducer surfaces. This statistical metamodel technique allows polynomial models to be produced without requiring complicated modeling or numerous data sets after the generation of damage, leading to considerably lower cost of creating diagnostic database. Finally, a numerical example is carried out regarding a steel-reinforced concrete (RC) beam model monotonically loaded up to its failure which is also retrofitted by a CFRP laminate to verify the validity of the present metamodeling monitoring technique. The load-carrying capacity of concrete is predicted in the present paper by utilizing an Ottosen-type failure surface in order to better take into account the passive confinement behavior of retrofitted concrete material under the application of FRP laminate.

• Smart Structures and Systems
• /
• v.1 no.2
• /
• pp.121-140
• /
• 2005

This paper presents a systematic investigation of the effect of sensor location on the data quality and subsequently, on the effectiveness of machine health monitoring. Based on an analysis of the signal propagation process from the defect location to the sensor, numerical simulations using finite element modeling were conducted on a bearing test bed to determine the signal strength at several representative sensor locations. The results showed that placing sensors closely to the machine component being monitored is critical to achieving high signal-to-noise ratio, thus improving the data quality. Using millimeter-sized piezoceramic plates, the obtained results were evaluated experimentally. A comparison with a set of commercial vibration sensors verified the developed structural dynamics-based sensor placement strategy. It further demonstrated that the proposed shock wave-based sensing technique provided an effective alternative to vibration measurement, while requiring less space for sensor installation.

• Journal of Information Processing Systems
• /
• v.15 no.3
• /
• pp.478-491
• /
• 2019

This work develops a monitoring system for the population with health concerns. A belt integrated with an on-body circuit and sensors measures a wearer's selected vital signals. The electrocardiogram sensors monitor heart conditions and an accelerometer assesses the level of physical activity. Sensed signals are transmitted to the circuit module through digital yarns and are forwarded to a mobile device via Bluetooth. An interactive application, installed on the mobile device, is used to process the received signals and provide users with real-time feedback about their status. Persuasive functions are designed and implemented in the interactive application to encourage users' physical activity. Two signal processing algorithms are developed to analyze the data regarding heart and activity. A user study is conducted to evaluate the performance and usability of the developed system.