• Journal of the Computational Structural Engineering Institute of Korea
• /
• v.33 no.4
• /
• pp.271-277
• /
• 2020

There are increasing cases of monitoring the structural response of structures using multiple sensors. However, owing to cost and management problems, limited sensors are installed in the structure. Thus, few structural responses are collected, which hinders analyzing the behavior of the structure. Therefore, a technique to predict responses at a location where sensors are not installed to a reliable level using limited sensors is necessary. In this study, a numerical study is conducted to predict the seismic response of low-rise buildings using limited information. It is assumed that the available response information is only the acceleration responses of the first and top floors. Using both information, the first natural frequency of the structure can be obtained. The acceleration information on the first floor is used as the ground motion information. To minimize the error on the acceleration history response of the top floor and the first natural frequency error of the target structure, the method for predicting the mass and stiffness information of a structure using the genetic algorithm is presented. However, the constraints are not considered. To determine the range of design variables that mean the search space, the parameter prediction method based on artificial neural networks is proposed. To verify the proposed method, a five-story structure is used as an example.

• Journal of the Korea institute for structural maintenance and inspection
• /
• v.20 no.4
• /
• pp.27-34
• /
• 2016

A new algorithm for determining optimal accelerometer locations is proposed by using a frequency-domain Hankel matrix which is much simpler to construct than a time-domain Hankel matrix. The algorithm was examined through simulation studies by comparing the outcomes with those from other available methods. To compare and analyze the results from different methods, a dynamic analysis was carried out under seismic excitation and acceleration data were obtained at the selected optimal sensor locations. Vibrational amplitudes at the selected sensor locations were determined and those of all the other degrees of freedom were determined by using a spline function. MAC index of each method was calculated and compared to look at which method could determine more effective locations of accelerometers. The proposed frequency-domain Hankel matrix could determine reasonable selection of accelerometer locations compared with the others.

• Journal of Electrical Engineering and Technology
• /
• v.8 no.6
• /
• pp.1320-1327
• /
• 2013

In this paper, two different electromagnetic energy harvesters using bulk micromachined silicon spiral springs and Polydimethylsiloxane (PDMS) packaging technique have been fabricated, characterized, and compared to generate electrical energy from ultra-low ambient vibrations under 0.3g. The proposed energy harvesters were comprised of a highly miniaturized Neodymium Iron Boron (NdFeB) magnet, silicon spiral spring, multi-turned copper coil, and PDMS housing in order to improve the electrical output powers and reduce their sizes/volumes. When an external vibration moves directly the magnet mounted as a seismic mass at the center of the spiral spring, the mechanical energy of the moving mass is transformed to electrical energy through the 183 turns of solenoid copper coils. The silicon spiral springs were applied to generate high electrical output power by maximizing the deflection of the movable mass at the low level vibrations. The fabricated energy harvesters using these two different spiral springs exhibited the resonant frequencies of 36Hz and 63Hz and the optimal load resistances of $99{\Omega}$ and $55{\Omega}$, respectively. In particular, the energy harvester using the spiral spring with two links exhibited much better linearity characteristics than the one with four links. It generated $29.02{\mu}W$ of output power and 107.3mV of load voltage at the vibration acceleration of 0.3g. It also exhibited power density and normalized power density of $48.37{\mu}W{\cdot}cm-3$ and $537.41{\mu}W{\cdot}cm-3{\cdot}g-2$, respectively. The total volume of the fabricated energy harvesters was $1cm{\times}1cm{\times}0.6cm$ (height).

• Journal of the Korean Geosynthetics Society
• /
• v.18 no.4
• /
• pp.107-114
• /
• 2019

In this paper, the P-wave multiple detection system for the fast and accurate earthquake early warning nearby the epicenter was developed. The developed systems were installed in five selected public buildings for the validation. During the monitoring, a magnitude 2.3 earthquake occurred in Pohang on 26 September 2019. P-wave initial detection algorithms were operated in three out of four systems installed in Pohang area and recorded as seismic events. At the nearest station, 5.5 km from the epicenter, P-wave signal was detected 1.2 seconds after the earthquake, and S-wave was reached 1.02 seconds after the P-wave reached, providing some alarm time. The maximum accelerations recorded in three different stations were 6.28 gal, 6.1 gal, and 5.3 gal, respectively. The alarm algorithm did not work, due to the high threshold of the maximum ground acceleration (25.1 gal) to operate it. If continuous monitoring and analysis are to be carried out in the future, the developed system could use a highly effective earthquake warning system suitable for the domestic situation.