• Smart Structures and Systems
• /
• v.29 no.1
• /
• pp.181-193
• /
• 2022

Data-driven structural health monitoring (SHM) of civil infrastructure can be used to continuously assess the state of a structure, allowing preemptive safety measures to be carried out. Long-term monitoring of large-scale civil infrastructure often involves data-collection using a network of numerous sensors of various types. Malfunctioning sensors in the network are common, which can disrupt the condition assessment and even lead to false-negative indications of damage. The overwhelming size of the data collected renders manual approaches to ensure data quality intractable. The task of detecting and classifying an anomaly in the raw data is non-trivial. We propose an approach to automate this task, improving upon the previously developed technique of image-based pre-processing on one-dimensional (1D) data by enriching the features of the neural network input data with multiple channels. In particular, feature engineering is employed to convert the measured time histories into a 3-channel image comprised of (i) the time history, (ii) the spectrogram, and (iii) the probability density function representation of the signal. To demonstrate this approach, a CNN model is designed and trained on a dataset consisting of acceleration records of sensors installed on a long-span bridge, with the goal of fault detection and classification. The effect of imbalance in anomaly patterns observed is studied to better account for unseen test cases. The proposed framework achieves high overall accuracy and recall even when tested on an unseen dataset that is much larger than the samples used for training, offering a viable solution for implementation on full-scale structures where limited labeled-training data is available.

• Wind and Structures
• /
• v.36 no.4
• /
• pp.221-236
• /
• 2023

The lateral component of turbulence and the vortices shed in the wake of a structure result in introducing dynamic wind load in the acrosswind direction and the resulting level of motion is typically larger than the corresponding alongwind motion for a dynamically sensitive structure. The underlying source mechanisms of the acrosswind load may be classified into motion-induced, buffeting, and Strouhal components. This study proposes a frequency domain framework to decompose the overall load into these components based on output-only measurements from wind tunnel experiments or full-scale measurements. First, the total acrosswind load is identified based on measured acceleration response by solving the inverse problem using the Kalman filter technique. The decomposition of the combined load is then performed by modeling each load component in terms of a Bayesian filtering scheme. More specifically, the decomposition and the estimation of the model parameters are accomplished using the unscented Kalman filter in the frequency domain. An aeroelastic wind tunnel experiment involving a tall circular cylinder was carried out for the validation of the proposed framework. The contribution of each load component to the acrosswind response is assessed by re-analyzing the system with the decomposed components. Through comparison of the measured and the re-analyzed response, it is demonstrated that the proposed framework effectively decomposes the total acrosswind load into components and sheds light on the overall underlying mechanism of the acrosswind load and attendant structural response. The delineation of these load components and their subsequent modeling and control may become increasingly important as tall slender buildings of the prismatic cross-section that are highly sensitive to the acrosswind load effects are increasingly being built in major metropolises.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2021.05a
• /
• pp.289-290
• /
• 2021

Recently, with the advent of the 4th industrial revolution, the role of robots is increasing, and the use of robots is also increasing in the service field. The most popular model for nonlinear research related to robots is the inverted pendulum system. A balancing robot using an inverted pendulum system is a representative nonlinear system and is mainly used to study control theory and other kinematic structures. In this paper, the state of the robot is measured using the 3-axis acceleration sensor (ADXL345) and 3-axis digital output gyro sensor (ITG-3200) or HMC5883L required for balancing robot control, and using the ESP32-WROOM-32 module. I want to design an MCU module that can control a balancing robot. In addition, by using the ESP32-WROOM-32 MCU module, we intend to design an MCU module that can monitor the state of the balancing robot based on WiFi or Bluetooth.

• Journal of the Earthquake Engineering Society of Korea
• /
• v.28 no.3
• /
• pp.149-158
• /
• 2024

Piloti-type structures with vertical irregularity are vulnerable to earthquakes due to the soft structure of the first story. Structural characteristics of buildings can significantly affect the seismic loss function, calculated based on seismic fragility, and therefore need to be considered. This study investigated the effects of the number of stories and core locations on the seismic loss function of piloti-type buildings in Korea. Twelve analytical models were developed considering two variations: three stories (4-story, 5-story, and 6-story) and four core locations (center core, x-eccentric core, y-eccentric core, and xy-eccentric core). The interstory drift ratio and peak floor acceleration were assessed through incremental dynamic analysis using 44 earthquake records, and seismic fragility was derived. Seismic loss functions were calculated and compared using the derived seismic fragility and repair cost ratio of each component. The results indicate that the seismic loss function increases with more stories and when the core is eccentrically located in the piloti-type structure model. Therefore, the uncertainty due to the number of stories and core location should be considered when deriving the seismic loss function of piloti-type structures.

• Journal of the Korean Society for Marine Environment & Energy
• /
• v.19 no.1
• /
• pp.7-17
• /
• 2016

The present study experimentally considers dynamic performance of large floating wave-offshore hybrid power generation platform in extreme conditions. In order to evaluate the motion performance of the large floating hybrid power generation platform, 1/50 scaled model was manufactured. A mooring line was also manufactured, and free-decay and static pull-out tests were carried out to check the mooring model. A mooring line table was introduced to satisfy the water depth, and environmental conditions were checked. Motion responses in regular waves were measured and complicated environmental conditions including wave, wind, and current were applied to see the dynamic performance in extreme/survival conditions. Maximum motion and acceleration were judged following the design criteria, and maximum offset and mooring tension were also checked based on the rule. The characteristics of hybrid power generation platform are discussed based on these data.

• Journal of KIISE:Software and Applications
• /
• v.34 no.12
• /
• pp.1045-1055
• /
• 2007

Latent topic models are statistical models which automatically captures salient patterns or correlation among features underlying a data collection in a probabilistic way. They are gaining an increased popularity as an effective tool in the application of automatic semantic feature extraction from text corpus, multimedia data analysis including image data, and bioinformatics. Among the important issues for the effectiveness in the application of latent topic models to the massive data set is the efficient learning of the model. The paper proposes an accelerated learning technique for PLSA model, one of the popular latent topic models, by an incremental EM algorithm instead of conventional EM algorithm. The incremental EM algorithm can be characterized by the employment of a series of partial E-steps that are performed on the corresponding subsets of the entire data collection, unlike in the conventional EM algorithm where one batch E-step is done for the whole data set. By the replacement of a single batch E-M step with a series of partial E-steps and M-steps, the inference result for the previous data subset can be directly reflected to the next inference process, which can enhance the learning speed for the entire data set. The algorithm is advantageous also in that it is guaranteed to converge to a local maximum solution and can be easily implemented just with slight modification of the existing algorithm based on the conventional EM. We present the basic application of the incremental EM algorithm to the learning of PLSA and empirically evaluate the acceleration performance with several possible data partitioning methods for the practical application. The experimental results on a real-world news data set show that the proposed approach can accomplish a meaningful enhancement of the convergence rate in the learning of latent topic model. Additionally, we present an interesting result which supports a possible synergistic effect of the combination of incremental EM algorithm with parallel computing.

• KSCE Journal of Civil and Environmental Engineering Research
• /
• v.35 no.1
• /
• pp.1-8
• /
• 2015

Wind power systems have gained much attention due to the relatively high reliability, good infrastructures and cost competitiveness to the fossil fuels. Advances have been made to increase the power efficiency of wind turbines while less attention has been focused on structural integrity assessment of structural sub-systems such as towers and foundations. Among many parameters for integrity assessment, the most perceptive parameter may be the induced horizontal displacement at the hub height although it is very difficult to measure particularly in large-scale and high-rise wind turbine structures. This study proposes an indirect displacement estimation scheme based on the combined use of inclinometers and accelerometers for more convenient and cost-effective measurements. To this end, (1) the formulation for data fusion of inclination and acceleration responses was presented and (2) the proposed method was numerically validated on an NREL 5 MW wind turbine model. The numerical analysis was carried out to investigate the performance of the propose method according to the number of sensors, the resolution and the available sampling rate of the inclinometers to be used.

• Journal of the Computational Structural Engineering Institute of Korea
• /
• v.25 no.4
• /
• pp.323-330
• /
• 2012

This study deals with the experiments of liquid dampers with multi cells whose vertical tubes are divided into several square columns for easily changing natural frequencies. Shaking table test is performed to verify control effectiveness of the dampers which are installed on a building structure. To design liquid dampers, a 64-story building structure is reduced to a SDOF structure with 1/20 of similitude laws based on acceleration. The structure model is made up to adjust its mass and stiffness easily, with separate mass and drive parts. Mass parts indicate real structure's weights and drive parts indicate real structure's stiffness with springs and LM guides. Manufactured liquid damper has 18 cells and its natural frequency ranges are 0.65Hz to 0.81Hz. Shaking table test is carried out with one way excitation to compare with only accelerations of a large-scale structure and a structure installed with liquid dampers. Control performance of the liquid damper is expressed by the transfer function from shaking table accelerations to the large-scale structure ones. Testing results show that the liquid damper reduced a large-scale structure's response by tuned natural frequencies.

• Journal of the Korean Geotechnical Society
• /
• v.25 no.11
• /
• pp.27-38
• /
• 2009

In this study, a series of 1 g shaking table model pile tests were carried out in saturated dense and loose sand to evaluate dynamic p-y curves for various conditions of flexural stiffness of a pile shaft, acceleration frequency and acceleration amplitude for input loads. Dynamic p-y backbone curve which can be applied to pseudo static analysis for saturated dense sand was proposed as a hyperbolic function by connecting the peak points of the experimental p-y curves, which corresponded to maximum soil resistances. In order to represent the backbone curve numerically, empirical equations were developed for the initial stiffness ($k_{ini}$) and the ultimate capacity ($p_u$) of soils as a function of a friction angle and a confining stress. The applicability of a p-y backbone curve was evaluated based on the centrifuge test results of other researchers cited in literature, and this suggested backbone curve was also compared with the currently available p-y curves. And also, the scaling factor ($S_F$) to account for the degradation of soil resistance according to the excess pore pressure was developed from the results of saturated loose sand.

• Earthquakes and Structures
• /
• v.23 no.4
• /
• pp.373-384
• /
• 2022

To improve the seismic performance of suspended ceiling structures, various vibration-damping devices have been developed. However, the devices made of metals have a limit in that they cause large deformation and seriously damages the exterior of the suspended ceiling structure from the wall. As a results, their strengthening effect of the suspended ceiling structure was minimal. Thus, this study employed a spring and vibration-proof rubber effectively controlled vibrations without increasing horizontal seismic loads on the ceiling to enhance the seismic resistance of suspended ceiling structures. The objective of the study is to examine the dynamic properties of a seismic damping-isolation unit (SDI) with various details developed. The developed SDI was composed of a spring, embossed rubbers, and prestressed bolts, which were the main factors enhancing the damping effect. The shaking table tests were performed on eight SDI specimens produced with the number of layers of embossed rubber (n_s), presence or absence of a spring, prestressed force magnitude introduced in bolts (f_ps), and mass weight (W_m) as the main parameters. To identify the enhancement effect of the SDI, the dynamic properties of the control specimen with a conventional hanger bolt were compared to those of the SDI specimens. The SDI specimens were effective in reducing the maximum acceleration (A_{c max}), acceleration amplification factor (α_p), relative displacement (δ_R), and increasing the damping ratio (ξ) when compared to the control specimen. The A_{c max}, α_p, and δ_R of the SDI specimens with two rubbers, spring, and f_ps of 0.1f_by, where f_by is the yielding strength of the screw bolt were 57.8%, 58.0%, and 61.9% lower than those of the conventional hanger bolt specimens, respectively, resulting in the highest ξ (=0.127). In addition, the α_p of the SDI specimens was 50.8% lower than those specified in ASCE 7 and FEMA 356. Consequently, to accurately estimate the α_p of the SDI specimens, a simple model was proposed based on the functions of f_ps, stiffness constant of the spring (K), W_m, and n_s.