• Structural Engineering and Mechanics
• /
• v.83 no.4
• /
• pp.537-549
• /
• 2022

In this paper, a novel multi-feature model predictive control (MPC) framework with real-time and adaptive performances is proposed for intelligent structural control in which some drawbacks of the algorithm including, complex control rule and non-optimality, are alleviated. Hence, Linear Programming (LP) is utilized to simplify the resulted control rule. Afterward, the Whale Optimization Algorithm (WOA) is applied to the optimal and adaptive tuning of the LP weights independently at each time step. The stochastic control rule is also achieved using Kalman Filter (KF) to handle noisy measurements. The Extreme Learning Machine (ELM) is then adopted to develop a data-driven and real-time control algorithm. The efficiency of the developed algorithm is then demonstrated by numerical simulation of a twenty-story high-rise benchmark building subjected to earthquake excitations. The competency of the proposed method is proven from the aspects of optimality, stochasticity, and adaptivity compared to the KF-based MPC (KMPC) and constrained MPC (CMPC) algorithms in vibration suppression of building structures. The average value for performance indices in the near-field and far-field (El earthquakes demonstrates a reduction up to 38.3% and 32.5% compared with KMPC and CMPC, respectively.

• Steel and Composite Structures
• /
• v.49 no.4
• /
• pp.407-417
• /
• 2023

After a disaster like the catastrophic earthquake, the government have to use rapid assessment of the condition (or damage) of bridges, buildings and other infrastructures is mandatory for rapid feedbacks, rescue and post-event management. Many domain schemes based on the measured vibration computations, including least squares estimation and neural fuzzy logic control, have been studied and found to be effective for online/offline monitoring of structural damage. Traditional strategies require all external stimulus data (input data) which have been measured available, but this may not be the generalized for all structures. In this article, a new method with unknown inputs (excitations) is provided to identify structural matrix such as stiffness, mass, damping and other nonlinear parts, unknown disturbances for example. An analytical solution is thus constructed and presented because the solution in the existing literature has not been available. The goals of this paper are towards access to adequate, safe and affordable housing and basic services, promotion of inclusive and sustainable urbanization and participation, implementation of sustainable and disaster-resilient buildings, sustainable human settlement planning and manage. Simulation results of linear and nonlinear structures show that the proposed method is able to identify structural parameters and their changes due to damage and unknown excitations. Therefore, the goal is believed to achieved in the near future by the ongoing development of AI and control theory.

• The Journal of Korea Robotics Society
• /
• v.18 no.4
• /
• pp.427-435
• /
• 2023

This paper proposes a method of estimating the pose of a mobile robot by using a learning model. When estimating the pose of a mobile robot, wheel encoder and inertial measurement unit (IMU) data are generally utilized. However, depending on the condition of the ground surface, slip occurs due to interaction between the wheel and the floor. In this case, it is hard to predict pose accurately by using only encoder and IMU. Thus, in order to reduce pose error even in such conditions, this paper introduces a pose estimation method based on a learning model using data of the wheel encoder and IMU. As the learning model, long short-term memory (LSTM) network is adopted. The inputs to LSTM are velocity and acceleration data from the wheel encoder and IMU. Outputs from network are corrected linear and angular velocity. Estimated pose is calculated through numerically integrating output velocities. Dataset used as ground truth of learning model is collected in various ground conditions. Experimental results demonstrate that proposed learning model has higher accuracy of pose estimation than extended Kalman filter (EKF) and other learning models using the same data under various ground conditions.

• Journal of the Institute of Convergence Signal Processing
• /
• v.24 no.1
• /
• pp.1-14
• /
• 2023

Underwater images carry information that is useful in the fields of aquaculture, underwater military security, navigation, transportation, and so on. In this research, we transmitted an underwater image through various underwater mediums in the presence of underwater turbulence and beam attenuation effects using a high-speed visible optical carrier signal. The optical beam undergoes scintillation because of the turbulence and attenuation effects; therefore, distorted images were observed at the receiver end. To understand the behavior of the communication media, we obtained the bit error rate (BER) performance of the system with respect to the average signal-to-noise ratio (SNR). Also, the structural similarity index (SSI) and peak SNR (PSNR) metrics of the received image were evaluated. Based on the received images, we employed suitable nonlinear filters to recover the distorted images and enhance them further. The BER, SSI, and PSNR metrics of the specific nonlinear filters were also evaluated and compared with the unfiltered metrics. These metrics were evaluated using the on-off keying and binary phase-shift keying modulation techniques for the 50-m and 100-m links for beam attenuation resulting from pure seawater, clear ocean water, and coastal ocean water mediums.

• The Journal of the Acoustical Society of Korea
• /
• v.26 no.3
• /
• pp.129-135
• /
• 2007

In this paper. we propose a prewhitening method for the km reverberation to enhance the target signal. The proposed algorithm uses the dechirping method which inversely compensates the frequency chirp rate of LFM and transforms the LFM reverberation to have stationary frequency property in each data block. Also, using the left and right adjacent beam signals as reference signals. we model frequency response of each data block by AR coefficients. From these coefficients, we implement inverse filter and prewhiten the LFM reverberation of the center beam efficiently.

• Journal of the Korean Society of Radiology
• /
• v.17 no.3
• /
• pp.305-314
• /
• 2023

With the development of medical technology and radiation treatment equipment, the frequency of high-precision radiation therapy such as intensity modulation radiation therapy has increased. Image-guided radiation therapy has become essential for radiation therapy in precise and complex treatment plans. In particular, with the introduction of imaging equipment for diagnosis in a linear accelerator, CBCT scanning became possible, which made it possible to calibrate and correct the patient's posture through 3D images. Although more precise reproduction of the patient's posture has become possible, the exposure dose delivered to the patient during the image acquisition process cannot be ignored. Radiation optimization is necessary in the field of radiation therapy, and efforts to reduce exposure are necessary. However, when acquiring 3D CBCT images by changing the imaging conditions to reduce exposure, there should be no image quality or artefacts that would make it impossible to align the patient's position. In this study, Rando phantom was used to scan and evaluate images for each shooting condition. The highest SNR was obtained at 100 kV 80 mA 25 ms F1 filter 180°. As the tube voltage and tube current increased, the noise decreased, and the bowtie filter showed the optimal effect at high tube current. Based on the actual scanned images, it was confirmed that patient alignment was possible under all imaging conditions, and that image-guided radiation therapy for patient alignment was possible under the condition of 70 kV 10 mA 20 ms F0 filter 180°, which showed the lowest SNR. In this study, image evaluation was conducted according to the imaging conditions, and low tube voltage, tube current, and small rotation angle scan are expected to be effective in reducing radiation exposure. Based on this, the patient's exposure dose should be kept as low as possible during CBCT imaging.

• Journal of the Computational Structural Engineering Institute of Korea
• /
• v.20 no.6
• /
• pp.769-778
• /
• 2007

In this paper, excitation systems using linear mass shaker (LMS) and active tuned mass damper (ATMD) are presented in order to simulate the wind induced responses of a building structure. The actuator force for the excitation systems is calculated by using the inverse transfer function of a target structural response to the actuator. Filter and envelop function are used such that the error between the wind and actuator induced responses is minimized by preventing the actuator from exciting unexpected modal response and initial transient response. The analyses results from a 76-story benchmark building problem in which wind load obtained by wind tunnel test is given, indicate that the excitation system installed at a specific floor can approximately embody the structural responses induced by the wind load applied to each floor of the structure. The excitation system designed by the proposed method can be effectively used for evaluating the wind response characteristics of a practical building structure and for obtaining an accurate analytical model of the building under wind load.

• Journal of Korean Society of Occupational and Environmental Hygiene
• /
• v.11 no.3
• /
• pp.235-240
• /
• 2001

This study was performed to compare the lead levels of 20 quality control standard samples(KOSHA:18-2000) and 72 field samples in lead-acid battery manufacturing plant between ICP and portable-XRF methods. 1. While the proficiencies of 20 quality control standard samples by ICP were 100%, those of analytic result values by XRF were 75%. 2. The correlation coefficient(r) between the reference values for quality control (REF) and the analytic result values by ICP (ICP) was 1.0(p<0.05), and simple linear regression equation and the coefficient(R2) were REF = -0.0009 + 1.016 ICP and 0.9997, respectively. 3. The correlation coefficient(r) between the analytic result values of quality control standard samples by ICP (ICP) and by XRF (XRF) was 0.975(p<0.05), and simple linear regression equation and the coefficient(R2) were ICP = -0.0003 + 1.002 XRF and 0.950, respectively. 4. The correlation coefficient(r) between the analytic result values for lead samples of a lead-acid battery manufacturing plant by ICP (ICP) and by XRF (XRF) was 0.993(p<0.05), and simple linear regression equation and the coefficient(R2) were ICP = -2.058 + 0.996 XRF and 0.987, respectively. 5. While the frequency distributions of XRF /ICP(Ratio) for each ICP concentration levels in a lead-acid battery manufacturing plant revealed high proportion in ratio range of 0.876-1.125 than in ration range of 1.126-1.375. Also, ICP concentration level in ration range of 0.786-1.125 was increased with increase of frequency distribution of XRF/ICP. 6. The limit of detection of XRF on lead was determined to be $6.11{\mu}g$/filter The data presented in this study indicated that relationship for lead level of quality control samples and field samples in a lead -acid battery manufacturing plant by ICP and portable-XRF methods was proved. The practicing industrial hygienist can use portable-XRF to produce a rapid on-site determination of lead exposure that can immediately becommunicated to workers and help identify appropriate levels of personal protection.

• Geophysics and Geophysical Exploration
• /
• v.6 no.4
• /
• pp.171-179
• /
• 2003

In land and marine seismic survey, we generally set receivers with equal interval suppose that sampling interval Is too narrow. But the cost of seismic data acquisition and that of data processing are much higher, therefore we should design proper receiver interval. Spatial aliasing can be occurred on seismic data when sampling interval is too coarse. If we Process spatial aliasing data, we can not obtain a good imaging result. Trace interpolation is used to improve the quality of multichannel seismic data processing. In this study, we applied the Spitz algorithm which is widely used in seismic data processing. This algorithm works well regardless of dip information of the complex underground structure. Using prediction filter and original traces with linear event we interpolated in f-x domain. We confirm our algorithm by examining for some synthetic data and marine data. After interpolation, we could find that receiver intervals get more narrow and the number of receiver is increased. We also could see that continuity of traces is more linear than before Applying this interpolation algorithm on seismic data with spatial aliasing, we may obtain a better migration imaging.

• Journal of Broadcast Engineering
• /
• v.27 no.2
• /
• pp.244-247
• /
• 2022

In this paper, the performance of the decoding schemes using linear MMSE filters in the frequency and time domains and the reinforcement Gauss-Seidel algorithm for the orthogonal time frequency space (OTFS) system that can improve robustness under high-speed mobile environments are compared. The reinforcement Gauss-Seidel algorithm can improve the bit error rate performance by suppressing the noise enhancement. The simulation results show that the performance of the decoding scheme using the linear MMSE filter in the frequency domain is severely degraded due to the effect of Doppler shift as the mobile speed increases. In addition, the decoding scheme using the reinforcement Gauss-Seidel algorithm under the channel environment with 120 km/h and 500 km/h speeds outperforms the decoding schemes using linear MMSE filters in the frequency and time domains.