• Journal of Electrical Engineering and Technology
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• v.9 no.5
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• pp.1753-1761
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• 2014

Due to the inherent inhomogeneous and anisotropy nature of the composite materials, the detection of internal defects in these materials with non-destructive techniques is an important requirement both for quality checks during the production phase and in service inspection during maintenance operations. The estimation of the time-of-arrival (TOA) and/or time-of-flight (TOF) of the ultrasonic echoes is essential in ultrasonic non-destructive testing (NDT). In this paper, we used split-spectrum processing (SSP) combined with matching pursuit signal decomposition (MPSD) to develop a dedicated ultrasonic detection system. SSP algorithm is used for Signal-to-Noise Ratio (SNR) enhancement, and the MPSD algorithm is used to decompose backscattered signals into a linear expansion of chirplet echoes and estimate the chirplet parameters. Therefore, the combination of SSP and MPSD (SSP-MPSD) presents a powerful technique for ultrasonic NDT. The SSP algorithm is achieved by using Gaussian band pass filters. Then, MPSD algorithm uses the Maximum Likelihood Estimation. The good performance of the proposed method is experimentally verified using ultrasonic traces acquired from three specimens of carbon fibre reinforced polymer multi-layered composite materials (CFRP).

• Earthquakes and Structures
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• v.23 no.4
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• pp.385-401
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• 2022

Uncertainty quantification is the most important challenge in seismic fragility assessment of structures. The precision increment of the quantification method leads to reliable results but at the same time increases the computational costs and the latter will be so undesirable in cases such as reliability-based design optimization which includes numerous probabilistic seismic analyses. Accordingly, the authors' effort has been put on the development and validation of an approach that has reduced computational cost in seismic fragility assessment. In this regard, it is necessary to apply the appropriate methods for consideration of two categories of uncertainties consisting of uncertainties related to the ground motions and structural characteristics, separately. Also, cable-stayed bridges have been specifically selected because as a result of their complexity and the according time-consuming seismic analyses, reducing the computations corresponding to their fragility analyses is worthy of studying. To achieve this, the fragility assessment of three case studies is performed based on existing and proposed approaches, and a comparative study on the efficiency in the estimation of seismic responses. For this purpose, statistical validation is conducted on the seismic demand and fragility resulting from the mentioned approaches, and through a comprehensive interpretation, sufficient arguments for the acceptable errors of the proposed approach are presented. Finally, this study concludes that the combination of the Capacity Spectrum Method (CSM) and Uniform Design Sampling (UDS) in advanced proposed forms can provide adequate accuracy in seismic fragility estimation at a significantly reduced computational cost.

• Korean Journal of Artificial Intelligence
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• v.12 no.1
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• pp.17-24
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• 2024

This paper introduces a novel approach to time-series estimation for energy load forecasting within Virtual Power Plant (VPP) systems, leveraging advanced artificial intelligence (AI) algorithms, namely Long Short-Term Memory (LSTM) and Seasonal Autoregressive Integrated Moving Average (SARIMA). Virtual power plants, which integrate diverse microgrids managed by Energy Management Systems (EMS), require precise forecasting techniques to balance energy supply and demand efficiently. The paper introduces a hybrid-method forecasting model combining a parametric-based statistical technique and an AI algorithm. The LSTM algorithm is particularly employed to discern pattern correlations over fixed intervals, crucial for predicting accurate future energy loads. SARIMA is applied to generate time-series forecasts, accounting for non-stationary and seasonal variations. The forecasting model incorporates a broad spectrum of distributed energy resources, including renewable energy sources and conventional power plants. Data spanning a decade, sourced from the Korea Power Exchange (KPX) Electrical Power Statistical Information System (EPSIS), were utilized to validate the model. The proposed hybrid LSTM-SARIMA model with parameter sets (1, 1, 1, 12) and (2, 1, 1, 12) demonstrated a high fidelity to the actual observed data. Thus, it is concluded that the optimized system notably surpasses traditional forecasting methods, indicating that this model offers a viable solution for EMS to enhance short-term load forecasting.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.41 no.8
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• pp.917-920
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• 2016

SpSF algorithm is direction-of-arrival estimation algorithm based on sparse representation of incident signlas. Cost function to be optimized for DOA estimation is multi-dimensional nonlinear function, which is hard to handle for optimization. After some manipulation, the problem can be cast into convex optimiztion problem. Convex optimization problem tuns out to be constrained optimization problem, where the parameter in the constraint has to be determined. The solution of the convex optimization problem is dependent on the specific parameter value in the constraint. In this paper, we propose a rule-of-thumb for determining the parameter value in the constraint. Based on the fact that the noise in the array elements is complex Gaussian distributed with zero mean, the average of the Frobenius norm of the matrix in the constraint can be rigorously derived. The parameter in the constrint is set to be two times the average of the Frobenius norm of the matrix in the constraint. It is shown that the SpSF algorithm actually works with the parameter value set by the method proposed in this paper.

• The Journal of the Acoustical Society of Korea
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• v.22 no.7
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• pp.554-561
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• 2003

Results of the numerical simulation and experimental data analysis for identification of mode cutoff frequency and estimation of sound speed of seabed from the spectrum of acoustic signal received at fixed source-receiver range are presented. Model simulations for Pekeris waveguide show that the frequency-dependent propagation loss and interference pattern are closely related to mode cutoff frequencies and it could be possible to the identify them from the changes of interference pattern. The concept considered at numerical simulations is applied to signals acquired at sea test. Cutoff frequency and sound speed of seabed are estimated from the interference pattern of measured signal. Propagation loss predicted using the estimated sound speed of seabed as model input parameter shows similar estimation result compared to propagation loss derived from measured data.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.36 no.1C
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• pp.48-56
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• 2011

Cognitive radio (CR) systems have received significant interest as a promising solution to the spectral shortage problem through efficient use of the frequency spectrum by opportunistically exploiting unlicensed frequency bands. Orthogonal frequency division multiplexing (OFDM) is widely regarded as a highly promising candidate for CR systems. However, the frequency bands used by CR systems are expected to suffer from non-Gaussian noise, which considerably degrades the performance of the conventional OFDM carrier frequency offset (CFO) estimation schemes. In this paper, robust CFO estimation schemes for OFDM-based CR systems in non-Gaussian channels are proposed. Simulation results demonstrate that the proposed estimators offer robustness and substantial performance improvement over the conventional estimator.

• Proceedings of the KSRS Conference
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• 2007.10a
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• pp.49-52
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• 2007

This study uses empirical method to estimate absorption coefficient of colored dissolved organic matter $(a_{dom})$ from GOCI satellite data with the relationship between band ratio of remote sensing reflectance $(R_{rs})$ and $a_{dom}$. For development of $a_{dom}$ estimation algorithm, the used data is in-situ data about ocean optical properties in the around seawater area of the Korean Peninsula during 1998 - 2005. The relationship of $R_{rs}$(412)/$R_{rs}$(555), $R_{rs}$(443)/$R_{rs}$(555), $R_{rs}$(490)/$R_{rs}$(555), $R_{rs}$(510)/$R_{rs}$(555) and $a_{dom}$(412) showed $R^2$ values of 0.707, 0.707, 0.597 and 0.552, respectively. The spectrum of $a_{dom}({\lambda})$ is shape of exponential function $a_{dom}({\lambda})$ value decreases with increasing wavelength. For estimation of $a_{dom}$ from satellite data, we developed an algorithm from the relationship of $a_{dom}$(412) and $R_{rs}$(412)/$R_{rs}$(555). This algorithm was employed on SeaWiFS imagery to estimate $R_{rs}$(412) in the South Sea, East Sea, Yellow Sea and northern East China Sea areas. Also, SeaDAS-derived $a_{dg}$(412) from same SeaWiFS imagery, These $a_{dg}$(412) was then compared with in-situ and empirical-algorithm-derived $a_{dom}$(412), but these values were different. We think two points that such different values are caused by discrepancy related to failure of standard atmospheric correction scheme, the other are caused by error related to definition of $a_{dom}$(412) and $a_{dg}$(412).

• The Journal of the Acoustical Society of Korea
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• v.24 no.3
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• pp.166-170
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• 2005

This paper describes the experimental study for the position estimation method of underwater sound source using the Nearfield Acoustic Holography. The result confirms that it can be used in the identification of underwater noise sources. The sound sources in the experimental work consists of 2 spherical projectors and the near-Held sound pressure is measured in the hologram plane. From the cross-power spectra of the measured data, the complex sound pressures on the hologram plane is derived and its spatial transformation gives sound fields in a source region. The obtained sound fields in a source region showed that the position of each sound source and their relative source strength are exactly estimated. In conclusion, this technique can be applied for estimation of each source position and its relative strength contribution for the underwater multiple sound sources.

• Journal of the Earthquake Engineering Society of Korea
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• v.20 no.6
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• pp.391-400
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• 2016

For earthquake loss estimation of building structures in Gangnam-Gu district in Seoul, three scenario earthquakes were selected by comparison of the response spectra of these scenario earthquakes with the design spectrum in Korean Building Code (KBC 2009), and then direct losses of the building structures in the Gangnam-Gu district under each scenario earthquake are estimated. The following conclusions are drawn from the results of damage and loss in the second scenario earthquake, which has a magnitude = 6.5 and epicentral distance =15 km: (1) The ratio of building stocks undergoing the extensive and complete damage level is 40.0% of the total. (2) The amount of direct economic losses appears approximately 19 trillion won, which is 1.2% of the national GDP of Korea. (3) About 25% of high-rise (over 10-story) RC building wall structures, were inflicted with the damage exceeding moderate level, when compared to 60% of low-rise building structures. (4) From the economical view point, the main loss, approximately 50%, was caused by the damage in the high-rise RC wall building structures.

• The Journal of the Korea institute of electronic communication sciences
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• v.16 no.3
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• pp.465-470
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• 2021

A robust speech recognition technology is required that does not degrade the performance of speech recognition and the quality of the speech when speech recognition is performed in an actual environment of the speech mixed with noise. With the development of such speech recognition technology, it is necessary to develop an application that achieves stable and high speech recognition rate even in a noisy environment similar to the human speech spectrum. Therefore, this paper proposes a speech enhancement algorithm that processes a noise suppression based on the MMSA-STSA estimation algorithm, which is a short-time spectral amplitude method based on the error of the least mean square. This algorithm is an effective nonlinear speech enhancement algorithm based on a single channel input and has high noise suppression performance. Moreover this algorithm is a technique that reduces the amount of distortion of the speech based on the statistical model of the speech. In this experiment, in order to verify the effectiveness of the MMSA-STSA estimation algorithm, the effectiveness of the proposed algorithm is verified by comparing the input speech waveform and the output speech waveform.