• Nuclear Engineering and Technology
• /
• v.55 no.6
• /
• pp.2096-2106
• /
• 2023

Rotating machinery is widely applied in important equipment of nuclear power plants (NPPs), such as pumps and valves. The research on intelligent fault diagnosis of rotating machinery is crucial to ensure the safe operation of related equipment in NPPs. However, in practical applications, data-driven fault diagnosis faces the problem of small and imbalanced samples, resulting in low model training efficiency and poor generalization performance. Therefore, a deep convolutional conditional generative adversarial network (DCCGAN) is constructed to mitigate the impact of imbalanced samples on fault diagnosis. First, a conditional generative adversarial model is designed based on convolutional neural networks to effectively augment imbalanced samples. The original sample features can be effectively extracted by the model based on conditional generative adversarial strategy and appropriate number of filters. In addition, high-quality generated samples are ensured through the visualization of model training process and samples features. Then, a deep convolutional neural network (DCNN) is designed to extract features of mixed samples and implement intelligent fault diagnosis. Finally, based on multi-fault experimental data of motor and bearing, the performance of DCCGAN model for data augmentation and intelligent fault diagnosis is verified. The proposed method effectively alleviates the problem of imbalanced samples, and shows its application value in intelligent fault diagnosis of actual NPPs.

• Nuclear Engineering and Technology
• /
• v.52 no.9
• /
• pp.2107-2118
• /
• 2020

The nuclear reactor coupled with supercritical carbon dioxide (S-CO₂) Brayton cycle has good prospects in generation IV reactors. Turbomachineries (turbine and compressor) are important work equipment in circulatory system, whose performances are critical to the efficiency of the energy conversion system. However, the sharp variations of S-CO₂ thermophysical properties make turbomachinery performances more complex than that of traditional working fluids. Meanwhile, almost no systematic analysis has considered the effects of turbomachinery efficiency under different conditions. In this paper, an in-house code was developed to realize the geometric design and performance prediction of S-CO₂ turbomachinery, and was coupled with systematic code for Brayton cycle characteristics analysis. The models and methodology adopted in calculation code were validated by experimental data. The effects of recompressed fraction, pressure and temperature on S-CO₂ recompression Brayton cycle were studied based on detailed design of turbomachinery. The results demonstrate that the recompressed fraction affects the turbomachinery characteristic by changing the mass flow and effects the system performance eventually. By contrast, the turbomachinery efficiency is insensitive to variation in pressure and temperature due to almost constant mass flow. In addition, the S-CO₂ thermophysical properties and the position of minimum temperature difference are significant influential factors of cyclic performance.

• Proceedings of the Korean Society of Broadcast Engineers Conference
• /
• 2012.07a
• /
• pp.164-166
• /
• 2012

In this paper, we proposed a method for extracting predominant melody of polyphonic music based on harmonic structure. Harmonic structure is an important feature parameter of monophonic signal that has spectral peaks at the integer multiples of its fundamental frequency. We extract all fundamental frequency candidates contained in the polyphonic signal by verifying the required condition of harmonic structure. Then, we combine those harmonic peaks corresponding to each extracted fundamental frequency and assign a rank to each after calculating its harmonic average energy. We run pitch tracking based on the rank of extracted fundamental frequency and continuity of fundamental frequency, and determine the predominant melody. For the query by singing/humming (QbSH) task, we proposed Dynamic Time Warping (DTW) based matching engine. Our system reduces false alarm by combining the distances of multiple DTW processes. To improve the performance, we introduced the asymmetric sense, pitch level compensation, and distance intransitiveness to DTW algorithm.

• Journal of Power Electronics
• /
• v.15 no.4
• /
• pp.1085-1092
• /
• 2015

In this paper, the expressions of the estimated information of a single-phase enhanced phase-locked loop (EPLL), when input signal contains harmonics and a DC offset while the fundamental component takes step changes, are derived. The theoretical analysis results indicate that in the estimated information, the n^th-order harmonics cause n+1^th-order periodic ripples, and the DC offset causes a periodic ripple at the fundamental frequency. Step changes of the amplitude, phase angle and frequency of the fundamental component cause a transient periodic ripple at twice the frequency. These periodic ripples deteriorate the performance of the EPLL. A hybrid filter based EPLL (HF-EPLL) is proposed to eliminate these periodic ripples. A delay signal cancellation filter is set at the input of the EPLL to cancel the DC offset and even-order harmonics. A sliding Goertzel transform-based filter is introduced into the amplitude estimation loop and frequency estimation loop to eliminate the periodic ripples caused by the residual input odd-order harmonics and step change of the input fundamental component. The parameter design rules of the two filters are discussed in detail. Experimental waveforms of both the conventional EPLL and the proposed HF-EPLL are given and compared with each other to verify the theoretical analysis and advantages of the proposed HF-EPLL.

• Structural Engineering and Mechanics
• /
• v.69 no.2
• /
• pp.155-162
• /
• 2019

It is very common to find an empirical formulation in an earthquake design code to calculate fundamental vibration period of a structural system. Fundamental vibration period or frequency is a key parameter to provide adequate information pertinent to dynamic characteristics and performance assessment of a structure. This parameter enables to assess seismic demand of a structure. It is possible to find an empirical formulation related to reinforced concrete structures, masonry towers and slender masonry structures. Calculated natural vibration frequencies suggested by empirical formulation in the literatures has not suits in a high accuracy to the case of rest of the historical masonry bridges due to different construction techniques and wide variety of material properties. For the listed reasons, estimation of fundamental frequency gets harder. This paper aims to present an empirical formulation through Mean Square Error study to find ambient vibration frequency of historical masonry bridges by using a non-linear regression model. For this purpose, a series of data collected from literature especially focused on the finite element models of historical masonry bridges modelled in a full scale to get first global natural frequency, unit weight and elasticity modulus of used dominant material based on homogenization approach, length, height and width of the masonry bridge and main span length were considered to predict natural vibration frequency. An empirical formulation is proposed with 81% accuracy. Also, this study draw attention that this accuracy decreases to 35%, if the modulus of elasticity and unit weight are ignored.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.21 no.4
• /
• pp.173-180
• /
• 2020

This is the report of a case study to describe the results of applying an evaluation tool for communication ability when performing core basic nursing skills in fundamental nursing practice education. The communication ability evaluation tool was constructed based on a literature review and expert advice. The tool was applied to test 94 students who were taking fundamental nursing practice courses from October to November 2019. As a result, five factors (self-introduction, eye contact, emotional support, information provision, and therapeutic touch) were derived as evaluable items of communication ability to be evaluated when performing core basic nursing skill, and were evaluated when performing core basic nursing skills to measure vital signs. The average communication ability was 3.96 out of 5 points. According to the rubric, 95.8% of all students attained 'medium' and reached their goal achievement level. The findings of this study are meaningful in providing an important basis for improving the performance outcome evaluation process and for constructing a systematic evaluation system in fundamental nursing practicum. Further studies to secure the validity and reliability of this communication ability evaluation tool and comparative studies with various evaluation tools are suggested.

• Proceedings of the KIEE Conference
• /
• 2009.07a
• /
• pp.203_204
• /
• 2009

In this paper, we propose a Fourier transform-based modified phasor estimation method to eliminate the adverse influence of exponentially decaying DC offsets. Discrete Fourier Transform (DFT) is generally used to calculate the phasor of the fundamental frequency component in digital protective relays. However, the output of the DFT contains an error due to exponentially decaying DC offsets. Therefore, the decaying DC components should be taken into consideration when calculating the phasor of the fundamental frequency component of a relaying signal. In this paper, the error due to DC offsets in a DFT is calculated and eliminated using the outputs of quaternity DFT, so that the phasor of the fundamental component can be accurately estimated. The performance of the proposed algorithm is evaluated by using computer-simulated signals and EMTP-generated signals. A performance evaluation showed that the proposed algorithm was not affected by system and fault conditions. Thus, the proposed algorithm can effectively suppress the adverse influence of DC offsets in a relaying signal.

• Journal of the Korea Society of Computer and Information
• /
• v.21 no.12
• /
• pp.131-137
• /
• 2016

In this paper, the peak finding algorithms corresponding to the Autocorrelation Function (ACF), which are widely exploited for detecting the pitch of voiced signal, are proposed. According to various researchers, it is well known fact that the estimation of fundamental frequency (F0) in speech signal is not only very important task but quite difficult mission. The proposed algorithms, presented in this paper, are implemented by using many characteristics - such as monotonic increasing function - of ACF function. Thus, the proposed algorithms may be able to estimate both reliable and correct the fundamental frequency as long as the autocorrelation function of speech signal is accurate. Since the proposed algorithms may reduce the computational complexity it can be applied to the real-time processing. The speech data, is composed of Korean emotion expressed words, is used for evaluation of their performance. The pitches are measured to compare the performance of proposed algorithms.

• Smart Structures and Systems
• /
• v.16 no.1
• /
• pp.1-26
• /
• 2015

Minimizing construction cost and reducing seismic damage are two conflicting objectives in the design of any new structure. In the present work, we try to develop a framework in order to solve the optimum performance-based design problem considering the construction cost and the seismic damage of steel moment-frame structures. The Park-Ang damage index is selected as the seismic damage measure because it is one of the most realistic measures of structural damage. The non-dominated sorting genetic algorithm (NSGA-II) is employed as the optimization algorithm to search the Pareto optimal solutions. To improve the time efficiency of the proposed framework, three simplifying strategies are adopted: first, simplified nonlinear modeling investigating minimum level of structural modeling sophistication; second, fitness approximation decreasing the number of fitness function evaluations; third, wavelet decomposition of earthquake record decreasing the number of acceleration points involved in time-history loading. The constraints of the optimization problem are considered in accordance with Federal Emergency Management Agency's (FEMA) recommended seismic design specifications. The results from numerical application of the proposed framework demonstrate the efficiency of the framework in solving the present multi-objective optimization problem.

• Proceedings of the Korea Concrete Institute Conference
• /
• 1999.10a
• /
• pp.263-266
• /
• 1999

This study aims to make high performance concrete for normal strength using crushed stone fines to control high strength of the high performance concrete. According to the experimental results, when crushed stone fines are increased every 10%, 15% of compressive strength is decreased, and 5% of drying shrinkage is increased, compared to normal high performance concrete. Also, high performance concrete has been evaluated to have good durability factor more than 100% in the 480cycle of freezing and thawing test, without regard to using AE and crushed stone fines.