• New & Renewable Energy
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• v.9 no.3
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• pp.5-13
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• 2013

In the previous research, dynamic results have been analyzed in the time and frequency regions. Time and frequency region can be transformed by the Fourier transform. This transform is very useful about analyzing system behaviors. However, because of coupling, it cannot give clear results in the real system including lots of defects. In this paper, we introduced the analysis based on quefrency region to represent physical means clearly from complicated results. We simulated the drive train system which has defects, and compared between frequency and quefrency region to show its excellence. To do this process, We established mathematical model. The equation of motion was derived by the Lagrange equation and constraint equations. The constraint equation included relationships about gear mesh, flexibility of shaft. About numerical analysis, the Newmark beta method was used to get results. And FFT (Fast Fourier Transform) which converts results from time domain to frequency, qufrequency was used.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.38 no.9
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• pp.21-28
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• 2001

The economical detection of dual-tone multi-frequency(DTMF) signals is an important factor when developing cost-effective telecommunication equipment. Each chanel has independently a DTMF receiver, and it informs the detected signal to processors. In order to detect the DTMF signals, the receiver use algorithm such DFT, FFT and Goertzel methods. This paper analyze the power spectra of the DTMF receiver by using the QFT algorithm. As experimental results, it show that can the improved performance of the DTMF receiver and can reduce memory waste and the real time processing.

• Journal of the Korean Institute of Intelligent Systems
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• v.19 no.1
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• pp.145-151
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• 2009

Orthogonal Frequency Division Multiplexing (OFDM) has been focused on as 4th generation communication method for realization of Ubiquitous Network in land mobile communications services, and has been a standard technology of Wireless Local Area Network (WLAN) for a High Date Rate communication. And in maritime data communication using high frequency (HF) band, 32-point FFT OFDM system is recommended by International Telecommunication Union (ITU). Maritime communication should be kept on connecting when maritime accident or the maritime disaster happen. Therefore, main device FFT should be operated with low power consumption. In this paper we propose a low power 32-point FFT algorithm using radix-2 and radix-4 for low power operation. The proposed algorithm was designed using VHSIC hardware description language (VHDL), and it was confirmed that the output value of Spartan-3 field-programmable gate array (FPGA) board corresponded to the output value calculated using Matlab. The proposed 32-point FFT algorithm will be useful as a leading technology in a HF maritime data communication.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.23 no.1
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• pp.116-124
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• 2009

This paper proposes a new Artificial-Intelligent(AI) Power Quality(PQ) diagnosis algorithm using Discrete Wavelet Transform(DWT), Fast Fourier Transform(FFT), Root-Mean-Square(RMS) value. The developed algorithm is able to detect and classify the PQ problems such as the transient, the voltage sag, the voltage swell, the voltage interruption and the total harmonics distortion. The 15.36[kHz] sampling frequency is used to measure the voltages in a power system. The measured signals are used for DWT, FFT, RMS calculation. For AI diagnosis of the PQ problems, a simple multi-layered Artificial Neural Network(ANN) with the back-propagation algorithm is adopted, programmed in C++ and tested in PSIM simulation studies. Finally, the algorithm, which is installed in MP PQ+256 with TI DSP320C6713, is proved to diagnose the PQ problems efficiently.

• Smart Structures and Systems
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• v.4 no.3
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• pp.343-365
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• 2008

In this study, the frequency domain method which utilizes the evaluation of changes in the structural mode shape is adopted to identify regions which contain localized damages. Frequency response function (FRF) values corresponding to the modal frequency, analogous to the mode shape coefficients, are used since change in natural frequency of the system is usually insignificant for localized damage. This method requires only few sensors to obtain the dynamic response of the structure at specific locations to determine the FRF via fast-Fourier transform (FFT). Numerical examples of an aluminum plate, which includes damages of varying severity, locations and combinations of multiple locations, are presented to demonstrate the feasibility of the method. An experimental verification of the method is also done using an aluminum plate with two different degrees of damage, namely a half-through notch and a through notch. The inconsistency in attaining the FRF values for practical applications due to varying impact load may be overcome via statistical averaging, although large variations in the loading in terms of the contact duration should still be avoided. Nonetheless, this method needs special attention when the damages induce notable changes in the modal frequency, such as when the damages are of high severity or cover more extensive area or near the boundary where the support condition is modified. This is largely due to the significant decrease in the frequency term compared to the increase in the vibration amplitude. For practical reasons such as the use of limited number of sensors and to facilitate automation, extending the resolution of this method of identification may not be efficient. Hence, methods based on wave propagation can be employed as a complement on the isolated region to provide an accurate localization as well as to trace the geometry of the damage.

• Journal of the Korea Society of Computer and Information
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• v.11 no.4 s.42
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• pp.55-60
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• 2006

The proposed method uses FFT(Fast Fourier Transform) and neural networks in order to extract texts in real time. In general, text areas are found in the higher frequency domain, thus, can be characterized using FFT. The neural network are learned by character region(high frequency) and non character region(low frequency). The candidate text areas can be thus found by applying the higher frequency characteristics to neural network. Therefore, the final text area is extracted by verifying the candidate areas. Experimental results show a perfect candidate extraction rate and about 95% text extraction rate. The strength of the proposed algorithm is its simplicity, real-time processing by not processing the entire image.

• The Journal of the Korea institute of electronic communication sciences
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• v.18 no.1
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• pp.115-126
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• 2023

Due to the fluctuating random and periodical nature of renewable energy generation power quality disturbances occurred more frequently in power generation transformation transmission and distribution. Various power quality disturbances may lead to equipment damage or even power outages. Therefore it is essential to detect and classify different power quality disturbances in real time automatically. The traditional PQD identification method consists of three steps: feature extraction feature selection and classification. However, the handcrafted features are imprecise in the feature selection stage, resulting in low classification accuracy. This paper proposes a deep neural architecture based on Convolution Neural Network and Long Short Term Memory combining the time and frequency domain features to recognize 16 types of Power Quality signals. The frequency-domain data were obtained from the Fast Fourier Transform which could efficiently extract the frequency-domain features. The performance in synthetic data and real 6kV power system data indicate that our proposed method generalizes well compared with other deep learning methods.

• Journal of the Korean Society of Safety
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• v.16 no.3
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• pp.135-142
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• 2001

This study discusses frequency analysis based on the frequency spectrum and process characterization in orthogonal cutting of Fiber-matrix composite materials. A sparsely distributed idealized composite material, namely a glass reinforced polyester(GFRP) was used as workpiece The present method employs a force sensor and the signals from the sensor are processed using the fast Fourier transform(FFT) technique. The experimental correlations between the different chip formation mechanisms and power spectrum me established. Effects of fiber orientation, cutting parameters and tool geometry on the cutting mechanisms me also discussed.

• Korean Journal of Applied Biomechanics
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• v.18 no.4
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• pp.49-57
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• 2008

The purpose of this study was to determine the effects of 12-week elastic resistance exercise for the elderly on the magnitude of frequency and variability of ground reaction force signals. To this aim, total 12 elderly women aged in their 70 were participated in this study and asked to do a 12-week elastic resistance exercise program. FFT(fast Fourier Transform) was used to analyze the frequency domain analysis of the ground reaction forces's signals and an accumulative PSD (power spectrum density) normalized by support phase of walking was calculated to reconstruct the certain signals. To estimate the gait stability between the before and after exercise, values of variability were determined in a coefficient of variance. The magnitude of frequency and variability analysis for media-lateral signal revealed significantly less after exercise (p<.05). In contrast, variability of this signal's frequency that have used to evaluate the local stability during walking exhibited significantly greater after exercise(p<.05). In summary, magnitude frequency and variability of media-lateral ground reaction force's signal were significantly changed after a 12-week elastic resistance exercise.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2007.11a
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• pp.895-902
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• 2007

Rotating machinery has two typical faults with clearance, one is partial rub and the other is looseness. Due to these faults, non-linear and non-stationary signals are occurred. Therefore, time-frequency analysis is necessary for exact fault diagnosis of rotating machinery. In this paper newly developed time-frequency analysis method, HHT(Hilbert-Huang Transform) is applied to fault diagnosis and compared with other method of FFT, SFFT and CWT. The results show that HHT can represent better resolution than any other method. Consequently, the faults of rotating machinery are diagnosed efficiently by using HHT.