• Title/Summary/Keyword: frequency component analysis

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Blind modal identification of output-only non-proportionally-damped structures by time-frequency complex independent component analysis

  • Nagarajaiah, Satish;Yang, Yongchao
    • Smart Structures and Systems
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    • v.15 no.1
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    • pp.81-97
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    • 2015
  • Recently, a new output-only modal identification method based on time-frequency independent component analysis (ICA) has been developed by the authors and shown to be useful for even highly-damped structures. In many cases, it is of interest to identify the complex modes of structures with non-proportional damping. This study extends the time-frequency ICA based method to a complex ICA formulation for output-only modal identification of non-proportionally-damped structures. The connection is established between complex ICA model and the complex-valued modal expansion with sparse time-frequency representation, thereby blindly separating the measured structural responses into the complex mode matrix and complex-valued modal responses. Numerical simulation on a non-proportionally-damped system, laboratory experiment on a highly-damped three-story frame, and a real-world highly-damped base-isolated structure identification example demonstrate the capability of the time-frequency complex ICA method for identification of structures with complex modes in a straightforward and efficient manner.

Term Frequency-Inverse Document Frequency (TF-IDF) Technique Using Principal Component Analysis (PCA) with Naive Bayes Classification

  • J.Uma;K.Prabha
    • International Journal of Computer Science & Network Security
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    • v.24 no.4
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    • pp.113-118
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    • 2024
  • Pursuance Sentiment Analysis on Twitter is difficult then performance it's used for great review. The present be for the reason to the tweet is extremely small with mostly contain slang, emoticon, and hash tag with other tweet words. A feature extraction stands every technique concerning structure and aspect point beginning particular tweets. The subdivision in a aspect vector is an integer that has a commitment on ascribing a supposition class to a tweet. The cycle of feature extraction is to eradicate the exact quality to get better the accurateness of the classifications models. In this manuscript we proposed Term Frequency-Inverse Document Frequency (TF-IDF) method is to secure Principal Component Analysis (PCA) with Naïve Bayes Classifiers. As the classifications process, the work proposed can produce different aspects from wildly valued feature commencing a Twitter dataset.

Optimization of a vehicle component under dynamic fatigue (동적 피로를 고려한 자동차 부품의 최적설계)

  • 이정준;주병현;이병채
    • Proceedings of the Korean Society of Precision Engineering Conference
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    • 2004.10a
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    • pp.898-901
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    • 2004
  • Generally, in case the natural frequency of vehicle components is larger than the reversing frequency of load history, we can obtain the analysis results with small errors. But in case of having the low natural frequency, we must avoidably carry out the dynamic analysis, and it requires much time and storage. Specially executing the fatigue analysis for vehicle components requires more time. To this end, it is not easy that we accomplish the optimization considering fatigue for the vehicle component based on the dynamic analysis. In this research we introduce an efficient method which performs the fatigue analysis based on the dynamic analysis. Finally as making the response surface we optimize the vehicle component under dynamic fatigue.

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The Analysis of a High Frequency Series Resonant DC-DC Converter (고주파 직렬공진형 DC-DC Converter의 특성 해석)

  • 이윤종;김철진
    • The Transactions of the Korean Institute of Electrical Engineers
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    • v.39 no.9
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    • pp.934-943
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    • 1990
  • There are no turn-on losses in the series Resonant Converter which operates above the resonance frequency, and the commutation stress on the switched component is low. For a given Series Resonant Converter with specified load resistance, the output voltage is a function of the operation frequency. This paper describes the static and dynamic characteristic analysis of the Series Resonant DC to DC Converter, which is operating above the resonant frequency, with frequency control. For the analysis method, state plane technique is adopted, and the circuit operation is defined from normalized switching frequency, Fsn. Under this condition, circuit performance is analyzed ideally. The validity of the proposed analysis is verified by comparing with experimental results, the stability of the converter is confirmed against small variations around the operating point by conventional frequency domain analysis, and the stress quantity added to switch component is shown.

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Development of the Extracting Technique of the Character Parameter for the Vibration Monitoring System in High Voltage Motor (고압전동기용 진동 감시 시스템을 위한 특징 파라미터 추출기법 개발)

  • Lee, Dal-Ho;Park, Jung-Cheul
    • The Journal of Korea Institute of Information, Electronics, and Communication Technology
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    • v.12 no.4
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    • pp.349-358
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    • 2019
  • This paper aimed at collecting sensor signals to extract characteristic parameter of the rotor. A vibration test rig has been developed to perform model tests. Signal characteristics were analyzed when driving normally. Envelope FFT Analysis is used to extract vibration components caused by periodic impacts from other vibration factors. Signal analysis was performed when load changes were given to speed sensors and vibration test rigs that show low frequency characteristics of the rotor and signal analysis according to rotational speed. The acceleration signal measured in the bearing housing has a small amplitude and produces only the rotational frequency component and harmonic component of the motor. As the number of rotations increases, the amplitude of acceleration can be seen. As the rotational speed increases, it can be seen that there is a difference in the shape of the original data and compared with the acceleration FFT graph, it can be seen that the noise is strong at low frequencies and the corresponding rotational frequency components are clearly represented. It can be seen that changing the load does not increase the main rotational frequency component.

Improvement of Vibration Performance for Wafer Transfer Robot using Frequency Analysis of Motion Profile (모션프로파일의 주파수분석을 통한 웨이퍼 이송로봇의 진동성능 향상)

  • Shin, Dongwon;Yun, Jang Kyu
    • Journal of the Korean Society for Precision Engineering
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    • v.31 no.8
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    • pp.697-703
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    • 2014
  • This paper is study of solving vibration problem occurred in moving hand of wafer transfer robot in semiconductor manufacturing line. Long settling time for decreasing vibration makes low production rate, and moreover the excessive vibration of hand sometimes breaks the wafer in a cassette. The ways of reducing the moving speed and changing the type of motion profile did not help for lessening vibration. Therefore, we analyzed the mechanical property of the hand such as natural frequency, and frequency component of the motion profile currently used in the manufacturing line. In several conditions of motion profile, we found the best condition of which the frequency component in near of natural frequency of the hand is minimal and this induced small vibration in moving hand. The results were verified theoretically and experimentally using frequency analysis.

Suppressing Artefacts in the ECG by Independent Component Analysis (독립성분 분석기법에 의한 심전도 신호의 왜곡 보정)

  • Kim, Jeong-Hwan;Kim, Kyeong-Seop;Kim, Hyun-Tae;Lee, Jeong-Whan
    • The Transactions of The Korean Institute of Electrical Engineers
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    • v.62 no.6
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    • pp.825-832
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    • 2013
  • In this study, Independent Component Analysis (ICA) algorithms are suggested to extract the original ECG part from the mixed signal contaminated with the unwanted frequency components and especially 60Hz power line disturbances. With this aim, we implement a novel method to suppress the baseline-wandering disturbances and power line artefacts contained in patch-electrodes sensory ECG data by separating the unmixed signal with finding the optimal weight W based on Kurtosis value. With applying brutal force and gradient ascent searching algorithm to find W, we can conclude that the unwanted frequency components especially in the ambulatory ECG data can be eliminated by Independent Component Analysis.

Separation of passive sonar target signals using frequency domain independent component analysis (주파수영역 독립성분분석을 이용한 수동소나 표적신호 분리)

  • Lee, Hojae;Seo, Iksu;Bae, Keunsung
    • The Journal of the Acoustical Society of Korea
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    • v.35 no.2
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    • pp.110-117
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    • 2016
  • Passive sonar systems detect and classify the target by analyzing the radiated noises from vessels. If multiple noise sources exist within the sonar detection range, it gets difficult to classify each noise source because mixture of noise sources are observed. To overcome this problem, a beamforming technique is used to separate noise sources spatially though it has various limitations. In this paper, we propose a new method that uses a FDICA (Frequency Domain Independent Component Analysis) to separate noise sources from the mixture. For experiments, each noise source signal was synthesized by considering the features such as machinery tonal components and propeller tonal components. And the results of before and after separation were compared by using LOFAR (Low Frequency Analysis and Recording), DEMON (Detection Envelope Modulation On Noise) analysis.

A Study on the Application of Wavelet Transform to Faults Current Discrimination (Wavelet 변환을 이용한 고장전류의 판별에 관한 연구)

  • 조현우;정종원;윤기영;김태우;이준탁
    • Proceedings of the Korean Society of Marine Engineers Conference
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    • 2002.05a
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    • pp.213-217
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    • 2002
  • Recently the subject of "wavelet analysis" has be drawn by both mathematical and engineering application fields such as Signal Processing, Compression/Decomposition, Wavelet-Neural Network, Statistics and etc. Even though its similar to courier analysis, wavelet is a versatile tool with much mathematical content and great potential for applications. Especially, wavelet transform uses localizable various mother wavelet functions in time-frequency domain. Therefore, wavelet transform has good time-analysis ability for high frequency component, and has good frequency-analysis ability for low frequency component. Using the discriminative ability is more easy method than other conventional techniques. In this paper, Morlet wavelet transform was applied to discriminate the kind of line fault by acquired data from real power transformation network. The experimental result presented that Morlet wavelet transform is easier, and more useful method than the FFW (Fast courier Transform).ransform).

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Optimization of ground response analysis using wavelet-based transfer function technique

  • Moghaddam, Amir Bazrafshan;Bagheripour, Mohammad H.
    • Geomechanics and Engineering
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    • v.7 no.2
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    • pp.149-164
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    • 2014
  • One of the most advanced classes of techniques for ground response analysis is based on the use of Transfer Functions. They represent the ratio of Fourier spectrum of amplitude motion at the free surface to the corresponding spectrum of the bedrock motion and they are applied in frequency domain usually by FFT method. However, Fourier spectrum only shows the dominant frequency in each time step and is unable to represent all frequency contents in every time step and this drawback leads to inaccurate results. In this research, this process is optimized by decomposing the input motion into different frequency sub-bands using Wavelet Multi-level Decomposition. Each component is then processed with transfer Function relating to the corresponding component frequency. Taking inverse FFT from all components, the ground motion can be recovered by summing up the results. The nonlinear behavior is approximated using an iterative procedure with nonlinear soil properties. The results of this procedure show better accuracy with respect to field observations than does the Conventional method. The proposed method can also be applied to other engineering disciplines with similar procedure.