• Title/Summary/Keyword: features of time and frequency domain

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Study of PD Location in Generators by PD Pulses Propagation

  • Cheng, Yang-Chun;Li, Cheng-Rong;Wang, Wei
    • Transactions on Electrical and Electronic Materials
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    • v.7 no.5
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    • pp.252-256
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    • 2006
  • When a partial discharge takes place at the stator of a generator, the electrical pulse will propagate along the stator bars and the capacitor chains formed by the end part of the stator winds. On the first path, the pulse propagates as a travel wave at slow speed. On the second path, the pulse propagates at quick speed. Based on the data of the experiments on a real 50 MW steam generator, the author has found the pulses can propagate by magnetic field of the stator winding. It was studied that how to locating the partial discharge by signals coming from the different paths, including the features of signals on the two paths at time domain and frequency domain, the measurement frequency rang of the signals, the blind area, the advantage and disadvantage of this method.

Neuro-Fuzzy Network-based Depression Diagnosis Algorithm Using Optimal Features of HRV (뉴로-퍼지 신경망 기반 최적의 HRV특징을 이용한 우울증진단 알고리즘)

  • Zhang, Zhen-Xing;Tian, Xue-Wei;Lim, Joon-S.
    • The Journal of the Korea Contents Association
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    • v.12 no.2
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    • pp.1-9
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    • 2012
  • This paper presents an algorithm for depression diagnosis using the Neural Network with Weighted Fuzzy Membership functions (NEWFM) and heart rate variability (HRV). In the algorithm, 22 different features were initially extracted from the HRV signal by frequency domain, time domain, wavelet transformed, and Poincar$\acute{e}$ transformed feature extraction methods; of these 6 optimal features were selected by significance evaluation using Non-overlap Area Distribution Measurement (NADM) based on NEWFM. The proposed algorithm uses these 6 optimal features to diagnose depression with an accuracy of 95.83%.

Defect classification of refrigerant compressor using variance estimation of the transfer function between pressure pulsation and shell acceleration

  • Kim, Yeon-Woo;Jeong, Weui-Bong
    • Smart Structures and Systems
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    • v.25 no.2
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    • pp.255-264
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    • 2020
  • This paper deals with a defect classification technique that considers the structural characteristics of a refrigerant compressor. First, the pressure pulsation of the refrigerant flowing in the suction pipe of a normal compressor was measured at the same time as the acceleration of the shell surface, and then the transfer function between the two signals was estimated. Next, the frequency-weighted acceleration signals of the defect classification target compressors were generated using the estimated transfer function. The estimation of the variance of the transfer function is presented to formulate the frequency-weighted acceleration signals. The estimated frequency-weighted accelerations were applied to defect classification using frequency-domain features. Experiments were performed using commercial compressors to verify the technique. The results confirmed that it is possible to perform an effective defect classification of the refrigerant compressor by the shell surface acceleration of the compressor. The proposed method could make it possible to improve the total inspection performance for compressors in a mass-production line.

Condition Monitoring of Tool wear using Sound Pressure and Fuzzy Pattern Recognition in Turning Processes (선삭공정에서 음압과 퍼지 패턴 인식을 이용한 공구 마멸 감시)

  • 김지훈
    • Proceedings of the Korean Society of Machine Tool Engineers Conference
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    • 1998.10a
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    • pp.164-169
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    • 1998
  • This paper deals with condition monitoring for tool wear during tuning operation. To develop economic sensing and identification methods for turning processes, sound pressure measurement and digital signal processing technique are proposed. To identify noise sources of tool wear and reject background noise, noise rejection methodology is proposed. features to represent condition of tool wear are obtained through analysis using adaptive filter and FFT in time and frequency domain. By using fuzzy pattern recognition, we extract features, which are sensitive to condition of tool wear, from several features and make a decision on tool wear. The validity of the proposed system is condirmed through the large number of cutting tests in two cutting conditions.

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A Design of a Scream Detecting Engine for Surveillance Systems (보안 시스템을 위한 비명 검출 엔진 설계)

  • Seo, Ji-Hun;Lee, Hye-In;Lee, Seok-Pil
    • The Transactions of The Korean Institute of Electrical Engineers
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    • v.63 no.11
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    • pp.1559-1563
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    • 2014
  • Recently, the prevention of crime using CCTV draws special in accordance with the higher crime incidence rate. Therefore security systems like a CCTV with audio capability are developing for giving an instant alarm. This paper proposes a scream detecting engine from various ambient noises in real environment for surveillance systems. The proposed engine detects scream signals among the various ambient noises using the features extracted in time/frequency domain. The experimental result shows the performance of our engine is very promising in comparison with the traditional engines using the model based features like LPC, LPCC and MFCC. The proposed method has a low computational complexity by using FFT and cross correlation coefficients instead of extracting complex features like LPC, LPCC and MFCC. Therefore the proposed engine can be efficient for audio-based surveillance systems with low SNRs in real field.

Prediction of Defibrillation Success of Ventricular Fibrillation ECG Signals using Time-Frequency Analysis (시-주파수 분석을 이용한 심실세동시 심전도 분석을 통한 제세동 예측에 관한 연구)

  • Sung, Hong-Mo;Shin, Jae-Woo;Lee, Hyun-Sook;Hwang, Sung-Ho;Yoon, Young-Ro
    • The Transactions of the Korean Institute of Electrical Engineers D
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    • v.55 no.4
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    • pp.181-188
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    • 2006
  • The purpose of this study is to predict the defibrillation success of a ventricular Fibrillation ECG signal using time-frequency analysis. During CPR, coronary perfusion pressure and electrocardiogram were measured. Parameters extracted from time-frequency domain were served as predictor of resuscitation success. Time frequency distribution(TFD) of ECG signals was estimated from the smoothed pseudo Wigner-Ville distribution(SPWVD). Median frequency, peak frequency, 1/f slope, frequency band ratios$(2{\sim}4Hz,\;4{\sim}6Hz,\;6{\sim}8Hz,\;8{\sim}10Hz,\;10{\sim}12Hz,\;12{\sim}15Hz)$ were extracted from each TFD as function of time. Paired t-test was used to determine the differences in ROSC and non-ROSC groups. In the statistical results, we selected four significant parameters - median frequency, 1/f slope, $2{\sim}4Hz$ band ratio, $8{\sim}10Hz$ band ratio. We made an attempt to predict defibrillation success by combining features extracted from time frequency distribution. Independent t-test was used to determine the differences ROSC and non-ROSC groups. Consequently, we selected four significant parameters-median frequency, 1/f slope, $2{\sim}4Hz$ band ratio, $8{\sim}10Hz$ band ratio. The relationship between coronary perfusion pressure and ECG parameters was analyzed with linear regression analysis. R-square value was 55%. 1/f slope and $8{\sim}10Hz$ band ratio had the significant relationship with coronary perfusion pressure.

Machining condition monitoring for micro-grooving on mold steel using fuzzy clustering method (퍼지 클러스터링을 이용한 금형강에 미세 그루브 가공시 가공상태 모니터링)

  • 이은상;곽철훈;김남훈
    • Journal of the Korean Society for Precision Engineering
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    • v.20 no.11
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    • pp.47-54
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    • 2003
  • Research during the past several years has established the effectiveness of acoustic emission (AE)-based sensing methodologies for machine condition analysis and process. AE has been proposed and evaluated for a variety of sensing tasks as well as for use as a technique for quantitative studies of manufacturing process. STD11 has been known as difficult-to-cut materials. The micro-grooving machine was developed for this study and the experiments were performed using CBN blade for machining STD11. Evaluating the machining conditions, frequency spectrum analysis of acoustic emission (AE) signals according to each conditions were applied. Fuzzy clustering method for associating the preprocessor outputs with the appropriate decisions was followed by frequency spectrum analysis. FFT is used to decompose AE signal into different frequency bands in time domain, the root mean square (RMS) values extracted from the decomposed signal of each frequency band were used as features.

Waveform Analysis Using Wavelet Transform (웨이블렛 변환에 의한 파형 해석)

  • Kim, Hee Joon
    • Economic and Environmental Geology
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    • v.28 no.5
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    • pp.527-533
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    • 1995
  • A disadvantage of Fourier analysis is that frequency information can only be extracted for the complete duration of a signal f(t). Since the Fourier transform integral extends over all time, from $-{\infty}$ to $+{\infty}$), the information it provides arises from an average over the whole length of the signal. If there is a local oscillation representing a particular feature, this will contribute to the calculated Fourier transform $F({\omega})$, but its location on the time axis will be lost There is no way of knowing whether the value of $F({\omega})$ at a particular ${\omega}$ derives from frequencies present throughout the life of f(t) or during just one or a few selected periods. This disadvantage is overcome in wavelet analysis which provides an alternative way of breaking a signal down into its constituent parts. The main advantage of the wavelet transform over the conventional Fourier transform is that it can not only provide the combined temporal and spectral features of the signal, but can also localize the target information in the time-frequency domain simultaneously. The wavelet transform distinguishes itself from Short Time Fourier Transform for time-frequency analysis in that it has a zoom-in and zoom-out capability.

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Incorporation preference for rubber-steel bearing isolation in retrofitting existing multi storied building

  • Islam, A.B.M. Saiful;Jumaat, Mohd Zamin;Hussain, Raja Rizwan;Hosen, Md. Akter;Huda, Md. Nazmul
    • Computers and Concrete
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    • v.16 no.4
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    • pp.503-529
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    • 2015
  • Traditionally, multi-story buildings are designed to provide stiffer structural support to withstand lateral earthquake loading. Introducing flexible elements at the base of a structure and providing sufficient damping is an alternative way to mitigate seismic hazards. These features can be achieved with a device known as an isolator. This paper covers the design of base isolators for multi-story buildings in medium-risk seismicity regions and evaluates the structural responses of such isolators. The well-known tower building for police personnel built in Dhaka, Bangladesh by the Public Works Department (PWD) has been used as a case study to justify the viability of incorporating base isolators. The objective of this research was to establish a simplified model of the building that can be effectively used for dynamic analysis, to evaluate the structural status, and to suggest an alternative option to handle the lateral seismic load. A finite element model was incorporated to understand the structural responses. Rubber-steel bearing (RSB) isolators such as Lead rubber bearing (LRB) and high damping rubber bearing (HDRB) were used in the model to insert an isolator link element in the structural base. The nonlinearities of rubber-steel bearings were considered in detail. Linear static, linear dynamic, and nonlinear dynamic analyses were performed for both fixed-based (FB) and base isolated (BI) buildings considering the earthquake accelerograms, histories, and response spectra of the geological sites. Both the time-domain and frequency-domain approaches were used for dynamic solutions. The results indicated that for existing multi-story buildings, RSB diminishes the muscular amount of structural response compared to conventional non-isolated structures. The device also allows for higher horizontal displacement and greater structural flexibility. The suggested isolation technique is able to mitigate the structural hazard under even strong earthquake vulnerability.

Electric Model of Li-Ion Polymer Battery for Motor Driving Circuit in Hybrid Electric Vehicle

  • Lee, June-Sang;Lee, Jae-Joong;Kim, Mi-Ro;Park, In-Jun;Kim, Jung-Gu;Lee, Ki-Sik;Nah, Wan-Soo
    • Journal of Electrical Engineering and Technology
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    • v.7 no.6
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    • pp.932-939
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    • 2012
  • This paper presents an equivalent circuit model of a LIPB (Li-Ion Polymer battery) for Hybrid Electric Vehicles (HEVs). The proposed equivalent circuit can be used to predict the charging/discharging characteristics in time domain as well as the impedance characteristic analysis in frequency domain. Based on these features, a one-cell model is established as a function of Depth of Discharge (DoD), and a 48-cell model for a battery pack was also established. It was confirmed by experiment that the proposed model predict the discharging and impedance (AC) characteristics quite accurately at different constant current levels. To check the usefulness of the proposed circuit, the model was used to simulate a motor driving circuit with an Insulated Gate Bipolar Transistor (IGBT) inverter and Brushless DC (BLDC) motor, and it is confirmed that the model can calculate the battery voltage fluctuation in time domain at different DoDs.