• Title/Summary/Keyword: Random noise

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Induction Motor Drives with Low Switching Acoustic Noise Based on the Two-Phase Modulated Random Lead-Lag PWM Scheme (2상 변조된 랜덤 Lead-Lag PWM기반의 저 스위칭 소음 유도모터 구동 시스템)

  • 위석오;정영국;임영철;양승학
    • The Transactions of the Korean Institute of Power Electronics
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    • v.8 no.2
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    • pp.151-164
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    • 2003
  • In this paper, induction motor drives with low switching acoustic noise based on the 2 phase modulated RLL(Random Lead-Lag) PWM is proposed and implemented. The proposed switching method is much bettor than 3 phase modulated RLL-PWM from the standpoint of the broadening effect of the acoustic noise spectrum. Along with the randomization of PWM Pulses, SVM(Space Vector Modulation) is executed in the TMS320C31 DSP(Digital Signal Processor). To verify the validity of the proposed RPWM(Random PWM), the experimental study was tried. The experimental results show that the performance of the proposed method and the 3 phase center-aligned SVM / conventional RLL-PWM are nearly the same from the viewpoint of the constant v/f centrel. But, in case of the proposed 2 phase modulated RLL-PWM, the spectrum characteristics of the voltage and the switching acoustic noise are shown to have better broadening effect than 3 phase modulated one.

Particle Velocity and Intensity Estimation Error in Spatial Discrete Domain (입자 속도 및 인텐시티를 공간 영역에서 이산화할 때 발생하는 오차)

  • 김양한;최영철
    • Transactions of the Korean Society for Noise and Vibration Engineering
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    • v.14 no.4
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    • pp.352-357
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    • 2004
  • This paper studies the errors that associated with particle velocity and intensity in a space. We theoretically derived their bias error and random error. The analysis shows that the more samples do not always guarantee the better results. The random error of the velocity and intensity are increased when we have many samples. The characteristics of the amplification of the random error are analyzed in terms of the sample spacing. The amplification was found to be related to the spatial differential of random noise. The numerical simulations are performed to verify theoretical results.

Quantification of Particle Velocity and Intensity Estimation Error in a Discrete Domain (이산 영역에서 공간상의 입자속도, 인텐시티 예측 오차의 정량화)

  • 최영철;김양한
    • Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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    • 2003.05a
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    • pp.403-407
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    • 2003
  • This paper studies the error of pressure, particle velocity, and intensity which are distributed in a space. Errors may be amplified when other sound field variables are predicted. We theoretically derive their bias error and random error. The analysis shows that many samples do not always guarantee good results. Random error of the velocity and intensity are increased when many samples are used. The characteristics of the amplification of the random error are analyzed in terms of the sample spacing. The amplification was found to be related to the spatial differential of random noise. The numerical simulations are performed to verify theoretical results.

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Acoustic Noise Spectra of the Pseudo-Random Carrier Modulation Technique According to the Different PRBS Bits (PRBS비트에 따른 준 랜덤 캐리어 변조기법의 소음 스펙트럼)

  • Kim, J.N.;Jung, Y.G.;Lim, Y.C.
    • Proceedings of the KIPE Conference
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    • 2005.07a
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    • pp.758-761
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    • 2005
  • This paper describes the acoustic noise spectra of the pseudo-random carrier modulation technique according to the different PRBS(Pseudo Random Binary Sequence) bits. To confirm the validity of the proposed method, a 130v three-phase 5-level inverter motor drives was implemented. The harmonics spectra broadening effect of pseudo random carrier and the acoustic noise radiated from the inverter drives were discussed and verified according to the different bits of shift resister operating as PRBS.

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Classification of Transport Vehicle Noise Events in Magnetotelluric Time Series Data in an Urban area Using Random Forest Techniques (Random Forest 기법을 이용한 도심지 MT 시계열 자료의 차량 잡음 분류)

  • Kwon, Hyoung-Seok;Ryu, Kyeongho;Sim, Ickhyeon;Lee, Choon-Ki;Oh, Seokhoon
    • Geophysics and Geophysical Exploration
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    • v.23 no.4
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    • pp.230-242
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    • 2020
  • We performed a magnetotelluric (MT) survey to delineate the geological structures below the depth of 20 km in the Gyeongju area where an earthquake with a magnitude of 5.8 occurred in September 2016. The measured MT data were severely distorted by electrical noise caused by subways, power lines, factories, houses, and farmlands, and by vehicle noise from passing trains and large trucks. Using machine-learning methods, we classified the MT time series data obtained near the railway and highway into two groups according to the inclusion of traffic noise. We applied three schemes, stochastic gradient descent, support vector machine, and random forest, to the time series data for the highspeed train noise. We formulated three datasets, Hx, Hy, and Hx & Hy, for the time series data of the large truck noise and applied the random forest method to each dataset. To evaluate the effect of removing the traffic noise, we compared the time series data, amplitude spectra, and apparent resistivity curves before and after removing the traffic noise from the time series data. We also examined the frequency range affected by traffic noise and whether artifact noise occurred during the traffic noise removal process as a result of the residual difference.

Analysis on random vibration of a non-linear system in flying vehicle due to stochastic disturbances (불규칙 교란을 받는 비행체에 장착된 비선형 시스템의 난진동 해석)

  • 구제선
    • Transactions of the Korean Society of Mechanical Engineers
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    • v.14 no.6
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    • pp.1426-1435
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    • 1990
  • Dynamic behaviour of point tracking system mounted on flying vehicle shaking in a random manner is investigated and the system dynamic is represented by nonlinear stochastic equations. 2-D.O.F. nonlinear stochastic equations are successfully transformed to linear stochastic equations via equivalent linearization procedure in stochastic sense. Newly developed hybrid technique is used to obtain response statistics of the system under non-white random excitation, which is proved to be remarkably accurate one by performing stochastic simulation.

Analysis of Fatigue Damage of the parts around the vehicle engine with Respect to Road surface conditions (도로 노면 조건을 고려한 차량 엔진 주변 부품의 피로손상도 분석)

  • Shin, Sung-Young;Kim, Chan-Jung;Lee, Bong-Hyeon
    • Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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    • 2014.10a
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    • pp.581-586
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    • 2014
  • In general vibration test considers both harmonic vibration and random vibration, When developing the vehicle component. But the effect of harmonic vibration is larger in the parts around the vehicle engine, sole testing the harmonic vibration is considered. In this study, the fatigue damage of the linear system fixed around the engine is analyzed when the effect of random vibration is higher, harsher than the normal road surface condition. In condition the vehicle speed and the engine RPM are similar, the higher the harshness of the road surface condition is, the larger the fatigue damage level is. Therefore both random vibration and harmonic vibration must be considered in vibration test of components around the engine. Proposing the sine on random(SOR) vibration test that can exam considering both of vibrations, harmonic and random.

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A Note On L$_1$ Strongly Consistent Wavelet Density Estimator for the Deconvolution Problems

  • Lee, Sungho
    • Communications for Statistical Applications and Methods
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    • v.8 no.3
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    • pp.859-866
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    • 2001
  • The problem of wavelet density estimation is studied when the sample observations are contaminated with random noise. In this paper a linear wavelet estimator based on Meyer-type wavelets is shown to be L$_1$ strongly consistent for f(x) with bounded support when Fourier transform of random noise has polynomial descent or exponential descent.

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A Note on Central Limit Theorem for Deconvolution Wavelet Density Estimators

  • Lee, Sungho
    • Communications for Statistical Applications and Methods
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    • v.9 no.1
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    • pp.241-248
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    • 2002
  • The problem of wavelet density estimation based on Shannon's wavelets is studied when the sample observations are contaminated with random noise. In this paper we will discuss the asymptotic normality for deconvolving wavelet density estimator of the unknown density f(x) when courier transform of random noise has polynomial descent.