• Proceedings of the Acoustical Society of Korea Conference
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• 1998.06d
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• pp.80-83
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• 1998

In this paper, we propose a new filtered-x least mean fouth (LMF) algorithm where the error raised to the power of four is minimized and analyze its convergence behavior or a multiple sinusoidal acoustic noise and Gaussian measurement noise. Application of the filtered-x LMF adaptive filter to active noise cancellation (ANC) requires estimating of the transfer characteristic of the acoustic path between the ouput and error signal of the adaptive canceller. The results of the convergence analysis of the filtered-x LMF algorithm indicates that the effects of the parameter estimation inaccuracy on the convergence behavior of the algorithm are characterized by two distinct component . Phase estimation error and estimated again. In particular , the convergence is shown to be strongly affected by the accuracy of the phase response estimate. Also, we newly show that convergence behavior can differ depending on the relative sizes of the Gaussian measurement noise and convergence constant.

• Proceedings of the KIPE Conference
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• 2007.07a
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• pp.369-371
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• 2007

Due to the measurement noise or system noise, the performance of photovoltaic power generation system can be degraded. If this noise is contained in the solar array voltage measurement signal, the correct operation of the maximum power point tracker can not be guaranteed. The application of the extended Kalman filter to the photovoltaic system can obtain enhanced states estimation result. The Kalman filter provides a recursive solution to optimally estimate from random noise signals. Additionally, as a consequence of Kalman filter, the unmeasurable state such as inductor current can be estimated without current sensor. The methods for system modeling and extended Kalman filter design are presented and the experimental results verify the validity of the proposed system.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 1996.10a
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• pp.91-97
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• 1996

We have all heard sounds that did not sound "right" while riding in an automobile. Objectionable sounds are difficult to find and understand because the sound field is complex and dynamic in the near field of an automobile. Many different noise sources and transmission paths must be understood before an engineering change can be recommended. This paper reviews the fundamental characterization of sound and chscusses the Sound Intensity measurement technique. Sound intensity measurements locate sources and sinks of acoustic energy. Used with narrowband analysis equipment, acoustic noise sources can be identified. Sound intensity measurements are made -in-situ and do not require specmi anechoic facilities. The measurement results in a vector representation of the near field sound field and can discriminate between multiple sound sources.d sources.

• The KIPS Transactions:PartC
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• v.12C no.4 s.100
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• pp.519-524
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• 2005

Due to various types of errors added to dynamic weight measurement data, proper methods to reduce measurement errors are required to produce reliable weights. It is very difficult to reduce the measurement error due to excessive oscillation of the system. To cope with parasitic types of errors in real systems, information provided by the photo sensors are utilized and combined in such a way to reduce the measurement errors of load cells. In addition to four channels of load cells from a model trailer, photo sensors are used to obtain the information to compensate the error induced from vertical movement of the vehicle due to the variation of ground level. A model trailer system is run to verify the effectiveness of the proposed method to reduce noise of dynamic weight measurements.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.44 no.4
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• pp.308-315
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• 2016

A new technique for Attitude & Heading Reference System (AHRS) by using sequential measurement noise covariance (SMNC) is addressed in a vibration environments in this paper. In particular, a low-cost inertial measurement unit in general diverges in the acceleration phase or vibrating environments due to inherent properties of gravity and acceleration. In this paper, by considering current and prior measurements to estimate actual attitudes and headings in a local frame, the proposed technique overcomes these problems efficiently. Finally, the performance of the suggested approach is verified by numerical simulations.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2012.04a
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• pp.507-508
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• 2012

• International Journal of Highway Engineering
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• v.15 no.2
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• pp.11-18
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• 2013

PURPOSES : This study presents the noise level and frequency characteristics investigated in the national highways with the consideration of various measuring conditions and/or methods. METHODS : The noise levels on the asphalt concrete pavement(ACP) and the jointed plain concrete pavement(JPCP) of the national highway were measured and analysed with respect to three variables, i.e., pavement type, surface condition, and measurement distance. The PASS-By method is utilized for the noise measurement and then using CPB spectrum analysis method with 1/3 octave bandwidth, the noise levels and frequency characteristics were calculated for two-second periods before and after the peak noise. RESULTS : Depending on the pavement type, the noise level was changed as the average noise levels are 73.3dB(A) and 78.3dB(A) for ACP and JPCP, respectively. With respect to the effect of surface condition, the average noise levels for crack H(high), M(medium), and L (low) sections are 77.4dB(A), 77.4dB(A), and 78.1dB(A), respectively. Regarding the measurement distance, 1.2meter difference in measuring location reduces 1.6dB(A) of noise level; the average noise levels at 5.3m and 7.5m from the centerline of outer lane are 72.8dB(A) and 71.2dB(A), respectively. It should be noted that the noise levels are slightly different as a function of vehicle speed and type. However, the overall trends for each case was similar. It was found that the domain frequency bands for ACP and JPCP were 400Hz~2000Hz and 500Hz~2000Hz, respectively. CONCLUSIONS : Based on the analysis with the measured noise date from national highway, it was concluded that the noise level and frequency band vary depending on the various conditions. It was also found that some variables significantly affect the noise level while others do not. With further systematic investigation, the comprehensive noise characteristics on the national highway can be achieved. Using such database, it is possible to develop the fundamental noise reduction technology.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2010.10a
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• pp.302-307
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• 2010

Development of light-weight high speed train (HST) based on distributed motor control with the top speed of 350 km/hr has engendered a need for abatement of the interior noise of the train cabin. The development of noise abatement measures is crucial at the design stage of the train car since the noise transmission characteristics of the car structure directly influences the cabin interior noise. Since the transmission loss measurement using the entire car structure is often not feasible, especially at the initial stages of the train development, investigation of transmission characteristics using small-scale reverberation chamber can furnish useful alternative source of predicting the noise level. In the present study, white noise is generated at source and transmission loss estimated by performing measurement of a specimen in a scaled reverberation chamber. Comparison of measured values with the previously derived numerical values show good agreement in the overall trend but appreciable quantitative differences still remain.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.60 no.12
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• pp.2346-2351
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• 2011

This paper presents the intelligent external noise analysis method for nonlinear maneuvering target. After recognizing maneuvering pattern of the target by the proposed method, we track the state of the target. The external noise can be divided into mere noise and acceleration using only the measurement. divided noise passes through the filtering step and acceleration is punched into dynamic model to compensate expected states. The acceleration is the most deterministic factor to the maneuvering. By dividing, approximating, and compensating the acceleration, we can reduce the tracking error effectively. We use the fuzzy c-means (FCM) clustering as the method to divide external noise. FCM can separate the acceleration from the noise without criteria. It makes the criteria with the data made by measurement at every sampling time. So it can show the adaptive tracking result. The proposed method proceeds the tracking target simultaneously with the learning process. Thus it can apply to the online system. The proposed method shows the remarkable tracking result on the linear and nonlinear maneuvering. Finally, some examples are provided to show the feasibility of the proposed algorithm.

• Journal of the Society of Naval Architects of Korea
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• v.37 no.1
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• pp.111-117
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• 2000

In the KRISO cavitation tunnel, the acoustic characteristics for the measurement of underwater noise are investigated, The background noise is measured and analyzed up to 100kHz at various test conditions. The noise level of the KRISO cavitation tunnel is compared with those of the other cavitation tunnels which have been designed for the noise study[HYKAT(Germany), GTH(France), etc.]. In order to investigate the background noise source. the coherence between structural vibration and noise level is analyzed using the B&K 3550 FFT analyzer. The experimental results show the possibility of the noise study and suggest the improvement plan.