• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2010.05a
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• pp.123-125
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• 2010

As the exterior noise emitted by a vehicle is getting more and more attention, simulated pass-by measurements become more important. This well established method provides information about the total noise emitted by the vehicle. For a vehicle manufacturer it is not only interesting to know about the total noise but also to know how this total exterior noise is composed of different contributions, such as for example the contribution of the engine, the intake or exhaust system. Transfer path analysis (TPA) provides a separation of these contributions for each of the pass-by microphones alongside the track. Presented is a method for fast and efficient determination of the contributions of multiple sources using operational transfer path analysis (OTPA). The calculation of the transfer characteristics between the reference measurement points on the vehicle and the corresponding response points of both microphone lines are carried out while operation of the vehicle. As result of the contribution analysis from operational transfer path analysis, the characteristic noise level as function of the covered distance is displayed for all individual sound sources, thus providing in depth information for sound quality engineering.

• Journal of Biomedical Engineering Research
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• v.26 no.4
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• pp.199-205
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• 2005

When recording single-unit responses from neural systems, a common problem is the accurate detection of spikes (action potentials) in the presence of competing unwanted (noise) signals. While some sources of noise can be readily dealt with through filtering or 'template subtraction' techniques, other sources present a more difficult problem. In particular, noise components introduced by power supplies, which contain harmonics of the power-line frequency, can be particularly troublesome in that they can mimic the shape of the desired spikes. Thus, standard 'template subtraction' techniques or notch-filtering approaches are not appropriate. In this study, we propose the use of a novel template-subtraction scheme that involves estimating the power-line noise waveform and using cross-correlation techniques to subtract them from the recordings. This technique requires two key steps: (1) cross-correlation analysis of each recorded waveform extracts a robust representation of the power-line noise waveform and (2) a second level of cross-correlation to successfully subtract that representation from each recorded waveform. This paper describes this algorithm and provides examples of its implementation using actual recorded waveforms that are contaminated with these noise signals. An improvement (reduction) in the noise level is reported, as are suggestions for future implementation of this strategy.

• JSTS:Journal of Semiconductor Technology and Science
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• v.9 no.4
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• pp.216-224
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• 2009

The endless scaling down of the semiconductor process made the impact of the power network noise on the performance of the state-of-the-art chip a serious design problem. This paper compares the performances of two popular circuit reduction approaches used to improve the efficiency of power network noise analysis: moment matching-based model order reduction (MOR) and node elimination-based MOR. As the benchmarks, we chose PRIMA and R2Power as the matching-based MOR and the node elimination-based MOR. Experimental results indicate that the accuracy, efficiency, and memory requirement of both methods very strongly depend on the structure of the given circuit, i.e., numbers of the nodes and sources, and the number of moments to preserve for PRIMA. PRIMA has higher accuracy in general, while the error of R2Power is also in the acceptable range. On the other hand, PRIMA has the higher efficiency than R2Power, only when the numbers of nodes and sources are small enough. Otherwise, R2Power clearly outperforms PRIMA in efficiency. In the memory requirement, the memory size of PRIMA increases very quickly as the numbers of nodes, sources, and preserved moments increase.

• 한국정보디스플레이학회:학술대회논문집
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• 2007.08b
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• pp.1155-1158
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• 2007

To reduce acoustic noise level of an AV projector, primary noise sources of AV projector were analyzed. Based on the analyzed result, methods to control each source are presented and tried. Structure-borne noise can be controlled by anti vibration design of mounting system, and air-borne noise by reducing flow resisitvity.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2003.05a
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• pp.536-541
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• 2003

When a rail vehicle transverses tight curves, it often emits an intense, high-pitched squeal. This squeal has always been noticed as one of the most disturbing noise sources of railway systems. At present, w cannot predicted squeal noise that is influenced by a large number of dependent parameters. In this study, we performed structural analysis to find out the frequency of the wheel and measured squeal noise at Seoul subway. We also tested reduction effectiveness of squeal noise through rail lubricator

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2003.05a
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• pp.353-356
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• 2003

Acoustic holography is adopted in identifying the noise sources of a vehicle's underbody. Wind noise from a vehicle's underbody accounts for a large portion of the overall noise level due to the complex flow structure. Current study presents the development process of acoustic holography in the vehicle underbody, and discusses the results obtained using the method. Difficulties associated with using acoustic holography as well as the implication of the results regarding future noise reduction possibilities are discussed.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2004.11a
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• pp.561-564
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• 2004

Acoustic holography is applied to automobile aeroacoustic noise. Automobile aeroacoustic noise has low coherence due to multiple independent sources and measurement noise. This paper discusses the reliability of acoustic holography on this low coherence condition. Main subjects are the number and position of reference microphones, which is used for a step-by-step scanning method, and measurement noise. A real automobile experiment verifies the results.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.23 no.12
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• pp.1117-1126
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• 2013

The standard impact sources, standardized to rate the sound insulation performance of floor structure, should simulate well the real floor impact sources, which is very important to grade the floor structure then to establish counter plan to improve the performance of floor. Recently the tire, the standard heavyweight impact source, has been discussed that the impact force is too big to represent the real impact force. And researches have been carried on the applicability as a substitute or a supplementary. In addition, tapping machine, the standard lightweight impact source, is also questionable if it is representative of real lightweight impact source. This study aims to examine the similarity of standard impact sources with living impact sources, comparing the physical characteristics such as impact force, frequency contents and sound level. The result showed that the physical characteristics of standard impact sounds were somewhat different with that of living impact sounds, and the standard sources couldn't be verified from this result. Later subjective evaluation should be followed to compare how the physical differences make relationship with the subjective differences.

• Journal of the Korean Society for Precision Engineering
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• v.22 no.8 s.173
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• pp.143-150
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• 2005

To verify applicability of multi-dimensional spectral analysis (MDSA) fur noise source identification two different approaches which are frequency response and coherent function have been investigated. The coherence function approach appears able to separate the correlated system when the noise sources were coherent. In this study, we identify contribution of structure-borne-noise of vehicle HVAC system using MDSA method. Firstly, to identify the applicability of MDSA method, 4-inputs of vehicle HVAC system were the signals measured by accelerometers attached on the selected noise sources which were composed of blower, evaporator, heater and duct. While 1-output which was driver's position sound was the SPL signals measured by a remote microphone, when the blower motor was operating. We identify efficiency of systems modeled with four Inputs/single output through ordinary coherence function (OCF) and partial coherence function (PCF). As a result of experiment, the blower accounted for $62-88\%$ of the overall level of sound energy density. Also, according to the analysis of acoustic signal and vibration signals measurement, an investigation of the noise source identification in the vehicle HVAC is presented. With the sound intensity method, the major sources of the vehicle HVAC radiation are verified. Also the method of improving the noise reduction is proposed by attaching damping patch access to blower motor and noise reduction is verified.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.22 no.10
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• pp.985-993
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• 2012

In this paper, a new method is proposed to estimate the sound pressure generated from gasoline direct injection (GDI) engine. There are many noise sources as much as components in GDI engine. Among these components, fuel pump, fuel injector, fuel rail, pressure pump and intake/exhaust manifolds are major components generated from top of the engine. In order to estimate the contribution of these components to engine noise, the total sound pressure at the front of the engine is estimated by using airborne source quantification (ASQ) method. Airborne source quantification method requires the acoustic source volume velocity of each component. The volume velocity has been calculated by using the inverse method. The inverse method requires many tests and has ill-condition problem. This paper suggested a method to obtain volume velocity directly based on the direct measurement of sound intensity and particle velocity. The method is validated by using two known monopole sources installed at the anechoic chamber. Finally the proposed method is applied to the identification and contribution of noise sources caused by the GDI components of the test engine.