• Journal of KSNVE
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• v.5 no.2
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• pp.197-206
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• 1995

Microphone array is designed to measure the equivalent source height of vehicle noise. The equivalent source position is defined for an arbirary distribution of acoustic sources above a perfectly reflecting plane and a microphone array for its measurement is developed. The normalized errors of the measured equivalent source heights are defined including the effects of background noise, the geometric near field, and source size. Normalized errors of the measured source heights obtained by a nemerical simulation for each parameter lead to optimization of the microphone spacing and to the design of an array which gives the equivalent source height as a function of frequency. The performance of the designed array is verified using the stationary loudspeaker experiments.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2004.11a
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• pp.911-915
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• 2004

Recently, several experimental techniques for identifying the noise sources distributed over a moving vehicle are being developed and used in order to design a low noise vehicle. The beamforming method, which uses phase information between several microphones to localize the source position, is proved to be one of the promising techniques applicable even under complicated test environments. In this study a beamforming algorithm is developed and applied to measure the dominant noise sources on a passenger car moving at constant speed. Unlike the acoustic signals from a stationary noise source, the sound generated from a moving source is distorted due to the Doppler effects. The sound pressure are measured with an spiral array system composed of 26 microphones and a pair of photo sensors are used to measure the. vehicle speed. The information about the speed and relative position of the vehicle are used to eliminate the Doppler effects from the measured pressure signal by using a de-Dopplerization algorithm. The noise generated from a moving vehicle can be grouped in many ways, however, tire noise and the noise generated from the engine are distinguishable at the speeds being tested.

• Proceedings of the KSR Conference
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• 2005.11a
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• pp.789-792
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• 2005

The dominant noise sources of Diesel Multiple Units are powerpack, which is composed of engine, transmission and cooling system, noise and wheel-rail rolling noise. The interior noise of a running vehicle is determined by structure-borne noise and air-borne noise from these noise sources. The contributions of interior noise from each noise source are calculated by air-borne transfer functions and structure-borne transfer functions of noise sources. In this paper, source separation technique is proposed to determine these transfer functions from the results of stationary and running tests of existing vehicle. With this technique, it is possible to get hold of contributions of interior noise from .noise sources of running vehicle. This source separation technique makes it possible to take efficient measures for reduction of interior noise at the early car-development stage.

• Journal of the Korean Regional Science Association
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• v.6 no.1
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• pp.57-68
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• 1990

The purpose of this study is to develop the models to predict the noise PCE (Passenger Car Equivalence) of large running vehicles through noise prediction models. The noises were measured at the distance of 7.5M, 11.0M, and 14.5M from the noise source with test vehicles running at the speed of 40 Km/h, 60 Km/h, and 80 Km/h while normal traffic were detoured. Total noise levels were measured while vehicles were running at given speeds, Engine noise level was considered as the noise of its idle running at the three vehicle speeds shown above friction noise level was ascertained by moving the vehicle at given speeds without the engin operating. The noise prediction models for each noise source were developed by factors which affect to the each noise level. As a result of this paper, the reduction of total vehicle noise by increasing the distance to the noise source from 10 M to 15 M is as much as that by dropping its speed from 60 Km/h to 40 Km/h. Also, the reduction of PCE of total noise of large vehicle by making the noise source to that by reducing its speed from 80 Km/h to 60 Km/h. Enging noise PCE, which is in range between 65 and 160, is larger than friction noise PCE which is in range 3.5 and 5.5. Engin noise is the main noise of the large vehicles while friction noise is that of the small vehicles. Machine noise for large vehicles, and engin noise for small vehicles should be tightly controlled to reduce the vehicle noise. A low noise engine and tire, and the shape of vehicle body are needed to be developed to reduce noise further.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2005.11b
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• pp.105-108
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• 2005

The radiated noise from the automotive intake system should be predicted at the design stage. To this end, the precise measurement of in-duct acoustic source parameters of the intake system, i.e., the source strength and source impedance, is essential. Most of previous works on the measurement of acoustic source parameters were performed under a fixed engine speed condition. However, the requirement of vehicle manufacturer is the noise radiation pattern as a function of engine speed. In this study, the direct method was employed to measure the source parameters of engine intake system under a fixed engine speed and engine run-up condition. It was noted that the frequency spectra of source impedance hardly changes with varying the engine speed. Thus, it is reasonable to calculate the source strength under the engine run-up condition by assuming that source impedance is invariant with engine speed. Measured and conventional source models, i.e., constant pressure source, constant velocity source, and non-reflective source, were utilized to predict insertion loss and radiated sound pressure level. A reasonable prediction accuracy of radiated sound pressure level spectra from the intake system was given in the test vehicle when using the measured source characteristics which were acquired under the operating condition.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.26 no.7
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• pp.774-780
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• 2016

In this paper noise source and transfer path of tactical vehicle are analyzed with partial coherence function and spectrum analysis. Engine, transmission, structure panel and aerodynamic are main source of cabin noise. To reduce cabin noise, identifying transfer path of sources and analyzing their contribution is important. With modeling of transfer path and partial coherence function, transfer path and principal noise source can be identified. Engine/transmission and structural resonance are principal source of low frequency noise and by adding stiffener and sound absorbing material, resonance of vibration and inflow air problem can be solved.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2003.05a
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• pp.125-129
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• 2003

The identification of location and strength distribution of extended noise sources is important in the practical noise control engineering, especially in the viewpoint of dealing with the inherent nature of noise problem in question. For noise source ranking inside an automotive vehicle, the window method has been mainly used due to its simplicity. However, time and cost drawbacks in the measurement and inaccuracy due to low-frequency tunneling and lack of phase information have been a serious problem in using this method. In this study, the inverse FRF method was employed to carry out the noise source ranking inside an automotive vehicle and it was also used to predict the interior sound pressure with the change of sound insulation materials. As a result, it was found that the source contribution of vehicle panels could be successfully identified in comparison with the window method. The sound pressure at driver's ear position was predicted based on the obtained data and was compared with the measured data. The agreement in spectral trends was acceptable and their difference in level was within 3㏈ above 500㎐.

• The Journal of the Acoustical Society of Korea
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• v.35 no.4
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• pp.310-318
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• 2016

This study deals with a method to localize a noise source occuring in a marine vehicle in a 3D environment. Even when access to the noise source is limited for a marine vehicle, such as a ship or a submarine in operation, the signal received on a hydrophone located elsewhere contains Doppler effected noise by moving relatively. This study suggests noise localization algorithm in 3D based on Doppler effect by moving marine vehicle. Using a known source mounted on the vehicle, the noise source was estimated by reducing the range of Doppler center and closest point of approach via the least square method. The algorithm was verified through various simulations and it was shown that the noise could be localized in 3D based on Doppler effect by employing two fixed hydrophones located at the vehicle's exterior points and a known reference signal generator located somewhere on the vehicle.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2014.04a
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• pp.662-663
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• 2014

In most vehicle manufactures have traditionally relied on find-fix method of human auditor, mainly due to variation excitation source. To solve the BSR noise, the requirements for BSR test are presented in terms of detection of noise source, analysis of time-frequency and sound pressure, sound quality for noise. A number of new technology direction, particularly in the field of noise source identification application and psycho-acoustics from the Zwicker's sound quality parameter, the computed objective sound metrics and subjective jury test result.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.20 no.7
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• pp.644-650
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• 2010

Among various elements to affect customer's evaluation of vehicle quality, BSR(Buzz, Squeak, Rattle) are considered to be a mostly contributing factor. In this paper, we provide the test method which can be used to reduce the BSR noise of instrument panel in a vehicle. First, potential source regions of the instrument panel for BSR are localized by using the vibration-excitor and near-acoustic field visualization system. Then, subjective evaluation of BSR noise from the detected potential noise source regions is made with the Zwicker's loudness and time-varying loudness methods. This illustrative analysis reveals that current experimental methods can be used as a test procedure to systematically tackle BSR issues in early stage of the vehicle development cycle, which can result in the reduction of the production cost.