• 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.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.29 no.12 s.243
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• pp.1597-1604
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• 2005

The identification of a moving noise source is important in reducing the source power of the transport systems such as airplanes or high speed trains. However, the direct measurement using a microphone running with noise source is usually difficult due to wind noise, white the source motion distorts the frequency characteristics of the pass-by sound measured at a fixed point. In this study the relationship between the spectra of the source and the pass-by sound signal is analyzed for an acoustic source moving at a constant velocity. Spectrum of the sound signal measured at a fixed point has an integral relationship with the source spectrum. Nevertheless direct conversion of the measured spectrum to the source spectrum is ill-posed due to the singularity of the integral kernel. Alternatively a differential equation approach is proposed, where the source characteristics can be recovered by solving a differential equation relating the source signal to the distorted measurement in time domain. The parameters such as the source speed and the time origin, required beforehand, are also determined only from the frequency-phase relationship using an auxiliary measurement. With the help of the regularization method, the source signal is successfully recovered. The effects of the parameter errors to the estimated frequency characteristics of the source are investigated through numerical simulations.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 1997.04a
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• pp.539-544
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• 1997

Although the identification of a moving noise source is important in reducing the source power of the transport systems such as airplane or high speed train, the direct measurement of the frequency characteristics is usually difficult due to wind noise when using a microphone running with that noise source. On the other hand the motion of a source causes the frequency characteristics of the pass-by sound measured at a fixed point to be distorted that it is quite difficult to identify the original source characteristics. In this study the relationship between the spectra of the source and the pass-by sound signal is analyzed for a source moving at a constant velocity. The effects of the speed and the frequency characteristics of the source on the pass-by noise spectrum are investigated through numerical simulations.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2006.05a
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• pp.138-142
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• 2006

Time Difference of Arrival (TDOA) algorithm was applied to sound source positioning. Using measured microphones signal, difference of distance from source to sensors were estimated by TDOA and speed of sound, and taken by navigational measurements. And iteration procedures were induced to find the actual source location. For the case of stationary and moving sound source, validation test were performed in the anechoic room. In the stationary case, the error of positioning is less then 1.3% in length scale, and it could be seen proper filtering processes were required in the application of moving sound source.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 1996.04a
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• pp.291-297
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• 1996

To visualize sound field or to identify noise sources, we can use many methods such as intensity method, acoustic holographic method, source identification method using line array, etc. Conventionally all these methods are performed with the assumption of stationary condition in space and time. But for moving source, spatial characteristics and frequency components are changing, so we need another processing algorithm. This paper shows some experimental results - sound field by moving noise sources. In the experiment cross type microphone line array is used for sensing pressure and cars and a motorcycle are used as moving sources that are assumed to have constant speed. The processing methods are acoustic holographic method, spherical beamforming and spectrogram.

• Journal of KSNVE
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• v.10 no.4
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• pp.669-678
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• 2000

This paper reviews the improved moving frame acoustic holography (MFAH) method and its application. Moving frame acoustic holography was originally proposed to increase the aperture size and the spatial resolution of hologram by using a moving line array of microphones. The hologram of scanned plane can be obtained by assuming the sound field to be product of spatial and temporal information. Although conventional MFAH was only applied to sinusoidal signals, it allows us to visualize the noise generated by moving noise sources by employing a vertical line array of microphones affixed to the ground. However, the sound field generated by moving sources becomes different from that of stationary ones due to the movement of the sources. Firstly, this paper introduces the effect of moving noise sources on the obtained hologram by MFAH and the applicability of MFAH to the visualization of moving sources. Secondly, this paper also reviews improved MFAH that can visualize a coherent narrow band noise and a pass-by noise. The practical applicability of the improved MFAH was demonstrated by visualizing tire noise during a pass-by test.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.36 no.3
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• pp.238-243
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• 2008

Several experimental techniques for identifying the noise sources distributed over a moving vehicle have been developed recently and are used 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 passing by. Unlike the acoustic signals from a stationary noise source, the sound generated from a moving source is distorted due to the Doppler effects. The information about the speed and relative position of the vehicle are used to eliminate the Doppler effects from the measured acoustic 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.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.19 no.8
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• pp.816-827
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• 2009

This paper deals with a bearing faults localization technique based on holographic approach by visualizing sound radiated from the faults. The main idea stems from the phenomenon that bearing faults in a moving vehicle generate impulsive sound. To visualize fault signal from the moving vehicle, we can use the moving frame acoustic holography [Kwon, H.-S. and Kim, Y.-H., 1998, "Moving Frame Technique for Planar Acoustic Holography," J. Acoust. Soc. Am. Vol. 103, No. 4, pp. 1734${\sim}$1741]. However, it is not easy to localize faults only by applying the method. This is because the microphone array measures noise(for example, noise from other parts of the vehicle and the wind noise) as well as the fault signal while the vehicle passes by the array. To reduce the effect of noise, we propose two ideas which utilize the characteristics of fault signal. The first one is to average holograms for several frequencies to reduce the random noise. The second one is to apply the partial field decomposition algorithm [Nam, K.-U., Kim, Y.-H., 2004, "A Partial Field Decomposition Algorithm and Its Examples for Near-field Acoustic Holography," J. of Acoust. Soc. Am. Vol. 116, No. 1, pp. 172${\sim}$185] to the moving source, which can separate the fault signal and noise. Basic theory of those methods is introduced and how they can be applied to localize bearing faults is demonstrated. Experimental results via a miniature vehicle showed how well the proposed method finds out the location of source in practice.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2001.05a
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• pp.85-89
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• 2001

The problem of the transient interaction of a plane acoustic shock wave which has an infinitely steep wave front with a cylindrical or spherical elastic shell has been studied analytically from early fifties based on the integral transform and series solution techniques. Huang adopted an inverse Laplace transform, and used a finite number of terms of the infinite series expansion of the equations for the shells. In the 1990s, the results have been used by many authors for validation of computer codes. The object of this paper is to discuss the interaction between a moving source and submerged spherical shells. Since the center of source is moving the first contact location between the waves and shell changes depending on the source velocity and distance. These are considered in the analysis. Furthermore, constant source strength and decreasing strength are considered in the analysis. Radial velocities at several locations on the structure are obtained and the results are discussed.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2009.04a
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• pp.681-688
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• 2009

This paper deals with a bearing faults localization technique based on holographic approach by visualizing sound radiated from the faults. The main idea stems from the phenomenon that bearing faults in a moving vehicle generate impulsive sound. To visualize fault signal from the moving vehicle, we can use the moving frame acoustic holography [H.-S. Kwon and Y.-H. Kim, "Moving frame technique for planar acoustic holography," J. Acoust. Soc. Am. 103(4), 1734-1741, 1998]. However, it is not easy to localize faults only by applying the method. This is because the microphone array measures noise (for example, noise from other parts of the vehicle and the wind noise) as well as the fault signal while the vehicle passes by the array. To reduce the effect of noise, we propose two ideas which utilize the characteristics of fault signal. The first one is to average holograms for several frequencies to reduce the random noise. The second one is to apply the partial field decomposition algorithm [K.-U. Nam, Y.-H. Kim, "A partial field decomposition algorithm and its examples for near-field acoustic holography," J. of Acoust. Soc. Am. 116(1), 172-185, 2004] to the moving source, which can separate the fault signal and noise. Basic theory of those methods is introduced and how they can be applied to localize bearing faults is demonstrated. Experimental results via a miniature vehicle showed how well the proposed method finds out the location of source in practice.