• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.12 no.7
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• pp.520-526
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• 2002

Identification of noose sources, their locations and strengths, has been taken great attention. The methods that can identify noise sources normally assume that noise sources are located in a free field. However, the sound in a reverberant field consists of that coming directly from the source plus sound reflected or scattered by the walls or objects in the field. In contrast to the exterior sound field. reflections are added to sound field. Therefore, we haute to consider the reverberation effect on the source identification method. The main objective of this paper is to identify noise source in the reverberant field. At fist, we try to identify noise sources in a rigid wall emc;psire using the beamforming method. In many cases of practical interest, the wall has admittance so that random reflections occur in an enclosure. In this paper, we assumed the complex reverberant field in the enclosure to be the sum of plane caves with random Incidence and magnitude. Then we try to explain effects of reverberant field at interior source identification.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2001.05a
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• pp.1203-1209
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• 2001

Identification of noise sources, their locations and strengths, have been taken great attention. The method that can identify noise sources normally assumes that noise sources are located at a free field. However, the sound in a reverberant field consists of that coming directly from the source plus sound reflected or scattered by the walls or objects in the field. In contrast to the exterior sound field, reflections are added to sound field. Therefore, we have to consider the reverberation effect on the source identification method. The main objective of this paper is to identify noise source in the reverberant field. At fist, we try to identify noise sources in a rigid wall enclosure using the spherical beamforming method. In many case of practical interest, the wall has an admittance so that complex reflection process occurred. In this paper, we assumed the complex reverberant field in the enclosure to be the sum of plane waves with random incidence and magnitude. Then the effects of reverberant field at interior source identification have been studied theoretically as well as experimentally

• Journal of the Korean Society for Precision Engineering
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• v.17 no.1
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• pp.83-92
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• 2000

Sound intensity method is well known as a visualization technique of sound field or sound propagation in noise control. Sound intensity or energy flux is a vector quantity which describes the amount and the direction of net flow of acoustic energy at a given position. Especially two dimensional sound intensity method is very useful in evaluating periodic characteristics and acoustic propagation mode of noise source. In this paper, we have studied the noise source Identification, acoustic sound field analysis, and characteristics of noise source of rotary compressor and scroll compressor for air conditioner using complex sound intensity method. Also we proposed a now method of time domain analysis which is used in evaluating of position of noise source in rotary and scroll compressor in this paper This paper presents the advantage, simplicity and economical efficiency of this method by analysing the characteristics of noise source with two dimensional complex sound intensity simultaneously.

• Smart Structures and Systems
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• v.29 no.3
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• pp.475-484
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• 2022

The loss of cable tension for civil infrastructure reduces structural bearing capacity and causes harmful deformation of structures. Currently, most of the structural health monitoring (SHM) approaches for cables rely on contact transducers. This paper proposes a cable tension identification technology using percussion sound, which provides a fast determination of steel cable tension without physical contact between cables and sensors. Notably, inspired by the concept of tensioning strings for piano tuning, this proposed technology predicts cable tension value by deep learning assisted classification of "percussion" sound from tapping a steel cable. To simulate the non-linear mapping of human ears to sound and to better quantify the minor changes in the high-frequency bands of the sound spectrum generated by percussions, Mel-frequency cepstral coefficients (MFCCs) were extracted as acoustic features to train the deep learning network. A convolutional neural network (CNN) with four convolutional layers and two global pooling layers was employed to identify the cable tension in a certain designed range. Moreover, theoretical and finite element methods (FEM) were conducted to prove the feasibility of the proposed technology. Finally, the identification performance of the proposed technology was experimentally investigated. Overall, results show that the proposed percussion-based technology has great potentials for estimating cable tension for in-situ structural safety assessment.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2009.10a
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• pp.229-230
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• 2009

A method is suggested for the noise source identification using the sound intensity method. The suggested method does not need to install the grid using wire or thread during the sound intensity measurement for the noise source identification. It utilizes a camera to show the grid on the screen not installing the real grid for the sound intensity method.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1997.10a
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• pp.560-563
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• 1997

Sound intensity method is well known as a visualization technique of sound field and sound propagation in noise control. Sound intensity is a vector quantity that describes the magnitude and the direction of net flow of acoustic energy at a given position. The current measuring method is expensive and difficult to identify the noise source exactly. In this paper, we have studied the noise source identification and the characteristics of noise source of rotary compressor for air conditioner using complex sound intensity method. The new method for instantaneous sound intensity is also proposed and it is useful for transient state and steady state. The criteria of these states select auto correlation coefficient. The advantage, simplicity and economic attribution of this method are verified by analyzing the characteristics of noise source with instantaneous sound intensity compared to mean sound intensity.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2003.05a
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• pp.960-963
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• 2003

Sound intensity method is well known as a visualization technique of sound field and sound propagation in noise control. Sound intensity is a vector quantity that describes the magnitude and the direction of net flow of acoustic energy at a given position. The current measuring method is expensive and difficult to identify the noise source exactly. In this paper, we have studied the noise source identification and the characteristics of noise source of rotary compressor for air conditioner using complex sound intensity method. The new method for instantaneous sound intensity is also proposed and it is useful for transient state and steady state. The criteria of these state, select auto correlation coefficient. The advantage, simplicity and economic attribution of this method are verified by analyzing the characteristics of noise source with instantaneous sound intensity compared to mean sound intensity.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2005.05a
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• pp.254-257
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• 2005

Locations and emission characteristics of noise source of rapier loom are important factors greatly. So, noise characteristics of rapier loom were investigated by the noise source identification as a part of experimental methods in this study. To identify the noise sources of the rapier loom sound intensity was measured under machine operation. In addition, frequency spectra of the sound at operator position was measured along with sound intensity to help identify the noise characteristics of the rapier loom. The results indicate that the sound power level occurs along the rapier loom.

• Journal of Korea Multimedia Society
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• v.24 no.11
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• pp.1500-1507
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• 2021

Identification and analysis of the first and second heart sounds(S1, S2) is the easiest way for cardiovascular disease prevention and early diagnosis. However, accurate identification is difficult because the heart sound includes organ movement, blood vortex, user experience, and noise influenced by subjective judgment. Therefore, an algorithm to automatically identify the S1 and S2 heart sounds based on blood vessel transit time(VTT) is presented in this paper. According to the experimental results of comparing the algorithm developed for S1 and S2 heart sound analysis with the conventional Shannon energy algorithm in 10 volunteers, it has been proven that the proposed algorithm can automatically identify S1 and S2 heart sounds with higher accuracy than existing algorithms.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2013.10a
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• pp.525-530
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• 2013

With the increasing the importance of emotional quality of vehicle, the sound quality of systems with electric motor components has become increasingly important. Electric motors are used for windows, seats, sun roof, mirrors, steering columns, windshield wiper, climate control blowers, etc. In this paper, a study was conducted to identify sound quality factors that contribute to customer's satisfaction and preference of the window lift system. Jury test for subjective evaluation was carried out and sound quality index was developed. Averaged sound pressure level and sharpness were significant factors when glass moves down. Also, maximum loudness at stop section and averaged loudness were significant factor when glass moves up. Noise source identification was carried out for the reduced the loudness and sharpness during glass transferred section and impulsive noise at stop section, Using the source identification result, several improvement points were applied. And finally, the degree of sound quality improvement was judged using sound quality index.