• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.22 no.8
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• pp.720-728
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• 2012

It is important for identification of noise and vibration problem of tire to consider influence of interaction between road and tire. A quantification of road noise is a challenging issue in vehicle NVH due to extremely complicated transfer paths of road noise as well as the difficulty in an experimental identification of input force from tire-road interaction. A noise caused by tire is divided into road noise(structure-borne noise) and pattern noise(air-borne noise). Pattern noise is caused by pattern shape of tire, which has larger than 500 Hz, but road noise is generated by the interactions between a tire and a vehicle body. In this paper, we define the quantitative analysis for road noise caused by interactions between tire and road parameters. For the identification of road noise, the chassis dynamometer that is equipped $10mm{\times}10mm $ square cleat in the semi-anechoic chamber is used, and the tire spindle forces are measured by load cell. The vibro-acoustic transfer function between ear position and wheel center was measured by the vibro-acoustic reciprocity method. In this study three tires with different type of mechanical are used for the experiment work.

• Journal of KSNVE
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• v.10 no.5
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• pp.806-810
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• 2000

This paper presents a practical method for reduction of interior noise and improvement of sound quality in compartment of passenger car. The tested vehicle has a booming noise problem at rear passenger seats. In order to identify the transfer path of interior noise, the running modal analysis, the vibro-acoustic frequency transfer response and the noise path analysis are systematically employed. Using these various methods, it has been founded that the rear part of the roof of the test car was a noise source for the booming noise. Through the modification of the roof, the booming noise has been reduced and sound quality inside car also has been improved.

• Journal of Internet of Things and Convergence
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• v.8 no.2
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• pp.79-84
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• 2022

This paper presents an enhancement method of document restoration capability which is robust for security, loss, and contamination, It is based on two methods, that is, encryption and DnCNN(DeNoise Convolution Neural Network). In order to implement this encryption method, a mathematical model is applied as a spatial frequency transfer function used in optics of 2D image information. Then a method is proposed with optical interference patterns as encryption using spatial frequency transfer functions and using mathematical variables of spatial frequency transfer functions as ciphers. In addition, by applying the DnCNN method which is bsed on deep learning technique, the restoration capability is enhanced by removing noise. With an experimental evaluation, with 65% information loss, by applying Pre-Training DnCNN Deep Learning, the peak signal-to-noise ratio (PSNR) shows 11% or more superior in compared to that of the spatial frequency transfer function only. In addition, it is confirmed that the characteristic of CC(Correlation Coefficient) is enhanced by 16% or more.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.22 no.3
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• pp.234-243
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• 2012

In this paper, a sound quality indices for the evaluation of vehicle intake and exhaust noise were developed through a correlation analysis of objective measurement data and subjective evaluation data. At first, intake and exhaust orifice noise were measured at the wide-open throttle sweep condition. And then, acoustic transfer function between intake orifice noise and interior noise at the steady state condition was measured. Also, acoustic transfer function for exhaust system was measured as the same method. Simultaneously, subjective evaluation was carried out by the paired comparison and semantic differential method by 27 engineers. Next, the correlation analysis between the psycho-acoustic parameters derived from the measured data and the subjective evaluation was performed. The most critical factor was determined and the corresponding sound quality index for the intake and exhaust noise was obtained from the multiple factor regression method. At last, the effectiveness of the proposed index was investigated.

• Journal of Korea Multimedia Society
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• v.6 no.7
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• pp.1131-1138
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• 2003

Active noise control(ANC) is an approach to noise reduction in which a secondary noise source destructively interferes with the unwanted noise is introduced. Generally, the performance of ANC is determined how well a secondary noise tracks noises. A secondary noise is generated from the cancelling speaker and a error sensor pick up error signal. The transfer function between the cancelling speaker and the error sensor is not flat and distorts secondary noises. Consequently, the performance of ANC is degraded by the transfer function. In this paper, a single sensor ANC which considers the characteristics of the speaker and the error sensor is proposed. To reduce distortion of secondary noises, the transfer function is estimated by adaptive inverse modelling and the primary noises are estimated by Kalman filter. Experimental results show that the proposed single sensor ANC effectively attenuates noises.

• Proceedings of the KSME Conference
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• 2000.11a
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• pp.618-622
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• 2000

This paper describes the correlation between the interior noise and the trunk wall vibration. Using the vibro-acoustic reciprocity, effect of the trunk wall vibration on the compartment noise is investigated on a medium size car. In the low frequency range, vehicle interior noise is dominated by several acoustic modes of the passenger compartment and the vibration modes of the surrounding shell parts. Especially, vibration of the trunk wall radiates sound and it is transferred through holes on the package tray into the passenger compartment. This paper experimentally reveals that sound can be well produced at some particular vibration modes of the trunk lid and it strongly influences the compartment noise through package tray holes. Contributions of the trunk walls to the interior noise are estimated by measuring the acoustic-structural transfer function, based on the vibro-acoustical reciprocity theorem.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.16 no.12
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• pp.1219-1228
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• 1991

In the actual case, a model of noise canceller using adaptive filter has both a channel transfer function from noise source to main signal input and to noise canceller input. The previous models of noise canceller have been considered to be only one side channel transfer function. Therefore, it is proposed that a new model has two channel transfer functions and derives an optimal tranfer function of adaptive noise canceller. The adaptive filter is using the joint process lattice filter that has fast adaptive speed. The signal noise radio has been improved by a model of ANC-ALE and it is confirmed with computer simulation. Beside, a dc bias is very effective for noise cancelling, especially to the particular signal.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2008.04a
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• pp.1000-1004
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• 2008

As performance of medical air compressor improve, the problem of noise increased. Noise is very important to medical air compressor because most of this installed inside of building. The main goal of this paper is show TPA (Transfer Path Analysis) result for contribution analysis using PAK system. Generally, the conventional TPA method consists of two steps. First, transfer functions between output sound and sources are measured by excitation experiment. Second, transferred sound in each transfer path is generated by multiplying the transfer function and the sound source signal. Then, if the output sound synthesized from all transferred sounds doesn't give good agreement with the measured output sound (i.e., the accuracies of the transfer functions are low), setting a suitable countermeasure guideline becomes difficult. For obtaining highly accurate transfer functions, eliminating correlations among transfer functions and noise included in the measured data are necessary. In the new method with PAK system, the vibration acceleration and sound signals around the sound sources and the output sound were measured simultaneously to obtain the transfer functions when compressor was operating. By applying PAK system, a highly accurate and efficient transfer path analysis method was developed that does not require an excitation experiment.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2000.11a
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• pp.201-206
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• 2000

In this work transfer function synthesis method based on FRF data of each substructure is investigated for a complex structure composed of many substructures. Though the transfer function synthesis method has superiority to analyze the characteristics of interfaces among substructures effectively, many problems arise in the computation process, especially matrix inversion process. Due to computational problems, the error between the data obtained by test and the predictions through computations is inevitable. So in this paper, computational aspects in the transfer function synthesis method are examined through a steering system problem of passenger car. For the FBS method, frequency response functions of 3 substructures are measured experimentally. Effects of several parameters such as matrix inversion method, connection conditions between substructures and off-diagonal terms on system response are studied numerically.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2002.11b
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• pp.517-522
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• 2002

The frequency response function(FRF) of each substructure is used for the transfer function synthesis method(TFS). The dynamic characteristics of the full system are obtained by synthesizing FRFs of each substructure. The validation of TFS depends on accuracy for FRF of each substructure. Impact hammer testing is widely used to obtain the modal characteristics of structures. However, the FRF obtained from impact hammer testing contains several errors, such as finite record length error and leakage error of which characteristic depends on data acquisition time which we call record length. In this paper, a method to remove these errors is proposed so as to enhance results of TFS. Numerical examples show that the FRF of full structure can be predicted exactly by the method proposed in this paper.