• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.20 no.11
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• pp.1089-1096
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• 2010

The relation between the vibration induced from machinery and the radiated sound is complicated. Acoustic intensity method is widely used to obtain the accuracy of noise measurement and noise identification. In this study, as groundwork, the complex acoustic intensity method is performed to identify noise source and transmission path on different free space point source fields. As an industrial application, the complex acoustic intensity method is applied to HVAC to identify sound radiation characteristics in the near field. Experimental complex acoustic intensity method was applied to HVAC, it is possible to identify noise sources in complicated sound field characteristics which noise sources are related with each other, and certificate the validity of complex acoustic intensity. Especially, it can be seen that complex acoustic intensity method using both of active and reactive intensity is vital in devising a strategy for identification of noise. Also, the vector flow of acoustic intensity was investigated to identify sound intensity distributions and energy flow in the near field of HVAC.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.7
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• pp.3268-3283
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• 2018

With the advent of the Information Age, the source identification of digital images, as a part of digital image forensics, has attracted increasing attention. Therefore, an effective technique to identify the source of digital images is urgently needed at this stage. In this paper, first, we study and implement some previous work on image source identification based on sensor pattern noise, such as the Lukas method, principal component analysis method and the random subspace method. Second, to extract a purer sensor pattern noise, we propose a sample selection method to improve the random subspace method. By analyzing the image texture feature, we select a patch with less complexity to extract more reliable sensor pattern noise, which improves the accuracy of identification. Finally, experiment results reveal that the proposed sample selection method can extract a purer sensor pattern noise, which further improves the accuracy of image source identification. At the same time, this approach is less complicated than the deep learning models and is close to the most advanced performance.

• Journal of Power System Engineering
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• v.7 no.1
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• pp.74-81
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• 2003

A system identification is to estimate the mathematical model on the base of input output data and to measure the output in the presence of adequate input for the controlled system. In the traditional system control field, most identification problems have been thought as estimating the unknown modeling parameters on the assumption that the model structures are fixed. In the system identification, it is possible to estimate the true parameter values by the adjusted least squares method in the input output case of no observed noise, and it is possible to estimate the true parameter values by the total least squares method in the input output case with the observed noise. We suggest the adjusted least squares method as a consistent estimation method in the system identification in the case where there is observed noise only in the output. In this paper the adjusted least squares method has been developed from the least squares method and the efficiency of the estimating results was confirmed by the generating data with the computer simulations.

• 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.

• Proceedings of the KOSOMBE Conference
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• v.1993 no.05
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• pp.74-77
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• 1993

Estimation and removal of power line interference in the electrocardiogram using adaptive noise cancelling techniques is presented. The system identification concepts are used to design the noise cancelling filter and the prediction error method is used to adjust filter coefficients. Computer simulation were performed to compare this method with the Lekov's method.

• The Journal of the Acoustical Society of Korea
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• v.37 no.3
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• pp.129-138
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• 2018

In port and coastal areas where ship traffic is frequent, ship noise dominantly influences underwater noise in low frequency band below 1 kHz. In this paper, we propose a modeling method to estimate the underwater shipping noise using the voyage information of ship observed in AIS (Automatic Identification System). For the purpose of ship noise modeling, the navigation information of the vessels operating in the southern part of Jeju was observed using AIS and underwater noise was measured by installing a hydrophone in the experimental area to verify the modeled ship noise. AIS data were used to model the noise level of ship and compared with measured underwater noise. The variation of noise level with time was found to be similar, and the cause of the error was discussed. Through this study, it was confirmed that the noise level of ship can be estimated within 5 dB error range using AIS data.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.21 no.9
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• pp.834-841
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• 2011

Obtaining the real exciting force is important for the analysis of structural vibration or sound radiation to represent the actual condition. But in most cases, it is so difficult to get the actual force signals by direct measurement using sensors due to complex geometry. This paper suggests advanced source identification method which can be applied to the prediction of radiated noise considering correlations between measured signals. This method was implemented to the identification of the fan force in the refrigerator. The analysis of structural vibration and radiated noise caused by the fan force was also performed. The comparison between predicted SPL and measured SPL of the radiated noise by the refrigerator fan showed good agreement.

• Korean Journal of Fisheries and Aquatic Sciences
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• v.36 no.5
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• pp.541-548
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• 2003

Species identification in hydroacoustic survey is one of the key requirements to estimate biomass of organism and to understand the structure of zooplankton community. Feasibility of species identification using two frequencies (38 and 120 kHz) was investigated on the basis of mean volume backscattering strength difference (MVBS). Virtual echogram technique was applied to two frequencies data sets that obtained from surveys in the Antarctic Ocean and Yellow Sea. Virtual echogram method using MVBS revealed the possibility of species identification, which species identification relying on visual scrutiny of single frequency acoustic data resulted in significant errors in biomass estimation. Through noise cancellation using MVBS, much of the acoustic noise caused by acoustic instruments could be removed in new virtual echogram, and the biomass estimation and data quality was improved.

• 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 for Noise and Vibration Engineering Conference
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• 2005.11b
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• pp.180-185
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• 2005

Gear whine noise of the axle and transmission is getting more important for reduction of vehicle noise, because major noise of vehicle was reduced. Therefore, in this paper, axle noise and vibration is measured, then the modal analysis and running modal analysis is applied for identification of axle gear whine noise. And To reduce axle noise, Various structural modifications are performed by using FEM and BEM techniques.