• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 1997.04a
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• pp.581-587
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• 1997

Numerical predictions of aerodynamic noise radiated by subsonic rotors are carried out. A time domain approach for Ffowcs-Williams Hawkings equation of acoustic analogy is used in developing a comprehensive rotor/fan noise prediction program to handle both arbitrary blade shapes and loading conditions. Since only the aeroacoustic aspects of rotors are considered here, the calculations are carried out for rotors with simple aerodynamic characteristics. Broadband noise from ingestion of turbulence is also considered. By incorporating discrete frequency noise prediction of steady loading with broadband spectrum, much better correlation at the low frequency region with experimental data is obtaind. The contributions from different noise mechanisms can also be analysed through this method.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.38 no.4
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• pp.587-593
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• 2018

The current road traffic noise prediction programs of Korea, which are widely used, are based upon foreign prediction model. Thus, it is necessary to verify foreign prediction models to find out whether they are suitable for the domestic road traffic environment. In addition, an analysis and an in-depth study on the main factors should be conducted in advance as the influence factors on the occurrence of traffic noise vary for each prediction model. Therefore, this study examined the influence factors and the existing prediction models used to forecast road traffic noise. Also, analyzed their relationship with the factors influencing the noise generated by driving vehicles through multiple regression analysis using a prediction model, taking into consideration of the traffic environment and the road geometric structure. In addition, this study will apply experimental values to the existing road traffic noise prediction model (NIER, RLS-90) and the deducted road traffic noise prediction model. As a result, the order of the absolute value sum of the errors are NIER, RLS-90, model value. Through comparison and verification, developed models are to be analyzed for providing basic research results for future study on road traffic noise prediction modeling.

• The KSFM Journal of Fluid Machinery
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• v.2 no.2 s.3
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• pp.46-56
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• 1999

This study is on the performance prediction and design of a sirocco fan. Slip coefficient is very important factor for the performance analysis of a centrifugal-type fan. Because generally used slip coefficient equations of backward curved centrifugal fan are not appropriate for forward curved sirocco fan, in this study a proper slip coefficient equation for a sirocco fan is suggested. Using this equation performance prediction program for sirocco fan is composed of and also included the total noise prediction that include the turbulent noise at the fan inlet and boundary layer noise. A comparison between the values obtained from performance prediction program and experimental values shows that the program predicts the sirocco fan performance in a practical rate.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.21 no.5
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• pp.1172-1179
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• 1996

General adaptive noise canceller(ANC) suffers from the misadjustment of adaptive filter weights, because of the gradient-estimate noise at steady state. In this paper, an adaptive noise cancellation algorithm with speech detector which is distinguishing speech from silence and adaptation-transient region is proposed. The speech detector uses property of adaptive prediction-error filter which can filter the highly correlated speech. To detect speech region, estimation error which is the output of the adaptive filter is applied to the adaptive prediction-error filter. When speech signal apears at the input of the adaptive prediction-error filter. The ratio of input and output energy of adaptive prediction-error filter becomes relatively lower. The ratio becomes large when the white noise appears at the input. So the region of speech is detected by the ratio. Sign algorithm is applied at speech region to prevent the weights from perturbing by output speech of ANC. As results of computer simulation, the proposed algorithm improves segmental SNR and SNR up to about 4 dBand 11 dB, respectively.

• The Journal of the Acoustical Society of Korea
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• v.13 no.1
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• pp.57-62
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• 1994

In order to establish a prediction method for road traffic noise generated from actual traffic flow, a new approach is proposed for practical use. One block in urban road is regarded as one box in this study. This prediction method is able to treat any kind of road traffic noise generated from one block. The validity of the proposed prediction method has been experimentally confirmed by applying it to actually observed road traffic noise data. The correlation between observed and predicted noise level is good.

• 유체기계공업학회:학술대회논문집
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• 1998.02a
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• pp.63-72
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• 1998

This study Is on the performance prediction and design of sirocco fan. Slip coefficient is very important factor for the performance analysis of centrifugal-type fan. Because generally used slip coefficient equations of backward curved centrifugal fan are not appropriate for forward curved sirocco fan, in this study a proper slip coefficient equation for sirocco fan is suggested. Using this equation performance prediction program for sirocco fan is composed and also included the total noise prediction that include turbulent noise at the fan Inlet and boundary layer noise. A comparison between the values obtained from performance prediction program and experimental values shows that the program predicts the sirocco fan performance in a practical rate.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2000.06a
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• pp.78-83
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• 2000

Exterior noise generated by the aircraft induces a serious noise pollution near the airport. For the prediction of an exterior noise radiation of aircraft an empirical formula is employed to model the acoustic sources. It is shown that the fan/compressor noise is the most dominant part of the acoustic sources in all cases.

• Journal of Environmental Impact Assessment
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• v.15 no.2
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• pp.93-100
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• 2006

In general, the verification to prediction formula in a national road and the main street of a town has been used recklessly in Korea. Therefore we investigated the validity of an existing prediction formula (NIER(87, 99), TR-Noise, KLC(2002)) with correction relationship which was based on both the prediction formular from apartment complex in the field and height 1.5m from the surface level. On the results of measuring the noise level form an isolated distance, the noise level showed that it was 4.5~5.5dB(A) by reason of becoming 2 folder far from a source. From the distribution of noise level measured by the apartment floors, the measurement point (1st floor) was 58.7~71.4dB(A) at its lowest level and the middle floors (3, 5, 7 and 10) were the highest distribution of noise level. From the analysis results on the application validity to an existing prediction formular (NIER(87, 99), TR-Noise, KLC(2002)) in the height 1.5m, the correction coefficients were 0.95~0.96 and the measured values were reasonably close to the predicted values, indicating the validity and adequacy of the predicted models. KLC(2002) model was found accurate within 3dB(A) with 36 data out of the total 42 data, showing the most accuracy among the predict models. However, the developed models have to improve the accuracy with a various of factors.

• Journal of the Society of Naval Architects of Korea
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• v.28 no.2
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• pp.293-306
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• 1991

During the last few years recommendations or regulations concerning permissible noise levels on shirts have been issued by the authorities in most countries. For these reasons the need for useful and accurate noise prediction computer programs has been emphasized. A noise prediction program can make it possible to find the most economical solution to achieve a certain noise requirement. This paper attempts to develop a noise prediction computer program using statistical energy analysis(SEA). In this paper, the SEA is used to predict the sound transmission loss for airborne noise and the vibration amplitude of the panel consisting of ship spaces such as floor, wall, and ceiling for structureborne noise. And in order to verify the prediction, a small passenger vessel, G/T120 tons, is selected. It has been shown that the prediction is capable of giving results in good practical agreement with measurements and therefore it is useful for predicting the nolle levels in ships and establishing the countermeasures at early design stage.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.12
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• pp.3242-3265
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• 2023

Ensuring reliability of a machinery system involve the prediction of remaining useful life (RUL). In most RUL prediction approaches, noise is always considered for removal. Nevertheless, noise could be properly utilized to enhance the prediction capabilities. In this paper, we proposed a novel RUL prediction approach based on noise injection and a Kalman filter ensemble of modified bagging predictors. Firstly, we proposed a new method to insert Gaussian noises into both observation and feature spaces of an original training dataset, named GN-DAFC. Secondly, we developed a modified bagging method based on Kalman filter averaging, named KBAG. Then, we developed a new ensemble method which is a Kalman filter ensemble of KBAGs, named DKBAG. Finally, we proposed a novel RUL prediction approach GN-DAFC-DKBAG in which the optimal noise-injected training dataset was determined by a GN-DAFC-based searching strategy and then inputted to a DKBAG model. Our approach is validated on the NASA C-MAPSS dataset of aero-engines. Experimental results show that our approach achieves significantly better performance than a traditional Kalman filter ensemble of single learning models (KESLM) and the original DKBAG approaches. We also found that the optimal noise-injected data could improve the prediction performance of both KESLM and DKBAG. We further compare our approach with two advanced ensemble approaches, and the results indicate that the former also has better performance than the latters. Thus, our approach of combining optimal noise injection and DKBAG provides an effective solution for RUL estimation of machinery systems.