• International Journal of Highway Engineering
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• v.14 no.2
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• pp.19-28
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• 2012

A measuring technique for tire-pavement interaction noise that uses a proposed noble close proximity(NCPX) method, which has been proofed in terms of the reliability and consistency of interaction noise measurement through several researches, equipped with surface microphones has been adopted in order to perform bridge deck pavement noise evaluations on four different pavement surfaces. Through field testing measurement of bridge deck pavement in Seoul inner ring road, the appropriate noise-measuring procedures have been used for evaluating the noise characteristics of four different surfaces. Measuring results show that tire-pavement noise levels vary depending on the surface types and vehicle speeds. Furthermore, the different characteristics of tire-pavement interaction noise can be found before and after the new surface construction of bridge deck pavements in terms of the 1/3 octave band analysis of vehicle speed.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.22 no.11
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• pp.1113-1120
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• 2012

This paper deals with the analysis of interior noise and low frequency noise characteristic for the Busan citizens to use public transport, Busan Metro Line 3. The interior noise evaluation index, articulation index(AI) is evaluated the lower value about average 22 % in a whole range, this is difficult to have a conversation. Also, noise criteria(NC) curve is partially evaluated as NC-65 below 2000 Hz, space type is evaluated as factories. Another of interior noise evaluation index, preferred speech interference level(PSIL) is evaluated the upper value about average 66 dB(A) in a whole range, this is evaluated to be interrupted. In the case of low frequency noise(20~200 Hz), the measurement of low frequency noise is assessed largely beyond noise criteria of ISO 226. The low frequency noise should be reduced because low frequency noise affects on psychological stress and displeasure although low frequency noise is not recognized by auditory sense. The low frequency noise criteria and guideline will be enacted from now on in Korea.

• Journal of the Korean Society of Marine Environment & Safety
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• v.12 no.3 s.26
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• pp.193-199
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• 2006

The noise levels on board ship recognized at Europe in the early 1970s and the noise regulations on the ship began to put in a statutory form. After that, in 1982 'International Code on Noise Levels on Board Ships' adopted by IMO and it became a standards to the newly built ship and it remains up to recently. Especially, the ship engine room, which have huge main engine and various kinds of subsidiary machines, is under an extremely loud condition and so the worker who works in it is easy to lose his hearing. Recently, each nation regulates the allowable noise exposure time by law to protect the industrial employee from the occupational hardness of hearing. In our country, the allowable noise exposure time is regulated by the labor. standard law but the international provisions regulated by IMO have been applied in case of the ship engine room. In this paper, the cabin's noise levels of cargo-passenger ships plies south-west coast line were investigated.

• The Journal of the Acoustical Society of Korea
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• v.42 no.6
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• pp.603-616
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• 2023

In this study, machine learning-based clustering and classification of residential noise in apartment buildings was conducted using frequency and temporal characteristics. First, a residential noise source dataset was constructed . The residential noise source dataset was consisted of floor impact, airborne, plumbing and equipment noise, environmental, and construction noise. The clustering of residential noise was performed by K-Means clustering method. For frequency characteristics, L_eq and L_max values were derived for 1/1 and 1/3 octave band for each sound source. For temporal characteristics, Leq values were derived at every 6 ms through sound pressure level analysis for 5 s. The number of k in K-Means clustering method was determined through the silhouette coefficient and elbow method. The clustering of residential noise source by frequency characteristic resulted in three clusters for both L_eq and L_max analysis. Temporal characteristic clustered residential noise source into 9 clusters for L_eq and 11 clusters for L_max. Clustering by frequency characteristic clustered according to the proportion of low frequency band. Then, to utilize the clustering results, the residential noise source was classified using three kinds of machine learning. The results of the residential noise classification showed the highest accuracy and f1-score for data labeled with L_eq values in 1/3 octave bands, and the highest accuracy and f1-score for classifying residential noise sources with an Artificial Neural Network (ANN) model using both frequency and temporal features, with 93 % accuracy and 92 % f1-score.

• Journal of Environmental Impact Assessment
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• v.26 no.1
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• pp.11-26
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• 2017

Approximate empirical equations obtained by measuring overall noise levels at different distances have been used to evaluate environmental influence of the railway noise though the accurate prediction of noise levels is important. In this paper, a noise prediction model considering the frequency characteristics of noise sources and propagation was suggested to improve the accuracy of noise prediction. The railway noise source was assorted into track, wheel, traction and aerodynamic components and they were characterized with the source strength and speed coefficient at each octave-band frequency. Correction terms for the acoustic roughness and the track/bridge condition were introduced. The sound attenuation from a source to a receiver was calculated taking account of the geometrical divergence, atmospheric absorption, ground effect, diffraction at obstacles and directivity of source by applying ISO 9613-2. For obtaining the source strength and speed coefficients, the results of rolling noise model, numerical analysis and measurements of pass-by noise were analyzed. We compared the predicted and measured noise levels in various vehicles and tracks, and verified the accuracy of the present model. It is found that the present model gives less error than the conventional one, so that it can be applied to make the accurate prediction of railway noise effect and establish its countermeasures efficiently.

• The Journal of the Acoustical Society of Korea
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• v.34 no.1
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• pp.12-19
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• 2015

In this paper, temporal variations of acoustic transmission loss (TL) affected by internal tide are studied by computer simulation using oceanic data measured in the southern sea of Jeju Island in summer. Temperature was measured with depth (bottom depth are nearly 80 m) in two sites near Seogwipo coast every one hour for 25 hours during July 27 and 28, 2009. The periodic fluctuation of temperature due to the internal tide was observed and its vertical displacement was more than 10 m. In order to investigate temporal variation of TL by internal tide, acoustic propagation between two measurement sites (3.8 km distance) was simulated with a source depth of 10 m. TL variation for 1/3 octave band of 100 Hz center frequency highly coincided with tidal period but more complex variation with indistinct tidal period was observed for 1 kHz. Maximun standard deviation of TL variation was 4.2 dB for 100 Hz at 2.8 km distance from a source and it was 3.7 dB for 1 kHz. The tidal variation was also shown in detection range and its maximum variance was less than 1 km. These results imply that temporal variation of TL should be considered for acoustic researches at the southern sea of Jeju Island.