• The Journal of the Acoustical Society of Korea
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• v.9 no.4
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• pp.45-54
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• 1990

As the results of actual survey of indoor noise in apartment houses, it represents that plumbing noise and floor impact noise are most unsatisfactory factors to inhabitants. In this paper, the actual condition of plumbing noise in apartment houses was measured and the methods of plumbing noise reduction are suggested. For these suggestions, the actual survey of plumbing noise and the model test on structure-borne sound of water supply pipe and drain sound were carried out.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 1994.10a
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• pp.277-281
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• 1994

본 연구에서는 공동주택의 욕실에 설비되어 있는 기기들을 대상으로, 급수압.토수량.배수량 등의 작동조건을 변화시켜가며 그에 따른 발생소음의 특성을 분석.평가하여, 급배수설비소음대책 마련을 위한 기초적인 자료를 제시해보고자 한다.

• The Magazine of the Society of Air-Conditioning and Refrigerating Engineers of Korea
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• v.25 no.5
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• pp.401-411
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• 1996

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2007.11a
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• pp.679-682
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• 2007

This study aims to select the proper vocabularies for evaluation about the noise emission from water supply and drain installations in apartment bathroom. As a result of surveying overlapping vocabularies and scores of them for each sound sources, 'annoying', 'noisy', 'dynamic' and 'strident' are main unpleasant vocabularies to the noise from water supply and drain installations in apartment bathroom. And vocabularies such as 'dynamic', 'sudden', 'loudness', 'noisy' are classified into the first factor by analysis.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2007.11a
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• pp.484-487
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• 2007

This study was analyzed the correlation between physically measured values and psychological response for noise of water supply and drain installations in apartment bathroom. It exhibited the noise criteria of water supply and drain installations in apartment bathroom after recording noise of water supply and drain installations. Also, It was carried out the field psycho-acoustic test to find a correlation between physically measured values and psychological response of the noise criteria of water supply and drain installations in apartment bathroom, and the results is that 40dB (A) to 45dB (A) was investigated suitable in lowest criteria.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.18 no.6
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• pp.663-673
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• 2008

The purpose of this study is to analyze the appropriate evaluation method for the water supply and drain noise of bathroom in apartment and to propose some fundamental idea on its regulation. For this reason, it was studied the acoustical characteristics of water supply and drain noise as modifying the water supply pressure for the washbasins and toilet stools and suggested the optimum evaluation method through psychoacoustic test. As a result of investigation of the levels by evaluating the adjectives and noise sources with 7-step criteria corresponding to each level of plumbing noises and analysis of the correlation between physical evaluation values by comparing the criteria, dB(A), N, and NC, with subject's response, determination coefficient($R^2$) was shown to be relatively fair or higher ranged from 0.65 to 0.92. It is shown that 'Harsh', 'Nervous', 'Unpleasant', 'Distasteful', and 'Repellent' as a second factor are to be appropriate to evaluate plumbing noise. Above these results could be used in basic data establishing KS(Korean Standard) for evaluation and rating procedure and measures reducing these noise.

• KIEAE Journal
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• v.7 no.1
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• pp.57-64
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• 2007

This study aims to propose appropriate evaluating method of noise emission from water supply and drain installations in apartment bathroom. The measurement procedure of water installations noise in apartment bathroom were established, so it is necessary to provide the evaluating method and criteria to improve the sound insulation performance of the apartment and to reduce the apartment dweller's unsatisfaction with the noise. Thus, this study reviewed the standards and evaluating methods about the water supply and drain installations noise of many other country. After measuring the noise emission from the installations in many apartment bathroom, The noise were evaluated dB(A), N, NC index, To induce the appropriate method, the coefficient of the correlation among the evaluated numbers were analyzed. As a result, the dB(A) method is most easy to evaluating and very high correlated with N and N index, So the dB(A) method is suitable to be adopted KS evaluating procedure of noise emission from water installations in apartment bathroom.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.17 no.3 s.120
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• pp.226-234
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• 2007

This study aims to evaluate noise emission from water supply and drain installations in apartment bathroom. These noise were one of the most annoying noise sources in apartment houses. Especially, drain plumbing system have used bellow bathroom ceiling, it was very discomfort to hear the noise in bellow apartment. Noise of closets and faucets were measured which were main noise source, then these noise were evaluate and analyzed the emitting characteristics varying the supplying water pressure. As increasing the water pressure, also total noise level of the water supplying stool noise and faucet noise were increased. Especially the water closet showed remarkably the increasing noise level in middle and high frequency bandwidth, while the noise level of faucets increased in $50\;Hz{\sim}250\;Hz$ of low frequency bandwidth. Vortex closet were favorable to syphon closet, and lever faucet were favorable to conventional lavatory faucet on reducing the noise. Above these results could be used in basic data establishing KS (Korean Standard) for evaluation and rating procedure and measures reducing these noise.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2006.11a
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• pp.5-10
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• 2006

This study aims to propose appropriate evaluating method of noise emission from water supply and drain installations in apartment bathroom. Because KS(Korean Standard) about water installations noise in apartment bathroom only are establishing the measurement procedure of it, Evaluation and rating procedure is necessary to improve the sound insulation performance of the apartment and to reduce the apartment dweller's unsatisfaction with the noise. Thus, this study reviewed the standards and evaluating methods about the water supply and drain installations noise of many other country. We measured the noise emission from the installations in many apartment bathroom, and then we calculated the noises to dB(A), N, NC evaluated numbers. We analyze the coefficient of the corelation among the evaluated numbers to induce the appropriate method. As a result, the dB(A) method is most easy to evaluateing and very high corelated wth N and N index, So the dB(A) method is suitable to be adopted KS evaluating procedure of noise emission from water installations in apartment bathroom.

• 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.