• 한국산업보건학회지
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• 제5권2호
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• pp.193-199
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• 1995

This study was designed to investigate the difference of time weighted average(TWA) of noise levels and noise doses by the different operating parameter settings such as exchange rate, threshold level and criterion level for noise dosimeter in the field measurements of noise at industrial working environments. The time weighted averages of noise level and noise doses for noise working environments were determined by noise dosimeter on 80 workers employed at 20 industrial establishments of 8 industries. The results obtained were as follows: 1. The mean time weighted average(TWA) of the noise working environments by the operating parameter settings showed 93.4 dB(A) in 3 dB of exchange rate, 80 dB of threshold level and 90dB of criterion level 92.0 dB(A) in 3 dB-exchange rate, 90 dB-threshold level and 90 dB-criterion level, in 90.8 dB(A) in 5 dB of exchange rate, 80 dB of threshold level and 90 dB of criterion level, and 86.7 dB(A) in 5 dB of exchange rate, 90 dB of threshold level and 90dB of criterion level. 2. ln group of noise level less than 90 dB(A), mean TWAs of 80 dB of threshold level were significantly higher than that of 90 dB of threshold level in 3 dB and 5 dB of exchange rate. 3. The case exceeded threshold limit value of noise was 49(61.3 %) in 3dB, 80dB and 90 dB setting, 44(55.0 %) in 3 dB, 90 dB, 90 dB setting, 33(41.3 %) in 5 dB, 80dB, 90 dB setting and 26(32.5%) in 5 dB, 90 dB, 90 dB setting. Above considerations in mind, it is suggested that exchange rate and threshold level be specified in related laws and regulations in the evaluation of working environments noise.

• 한국소음진동공학회:학술대회논문집
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• 한국소음진동공학회 2006년도 춘계학술대회논문집
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• pp.1459-1464
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• 2006

In the previous studies on railway noise analysis, the main purpose of noise analysis is concerned with the reduction of A-weighted sound pressure level in order to satisfy noise regulations. However, more important facts on noise reduction are the subjective feelings of the human being on noise because people might be annoyed from the noise caused by train. In this paper, railway noise from different type of train are compared using the calculation of sound quality metrics with using strength related method that is calculation of A-weighted sound pressure level.

• 동력기계공학회지
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• 제3권3호
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• pp.97-103
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• 1999

As the noise of ship engine room is too loud, the engineer who works in a ship engine-room has the trouble of hearing. In this paper deals the investigation of the noise of ship engine room and cabins with the internationally allowable noise exposure level and noise exposure time. Recently, the problem of engine-room noise is more serious because of shipowner wants to make small number and larger size of cylinder. Therefore, engineers work in a ship engine-room for a long time have the trouble of hearing when they are exposed the high noise level. In this study, two kinds of vessels were used to investigate the noise of engine room, engine-control room, bridge, offices and cabins. As criteria of sound levels, A-weighted sound pressure level and octave band pressure level were used.

• 콘크리트학회논문집
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• 제15권2호
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• pp.352-359
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• 2003

Portland cement concrete (PCC) pavements are more durable and have superior surface friction compared to most dense-graded asphalt. However, data collected to date generally show PCC pavements to create more noise than asphaltic surfaces. Recent research has shown that some of the new concrete pavement textures are worthy of further examination. One of these, exposed aggregate surfaces, appear to provide better noise quality characteristics as well as good frictional characteristics and durability. In this paper, we considered the relationship between noise level and various textures of exposed aggregate concrete (EAC) pavement by tire impact noise measurement. As the results of that, it was suggested that optimum surface texture and manufacturing condition of EAC in order to reduce tire and pavement interaction noise. Conclusively, we would like to recommend optimum condition of EAC pavement at the respects of materials and treatment. Furthermore, Frequency spectrum as well as A-weighted noise level was also evaluated to analyze properties of noise between PCC and EAC.

• 한국소음진동공학회:학술대회논문집
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• 한국소음진동공학회 2002년도 추계학술대회논문초록집
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• pp.332.2-332
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• 2002

Booming sound is one of the most important interior sound of a passenger car. The conventional booming noise research was focused on the reduction of the A-weighted sound pressure level. However A-weighted sound pressure level can not give the whole story about the booming sound of a passenger car. In this paper, we employed sound metric which is the subjective parameter used in psychoacoustics. (omitted)

• 한국소음진동공학회:학술대회논문집
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• 한국소음진동공학회 2007년도 추계학술대회논문집
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• pp.1191-1196
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• 2007

This research presents a laboratory study about an annoyance of impulsive sound caused by construction site(breaker and blasting). The sources are sampled from outdoor noise and their levels range from 40 to 75 dB at the interval of 5dB. The noise unit is based on A-weighted sound exposure level (ASEL; $L_{AE}$). To make equal ASEL of outdoor noise, finite impulse response (FIR) filter is applied to the originally sampled source to include the effect of distance attenuation. The evaluation method of jury test adopted a Semantic Difference Method (SDM). In the result of the Jury test for impulsive noise, the annoyance response of blasting noise was higher than that of breaker noise.

• 한국산업보건학회지
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• 제1권2호
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• pp.181-191
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• 1991

The present study determined the overall noise level and the distribution of sound pressure level over audible frequency range of noise produced at various work sites. Work-related noise greater than 80dBA produced from 98 separate work sites at 37 manufacturing companies and machine shops were analysed for the overall sound level (dBA) and frequency distribution. In addition, to determine the possible hearing loss related to work site noise, a hearing test was also conducted on 1,374 workers in these work sites. The results of the study were as follows ; 1. Of the total 98 work sites, 57 work sites(58.2%) produced noise exceeding threshold limit value (${\geq}90dBA$) set by the Ministry 01 Labor. In terms of different manufacturing industries the proportion of work sites which exceeded 90dBA was the highest for the cut-stone products industry with 6/6 work sites and lowest for the commercial printing industry with 1/13 work sites. 2. The percentage of workers who were exposed to noise greater than 90dBA was 19.8% (1,040 workers) 01 the total 5,261 workers. In terms of different industries, cut-stone products industry had the most workers exposed to noise exceeding 90dBA with 82.8%, textile bleaching and dyeing industry was next at 30.6% followed by fabricated metal products industry with 27.9%, plastic products manufacturing industry had the lowest percentage of workers exposed to 90dBA exceeding noise with 4.5%. 3. There was a statistically significant correlation between the frequency of noise-induced hearing loss and the percentage of workers exposed to noise exceeding 90dBA (P<0.05). 4. The frequency analysis of noise produced at the 98 work sites revealed that 44 work sites (44.9%) had the maximum sound pressure level at high-frequencies greater than 2KHz. In addition, significantly higher sound pressure level was detected at the high-frequencies at 90dBA exceeding work sites as compared to below 90dBA work sites (P<0.01). 5. The differences in sound level meter's A-and C-weighted sound pressure levels were analysed by frequencies. Of the 28 work sites which showed 0-1 dB difference in the two weighted sound levels, 20 work sites (71.4%) had significantly higher sound pressure levels at high-frequencies greater than 2KHz (P<0.01). Furthermore, there was a tendency for higher sound pressure levels to occur in the high-frequency range as the differences in the two weighted sound levels decreased.

• 한국소음진동공학회:학술대회논문집
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• 한국소음진동공학회 2008년도 춘계학술대회논문집
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• pp.714-720
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• 2008

This research presents a laboratory study about an subjective response of impulsive sound caused by leisure shooting. The sources are sampled from outdoor noise and their levels range from 40 to 75 dB at the interval of 5dB. The noise unit is based on A-weighted sound exposure level (ASEL; $L_{AE}$). To make equal ASEL of outdoor noise, finite impulse response (FIR) filter is applied to the originally sampled source to include the effect of distance attenuation. The evaluation method of the jury test adopted a Semantic Difference(SD) Method. In the result of the jury test for impulsive noise, the mean response rating expressed a linear relation and %HA(percent highly annoyed) displayed a exponential growth relation.

• 대한전자공학회논문지SP
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• 제42권6호
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• pp.73-82
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• 2005

본 논문은 weighted FCM(Fuzzy C-Means) 알고리즘을 적용한 컬러 영상 multi-level thresholding을 제안한다. FCM 알고리즘은 기존의 thresholding 방법들과 달리 최적의 임계치를 결정할 수 있으며 multi-level thresholding으로의 확장이 가능하다. 그러나 공간정보를 포함하고 있지 않기 때문에 잡음 등에 민감하다는 단점을 가진다. 본 논문은 이러한 단점을 해결하기 위해서 이웃 화소들로부터 얻은 entropy 기반의 가중치(weight)를 FCM 알고리즘에 적용함으로써 잡음의 제거가 가능하다. 그리고 각 색상별 성분의 군집 화소들을 기반으로 생성한 코드 영상에 대해서 군집 내부의 거리값을 이용하여 최적의 군집수를 결정한다. 실험에서 제안한 방법이 기존의 방법들보다 잡음에 대해서 강건하며 우수한 분할 성능을 보였다.

• 한국소음진동공학회논문집
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• 제18권7호
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• pp.746-755
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• 2008

This research presents a laboratory study on subjective response of impulsive sound caused by construction site (breaker and blasting). The sources are sampled from outdoor noise and their levels range from 40 to 75 dBA at the interval of 5 dBA. The noise unit is based on A-weighted sound exposure level(ASEL; $L_{AE}$). To make equal ASEL of listening level, finite impulse response(FIR) filter is applied to the originally sampled source to include the effect of propagation attenuation. Sixty-three subjects, forty-two males and twenty-one female, between 18 and 29 years of age, participated in the experiment. The evaluation method of jury test adopted a semantic difference method(SDM). In the test results for impulsive noise, the subjective response of blasting noise was higher than that of breaker noise. The result of %HA that has been combined responses of the three methods except for pink-noise was executed by regression analysis and was shown as the following equation.: $%HA=746.53/(1+{\exp} (L_{AE}-93.3))+0.34$.