• Title/Summary/Keyword: A-weighting Sound Pressure Level

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Comparison of Rating Methods for the Floor Impact Sound Insulation Performance (바닥충격음 차단성능 평가방법의 상호비교)

  • Kim, Kyoung-Woo;Choi, Hyun-Jung;Yang, Kwan-Seop;Lee, Seung-Eon
    • Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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    • 2005.05a
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    • pp.291-294
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    • 2005
  • In this study, we compared and analyzed the floor impact sound insulation performance produced by the rating methods. The rating methods are using reversed A-weighting curve, A-weighted sound pressure levels and arithmetic average. On-site floor impact sound pressure levels of living room and room are measured. The results of this study are 1)the rating using reversed A-weighting curve for heavy-weight impact sound's standard deviation is lower than that of light-weight impact sound, 2)the number of rating using A-weighted sound pressure levels and arithmetic average is larger than that of using reversed A-weighting curve, and 3)the number of rating using reversed A-weighting curve mainly depends on impact sound pressure level of 63Hz in heavy-weight impact sound.

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Comparison of Rating Methods for the Floor Impact Noise (바닥충격음 평가방법 중 단일수치평가량과 dB(A) 비교)

  • Park, Cheol-Yong;Jang, Dong-Woon
    • Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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    • 2006.11a
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    • pp.612-615
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    • 2006
  • In this study, we compared and analyzed the floor impact noise insulation performance produced by the rating methods. The rating methods are using reversed A-weighting curve, A-weighted sound pressure levels(dB(A)). The results of this study are(1)dB(A) by the specified frequency is 0.5dB(A) at light weight and 2.5dB(A) at heavy weight upper than all pass dB(A)(2)the rating using reversed A-weighting curve is 5dB lower than dB(A)(3)the number of rating using reversed A-weighting curve mainly depends on impact noise pressure level of 63Hz in heavy weight but dB(A) does not.

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A Study on the Prediction & Transformation of Blasting Noise for Environmental Regulation Standard (발파소음의 예측기법과 환경규제 기준으로의 변환 연구)

  • 김남수;양형식
    • Explosives and Blasting
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    • v.18 no.2
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    • pp.14-22
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    • 2000
  • The estimation of proper prediction method and the alteration of transformation method of environmental regulation standard were carried out by measuring blasting noise in construction field. The correlation of scaled distance with sound pressure level were better than with sound level, but it was proved to be difficult to control blasting noise because the correlation factor was too 1ow. three methods to transform sound pressure levee to sound level were examined. The method is the transformation by correlation equation of sound pressure level and sound level which are measured at the same time, and simplified transformation of A-weighting network corresponding to dominant frequency, and the transformation of sound pressure level by FFT. There were many errors to transform. The best effective method is the transformation using correlation equation of sound pressure level and sound level which are measured at the same time.

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Design and Implementation of an Indoor Particulate Matter and Noise Monitoring System (실내 미세먼지 및 소음 모니터링 시스템 설계 및 구현)

  • Cho, Hyuntae
    • IEMEK Journal of Embedded Systems and Applications
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    • v.17 no.1
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    • pp.9-17
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    • 2022
  • As the COVID-19 pandemic situation worsens, the time spent indoors increases, and the exposure to indoor environmental pollution such as indoor air pollution and noise also increases, causing problems such as deterioration of human health, stress, and discord between neighbors. This paper designs and implements a system that measures and monitors indoor air quality and noise, which are representative evaluation criteria of the indoor environment. The system proposed in this paper consists of a particulate matter measurement subsystem that measures and corrects the concentration of particulate matters to monitor indoor air quality, and a noise measurement subsystem that detects changes in sound and converts it to a sound pressure level. The concentration of indoor particulate matters is measured using a laser-based light scattering method, and an error caused by temperature and humidity is compensated in this paper. For indoor noise measurement, the voltage measured through a microphone is basically measured, Fourier transform is performed to classify it by frequency, and then A-weighting is performed to correct loudness equality. Then, the RMS value is obtained, high-frequency noise is removed by performing time-weighting, and then SPL is obtained. Finally, the equivalent noise level for 1 minute and 5 minutes are calculated to show the indoor noise level. In order to classify noise into direct impact sound and air transmission noise, a piezo vibration sensors is mounted to determine the presence or absence of direct impact transmitted through the wall. For performance evaluation, the error of particulate matter measurement is analyzed through TSI's AM510 instrument. and compare the noise error with CEM's noise measurement system.

A Design Method for Direction Selective Structural-acoustic Coupled Radiator (구조-음향 연성현상을 갖는 방사 방향을 가질 수 있는 방사체 설계방법)

  • Seo, Hee-Seon;Kim, Yang-Hann
    • Transactions of the Korean Society for Noise and Vibration Engineering
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    • v.15 no.2 s.95
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    • pp.225-231
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    • 2005
  • This paper presents a design method for the structural-acoustic coupled radiator that can emit sound in the desired direction. A coupled system that has a finite space and a semi-infinite space separated by two flexible walls and an opening is considered. An objective function is selected to maximize radiation power on a main axis and minimize a side lobe level. To get initial values, prediction of a pressure distribution on field points and radiation pattern of the structural-acoustic coupling system is shown at a coupled-resonant frequency. Three different optimization methods are adapted to design the coupled radiator. Pressure and intensity distribution of the designed radiator is presented.

Evaluation of a Traffic Noise Predictive Model for an Active Noise Cancellation (ANC) System (능동형 소음저감 기법을 위한 도로교통소음 예측 모형 평가 연구)

  • An, Deok Soon;Mun, Sung Ho;An, Oh Seong;Kim, Do Wan
    • International Journal of Highway Engineering
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    • v.17 no.6
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    • pp.11-18
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    • 2015
  • PURPOSES : The purpose of this thesis is to evaluate the effectiveness of an active noise cancellation (ANC) system in reducing the traffic noise level against frequencies from the predictive model developed by previous research. The predictive model is based on ISO 9613-2 standards using the Noble close proximity (NCPX) method and the pass-by method. This means that the use of these standards is a powerful tool for analyzing the traffic noise level because of the strengths of these methods. Traffic noise analysis was performed based on digital signal processing (DSP) for detecting traffic noise with the pass-by method at the test site. METHODS : There are several analysis methods, which are generally divided into three different types, available to evaluate traffic noise predictive models. The first method uses the classification standard of 12 vehicle types. The second method is based on a standard of four vehicle types. The third method is founded on 5 types of vehicles, which are different from the types used by the second method. This means that the second method not only consolidates 12 vehicle types into only four types, but also that the results of the noise analysis of the total traffic volume are reflected in a comparison analysis of the three types of methods. The constant percent bandwidth (CPB) analysis was used to identify the properties of different frequencies in the frequency analysis. A-weighting was applied to the DSP and to the transformation process from analog to digital signal. The root mean squared error (RMSE) was applied to compare and evaluate the predictive model results of the three analysis methods. RESULTS : The result derived from the third method, based on the classification standard of 5 vehicle types, shows the smallest values of RMSE and max and min error. However, it does not have the reduction properties of a predictive model. To evaluate the predictive model of an ANC system, a reduction analysis of the total sound pressure level (TSPL), dB(A), was conducted. As a result, the analysis based on the third method has the smallest value of RMSE and max error. The effect of traffic noise reduction was the greatest value of the types of analysis in this research. CONCLUSIONS : From the results of the error analysis, the application method for categorizing vehicle types related to the 12-vehicle classification based on previous research is appropriate to the ANC system. However, the performance of a predictive model on an ANC system is up to a value of traffic noise reduction. By the same token, the most appropriate method that influences the maximum reduction effect is found in the third method of traffic analysis. This method has a value of traffic noise reduction of 31.28 dB(A). In conclusion, research for detecting the friction noise between a tire and the road surface for the 12 vehicle types needs to be conducted to authentically demonstrate an ANC system in the Republic of Korea.