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    題名: 頻譜分析應用於噪音源辨識之研究
    其他題名: Research on the application of spectral analysis in noise source identification
    作者: 胡友馨;吳志超;楊惠玲;陳劭瑜;李冠廷;江向才;徐湘文
    Hu, Yu-Hsin;Wu, Chih-Chao;Yang, Hui-Ling;Chen, Shao-Yu;Li, Guan-Ting;Chiang, Hsiang-Tsai;Shu, Shung-Wen
    貢獻者: 逢甲大學環境工程與科學學系;逢甲大學環境工程與科學學系;逢甲大學環境科技與智慧研究中心;逢甲大學環境工程與科學學系;逢甲大學環境工程與科學學系;逢甲大學會計學系;台塑企業安衛環中心環境評估處
    Department of Environmental Engineering and Science, Feng Chia University;Department of Environmental Engineering and Science, Feng Chia University;Research Institute for Environmental Intelligence Technologies, Feng Chia University;Department of Environmental Engineering and Science, Feng Chia University;Department of Environmental Engineering and Science, Feng Chia University;Department of Accounting, Feng Chia University;Center for Occupational Safety and Environment Protection, Formosa Plastics Group
    關鍵詞: 噪音源辨識,頻譜分析,交通噪音,自然音源,非人為音源
    noise source identification;spectral analysis;traffic noise;natural-sounds source;non-human sounds
    日期: 2021-06-01
    上傳時間: 2021-11-22 15:03:10 (UTC+8)
    出版者: 南華大學旅遊管理學系;台灣慢遊協會
    摘要: 本研究旨在辨識橋頭小學周邊常見噪音源,由於雲林離島工業區開發和環境影響評估的需求,橋頭國小噪音測站長期進行噪聲監測。由於國小學位於連接離島工業區之154縣道上,其噪音環境品質一直備受關注。為確實掌握其周邊各種可能造成監測值偏高之音源,本研究利用全頻噪音計進行現場噪音偵測,並篩選超標或具有超標潛勢之監測時間點,進行頻譜比對分析,希望藉由音頻的分析,確認可能噪音源,建立音源查找之作業流程,以及常見之生活音源頻譜資料,提供未來音源判定之應用。結果顯示,即使為單一重機行經測站、或2~3聲大型車喇叭聲,皆可能導致該時段之噪音值超標;另自然界之聲音,包含蟬鳴與鳥叫,亦可能導致噪音測值超標,故在掌握監測環境之實質狀況時,利用聲音頻譜進行音源查找,確實有其必要性。
    This research is aimed at the identification of common noise sources around the Ciaotou Elementary School, which has been set noise monitoring station for long-term noise monitoring due to the development of the Yunlin Offshore Industrial Park and the need for environmental impact assessment. Due to the location of Ciaotou Elementary School on the 154 County Road, the main road connect to the Yunlin Offshore Industrial Park, the noise environment quality is always concerned. In order to identify the various noise sources around the school, this study uses a full-frequency noise audiometer to detect the sound spectrum, and selects several monitoring noise time interval that exceed the allowable volume or have the potential beyond the standard to perform spectrum analysis Consequently we can identify possible noise sources by applying audio spectrum analysis. In addition, we can establish an operation process with sound source identification. Furthermore, we proposed the common noise spectrum in our daily life as references for future applications. The study results show that even the traffic noises or natural sounds, such as single heavy motorcycle or cicadas and bird calls, may also cause noise values to exceed the standard. Therefore it is important to apply the sound spectrum to identify the source in the monitoring situation.
    關聯: 環境與管理研究
    22卷
    顯示於類別:[本校期刊] 環境與管理研究
    [旅遊管理學系(旅遊管理碩士班)] 環境與管理研究

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