题名

探討行動裝置於噪音量測之應用性－以iOS作業系統為例

并列篇名

The Study of Mobile Phone Application in Noise Measurement for iOS system

作者

李昆哲(Kun-Che Lee)；張奕瑞(Yi-Jui Chang)；吳煜庭(Yu-Ting Wu)；邱奕豪(Yi-Hao Ciou)；周芳儀(Fang-Yi Chou)

关键词

智慧型行動裝置 ； 噪音量測應用程式 ； 外接式麥克風 ； Mobile devices ； Noise measurement apps ； External microphone

期刊名称

勞動及職業安全衛生研究季刊

卷期/出版年月

31卷1期（2023 / 03 / 20）

页次

34 - 44

内容语文

繁體中文;英文
中文摘要

作業場所的噪音改善程序包含：認知、評估與控制，其中認知噪音的來源、發生的時間與地點等資訊，可促使管理者評估危害與改善方案，並採取適當的控制措施。本研究係運用智慧型行動裝置普及之優勢，探討應用智慧型行動裝置進行噪音量測之應用性。本研究使用iOS作業系統裝置搭配3款外接式麥克風（Dayton Audio IMM-6, Dayton Audio UMM-6, MiniDSP UMIK-1）及3款噪音量測應用程式（Decibel X, Decibel Sound Meter Pro, NIOSH SLM）於迴響室進行噪音量測實驗，噪音源為60～115 dBA之粉紅噪音（Pink Noise），並以每5 dBA為一級距，所使用之量測裝置於實驗前皆以聲源校正器完成校正程序（校正值為94 dB，頻率為1k Hz純音），並與Class 1及Class 2等級噪音計之量測結果進行比較。本研究所使用之智慧型行動裝置、外接式麥克風及噪音量測應用程式等軟硬體搭配條件下，透過噪音量測實驗結果顯示，於各噪音級距下，不同的軟硬體組合與噪音計量測結果相比，仍會產生不同的量測誤差值。而所獲得之量測結果與Class 1等級噪音計相比，其屬高度相關性（r=0.9 以上），60∼100 dBA噪音級距區間之誤差可≦2 dBA，此結果與Class 2等級噪音計之精準度（±1.5 dB）要求相近似；而與Class 2等級噪音計相比，60～115 dBA噪音級距區間之誤差為2～5 dBA。惟部分情況下，於高噪音級距（110～115 dBA）會產生較大之量測誤差（約9～55 dBA）。
英文摘要

The noise improvement program in the workplace includes the following: recognition, evaluation and control. Recognizing the source of noise, the time and place of occurrence and so forth, enables managers to evaluate hazards and improvement plans and take appropriate control plan. This study makes use of the popularity of smart mobile devices to explore the feasibility of noise measurement using smart mobile devices. In this study, iOS system was used with three external microphones (Dayton Audio IMM-6, Dayton Audio UMM-6, MiniDSP UMIK-1) and three noise measurement applications (Decibel X, Decibel Sound Meter Pro, NIOSH SLM) to conduct noise measurement experiments in the Reverberation Chamber. The noise source was pink noise of 60~115 dBA, and the interval was each 5 dBA. All measurement devices used were calibrated with a sound calibrator before the experiment. Under the conditions of the combination of software and hardware such as smart mobile devices, external microphones, and noise measurement applications used in this study, the experiment results show that in each noise level, different combinations of software and hardware will still produce different measurement error values compared with the measurement results of noise meter. The results are highly correlated (r=0.9 or more) compared with the Class 1 noise meter, and the error in the noise level range of 60~100 dBA can be ≤ 2 dBA. This result is similar to the accuracy(±1.5 dB) requirement of the Class 2 noise meter; compared with the Class 2 noise meter, the error in the noise level interval of 60~115 dBA was 2~5 dBA. However, in some cases, a large error (about 9~55 dBA) will occur at high noise level (110~115 dBA).
主题分类 醫藥衛生 > 預防保健與衛生學
醫藥衛生 > 社會醫學
工程學 > 市政與環境工程
参考文献
  1. (2020).109 年職業傷病防治年報.勞動部職業安全衛生署.
  2. 勞動部勞動統計查詢網，https://statdb.mol.gov.tw/statis/jspProxy.aspx?sys=100&-kind=10&type=1&funid=q0902&rdm=aWBieinp。
  3. 勞動部職業安全衛生署官網，https://tmsc.osha.gov.tw/。
  4. Celestina, M.,Hrovat, J.,Kardous, C. A.(2018).Smartphone-based sound level measurement apps: Evaluation of compliance with international sound level meter standards.Applied Acoustics,139,119-128.
  5. Cheng, T.(2020).Evaluation of Smartphone-based Sound Level Meters.2020 IEEE Integrated STEM Education Conference (ISEC),Princeton, New Jersey, USA:
  6. European Environment Agency. (2013). eyeonearth.org. http://eyeonearth.org/map/Noise-Watch/ (Last viewed June 23, 2013).
  7. Kanhere, S. S.(2013).Participatory sensing: Crowdsourcing data from mobile smartphones in urban spaces.International Conference on Distributed Computing and Internet Technology,Berlin, Heidelberg:
  8. Kardous, C. A.,Shaw, P. B.(2016).Evaluation of smartphone sound measurement applications (apps) using external microphones-A follow-up study.The Journal of the acoustical society of America,140(4),EL327-EL333.
  9. Kardous, C. A.,Shaw, P. B.(2014).Evaluation of smartphone sound measurement applications.The Journal of the Acoustical Society of America,135(4),EL186-EL192.
  10. Maisonneuve, N.,Stevens, M.,Ochab, B.(2010).Participatory noise pollution monitoring using mobile phones.Information polity,15(1, 2),51-71.
  11. Nast, D R.,Speer, W S.,Le Prell, C G.(2014).Sound level measurements using smartphone "apps": useful or inaccurate?.Noise & Health,16(72),251-256.
  12. Roberts, B.,Kardous, C.,Neitzel, R(2016).Improving the accuracy of smart devices to measure noise exposure.Journal of Occupational and Environmental Hygiene,13(11),840-846.
  13. Shahnaz, N,Brown, S(2020).How accurate are these smartphone sound measurement apps?.Audiologist,7(6)
  14. 吳聰能(1988)。影響噪音性聽力損失的其它因素與個人身體特質。工業安全衛生月刊，69，8-18。
  15. 吳聰能,江宏哲(1993)。噪音與聽力損失。工業安全衛生月刊，50，26-37。
  16. 林桂儀,林政佑(2016).評估職場噪音暴露對勞工夜間睡眠品質之影響.新北市:勞動部勞動及職業安全衛生研究所.
  17. 林進基,陳秋蓉,董貞吟,張錦輝,葉文裕,徐儆暉,陳金文,盧士一,黃百粲,林桂儀(2013).勞工聽力保護計畫指引.新北市:行政院勞工委員會勞工安全衛生研究所.
  18. 張錦松,韓光榮(1995).噪音振動控制.臺北市:高立圖書有限公司.
  19. 陳小娟,劉秀丹(1999)。噪音型聽力損失勞工的聽力與溝通問題。特殊教育與復健學報，7，145-181。
  20. 蘇德勝(2000).噪音原理及控制.臺北市:臺隆書店.
print cancel