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| DC 欄位 | 值 | 語言 |
|---|---|---|
| dc.contributor.advisor | 陳琪芳 | zh_TW |
| dc.contributor.advisor | Chi-Fang Chen | en |
| dc.contributor.author | 陳詩婷 | zh_TW |
| dc.contributor.author | Shih-Ting Chen | en |
| dc.date.accessioned | 2026-01-13T16:12:42Z | - |
| dc.date.available | 2026-01-14 | - |
| dc.date.copyright | 2026-01-13 | - |
| dc.date.issued | 2025 | - |
| dc.date.submitted | 2025-12-29 | - |
| dc.identifier.citation | [1] PAME, Underwater Noise in the Arctic: A State of Knowledge Report. PAME Secretariat, 2019.
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Noise pollution filters bird communities based on vocal frequency. PLoS ONE, 2012, 7（11）: e50573. [27] 方銀營. （2011）. 鯨豚聲音偵測研究. 國立臺灣大學工程科學及海洋工程學系學位論文, 1-104. [28] IMO, Guidelines for the Onboard Operational Use of Shipborne Automatic Identification Systems （AIS）. Resolution A.917（22）, 2001. [29] Laye, S.G., IALA. Recommendation A-124 On Automatic Identification System （AIS） Shore Station and Networking Aspect relating to AIS. IALA Document, 2003. [30] Harati-Mokhtari, A., Wall, A., Brooks, P., Wang, J. Automatic Identification System （AIS）: Data Reliability and Human Error Implications. J. Navigation, 2007, 60（3）: 373–389. [31] Wang, T., et al. Big data analytics for improving maritime risk assessment using AIS data. Reliability Engineering & System Safety, 2019, 189: 106–124. [32] Silveira, P.A., Teixeira, A.P., Soares, C.G. Use of AIS data to characterise marine traffic patterns. Reliability Engineering & System Safety, 2013, 115: 1–12. [33] 謝秉勳, 利用 AIS 估算台灣南部海域船舶噪音之可行性探討. 碩士論文, 國立中山大學, 2015. [34] 吳政峰. （2012）. 商船資訊自動化識別於高雄港灣防護技術之應用 （Doctoral dissertation, 撰者）. [35] Bassett, C., Polagye, B., Holt, M., & Thomson, J. A vessel noise budget for admiralty inlet, puget sound, washington （usa）.,2012, Journal of the Acoustical Society of America, 132（6）, 3706-3719. [36] 何聲衛. （2022）. 各類型船舶水下輻射噪音分析. 國立臺灣大學工程科學及海洋工程學系學位論文, 1-61. [37] DeepOcean, 電纜鋪設船Maersk Connector Cable Lay Vessel: Specification Sheet, DeepOcean Group, May 2017. [Online]. Available: https://www.deepoceangroup.com [38] Dong Fang Offshore, 離岸工作支援船Onyx: Vessel Specification Sheet, Dong Fang Offshore, Jan. 2022. [Online]. Available: https://www.dfo.com.tw [39] Topaz Marine, 多功能鋪纜船Topaz Installer: Vessel Specification Sheet, Topaz Energy and Marine, Oct. 2016. [Online]. Available: https://www.topazworld.com [40] Ocean Instruments, SoundTrap ST300 Digital Sound Recorders: STD & HF Models, Ocean Instruments, [Online]. Available: https://www.oceaninstruments.co.nz [41] Wittekind, D.K., A simple model for the underwater noise source level of ships. Journal of Ship production and design, 2014. 30（1）: p. 1-8. [42] Bagheri, M., M. Seif, and H. Mehdigholi, Numerical simulation of underwater propeller noise. Journal of Ocean, Mechanical and Aerospace, Science and Engineering, 2014. 4. [43] Kim, T., et al. Numerical and experimental prediction methods of cavitation noise radiated by underwater propellers. in Proceedings of the 22nd international congress on acoustics. 2016. ICA Buenos Aires. [44] Takinacı, A.C. and T. Taralp, Prediction and simulation of broadband propeller noise. Journal of Marine Science and Technology, 2021. 21（5）: p. 6. [45] Winarno, E., W. Hadikurniawati, and R. Rosso, Location based service for presence system using haversine method. 2017. 1-4. [46] Machin, J. and P. Allan, State-of-the-art jet trenching analysis in stiff clays. 2010. p. 871-876. | - |
| dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/101284 | - |
| dc.description.abstract | 本研究以2022年彰芳外海離岸風場施工期間的三艘工作船（電纜鋪設船Maersk Connector、離岸工作支援船Onyx、多功能鋪纜船Topaz Installer）為對象，利用水下收音機陣列於點位UN1蒐集長達一個月的水下聲音資料，並透過自動識別系統AIS（Automatic Identification System）定位船舶實際通過時間與距離。研究方法包含四大步驟：首先，進行音檔的頻譜圖分析與特徵區段擷取；其次，透過希爾伯特轉換進行包絡解調，強化螺旋槳通過頻率（Blade-Pass Frequency, BPF）訊號的辨識度；再者，設計帶通濾波器過濾背景噪音並正規化訊號；最後以修改後的模擬音源作為模板，進行匹配濾波偵測，評估其在不同距離與背景環境下的有效性。
聲源模擬部分，參考Wittekind及Takinacı文獻所提經驗公式，結合線性相位、傅立葉調變與振幅調變技術，成功生成具時間特徵之模擬聲音訊號。透過匹配濾波器進行實測比對後發現，10公里內為穩定高效的偵測距離區，超過20公里後偵測性能逐漸下降，30公里則接近失效門檻。此外，同一艘船於日夜不同背景噪音條件下的偵測表現亦有顯著差異。 本研究整合聲學模擬與AIS輔助資訊，並透過實地量測資料驗證模擬結果，不僅展現匹配濾波器於水下聲紋偵測的高準確性，也提供日後海洋噪音監測系統設計與風場環評中重要的技術參考與基礎資料。 | zh_TW |
| dc.description.abstract | Three work vessels—Maersk Connector, Onyx, and Topaz Installer—operating near the Changfang offshore wind farm during construction in 2022 were selected as case vessels. One-month continuous underwater acoustic recordings were obtained using the position UN1 hydrophone array, while AIS data provided precise passage times and distances. The methodology comprises four main steps: spectrogram analysis and extraction of characteristic segments; envelope demodulation via the Hilbert transform to enhance blade-pass frequency （BPF） recognition; design of a band-pass filter to suppress background noise and normalize signal amplitude; and matched-filter detection using the processed simulated source as the template, with performance evaluated across varying ranges and ambient conditions.
Source simulation was based on empirical formulas proposed by Wittekind and Takinacı, combining linear-phase filtering, Fourier-based modulation, and amplitude modulation to create time-characterized synthetic signals. Field validation revealed stable, highly efficient detection within 10 km, progressively declining performance beyond 20 km, and near-threshold detection at 30 km. Significant day-night differences in detection efficacy were also observed. By integrating acoustic simulation with AIS-aided field measurements, this work demonstrates the high accuracy of matched-filter techniques for underwater ship-signal detection and offers critical technical insights for future marine noise monitoring system design and environmental impact assessments in offshore wind projects. | en |
| dc.description.provenance | Submitted by admin ntu (admin@lib.ntu.edu.tw) on 2026-01-13T16:12:42Z No. of bitstreams: 0 | en |
| dc.description.provenance | Made available in DSpace on 2026-01-13T16:12:42Z (GMT). No. of bitstreams: 0 | en |
| dc.description.tableofcontents | 誌謝 i
中文摘要 ii Abstract iii 目次 iv 圖次 vi 表次 xi 第一章 緒論 1 1.1 研究目的與動機 1 1.2 文獻回顧 1 1.2.1 船舶噪音 1 1.2.2 聲景 4 1.2.3 自動識別系統（Automatic Identification System, AIS） 6 1.3 論文架構 7 第2章 第二章 量測資料 8 2.1 船隻介紹 8 2.1.1 電纜鋪設船Maersk Connector 8 2.1.2 離岸工作支援船Onyx 9 2.1.3 多功能鋪纜船Topaz Installer 10 2.2 聲學資料 11 2.2.1 聲學記錄儀器 11 2.2.2 聲學音檔 13 2.3 AIS與船舶噪音 14 第3章 第三章 研究方法 15 3.1 音檔時頻分析 15 3.1.1 傅立葉轉換 15 3.1.2 短時傅立葉轉換 16 3.1.3 頻譜圖產生 16 3.2 音檔訊號前處理 21 3.2.1 解調（Demodulation） 21 3.2.2 帶通濾波器（Band Pass Filter） 22 3.2.3 訊號正規化（Normalization） 22 3.3 船舶訊號合成與偵測 23 3.3.1 船舶訊號合成 23 3.3.2 電纜鋪設船Maersk Connector 實際音檔與模擬音檔 25 3.3.3 離岸工作支援船Onyx 實際音檔與模擬音檔 27 3.3.4 多功能鋪纜船Topaz Installer 實際音檔與模擬音檔 29 3.4 匹配濾波器（Matched Filter） 31 3.5 AIS資料處理 31 3.5.1 AIS數據選擇 31 3.5.2 Haversine Formula公式使用 32 第4章 第四章 結果與討論 34 4.1 真實模板之匹配濾波偵測 34 4.2 AIS距離與真實訊號偵測數量分析 36 4.2.1 電纜鋪設船Maersk Connector分析結果 36 4.2.2 離岸工作支援船Onyx分析結果 39 4.2.3 多功能鋪纜船Topaz Installer分析結果 41 4.3 模擬模板之匹配濾波器偵測 44 4.3.1 電纜鋪設船Maersk Connector偵測結果 45 4.3.2 離岸工作支援船Onyx偵測結果 48 4.3.3 多功能鋪纜船Topaz Installer偵測結果 50 4.4 結果 52 第5章 第五章 結論與未來展望 53 5.1 結論 53 5.2 未來展望 53 參考文獻 54 附錄一、電纜鋪設船Maersk Connector偵測結果 57 附錄二、離岸工作支援船Onyx偵測結果 68 附錄三、多功能鋪纜船Topaz Installer偵測結果 76 附錄四、電纜鋪設船Maersk Connector AIS資料 88 附錄五、離岸工作支援船Onyx AIS資料 98 附錄六、多功能鋪纜船Topaz Installer AIS資料 108 | - |
| dc.language.iso | zh_TW | - |
| dc.subject | 匹配濾波器 | - |
| dc.subject | 船舶訊號 | - |
| dc.subject | 空化噪音 | - |
| dc.subject | 自動識別系統 | - |
| dc.subject | 水下聲學 | - |
| dc.subject | Matched Filter | - |
| dc.subject | Ship Noise | - |
| dc.subject | Cavitation Noise | - |
| dc.subject | Automatic Identification System（AIS） | - |
| dc.subject | Underwater Acoustics | - |
| dc.title | 應用匹配濾波器與聲學經驗公式模擬偵測分析船舶運行低頻噪音 | zh_TW |
| dc.title | Application of Matched Filter and Empirical Acoustic Formulas for Simulating and Detecting Low-Frequency Noise from Ship Operations | en |
| dc.type | Thesis | - |
| dc.date.schoolyear | 114-1 | - |
| dc.description.degree | 碩士 | - |
| dc.contributor.oralexamcommittee | 黃維信;方銀營 | zh_TW |
| dc.contributor.oralexamcommittee | Wei-Shin Huang;Yin-Ying Fang | en |
| dc.subject.keyword | 匹配濾波器,船舶訊號空化噪音自動識別系統水下聲學 | zh_TW |
| dc.subject.keyword | Matched Filter,Ship NoiseCavitation NoiseAutomatic Identification System（AIS）Underwater Acoustics | en |
| dc.relation.page | 117 | - |
| dc.identifier.doi | 10.6342/NTU202504839 | - |
| dc.rights.note | 同意授權(全球公開) | - |
| dc.date.accepted | 2025-12-29 | - |
| dc.contributor.author-college | 工學院 | - |
| dc.contributor.author-dept | 工程科學及海洋工程學系 | - |
| dc.date.embargo-lift | 2026-01-14 | - |
| 顯示於系所單位： | 工程科學及海洋工程學系 | |
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