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  1. NTU Theses and Dissertations Repository
  2. 電機資訊學院
  3. 電機工程學系
請用此 Handle URI 來引用此文件: http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/43499
完整後設資料紀錄
DC 欄位值語言
dc.contributor.advisor蔡坤諭
dc.contributor.authorChao-Wen Huangen
dc.contributor.author黃昭文zh_TW
dc.date.accessioned2021-06-15T02:22:29Z-
dc.date.available2015-02-24
dc.date.copyright2010-02-24
dc.date.issued2009
dc.date.submitted2009-08-18
dc.identifier.citation[1] 戎凱 官文霖 蘇水灶 1999 黑盒子解讀能量之建立與飛安之關係 民航季刊 第一卷 第一期
[2] 莊禮彰 官文霖 蘇水灶 2007 座艙語音記錄器之整合與應用 2007航太學術研討會
[3] Office of Research and Engineering Office of Aviation Safety 2000 Flight Data Recorder Handbook for Aviation Accident Investigation (Washington DC: National Transportation Safety Board)
http://www.ntsb.gov/Aviation/Manuals/FDR_Handbook.pdf
[4] Office of Research and Engineering Office of Aviation Safety 2001 Cockpit Voice Recorder Handbook for Aviation Accident Investigation (Washington DC: National Transportation Safety Board)
http://www.ntsb.gov/Aviation/Manuals/CVR_Handbook.pdf
[5] U.S. Government Printing Office 2009 Code of Federal Regulations 14CFR135.152 (Washington DC: GPO Access) pp 675-8
[6] Thiele H H K 1995 Audio Engineering in Field of Aviation Security Preprints Audio Engineering Society
[7] Stearman R O, Schulze G H and Rohre S M 1997 Aircraft damage detection from acoustic and noise impressed signals found by a cockpit voice recorder J. Acoust. Soc. Am. 101 3085
[8] Xiao X, Yao H and Guo C 2009 Automatic detection of alarm sounds in cockpit voice recordings Proceedings of the IITA ICCASE 00 599-602
[9] ARINC 2009 767-1 Enhanced airborne flight recorder
[10] EUROCAE 2003 ED-112 Minimum operational performance specification for crash protected airborne recorder systems
[11] U.S. Government Printing Office 2009 Code of Federal Regulations 14CFR29.1457 (Washington DC: GPO Access) pp 793-4
[12] U.S. Government Printing Office 2009 Code of Federal Regulations 14CFR121.471 (Washington DC: GPO Access) pp 456-7
[13] Fang B T 1986 Trilateration and extension to global positioning system navigation J. Guidance 9 715-7
[14] Manolakis D E 1996 Efficient Solution and Performance Analysis of 3-D Position Estimation by Trilateration IEEE Trans. Aerosp. Elect. Syst. ASSP-35 8
[15] James Bao-Yen Tsui 2000 Fundamentals of Global Positioning System Receivers: A Software Approach (New York, NY: John Wiley & Sons, Inc.)
[16] Lee K W, Park J B and Lee B H 2008 Dynamic localization with hybrid trilateration for mobile robot in intelligent space Intel Serv Robotics 1 221-35
[17] Tinos R, Navarro-Serment L E and Paredis C J J 2001 Fault tolerant localization for teams of distributed robots Proc. IEEE/RSJ Int. Conf. Intel-ligent Robots and Systems 2 1061-66
[18] Lee H B 1975 A novel procedure for assessing the accuracy of hyperbolic multilateration systems IEEE Trans. Aerosp. Elect. Syst. AES-11 2–15
[19] Schau H C and Robinson A Z 1987 Passive source localization employing intersecting spherical surfaces from time-of-arrival differences IEEE Trans. Acoust. Speech Signal Processing ASSP-35 1223-25
[20] Zhang D, Rolt S and Maropoulos P G 2005 Modelling and optimization of novel laser multilateration schemes for high-precision applications Meas. Sci. Technol. 16 2541-7
[21] Petrochilos N, Galati G and Piracci E 2009 Separation of SSR signals by array processing in multilateration systems IEEE Trans. Aerosp. Elect. Syst. 45 965-82
[22] Bock O, Thom C, Kasser M and Pelon J R 1999 Multilateration with the wide-angle laser ranging system: ranging performance and first ground-based validation experiment IEEE Trans. Geosci. Remote Sensing 37 739-47
[23] Brandstein M S, Adcock J E and Silverman H F 1997 A closed-form location estimator for use with room environment microphone arrays IEEE Trans. Speech and Audio Processing 5 45-50
[24] Chen Y C and Hsiao F B 2004 The study of aircraft cockpit sound sources localization Master thesis Institute of Aeronautics and Astronautics National Cheng Kung University
[25] The Boeing Company 1999 767-31A/-3Z9 Operations Manual (Chicago, IL: The Boeing Company)
[26] HoneyWell ED-56a voice recording system solid-state cockpit voice recorder (SSCVR) product description available at http://www.honeywell.com/aero/.
[27] L-3 Communications FA2100 cockpit voice and data recorder (CVDR) product description available at http://www.l-3com.com/.
[28] Oppenheim A V, Willsky A S and Hamid Nawab S 1997 Signal & Systems (New Jersey; Prentice Hall) pp 167-8
[29] Knapp C H 1976 The generalized correlation method for estimation of time delay IEEE Trans. Acoust. Speech Signal Processing ASSP-24 320-7
[30] Atmoko H, Tan D C, Tian G Y and Fazenda B 2008 Accurate sound source localization in a reverberant environment using multiple acoustic sensors Meas. Sci. Technol. 19 1-10
[31] Spence L E, Insel A J and Friedberg S H 2000 Elementary linear algebra (New Jersey: Prentice Hall) pp 323-7
[32] Spiesberger J L 2001 Hyperbolic location errors due to insufficient numbers of receivers J. Acoust. Soc. Am. 109 3067-79
[33] Pandey S and Agrawal P 2006 A survey on localization techniques for wireless networks J. Chin. Inst. Eng. 29 1125-48
[34] MATLAB is a commericial product available from The Mathworks Inc. Online information is available at http://www.mathworks.com/
dc.identifier.urihttp://tdr.lib.ntu.edu.tw/jspui/handle/123456789/43499-
dc.description.abstract分析座艙語音紀錄器(Cockpit Voice Recorder, CVR)的資料對於大部分的飛航事故調查來說是最重要的一個步驟。透過語音或是其他音訊的辨識,人為以及非人為的因素如通訊溝通錯誤、違反標準操作程序、機艙損壞以及警報聲響的種類都能被判斷出來。然而,要辨別出位於不同位置的相同種類開關是很困難的。傳統的聲源定位方式需要最少四支麥克風所測量出來的抵達時間差(Time Difference of Arrival, TDOA)才能進行定位,但是在座艙內通常只有三支麥克風的聲音會被錄進座艙語音紀錄器之中。因此在此提出了兩種方法,利用對座艙環境的已知來越過由麥克風數目所造成的限制。Multilateration with insufficient sensors (MLATIS)利用trilateration求得由抵達時間差及麥克風位置算出的兩個雙曲面的交線,再以此交線和以知的開關分布平面求交點,則此交點就是MLATIS所辨識出的聲源位置。Source identification by location lookup table (SI-LLT)事先對於每個開關的抵達時間差的建立數據表,在以此和測得的抵達時間差做比對以辨識可能的開關位置。接著以蒙地卡羅模擬(Monte Carlo simulation)來分析取樣頻率與駕駛員所配戴的麥克風的位置不確定性對於辨識準確度的影響。最後,以初步實驗的結果驗證模擬所預測出來的趨勢的確與實驗相符合。zh_TW
dc.description.abstractAnalysis of the cockpit voice recorder (CVR) data retrieved from black box flight recorders is critical to most aviation accident investigations. By speech or signal recognition techniques in some form, anthropogenic and non-anthropogenic factors such as vocal communication errors, violation of standard operating procedures, fuselage damage, and alarm classification can be inspected. However, identification of activated switches in a cockpit is difficult because there are same types of switches at different locations. Conventional source localization algorithms cannot be used because they require at least four time-difference-of-arrival (TDOA) sensors while usually there are only three microphone signals recorded in a CVR. In this thesis, two methods to overcome this constraint by exploited a priori cockpit geometry information are proposed. Multilateration with insufficient sensors (MLATIS) estimates source locations by intersecting a two-hyperboloid curve derived from estimated TDOAs and modified trilateration with a known switch distribution surface. Source identification by location lookup table (SI-LLT) identifies an activated switch by comparing the estimated TDOA to a TDOA table based on known switch locations. Impacts of sampling rates and uncertain headset microphone positions on identification accuracy are analyzed by Monte Carlo simulation techniques. Preliminary experimental results verify some of the trends predicted by simulations.en
dc.description.provenanceMade available in DSpace on 2021-06-15T02:22:29Z (GMT). No. of bitstreams: 1
ntu-98-J95921029-1.pdf: 3527439 bytes, checksum: c72cb84bd3f1aa9eed0603690e7b5f44 (MD5)
Previous issue date: 2009
en
dc.description.tableofcontents中文摘要 2
Abstract I
Statement of Contributions II
誌謝 III
Table of Contents IV
List of Figures VI
List of Table VIII
Chapter 1 Introduction 1
Chapter 2 Simulation Conditions 5
2.1 Cockpit geometry information 5
2.2 CVR data assumptions 6
Chapter 3 Time Difference of Arrival Estimation 9
Chapter 4 Sound Source Localization and Identification with Three Microphones 11
4.1 Multilateration with insufficient sensors (MLATIS) 11
4.2 Source identification by location lookup table (SI-LLT) 21
Chapter 5 Simulations and Results 23
5.1 Switch identification with microphones at default positions 23
5.2 Switch identification with uncertain headset microphone displacements 26
Chapter 6 Preliminary Experiments 35
Chapter 7 Conclusions and Discussion 40
Appendix A: Influence of different standard deviations 43
References 45
dc.language.isoen
dc.subject抵達時間差 (TDOA)zh_TW
dc.subject聲源定位、座艙通話紀錄器(CVR)zh_TW
dc.subjecttrilaterationzh_TW
dc.subjectcockpit voice recorder (CVR)en
dc.subjectsound source localizationen
dc.subjecttime difference of arrival (TDOA)en
dc.subjecttrilaterationen
dc.title以座艙通話紀錄器資料及座艙環境資訊進行飛安事故調查之操作開關辨識zh_TW
dc.titleActivated Switch Identification from Cockpit Voice Recorder Data and Cockpit Geometry Information for Aviation Accident Investigationen
dc.typeThesis
dc.date.schoolyear97-2
dc.description.degree碩士
dc.contributor.oralexamcommittee顏家鈺,陳永耀,莊禮彰
dc.subject.keyword聲源定位、座艙通話紀錄器(CVR),trilateration,抵達時間差 (TDOA),zh_TW
dc.subject.keywordsound source localization,cockpit voice recorder (CVR),trilateration,time difference of arrival (TDOA),en
dc.relation.page48
dc.rights.note有償授權
dc.date.accepted2009-08-19
dc.contributor.author-college電機資訊學院zh_TW
dc.contributor.author-dept電機工程學研究所zh_TW
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