現在位置首頁 > 博碩士論文 > 詳目
論文中文名稱:應用小波與經驗模式分解於主動式噪音控制 [以論文名稱查詢館藏系統]
論文英文名稱:Application of Wavelet and Empirical Mode Decomposition to Active Noise Control [以論文名稱查詢館藏系統]
院校名稱:臺北科技大學
學院名稱:機電學院
系所名稱:機電整合研究所
畢業學年度:99
出版年度:100
中文姓名:陳垣圻
英文姓名:Yuan-chi Chen
研究生學號:97408001
學位類別:碩士
語文別:中文
口試日期:2011-01-31
論文頁數:51
指導教授中文名:蕭俊祥
口試委員中文名:李春穎;盧士一
中文關鍵詞:主動噪音控制FXLMS演算法小波希爾伯特黃轉換經驗模式分解迴授式主動減噪
英文關鍵詞:Active Noise ControlFXLMS AlgorithmWaveletHilbert-Huang TransformEmpirical Mode DecompositionFeedback Active Noise Control
論文中文摘要:研究應用小波與經驗模式分解於回授式主動管路減噪系統,可在誤差訊號受到白雜訊或週期雜訊之干擾下,仍可有效降低噪音。主動噪音控制管路系統中第二路徑行為(即控制聲源)以FIR 或IIR濾波器代表,並以系統鑑別得到。控制器取為FIR濾波器,其權重由Filtered-X LMS演算法線上調整而得。本研究在誤差訊號中加入雜訊、回授路徑中加入多種數位訊號處理技術,包含低通濾波器、小波,與經驗模式分解,對誤差訊號進行處理並進行雜訊濾除,再經由控制器輸出反噪音,達到減噪之成效。經電腦模擬可發現,在誤差訊號受到白雜訊或複頻週期雜訊之干擾下,加入了訊號處理技術的減噪系統,較傳統FXLMS演算法的減噪系統,有更佳的性能。除電腦模擬外,本研究藉由數位訊號處理套件TMS320C6713 DSK進行理論之實現。由實驗可驗證電腦模擬之結果;在誤差訊號受到複頻週期雜訊之干擾下,FXLMS結合小波演算法的減噪效果明顯比傳統的FXLMS演算法佳。
論文英文摘要:In this paper, a feedback active duct noise control with wavelet and empirical mode decomposition method is proposed for effectively reducing the duct noise when the error signals are contaminated by white noise or periodic noise. In ANC system, the secondary path system dynamics was identified by an FIR or IIR filter and the coefficients of FIR controller were tuned by the FXLMS algorithm. In this paper, the error signals are contaminated by white noise or periodic noise. Then the contaminated error signal was denoised by several digital signal processing techniques such as using low pass filter, wavelet, and empirical mode decomposition. After that, the signal processed was then input to the FIR controller for producing the anti-noise. By computer simulation results, we found that when the error signals are contaminated by white noise or periodic noise, the performance of an active noise control system with some digital signal processing techniques is more excellent than the one without. In addition, a TI TMS320C6713 DSP card is employed for executing the control algorithms in a duct noise attenuation experiment when the error signal is contaminated by periodic noise. It is verified that the controller with wavelet filtering has much better duct noise reduction performance than the one without, and the one using low pass filter.
論文目次:中文摘要 i
英文摘要 ii
誌謝 iii
目錄 iv
表目錄 vi
圖目錄 vii
第一章 緒論 1
1.1 前言 1
1.2 聲學簡介 2
1.2.1 聲波 2
1.2.2 聲壓 3
1.2.3 聲功率 3
1.2.4 聲強 3
1.3 研究動機 4
1.4 文獻回顧 4
第二章 控制理論與訊號處理技術 8
2.1主動式噪音控制 8
2.2小波分析 8
2.2.1 窗函數 9
2.2.2 積分小波轉換 10
2.2.3 離散小波轉換 12
2.2.4 多解析度空間 13
2.2.5 小波的分解與重建 15
2.3 希爾伯特黃轉換 16
2.4 經驗模式分解 17
第三章 管路減噪系統模擬 21
3.1 模擬簡介 21
3.2 白雜訊干擾下之減噪性能比較 23
3.3 雙頻週期雜訊干擾下之減噪性能比較 26
3.4 四頻週期雜訊干擾下之減噪性能比較 30
3.5 程式模擬結果討論 33
第四章 實驗設備與控制流程 35
4.1 實驗架構簡介 35
4.2 實驗設備介紹 35
4.2.1 壓克力管路 35
4.2.2 TMS320C6713 DSK 36
4.2.3 TMS320C67x DSP函式庫 39
4.2.4 Rion NL-20噪音計 40
4.3 實驗環境 41
4.4 控制流程 42
第五章 實驗結果 44
5.1 實驗步驟 44
5.2 實驗結果 44
第六章 結論與展望 47
6.1 結論 47
6.2 未來展望 47
參考文獻 49
作者簡介 51
論文參考文獻:[1] S. M. Kuo and D. R. Morgan, Active Noise Control Systems—Algorithms and DSP Implementations, New York: Wiley, 1996.
[2] 黃玠理、蕭俊祥,以TI TMS320C6713 DSP實現卡爾曼濾波器於主動式管路減噪,碩士論文,國立臺北科技大學,臺北,2008.
[3] P. Babu, A. Krishnan and V. Saravanan, “A New Variable Threshold Based Active Noise Control Systems for Improving Performance”, International Conference on Advances in Computer Engineering, Bangalore, India, 2010, pp.100-104.
[4] Norden E. Huang and Samuel S. Shen, Hilbert-Huang Transform and Its Applications, Singapore: World Scientific, 2005, pp.1-24.
[5] Q. Shen and A. Spanias, "Time and frequency domain X-block LMS algorithms for single channel active noise control," Second International Congress on Recent Developments in Air- and Structure-Borne Sound and Vibration, Auburn, Alabama, 1992, pp. 353–360.
[6] K. M. Reichard and D. C. Swanson, “Frequency-domain implementation of the filtered-X algorithm with on-line system identification,” Second Conference on Recent Advances in Active Control of Sound and Vibration, Blacksburg, Virginia, 1993, pp. 562–573.
[7] S.M.Kuo and D.R.Morgan, "Active Noise Control: A Tutorial Review," Proceedings of the IEEE, vol.87, Issue 6, June 1999, pp.943-973.
[8] N. Chatlani and J. J. Soraghan, “Adaptive Empirical Mode Decomposition for Signal Enhancement with Application to Speech”, IEEE International Conference on Systems, Signals and Image Process- ing IWSSIP, Bratislava, Slovak Republic, 2008, pp.101-104.
[9] Michel Misiti, Yves Misiti, Georges Oppenheim and Jean-Michel Poggi, Wavelets and their Applications, London: ISTE Limited, 2003
[10] 黃雪珠、王昭男,基於小波轉換之語者識別分析,碩士論文,國立台灣大學,臺北,2003
[11] Charles K. Chui, An Introduction to Wavelets, Boston: Academic Press, 1992.
[12] Albert Boggess and Francis J. Narcowich, A First Course in Wavelets with Fourier Analysis, New Jersey: Prentice-Hall, Inc., 2001, pp.172-182
[13] G. Gai, “The processing of rotor startup signals based on empirical mode decomposition,” Mechanical Systems and Signal Processing, Vol. 20, 2006, pp. 222-235.
[14] Spectrum Digital, Incorporated, TMS320C6713 DSK Technical Reference, 506735-0001 Rev. B, 2004
[15] Texas Instruments, TMS320C6000 DSP Multichannel Buffered Serial Port (McBSP) Reference Guide, 2006
[16] Texas Instrument, TMS320C67x DSP Library Programmer's Reference Guide, 2005
論文全文使用權限:不同意授權