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دانلود مقاله ارائه روش جديد جهت حذف نويز آكوستيكی در يك مجرا

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دانلود مقاله ارائه روش جديد جهت حذف نويز آكوستيكی در يك مجرا

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تعداد صفحات : 105 صفحه

قسمتی از متن :
چكيده
فصل صفر: مقدمه
1
2
فصل اول: مقدمه اي بر كنترل نويز آكوستيكي 7
1-1) مقدمه 8
1-2) علل نياز به كنترل نويزهاي صوتي (فعال و غير فعال) 9
1-2-1) بيماري هاي جسمي 9
1-2-2) بيماري هاي رواني 9
1-2-3) راندمان و كارايي افراد 9
1-2-4) فرسودگي 9
1-2-5) آسايش و راحتي 9
1-2-6 جنبه هاي اقتصادي 10
1-3) نقاط ضعف كنترل نويز به روش غيرفعال 10
1-3-1) كارايي كم در فركانس هاي پايين 10
1-3-2) حجم زياد عايق هاي صوتي 10
1-3-3) گران بودن عايق هاي صوتي 10
1-3-4) محدوديت هاي اجرايي 10
1-3-5) محدوديت هاي مكانيكي 10
1-4) نقاط قوت كنترل نويز به روش فعال 11
1-4-1) قابليت حذف نويز در يك گسترده ي فركانسي وسيع 11
1-4-2) قابليت خود تنظيمي سيستم 11
1-5) كاربرد ANC در گوشي فعال 11
1-5-1) تضعيف صدا به روش غير فعال در هدفون 12
1-5-2) تضعيف صدا به روش آنالوگ در هدفون 13
1-5-3) تضعيف صوت به روش ديجيتال در هدفون 15
1-5-4) تضعيف صوت به وسيله ي تركيب سيستم هاي آنالوگ و ديجيتال در هدفون 16
1-6) نتيجه گيري 17

فصل دوم: اصول فيلترهاي وفقي
18
2-1) مقدمه 19
2-2) فيلتر وفقي 20
2-2-1) محيط هاي كاربردي فيلترهاي وفقي 22
2-3) الگوريتم هاي وفقي 25
2-4) روش تحليلي 25
2-4-1) تابع عملكرد سيستم وفقي 26
2-4-2) گراديان يا مقادير بهينه بردار وزن 28
2-4-3) مفهوم بردارها و مقادير مشخصه R روي سطح عملكرد خطا 30
2-4-4) شرط همگرا شدن به٭ W 32
2-5) روش جستجو 32
2-5-1) الگوريتم جستجوي گردايان 32
2-5-2) پايداري و نرخ همگرايي الگوريتم 35
2-5-3) منحني يادگيري 36
2-6) MSE اضافي 36
2-7) عدم تنظيم 37
2-8) ثابت زماني 37
2-9) الگوريتم LMS 38
2-9-1) همگرايي الگوريتم LMS 39
2-10) الگوريتم هاي LMS اصلاح شده 40
2-10-1) الگوريتم LMS نرماليزه شده (NLMS) 41
2-10-2) الگوريتم هاي وو LMS علامتدار وو (SLMS) 41
2-11) نتيجه گيري 43

فصل سوم: اصول كنترل فعال نويز
44
3-1) مقدمه 45
3-2) انواع سيستم هاي كنترل نويز آكوستيكي 45
3-3) معرفي سيستم حذف فعال نويز تك كاناله 47
3-4) كنترل فعال نويز به روش پيشخور 48
3-4-1) سيستم ANC پيشخور باند پهن تك كاناله 49
3-4-2) سيستم ANC پيشخور باند باريك تك كاناله 50
3-5) سيستم هاي ANC پسخوردار تك كاناله 51
3-6) سيستم هاي ANC چند كاناله 52
3-7) الگوريتم هايي براي سيستم هاي ANC پسخوردار باند پهن 53
3-7-1) اثرات مسير ثانويه 54
3-7-2) الگوريتم FXLMS 57
3-7-3) اثرات فيدبك آكوستيكي 61
3-7-4) الگوريتم Filtered- URLMS 66
3-8) الگوريتم هاي سيستم ANC پسخوردار تك كاناله 69
3-9) نكاتي درباره ي طراحي سيستم هاي ANC تك كاناله 70
3-9-1) نرخ نمونه برداري و درجه ي فيلتر 72
3-9-2) عليت سيستم 73
3-10) نتيجه گيري 74

فصل چهارم: شبيه سازي سيستم ANC تك كاناله
75
4-1) مقدمه 76
4-2) اجراي الگوريتم FXLMS 76
4-2-1) حذف نويز باند باريك فركانس ثابت 76
4-2-2) حذف نويز باند باريك فركانس متغير 81
4-3) اجراي الگوريتم FBFXLMS 83
4-4) نتيجه گيري 85

فصل پنجم: كنترل غيرخطي نويز آكوستيكي در يك ماجرا
86
5-1) مقدمه 87
5-2) شبكه عصبي RBF 88
5-2-1) الگوريتم آموزشي در شبكه ي عصبي RBF 90
5-2-2) شبكه عصبي GRBF 93
5-3) شبكه ي TDNGRBF 94
5-4) استفاده از شبكه ي TDNGRBF در حذف فعال نويز 95
5-5) نتيجه گيري 98

فصل ششم: نتيجه گيري و پيشنهادات
99
6-1) نتيجه گيري 100
6-2) پيشنهادات 101
مراجع I
مراجع

[1] C.Mosquera, J.A.Gomez, F.perez, M. Sobreira, ,,Adaptive IIR Fjlters for Active noise Control, “ Sixth International Congress on Sound and Vibration, 5-8 July 1999, Copenhagen, Denmark.

[2] P.Lveg, “process of silencing sound oscillations,”U.S.Patent 2043416,June 9,1936.

[3] Widrow,B., and S.D.Steans.” Adaptive Signal Processing”,Prentice-Hall, Englewood Cliffs, NJ.1985.

[4] Morgan,”D.R.” Analysis of Multiple Correlation Cancelation Loop With a Filter in the Auxiliary path,”IEEE Trans. on ASSP, Vol. ASSP –28, NO .4, PP. 454-467 August, 1980.

[5] Burgess, J.C.,”Active Adaptive Sound Control in a Duct: A Computer Simulation,”J.Acoust. Soc. Am., Vol. 70, No.3, p.p.715-726, Sept, 1981.

[6] Kuo, SM et al,”Design Of Active noise control systems with the TMS320 family “Texas Instruments, 1996.

[7] Boaz Rafaely,”Active noise Reducing Headser”,http://www.Osee.Net/white papers/paper489. Pdf, 2000.

[8]L.J.Eriksson and M.C.Allie.”System Considerations for Adaptive Modelling Applied to Active Noise Control.”.IEEE International Symposisum on,pp: 2390, Vol. 3, 7-9 JUNE 1988.

[9] Petre Stoica and Torsten Soderstrom,” Statistical Analysis of Music and Subspace Rotation Estimates of Sinusoidal Frequencies”. IEEE Trans. On Signal processing, Vol.39, No.8, August 1991.

[10] oliver Besson and petre Stoccia ,”Analysis of MUSIC and ESPRIT Frequency Estimations for Sinusoidal Signal with Lowpass Envelopes”.IEEE, Trans. On signal processing, Vol.44,No.9, September 1999.

[11] Sen M.kuo and Dennis R.Morgan , ''active noise control : A Tutorial Review , ,, proceeding of the IEEE , Vol.87,no.6,june1999.

[12] Sen M.Kuo and Dennis R.Morgan,”Active Noise Control: A Tutorial Revie
”proceeding,of the IEEE, Vol.87, No.6,June 1999.

[13] E. Bjarnason, “Analysis of the Filtered –X LMS algorithm.”IEEE Trans. On Speech and Audio Processing, 3:504-514,November 1995.

[14] M.Rupp, “Saving Complexity of Modified Filtered-x-LMS and Delayed Update LMS Algorithms.”IEEE Trans. On Circuits and System II, 44:57-60, January 1997.

[15] S.J.Elliott and P.A.Nelson. “Active Noise Control” .IEEE processing PP.12-35,oct.1993

[16] Anjelo J.Campanella,”active Noise control or cancellaction “ , campanella Associates ,2000.

[17] Jacqueline Lamuth ,”noise “, ohio state university fact sheet ,community Development ,1998.

[18] Olson ,H.F.and May,E.G,” electronic sound absorber “ .Journal of the Acoustical Society of America ,25,1130-1136,1953.

[19] E.D.Simshauser and M.E.Hawely .” The Noise Canceling Headset an active ear defender ,” Journal of the acoustical society of America ,27,207,1995.

[20] M.H.Hawley , “ acoustic interference for of noise control ,” Noise control ,2,61,63,1956.

[21] W.F.Meeker,”componenets characteristics for an active ear Defender ,” Journal of the Accoustical society of America ,29,1252,1957.

[22] A. Roure,”Self Adaptive Broadband Active sound control system .” journal of sound and vibration , 101,429-441,1985.

[23] L.J.Eriksoon and M.C Allie , “ Use of Random noise for on-line transducer Modoling in an Adaptive active attenuatuion system ,” journal of the acoustical society of America ,85,797-802,1989.

[24] W.K.Tseng, B,rafaely and S.J.Ellitt,”Combined Feedback – feed forward active control of sound in a room , “ journal of the Acoustival society of America ,104 (6), 3417-3425,1985.

[25] M.Winberg,S.Johansson , T.logo and I. classon ,” A new passive / active hybrid for a helicopter application , “ International journal of acoustics and vibration 4(2),51-58.1999.

[26] C.Carme , “ the third principle of active control : the feed forback , “ Active99 Conference , Ft.Laudaredle 885-896.2-4 December , 1999.

[27] L.J.Ericsson,M.c.Allie , and R.A.greiner . “ The selection and application of IIR adaptive filter for use in active sound attenuation “ . IEEE Trance . on Acoustics , speech and signal processing , ASSP-35:433-437,April 1987.

[28] S.M>kuo and C.chen , “ Implementation of adaptive filters with the Tms30c25 or The TmS32oc30 , “ in digital Signah processing Applications with The TMs320 family , vol . 3,p,pamichalis , Ed.englewood Cliffs , Nj: prentice Hall , ch.7 , pp.191-271,1990.

[29] Alan V.Oppenheim , Ronald W.Schafer , “Discrete_Time signal processing , “ published by prentice_Hall,Inc.Upper saddle River , new jersey 07458,1999.

[30] T.Kailath , “ A View of Three decades of linear Filtering Theory , “ IEEE Trams Inf. Theory , vol.It-20,pp.145-181,mar,1974.

[31] Gibson J.D. “ Backward Adaptive Prediction as spectral Analysis Whithin a closed Loop , “ IEEE Trans . Aeoustics , Speech and signal Processing Vol. ASSp-33,pp.1166-1174.oct.1985.

[32] B.Widrow,J.M.Mc cool , M.G.Larimore , and C.R.Johnson , Jr.” Stationary and No stationary learning Characteristics of LMS Adaptive Filter. “Proc. IEEE. VOL 64,pp1151-1162,Aug.1976.

[33] D.C.Farden ,”Traking properties of Adaptive signal Proccessing Algorithms , “ IEEE Trans.Speech Signal Process,Vol ASSP-29,439.gum.1981.

[34] A.Fever and E,Weinstein., ”Convergence Analysis of LMS Filters with uncorrelated Gaussin data., ”LEEE Trans.,Acoust.,Speech, Singnal Processing. ASSP-33:222-230.Feb.1985.

[35] J.R. Treichler C.R .Johnson. and M.G.Larimore, ”Theory and Design of Adaptive Filters, ”John Wiley & sons.1987.

[36] B.Widrow, J.M.Mc Cool, and M.Ball, ”The Complex LMS Algorithm,Proc.IEEE.63:719-720.Apr.1975

[37] D.C.Swanson. ”A tability Robustness Comparison of Adaptive Feedforward and Feedback Control Algorthms, ”In Proc.Recent Advances in Active Control of Sound Vibration ,P.P.165-168.1991.

[38] M.Miyoshi and Y.Kaneda. ”Inverse Filtering of Room Acoustics, ”.IEEE , Trans Acoust.,Speech,Singnal Processing.(36):145-152.1998.

[39] Shuichi Adachi and Hisashisonal, ”Modeling of Acoustic Field for Feedback Active Noise Control, ”.IEEE Signal Processing magazine ,1999.

[40] Shuichi Adachi and Hisashisonal, ”Active Noise Control System for Automobiles Based on Adeptive and Robust Control, ”Processing of the IEEE,International control Application, P.P.1125-1126,September 1998.

[41] S.D.Synder and C.M.Hansen, ”The Effect of Transfer, ”Function Estimation Errors on the Filtered x LMS Algorithm , ”IEEE Transactions on Signal Processing, Vol.42,P.P.950-953,1994.

[42] D.R.Morgan” An Adaptive Model Based Active Control System. ”Jourmal of The Acoustical Society of America,Vol.89,P.P248-256,1991.

[43] Eriksson,L.J., ”Development of the Filtered U Algorithm for Active Noise control, ”.Acoust.Soc.Am.,Vol.89,No.1,PP.256-265,January,1991.

[44] Lennart Ljung and Suante Gunarsoon, ”Adaptation and Tracking in system Identification A Survey”,Automazine, Vol.26,No.1,PP.7-21,1990.

[45] 1.J.Elliott, M.C.Allie and R.A.Greiner, ” The Selection and Application of an IIR Adaptive Filter for Use in Attenion, ” IEEE Trans. On Acoustics,Speech and Signal Processing,Assp-35,PP.433-437,1987.

[46] M.Takahashi, T.Turbayashi, K.Hamada, T.Enikoda and T.Mura , ” Electric Sound Cancellation in Air_ Conditioning Duct System, ” Proceeding Inter _Noise,PP.607-610,1986.

[47] L.J.Eriksson. ”Active Sound Attenuation Using Adaptive Digital Signal Processing techniques , ”.University of Wisconsin .Madison.1985.

[48] S.J.Elliott and L.Biller, ”Adaptive Control of Flexural Waves Propagating in a beam ”, Journal of Sound and Vibration ,Vol .163,PP.265-310,1993.

[49] Feintuch,P.F., ”An Adaptive Recursive LMS Filter, ” Proc, of IEEE,Vol.64,PP.1622-1624,November 1976.

[50] S.M.Kuo and D.R.Morgan , ”Active Noise Control Systems: Algorithms and Dsp Implementations, ”New York, Wiley ,1996.

[51] S.D.Snyder and N.Tanaka, ”Active Control. Of Vibration Using a Neural Network,IEEE Trans. Networks, Vol.6,No.4,1995.

[52] M.Bochard , B.Pillard and C.T.Le Dinh, ”Improved Training of Neural Networks For the Nonlinerar Active Control of Sound and Vibration , ”IEEE Transaction on Neural Networks,Vol.10,no.2,PP.391-401,Maret 1999.

[53] S.D.Snyder and N.TanaKa, ” Active Control of Vibration Using a Neural Network , ,, IEEE Trans .Neural Network , Vol.6,No.4,1995.

[54] S.Kumpati Narendra and Snehasis Mukhopadhyay , ,,Adaptive control using netrral Networks and Approximate Models , ,, IEEE Trasactions on Netural Networks, vol.8,No.3,PP.475-485,May,1997.

[55] R.Bambang , ,,Active Cancellation Using Recurrent Radial Basis Function Neural Networks , ,, IEEE , Asia-Pcific Conference on , vol.2,PP.231-26A,28-31 Oct,2002.

[56] M.R.Berthold , ,, A Time Delay Radial Basis function network for phoneme recognition , ,, IEEE International conference on neural network , vol.7,PP.4470-4473,1994.

[57] S.Haykin , ,, neural networks a comprehensive foundation , ,, Macmillan college publishing company , inc .1994.

[58] Seng kah phooi,man zhihong,h.r.wu , ,, nonilinear active noise control using lyapunov theory , and RBF network , ,, IEEE, Neural networks for signal processing , vol.2,PP.916-925,11-13 Dec.2000.

[59] I.Gath, A.B.Geua, " Unsupervised Optimal Fuzzy Clustering , " Pattern Analysis and Machine Intelligence, IEEE Trans.on, Vol.11,PP:773-780,7 July, 1989.

[60] J.Bezdek, R.Ehrlich and W.Full, " FCM: The Fuzzy c-means Clustring algorithm" Cornnput Geo sci, Vol.10,PP.191-203,1984.

[61] N. Watanabe , T. Imaizumi , "Fuzzy K-Mean Clustering with Crisp Regions, " The 10th IEEE International Conference on, Vol.1,PP.199-202,2-5 Dec, 2001.

[62] J. Dobsa, B.D. Basic , " Concept Decomposition by Fuzzy k-means Algorithm" IEEE/WIC International conference on, PP.684-688, Oct, 2003.

Abstract
In acoustic noise cancelling, Active and Passive methods are used. Inspite of Passive method, Active method can cancel or reduse noise in low frequencies. In Active method a type of adaptive filter is used. FXLMS Algorithm is know as a basic way because of good tracking in a noisy space, but can be used just in linear control problems. That means in variable frequency noise or nonlinear control systems, it diverges or doesn't work.
In this thesis, At first a kind of FXLMS Algorithm which has the ability of noise canceling in a duct at the time is introduced. Because of that an optimum adaptive step size in FXLMS Algorithm is used. Arange of optimal step size at special frequencies (200-500HZ) in a duct is calculated to it as a spline curve. The frequency of input signal with MUSIC Algorithm is guessed and optimum step size predicted from spline curve and can be put in FXLMS Algorithm to make it converge at the least time. It can be shown that general FXLMS with constant step size diverges by changing the frequency. There fore it is possible to track variable frequency by the new method of this study.

Having nonlinear properties, in Acoustic Noise canceling systems, a kind of RBF neural network (TDNGRBF) has been studied that is able to model nonlinear behaviours. Therefore it is used to cancel narrowband variable frequency noise in a duct and comparison with FXLMS Algorithm. This new method in comparison with FXLMS Algorithm has higher speed and less error, with out estimating secondary path. To cancel noise with TDNGRBF, at first a duct is studied by a GRBF neural network. Then by the use of N number of time delay from input signal, N number of networks GRBF with output linear composition, it will be possible to know nonlinear systems on – line. Coefficions used in linear compositions is optimized by NLMS Algorithm.

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