Please use this identifier to cite or link to this item: http://hdl.handle.net/11455/2103
標題: 受制於干擾之寬頻主動式噪音控制系統
Wideband Active Noise Control Systems subject to Disturbance
作者: 莊謦鴻
Chuang, Ching-Hung
關鍵字: active noise control (ANC);主動噪音控制;online model;neural network (NN);disturbance;線上鑑別;類神經網路;干擾
出版社: 機械工程學系所
引用: [1] Lueg, P., “Process of Silencing Sound Oscillations”, U.S. Patent, No.2043416, June 1936. [2] Chang, C.-Y. and Shyu, K.-K., “Active Noise Cancellation with a Fuzzy Adaptive Filtered-X Algorithm”, IEE Proceedings, Circuits, Devices and Systems, Vol. 150, pp. 416-422, October 2003. [3] Snyder, S. D., and Tanaka, N., “Active Control of Vibration Using a Neural Network”, IEEE Trans. Neural Networks, Vol. 6, No. 4, pp. 819-828, July 1995. [4] Chen, C. K., Chiueh, T.-D. and Chen, J.-H., “Active Cancellation System of Acoustic Noise in MR Imaging”, IEEE Trans. Biomedical Engineering, Vol. 46, No. 2, pp. 186-191, February 1999. [5] 周俊弘,管道聲場之類神經網路控制,國立台灣大學工程科學及海洋工程學研究所,碩士論文,2003。 [6] 黃靜宜,狹帶延遲類神經網路於主動噪音控制之應用,國立中興大學機械工程研究所,碩士論文,2006。 [7] Ching-Wen Liao, Jong-Yih Lin, “New FIR filter-based adaptive algorithms incorporating with commutation error to improve active noise control performance”, automatica, ScienceDirect, Vol. 43, pp. 325 – 331, 2007. [8] S. M. Kuo and M. Ji, “Passband disturbance reduction in periodic active noise control systems,” IEEE Trans. Speech Audio Process, Vol. 4, No. 2, pp. 96–103, March 1996. [9] Xu Sun and Sen M. Kuo, “Active Narrowband Noise Control Systems Using Cascading Adaptive Filters” IEEE Transactions on Audio, Speech, and Language Processing, Vol. 15, No. 2, February 2007. [10] S. M Kuo and D. R Morgan, “Active Noise Control System: Algorithms and DSP Implementations”, 605 Third Avenue, New York, 10158-0012, 1996. [11] 羅華強,類神經網路-MATLAB的應用,清蔚科技,2001。
摘要: 
在實際的主動噪音控制(ANC)系統應用中,干擾訊號的存在會破壞系統的性能。本文提出了利用FXNBP/CED演算法來解決干擾對應用類神經網路之寬頻主動噪音控制系統的影響,並利用離線的技術估算出第一路徑與第二路徑的動態效應轉移函數來實現此演算法。在第一路徑動態效應轉移函數不容易利用離線的技術估算出來的情況下,可以利用串聯一個適應性FIR濾波器的方法來線上估算出第一路徑動態效應轉移函數,則干擾也可以被估算出來並由誤差訊號中扣除而得到新的殘留誤差。因此類神經控制器可以利用新的殘留誤差來更新權重並產生適合的控制訊號,然後利用控制訊號去推動控制喇叭產生控制聲波來消除噪音。最後由電腦模擬與實驗結果驗證本文所使用的方法,可以有效降低干擾對寬頻噪音抑制過程的影響,使得噪音抑制效果更加顯著。

In active noise control (ANC) applications, the existence of disturbance can significantly degrade performance of ANC systems. A new ANC algorithm referred to as FXNBP/CED algorithm is developed for a neural network-based ANC system to deal with the problem caused by the disturbance in this study. Estimated transfer functions of primary and secondary paths of the ANC system are required to implement the developed algorithm. If the transfer function of primary path is difficult to estimate or may be time-varying, an adaptive FIR filter can be used to model the primary path on-line. Disturbance can then be estimated for the neural network controller to update the weights and generate suitable control signal. Simulations and experiments will be used to demonstrate that the proposed method can effectively reduce the influence of the disturbance in wideband ANC applications.
URI: http://hdl.handle.net/11455/2103
其他識別: U0005-2307200818160900
Appears in Collections:機械工程學系所

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