應用小波與經驗模式分解於主動式噪音控制

Application of Wavelet and Empirical Mode Decomposition to Active Noise Control

陳垣圻(Yuan-chi Chen)

指導教授 ： 蕭俊祥

國立臺北科技大學/機電學院/機電整合研究所/碩士(2011年)

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。

關鍵字

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

並列摘要

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.

並列關鍵字

Active Noise Control ； FXLMS Algorithm ； Wavelet ； Hilbert-Huang Transform ； Empirical Mode Decomposition ； Feedback Active Noise Control

參考文獻

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