频域有源噪声控制算法性能研究
发布时间：2018-10-24 18:55
【摘要】：为了应对日益严重的噪声污染问题,有源噪声控制技术得到日益广泛的应用。对常用的前馈有源噪声控制系统而言,自适应算法的性能好坏直接决定了控制器的降噪性能。与时域自适应算法相比,频域自适应算法有较快的收敛速度和较低的运算量,这使得其很适合在实时有源噪声控制系统中使用。但在有源噪声控制系统中,由于参考通道和次级通道的存在,系统往往会面临滤波器阶数不足和非因果的问题。本文重点探索频域自适应算法在有源噪声控制系统中的性能。首先,本文介绍了块LMS(BLMS)算法、频域LMS(FDLMS)算法和LMS算法误差与维纳误差的关系。FDLMS算法是BLMS算法的快速实现方式,其收敛速度可以通过使用归一化各频点功率得到的收敛因子来获得改善。LMS算法误差为维纳误差作为输入信号的线性时不变系统的输出,系统函数主要依赖于参考信号功率谱估计。对于某些信号,可能存在LMS算法误差小于维纳误差的情况。其次,针对有源噪声控制系统中遇到的非因果问题,分析了归一化频域算法(NFDLMS)在非因果条件下稳态解的特性,发现NFDLMS算法的收敛结果与参考信号功率谱估计的平坦程度有关。参考信号功率谱平坦度越高,稳态解越接近维纳解。与之相对应的一个值得关注的结论是：在非因果条件下,滤波器阶数越高,NFDLMS算法的收敛结果可能越差。仿真和实验验证了理论分析的有效性。最后,针对非因果条件和滤波器阶数不足时NFDLMS算法收敛不到维纳解的问题,提出一种改进归一化频域算法(MNFDLMS).理论证明MNFDLMS算法在非因果条件和滤波器阶数不足时也能收敛到维纳解。仿真和实验同样验证了理论分析的有效性。
[Abstract]:In order to deal with the increasingly serious problem of noise pollution, active noise control technology has been increasingly widely used. For the commonly used feedforward active noise control systems, the performance of the adaptive algorithm directly determines the noise reduction performance of the controller. Compared with the time-domain adaptive algorithm, the frequency-domain adaptive algorithm has higher convergence speed and lower computational complexity, which makes it suitable for use in real-time active noise control systems. However, in active noise control systems, due to the existence of reference channels and secondary channels, the system often faces the problems of insufficient filter order and non-causality. This paper focuses on the performance of frequency domain adaptive algorithm in active noise control system. First of all, this paper introduces the relationship between block LMS (BLMS) algorithm, frequency-domain LMS (FDLMS) algorithm and LMS algorithm error and Wiener error. FDLMS algorithm is the fast implementation of BLMS algorithm. The convergence rate can be improved by using the convergence factor of normalized power at each frequency point. The error of LMS algorithm is the output of linear time-invariant system with Wiener error as input signal. The system function mainly depends on the power spectrum estimation of the reference signal. For some signals, the LMS algorithm error may be less than Wiener error. Secondly, aiming at the non-causality problem in active noise control system, the characteristics of steady-state solution of normalized frequency-domain algorithm (NFDLMS) under non-causality condition are analyzed. It is found that the convergence of NFDLMS algorithm is related to the flatness of power spectrum estimation of reference signal. The higher the power spectrum flatness of the reference signal, the closer the steady-state solution is to the Wiener solution. The corresponding conclusion is that the higher the filter order, the worse the convergence result of NFDLMS algorithm under the condition of non-causality. The effectiveness of the theoretical analysis is verified by simulation and experiments. Finally, an improved normalized frequency domain algorithm (MNFDLMS).) is proposed to solve the problem that the NFDLMS algorithm can not converge to the Wiener solution when the non-causality condition and the filter order are insufficient. It is proved theoretically that the MNFDLMS algorithm can converge to Wiener solution when the non-causality condition and the filter order are not sufficient. Simulation and experiment also verify the effectiveness of the theoretical analysis.
【学位授予单位】：南京大学
【学位级别】：硕士
【学位授予年份】：2014
【分类号】：TB535
本文编号：2292258
[Abstract]:In order to deal with the increasingly serious problem of noise pollution, active noise control technology has been increasingly widely used. For the commonly used feedforward active noise control systems, the performance of the adaptive algorithm directly determines the noise reduction performance of the controller. Compared with the time-domain adaptive algorithm, the frequency-domain adaptive algorithm has higher convergence speed and lower computational complexity, which makes it suitable for use in real-time active noise control systems. However, in active noise control systems, due to the existence of reference channels and secondary channels, the system often faces the problems of insufficient filter order and non-causality. This paper focuses on the performance of frequency domain adaptive algorithm in active noise control system. First of all, this paper introduces the relationship between block LMS (BLMS) algorithm, frequency-domain LMS (FDLMS) algorithm and LMS algorithm error and Wiener error. FDLMS algorithm is the fast implementation of BLMS algorithm. The convergence rate can be improved by using the convergence factor of normalized power at each frequency point. The error of LMS algorithm is the output of linear time-invariant system with Wiener error as input signal. The system function mainly depends on the power spectrum estimation of the reference signal. For some signals, the LMS algorithm error may be less than Wiener error. Secondly, aiming at the non-causality problem in active noise control system, the characteristics of steady-state solution of normalized frequency-domain algorithm (NFDLMS) under non-causality condition are analyzed. It is found that the convergence of NFDLMS algorithm is related to the flatness of power spectrum estimation of reference signal. The higher the power spectrum flatness of the reference signal, the closer the steady-state solution is to the Wiener solution. The corresponding conclusion is that the higher the filter order, the worse the convergence result of NFDLMS algorithm under the condition of non-causality. The effectiveness of the theoretical analysis is verified by simulation and experiments. Finally, an improved normalized frequency domain algorithm (MNFDLMS).) is proposed to solve the problem that the NFDLMS algorithm can not converge to the Wiener solution when the non-causality condition and the filter order are insufficient. It is proved theoretically that the MNFDLMS algorithm can converge to Wiener solution when the non-causality condition and the filter order are not sufficient. Simulation and experiment also verify the effectiveness of the theoretical analysis.
【学位授予单位】：南京大学
【学位级别】：硕士
【学位授予年份】：2014
【分类号】：TB535
【共引文献】
相关硕士学位论文 前1条
1 王月琳;封闭空间主动噪声控制试验平台[D];清华大学;2014年
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