基于优化算法的主动噪声控制及应用研究
发布时间：2018-09-18 11:13
【摘要】：随着社会的不断发展，人们对生活质量的要求越来越高，噪声污染已越来越受到社会的重视。相对于传统的被动噪声控制，主动噪声控制由于可以更有效地对低频段噪声进行控制，从而在噪声控制领域具有越来越重要的地位。因此本文对主动噪声控制的改进及应用进行了研究。 本文首先以前馈型、反馈型以及混合型主动噪声控制为例，，简单介绍了主动噪声控制的结构及原理。在此基础上，推导了传统主动噪声控制算法，即次通道离线估计算法、次通道在线估计算法以及滤波-X最小均方算法，且在理论上分析了主动噪声控制采用传统算法时必须进行次通道估计的缺点，并通过MATLAB仿真结果验证了此理论分析，从而给出了基于优化算法改进主动噪声控制的意义。 接着通过分析讨论，选择了细菌觅食优化算法作为本文所要讨论的优化算法，并详细介绍了细菌觅食优化算法的原理、算法流程及各主要参数的选择。在此基础上，对细菌觅食优化算法进行了改进，使其适用于主动噪声控制，并且找到了该算法与主动噪声控制原理的衔接点，最终给出了基于此优化算法的主动噪声控制。 随后，在MATLAB平台上，对此基于优化算法的主动噪声控制进行了应用仿真，应用对象为日常洗衣机运行“脱水”程序时发出的噪声。仿真结果验证了该改进后的主动噪声控制系统克服了基于传统算法的主动噪声控制系统需要对次通道进行提前估计的缺点，并通过仿真验证了优化算法主要参数的选择对降噪效果的影响。本文最后简单讨论了基于优化算法的主动噪声控制的硬件设计思路。
[Abstract]:With the development of society, people are demanding more and more high quality of life, and noise pollution has been paid more and more attention by the society. Compared with the traditional passive noise control, active noise control plays a more and more important role in the field of noise control because it can effectively control the noise in the low frequency band. Therefore, the improvement and application of active noise control are studied in this paper. In this paper, the structure and principle of active noise control are introduced by taking feedforward, feedback and hybrid active noise control as examples. On this basis, the traditional active noise control algorithms, namely, the subchannel off-line estimation algorithm, the sub-channel on-line estimation algorithm and the filter -X minimum mean square algorithm, are derived. The disadvantages of sub-channel estimation when active noise control is used in traditional algorithm are analyzed theoretically. The theoretical analysis is verified by MATLAB simulation results, and the significance of improving active noise control based on optimization algorithm is given. Then through the analysis and discussion, we select the bacterial foraging optimization algorithm as the optimization algorithm discussed in this paper, and introduce the principle, algorithm flow and the selection of the main parameters of the bacterial foraging optimization algorithm in detail. On this basis, the bacterial foraging optimization algorithm is improved to be suitable for active noise control, and the convergence point between the algorithm and the principle of active noise control is found. Finally, the active noise control based on this optimization algorithm is given. Then, on the MATLAB platform, the active noise control based on the optimization algorithm is simulated. The application object is the noise emitted when the washing machine is running "dehydration" program. The simulation results show that the improved active noise control system overcomes the shortcoming that the active noise control system based on the traditional algorithm needs to estimate the secondary channel in advance. The effect of the main parameters of the optimization algorithm on the noise reduction effect is verified by simulation. Finally, the hardware design of active noise control based on optimization algorithm is briefly discussed.
【学位授予单位】：哈尔滨工业大学
【学位级别】：硕士
【学位授予年份】：2014
【分类号】：TB535;TP18
本文编号：2247735
[Abstract]:With the development of society, people are demanding more and more high quality of life, and noise pollution has been paid more and more attention by the society. Compared with the traditional passive noise control, active noise control plays a more and more important role in the field of noise control because it can effectively control the noise in the low frequency band. Therefore, the improvement and application of active noise control are studied in this paper. In this paper, the structure and principle of active noise control are introduced by taking feedforward, feedback and hybrid active noise control as examples. On this basis, the traditional active noise control algorithms, namely, the subchannel off-line estimation algorithm, the sub-channel on-line estimation algorithm and the filter -X minimum mean square algorithm, are derived. The disadvantages of sub-channel estimation when active noise control is used in traditional algorithm are analyzed theoretically. The theoretical analysis is verified by MATLAB simulation results, and the significance of improving active noise control based on optimization algorithm is given. Then through the analysis and discussion, we select the bacterial foraging optimization algorithm as the optimization algorithm discussed in this paper, and introduce the principle, algorithm flow and the selection of the main parameters of the bacterial foraging optimization algorithm in detail. On this basis, the bacterial foraging optimization algorithm is improved to be suitable for active noise control, and the convergence point between the algorithm and the principle of active noise control is found. Finally, the active noise control based on this optimization algorithm is given. Then, on the MATLAB platform, the active noise control based on the optimization algorithm is simulated. The application object is the noise emitted when the washing machine is running "dehydration" program. The simulation results show that the improved active noise control system overcomes the shortcoming that the active noise control system based on the traditional algorithm needs to estimate the secondary channel in advance. The effect of the main parameters of the optimization algorithm on the noise reduction effect is verified by simulation. Finally, the hardware design of active noise control based on optimization algorithm is briefly discussed.
【学位授予单位】：哈尔滨工业大学
【学位级别】：硕士
【学位授予年份】：2014
【分类号】：TB535;TP18
【参考文献】
相关期刊论文 前1条
1 赵晓云;李功宇;王程荣;阮重胜;;一维多谐频声源主动噪声控制算法[J];科学技术与工程;2010年33期
相关博士学位论文 前2条
1 刘剑;基于FXLMS算法的窄带主动噪声控制系统性能分析研究[D];哈尔滨工业大学;2011年
2 许鑫;细菌觅食优化算法研究[D];吉林大学;2012年
本文编号：2247735
本文链接：https://www.wllwen.com/guanlilunwen/gongchengguanli/2247735.html
