管道噪声有源控制系统的次级声源和误差传感器位置优化被引量：6

Position optimization for secondary speaker and error sensor of duct active noise control system

导出

摘要基于直流电机运行噪声的特点,对于管道有源噪声控制系统的次级声源和误差传感器位置选择,提出了两种优化策略并给出了物理系统的优化设计结果,通过实验验证了两种优化策略的可行性。在优化后的管道实验平台中使用不同有源噪声控制算法进行管道噪声控制实验,噪声源分别为160~550 Hz的单频率正弦周期信号和基波100 Hz,1—5次谐波的多频率正弦周期信号时,两种优化策略最大的降噪量分别达36.2 dB和26.4 dB,降噪效果显著,表明有源控制系统可以有效降低电机运行噪声。 Two optimized methods were developed to determine the appropriate positions of the secondary speaker and the error sensor in a duct active noise control（ANC） system based on the characteristics of the direct current motor operating noise.Test results on an optimized duct platform with various adaptive algorithms with single tone noises show that the maximum sound pressure reduction is about 36.2 dB with a single frequency 160-550 Hz sinusoidal wave and 26.4 dB for the first to fifth order harmonics sinusoidal waves with a 100 Hz fundamental frequency primary noises.The significant noise reduction by this duct noise control system indicates how effective the system is for reducing motor operating noise.

作者刘会灯邱阿瑞

机构地区清华大学电机工程与应用电子技术系

出处《清华大学学报（自然科学版）》 EI CAS CSCD 北大核心 2011年第3期382-389,共8页 Journal of Tsinghua University(Science and Technology)

关键词有源噪声控制管道噪声 active noise control duct acoustics noise

分类号 TB535 [理学—声学]

引文网络
相关文献

参考文献15

1Lueg P. Process of Silencing Sound Oscillations [P]. 2043416. USA, 1936.
2Kuo S M, Morgan D R. Active noise control: A tutorial review [J]. Proceedings of the IEEE, 1999, 87(6): 943 973.
3Slock D T, Kailath M T. Numerically stable fast transversal filters for recursive least squares adaptive filtering [J]. IEEE Transactions on Signal Processing, 1991, 39(1):92-114.
4Albu F, Bouchard M, Zakharov Y. Pseudo affine projection algorithms for multichannel active noise control [J]. IEEE Transactions on Audio, Speech and Language Processing, 2007, 15(3): 1044-1052.
5Cornelis D P, Rufus F, Ben S C, et al. A Kalman filter approach to virtual sensing for active noise control[J]. Mechanical Systems and Signal Processing, 2008, 12(2) : 49O 5O8.
6宫赤坤,张从敏.基于卡尔曼滤波的有源噪声自适应逆控制[J].噪声与振动控制,2008,28(3):96-99. 被引量：5
7Huynh V T, Duong H N. A fuzzy neural network feedback active noise controller [C]//10th International Conference on Control, Automation, Robotics and Vision. Hanoi, Vietnam, 2008;1109-1114.
8张晓宇,仪垂杰.基于神经网络的有源噪声控制实验研究[J].噪声与振动控制,2009,29(2):66-68. 被引量：3
9Russo F, Sicuranza G L. Accuracy and performance evaluation in the genetic optimization of nonlinear systems for active noise control [J]. IEEE Transactions on Instrumentation and Measurement, 2007, 56(4) : 1443 1450.
10郑陶冶,高翔.一种基于混合遗传算法的有源噪声控制方法[J].东南大学学报（自然科学版）,2004,34(2):171-174. 被引量：2

二级参考文献11

1刘学广,王登峰,刘宗巍,梁杰.车内多次级声源自适应有源消声研究[J].农业机械学报,2005,36(2):27-30. 被引量：6
2Colin H. Hansen. Current and future industrial applications of active noise control [ J ]. Noise Control Engineering Journal, 2005, 53 (5) :181 - 196.
3Guillaume Barrauh, J. C. M. Bermudez, Arcanjo Lenzi. New analytical model for the filtered-x least mean square algorithm verified through active noise control experiment [J]. Mechanical Systems and Signal Processing, 2007, 21 (4) :1839 - 1852.
4C H 汉森,S D 斯奈德.噪声和振动的主动控制[M].仪垂杰,译.北京:科学出版社,2002.
5Kenneth P.Laberteaux,et al.An Adaptive Inverse Controller for Explicit rate Congestion Control with Guaranteed Stability and Fairness.Int[J].Control.2003.Vol.76.No 1:24-47.
6A.M.Karashenas,M.W.Dunnigan and B.W.Williams.Adaptive Inverse Control Algorithm for Shock Testing.IEE Proc.-Control Theory Appl.,2000,147(3):2000.
7威德罗·B,瓦莱斯·E.自适应逆控制[M].刘树棠,韩崇昭,译.西安:西安交通大学出版社,2000.
8姚天任,孙洪.现代信号处理[M].武汉:华中理工大学出版社,1999.
9张奇志,周雅莉,贾永乐.一维噪声的有源控制[J].北京机械工业学院学报,2000,15(1):6-12. 被引量：14
10赵斌,张如辉,齐占庆.基于U-滤波LMS算法的自适应逆控制系统[J].自动化与仪器仪表,2002(6):7-10. 被引量：3