高效远程传声技术窄带主动噪声控制研究

摘要
图/表
参考文献(19)
相关文章 (2)

全文: PDF (2177 KB) HTML (1 KB)
输出: BibTeX | EndNote (RIS)

摘要远程传声技术（Remote Microphone Technique，RMT）是一种经典的虚拟麦克风主动噪声控制技术，该技术能扩大对噪声的控制范围，在车内主动噪声控制(Active noise Control，ANC)中拥有很大的研究潜力。但其较大的运算量使得处理器的成本提高，一定程度上限制其在量产车上的应用。本文将自适应陷波算法引入到RMT当中，提出融合自适应陷波算法的远程传声技术，与传统的远程传声技术相比有效地降低了运算量。用多频率混合噪声作为初级声源进行仿真实验，对比以上两种远程传声技术的降噪性能和算法算力，结果表明，本文所提出的远程传声技术降噪能力与传统技术相当，程序运行时间却小于传统的远程传声技术。将本文提出的远程传声技术应用到ANC系统台架实验中，结果表明，在目标降噪区域远离物理麦克风的条件下，系统依然能快速收敛并实现良好的降噪效果。

	服务

	把本文推荐给朋友
	加入我的书架
	加入引用管理器
	E-mail Alert
	RSS
	作者相关文章
	吴方博1
	2
	卢炽华1
	2
	刘志恩1
	2
	杨忠礼1
	2

关键词 ：远程传声技术, 虚拟麦克风, 主动噪声控制, 自适应陷波算法

Abstract：Remote Microphone Technique (RMT) is a classic virtual microphone active noise control technology. This technology can expand the range of noise control, and has great research potential in Active Noise Control (ANC) in car. However, its large computational load increases the cost of the processor, which limits its application in mass-produced vehicles to a certain extent. This paper introduces the adaptive notch algorithm into RMT, and proposes a remote microphone technique combined with the adaptive notch algorithm, which effectively reduces the amount of calculation compared with the traditional remote microphone technique. Using multi-frequency mixed noise as the primary sound source for simulation experiments, comparing the noise reduction performance and algorithm calculation power of the above two remote microphone techniques. The results show that the noise reduction ability of the remote microphone technique proposed in this article is equivalent to the traditional technology, and the running time is shorter than the traditional one. The remote microphone technique proposed in this paper is applied to the ANC system bench experiment. The results show that the system can still quickly converge and achieve a good noise reduction effect when the target noise reduction area is far away from the physical microphone.

Key words： remote microphone technique virtual microphone active noise control adaptive notch algorithm

收稿日期: 2022-03-17 出版日期: 2023-05-15

引用本文:

吴方博1,2，卢炽华1,2，刘志恩1,2，杨忠礼1,2. 高效远程传声技术窄带主动噪声控制研究[J]. 振动与冲击, 2023, 42(9): 268-274.
WU Fangbo1,2, LU Chihua1,2, LIU Zhi’en1,2, YANG Zhongli1,2. Narrow-band active noise control using highly efficient remote microphone technique. JOURNAL OF VIBRATION AND SHOCK, 2023, 42(9): 268-274.

链接本文:

http://jvs.sjtu.edu.cn/CN/ 或 http://jvs.sjtu.edu.cn/CN/Y2023/V42/I9/268

[1] Kuo S M, Morgan D R. Active Noise Control Systems Algorithms and DSP Implementations[M]. New York: Wiley, 1996.
[2] Burgess J C. Active adaptive sound control in a duct: A computer simulation[J]. New York:The Journal of the Acoustical Society of America, 1981,70(3):715-726.
[3] 张立军, 张希玉, 孟德建. 基于 NFXLMS 算法的车内道路噪声主动控制系统[J]. 振动与冲击, 2020, 39(21): 173-178.
Zhang Lijun, Zhang Xiyu, Meng Dejian. Active control system for in-vehicle road noise based on NFXLMS algorithm [J]. Journal of Vibration and Shock, 2020, 39(21): 173-178.
[4] 周刘彬, 刘记心, 杨铁军. 多线谱振动噪声主动控制中误差传感器的优化配置[J]. 振动与冲击, 2017, 36(10): 175-181.
Zhou Liubin, Liu Jixin, Yang Tiejun. Optimal configuration of error sensors in active control of multi-line spectrum vibration and noise [J]. Journal of Vibration and Shock, 2017, 36(10): 175-181.
[5] 李以农, 张锋, 王雷等. 次级通道在线辨识的齿轮啮合振动主动控制[J]. 振动与冲击, 2013, 204(16): 7-12.
Li Yinong, Zhang Feng, Wang Lei, etc. Active control of gear meshing vibration based on online identification of secondary channels [J]. Journal of Vibration and Shock, 2013, 204(16): 7-12.
[6] 刘宗巍. 基于发动机转速的车内噪声自适应主动控制系统研究[D]. 长春：吉林大学. 2004.
Liu Zongwei. Research on adaptive active control system for interior noise based on engine speed [D]. Changchun: Jilin University. 2004.
[7] 孙吉东. 基于陷波法的车内噪声主动控制系统研究[D]. 长春：吉林大学. 2016.
Sun Jidong. Research on active control system of vehicle interior noise based on notch method [D]. Changchun: Jilin University. 2016.
[8] 陈祥君. 基于陷波延时LMS算法的乘用车内自适应有源噪声控制技术研究[D]. 长春：吉林大学. 2019.
Chen Xiangjun. Research on adaptive active noise control technology in passenger cars based on notch delay LMS algorithm [D]. Changchun: Jilin University. 2019.
[9] Xiangbin M, Ko J S, Rheem J Y. Performance improvement of a quiet zone using multichannel real-time active noise control system[J]. The Journal of the Acoustical Society of Korea, 2016, 35, 216–222.
[10] S. Elliott, A. David. A virtual microphone arrangement for local active sound control[J]. Yokohama:Proceedings of the First International Conference on Motion and Vibration Control, 1992, 1027–1031.
[11] A. Roure, A. Albarrazin. The remote microphone technique for active noise control[J]. Florida:Proceedings of Active 1999, 2000, 1233–1244.
[12] Debi Prasad Das. Adjoint nonlinear active noise control algorithm for virtual microphone[J]. London:Mechanical Systems and Signal Processing, 2012, 27: 743–754.
[13] 王宇. 结合虚拟传声器的汽车车内噪声主动控制方法[D]. 北京：清华大学. 2017.
Wang Yu. Active control method of vehicle interior noise combined with virtual microphone [D]. Beijing: Tsinghua University. 2017.
[14] Zhang J, Elliott S J, Cheer J. Robust performance of virtual sensing methods for active noise control[J]. Mechanical Systems and Signal Processing, 2021, 152: 107453.
[15] 刘宋祥,陈仁文,张宇翔,丁学宇.复杂声场下自适应LMS-VMT算法的研究[J].噪声与振动控制, 2021, 41(03): 67-72+87.
Liu Songxiang, Chen Renwen, Zhang Yuxiang, Ding Xueyu. Research on Adaptive LMS-VMT Algorithm in Complex Sound Field [J]. Noise and Vibration Control, 2021, 41(03): 67-72+87.
[16] 邹海山,邱小军.复杂声学环境中人耳附近空间有源降噪研究综述[J].物理学报, 2019, 68(05): 7-18.
Zou Haishan, Qiu Xiaojun. A review of research on active noise reduction in spaces near the human ear in complex acoustic environments [J]. Acta Physica Sinica, 2019, 68(05): 7-18.
[17] Jung W, Elliott S J, Cheer J. Local active control of road noise inside a vehicle[J]. Mechanical Systems and Signal Processing, 2019, 121: 144-157.
[18] Sun H, Zhang J, Abhayapala T D, et al. Active Noise Control Over 3D Space with Remote Microphone Technique in the Wave Domain[C]//2021 IEEE Workshop on Applications of Signal Processing to Audio and Acoustics (WASPAA). IEEE, 2021: 301-305.
[19] 王登峰, 刘学广, 刘宗巍等. 基于发动机转速的车内有源消声控制策略和自适应算法[J]. 公路交通科技, 2004, 21(10):126-129.
Wang Dengfeng, Liu Xueguang, Liu Zongwei, etc. Active Noise Cancellation Control Strategy and Adaptive Algorithm Based on Engine Speed [J]. Highway Traffic Science and Technology, 2004, 21(10):126-129.