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虚拟传声器的有源噪声控制 被引量:2

Active Noise Control Using Virtual Sensors
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摘要 研究虚拟传声器的有源噪声控制问题。该技术适用于控制区域不适合放置误差传声器的场合。将误差传声器置于控制区域之外,得到测量误差。采用前向差分预测算法预测控制区域内的残余误差信号,然后利用自适应LMS算法,得到最优的噪声控制滤波器。为了尽量消除预测中存在的误差,采用自适应变权值预测算法。仿真结果表明该方法能有效地抑制噪声,使控制区域内的噪声信号得到明显衰减。 The active noise control using virtual sensors is studied. The virtual sensors technique is used for these cases that the error sensors are unlikely to be placed in the control region. The error sensors are placed out of the control area to get measurement errors. Then the residual error signal is predicted using the forward finite-difference method, and the adaptive LMS algorithm is used to get optimal active noise control filter. In order to reduce errors in the prediction, the adaptive varying weight prediction control approach is introduced. Simulation results show that the noise signals are obviously reduced in the control area using virtual sensors.
出处 《噪声与振动控制》 CSCD 北大核心 2009年第2期62-65,共4页 Noise and Vibration Control
基金 北京市属市管高校人才强教计划资助项目(PXM2008_014215_055942) 北京市优秀人才培养资助(20061D0500600164)
关键词 声学 有源噪声控制 虚拟传声器 仿真 前向差分预测 acoustics active noise control virtual sensor simulation forward finite-difference prediction
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参考文献4

  • 1Jacqueline M. Munn. Virtual sensors for active noise control[ D]. Australia: The University of Adelaide South Australia, 2003.
  • 2Marek P. Adaptive Noise Control Algorithms for Active Headrest System [ J ]. Control engineering practice, 2004 (12) :1101 -1112.
  • 3Snyder. S. D , Tanaka. N. Active Control of Vibration Using a Neural Network [ J ]. IEEE Trans. Neural Networks, 1995 (4):819-828.
  • 4Zhou, Y. L., Zhang, Q.Z., Li, X. D. , Gan, W.S. Analysis and DSP Implementation of an ANC System using a Filtered-Error Neural Network [ J ]. Journal of Sound and Vibration, 2005 ( 1 ) : 1 - 25.

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