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Article(id=1227614520194035920, tenantId=1146029695717560320, journalId=1225147924628267009, issueId=1227614514896634485, articleNumber=null, orderNo=null, doi=10.16385/j.cnki.issn.1004-4523.2024.04.014, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1665158400000, receivedDateStr=2022-10-08, revisedDate=1670947200000, revisedDateStr=2022-12-14, acceptedDate=null, acceptedDateStr=null, onlineDate=1770615709589, onlineDateStr=2026-02-09, pubDate=1714233600000, pubDateStr=2024-04-28, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1770615709589, onlineIssueDateStr=2026-02-09, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1770615709589, creator=13701087609, updateTime=1770615709589, updator=13701087609, issue=Issue{id=1227614514896634485, tenantId=1146029695717560320, journalId=1225147924628267009, year='2024', volume='37', issue='4', pageStart='539', pageEnd='728', issueExtLink='null', onlineDate='null', pubDate='null', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=null, createTime=1770615708325, creator=13701087609, updateTime=1770795248114, updator=13701087609, preIssue=null, nextIssue=null, ext={EN=IssueExt(id=1228367559410512191, tenantId=1146029695717560320, journalId=1225147924628267009, issueId=1227614514896634485, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1228367559410512192, tenantId=1146029695717560320, journalId=1225147924628267009, issueId=1227614514896634485, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null}, startPage=677, endPage=685, ext={EN=ArticleExt(id=1227614520420528340, articleId=1227614520194035920, tenantId=1146029695717560320, journalId=1225147924628267009, language=EN, title=Performance of active noise reduction in large-scale space based on virtual error sensing, columnId=null, journalTitle=Journal of Vibration Engineering, columnName=null, runingTitle=null, highlight=null, articleAbstract=

Aimed at the problem of limited placement of error microphones in large-scale spatial active noise reduction systems，this paper used the virtual error sensing technology to place multiple virtual error microphones in the noise reduction target area，and transferred the quiet zones from the physical error microphone points to the virtual error microphone points，expanded the range of the quiet zones in the noise reduction target area. In order to analyze and study the noise reduction performance and influencing factors，the principle and algorithm of multi-channel virtual error sensing were given first，and then the noise reduction performance and the number and placement of physical and virtual error microphones ware simulated and analyzed. Finally，the noise reduction performance and influencing factors were verified experimentally in a model cabin of a turboprop aircraft. The simulation and experimental results show that the used virtual error sensing was beneficial to increase the average noise reduction and quiet zone of the target noise reduction area，the placement of the physical and virtual error microphones directly affects the distribution of the quiet zones，a reasonable number and placement of physical and virtual error microphones can expand the quiet zones to cover the noise reduction target area 100%，and the optimal number of error microphones was related to the noise frequency characteristics of the primary sound field.

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针对大尺度空间有源降噪系统误差传声器布放位置受限问题，本文使用虚拟误差传感在降噪目标区域放置多个虚拟误差传声器，将静音区由物理误差传声器点转移至虚拟误差传声器点，扩大降噪目标区域中静音区范围。为了对降噪性能及影响因素进行分析与研究，给出多通道虚拟误差传感的原理和算法，对降噪性能及物理与虚拟误差传声器的数量和布放等因素进行仿真分析，在飞机模型舱内进行实验验证。仿真及实验结果表明：使用虚拟误差传感有利于增大降噪目标区域降噪量及静音区；物理与虚拟误差传声器的布放影响静音区的分布；合理的物理与虚拟误差传声器数量及布放可以扩大静音区使其100%覆盖降噪目标区域，最优数量与初级声场频率特性相关。

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陈克安（1965—），男，博士，教授。电话： （029） 88494183； E-mail： 。
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代 海（1988—），男，博士研究生。电话： （029） 88494183； E-mail：。

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代 海（1988—），男，博士研究生。电话： （029） 88494183； E-mail：。

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代 海（1988—），男，博士研究生。电话： （029） 88494183； E-mail：。

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Technical Acoustics， 2008， 27（6）： 789-795., articleTitle=A comparison of cost functions for the virtual sound barrier system, refAbstract=null)], funds=[Fund(id=1227639803852812435, tenantId=1146029695717560320, journalId=1225147924628267009, articleId=1227614520194035920, awardId=11974287, language=CN, fundingSource=国家自然科学基金资助项目(11974287), fundOrder=null, country=null)], companyList=[AuthorCompany(id=1227639796487615380, tenantId=1146029695717560320, journalId=1225147924628267009, articleId=1227614520194035920, xref=1, ext=[AuthorCompanyExt(id=1227639796496003990, tenantId=1146029695717560320, journalId=1225147924628267009, articleId=1227614520194035920, companyId=1227639796487615380, language=EN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=1School of Marine Science and Technology, Northwestern Polytechnical University, Xi'an 710072, China), AuthorCompanyExt(id=1227639796500198295, tenantId=1146029695717560320, 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articleId=1227614520194035920, language=EN, label=Tab.1, caption=

Comparison of average noise reduction between physical and virtual error points

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控制方式降噪量均值/dB(A)
物理误差点虚拟误差点
控制物理误差点19.56.2
控制虚拟误差点6.819.9
虚拟误差传感8.619.7
), ArticleFig(id=1227639803236249720, tenantId=1146029695717560320, journalId=1225147924628267009, articleId=1227614520194035920, language=CN, label=表1, caption=

物理和虚拟误差点平均降噪量对比

, figureFileSmall=null, figureFileBig=null, tableContent=
控制方式降噪量均值/dB(A)
物理误差点虚拟误差点
控制物理误差点19.56.2
控制虚拟误差点6.819.9
虚拟误差传感8.619.7
), ArticleFig(id=1227639803315941499, tenantId=1146029695717560320, journalId=1225147924628267009, articleId=1227614520194035920, language=EN, label=Tab.2, caption=

Noise reduction comparison test groups

, figureFileSmall=null, figureFileBig=null, tableContent=
分组名称误差传声器编号
E4Ev4-1E2, E4, E6, E8, Ev2, Ev4, Ev6, Ev8
E4Ev4-2E1, E3, E5, E7, Ev2, Ev4, Ev6, Ev8
E8Ev4-3E1~E8, Ev2, Ev4, Ev6, Ev8
E8Ev8-4E1~E8, Ev1~Ev8
E8Ev0-5E1~E8
E0Ev8-6Ev1~Ev8
), ArticleFig(id=1227639803408216192, tenantId=1146029695717560320, journalId=1225147924628267009, articleId=1227614520194035920, language=CN, label=表2, caption=

降噪对比实验分组

, figureFileSmall=null, figureFileBig=null, tableContent=
分组名称误差传声器编号
E4Ev4-1E2, E4, E6, E8, Ev2, Ev4, Ev6, Ev8
E4Ev4-2E1, E3, E5, E7, Ev2, Ev4, Ev6, Ev8
E8Ev4-3E1~E8, Ev2, Ev4, Ev6, Ev8
E8Ev8-4E1~E8, Ev1~Ev8
E8Ev0-5E1~E8
E0Ev8-6Ev1~Ev8
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Comparison of average noise reduction between physical and virtual error points

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分组名称降噪量均值/dB(A)
物理误差监测点虚拟误差监测点
E4Ev4-14.810.3
E4Ev4-25.412.5
E8Ev4-36.214.8
E8Ev8-48.418.6
E8Ev0-519.85.9
E0Ev8-66.219.2
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物理和虚拟误差监测点平均降噪量

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物理误差监测点虚拟误差监测点
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E4Ev4-25.412.5
E8Ev4-36.214.8
E8Ev8-48.418.6
E8Ev0-519.85.9
E0Ev8-66.219.2
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基于虚拟误差传感的大尺度空间有源降噪性能研究
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代海 1, 2 , 陈克安 1 , 李荣 2 , 玉昊昕 2
振动工程学报 | 2024,37(4): 677-685
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振动工程学报 | 2024, 37(4): 677-685
基于虚拟误差传感的大尺度空间有源降噪性能研究
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代海1, 2 , 陈克安1 , 李荣2, 玉昊昕2
作者信息
  • 1西北工业大学航海学院，陕西　西安　710072
  • 2西安艾科特声学科技有限公司，陕西　西安　710075

    • 代 海（1988—），男，博士研究生。电话： （029） 88494183； E-mail：。

通讯作者:

陈克安（1965—），男，博士，教授。电话： （029） 88494183； E-mail： 。
Performance of active noise reduction in large-scale space based on virtual error sensing
Hai DAI1, 2 , Ke-an CHEN1 , Rong LI2, Hao-xin YU2
Affiliations
  • 1School of Marine Science and Technology, Northwestern Polytechnical University, Xi'an 710072, China
  • 2Xi'an ACT Acoustic Technology Co., Ltd., Xi'an 710075, China
出版时间: 2024-04-28 doi: 10.16385/j.cnki.issn.1004-4523.2024.04.014
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摘要
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针对大尺度空间有源降噪系统误差传声器布放位置受限问题，本文使用虚拟误差传感在降噪目标区域放置多个虚拟误差传声器，将静音区由物理误差传声器点转移至虚拟误差传声器点，扩大降噪目标区域中静音区范围。为了对降噪性能及影响因素进行分析与研究，给出多通道虚拟误差传感的原理和算法，对降噪性能及物理与虚拟误差传声器的数量和布放等因素进行仿真分析，在飞机模型舱内进行实验验证。仿真及实验结果表明：使用虚拟误差传感有利于增大降噪目标区域降噪量及静音区；物理与虚拟误差传声器的布放影响静音区的分布；合理的物理与虚拟误差传声器数量及布放可以扩大静音区使其100%覆盖降噪目标区域，最优数量与初级声场频率特性相关。

有源噪声控制  /  虚拟误差传感  /  静音区  /  空间降噪  /  误差传声器

Aimed at the problem of limited placement of error microphones in large-scale spatial active noise reduction systems，this paper used the virtual error sensing technology to place multiple virtual error microphones in the noise reduction target area，and transferred the quiet zones from the physical error microphone points to the virtual error microphone points，expanded the range of the quiet zones in the noise reduction target area. In order to analyze and study the noise reduction performance and influencing factors，the principle and algorithm of multi-channel virtual error sensing were given first，and then the noise reduction performance and the number and placement of physical and virtual error microphones ware simulated and analyzed. Finally，the noise reduction performance and influencing factors were verified experimentally in a model cabin of a turboprop aircraft. The simulation and experimental results show that the used virtual error sensing was beneficial to increase the average noise reduction and quiet zone of the target noise reduction area，the placement of the physical and virtual error microphones directly affects the distribution of the quiet zones，a reasonable number and placement of physical and virtual error microphones can expand the quiet zones to cover the noise reduction target area 100%，and the optimal number of error microphones was related to the noise frequency characteristics of the primary sound field.

active noise control  /  virtual error sensing  /  quiet zone  /  spatial noise reduction  /  error microphone
代海, 陈克安, 李荣, 玉昊昕. 基于虚拟误差传感的大尺度空间有源降噪性能研究. 振动工程学报, 2024 , 37 (4) : 677 -685 . DOI: 10.16385/j.cnki.issn.1004-4523.2024.04.014
Hai DAI, Ke-an CHEN, Rong LI, Hao-xin YU. Performance of active noise reduction in large-scale space based on virtual error sensing[J]. Journal of Vibration Engineering, 2024 , 37 (4) : 677 -685 . DOI: 10.16385/j.cnki.issn.1004-4523.2024.04.014
正文
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引言
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有源噪声控制（Active Noise Control，ANC）对中低频噪声的抑制有较好的效果［1］，近年来，ANC应用技术的发展十分迅速，大量的有源降噪产品被研发出来并投入市场应用。目前针对小尺度空间的ANC技术更为成熟，典型的应用场景有耳机、头盔和头靠等。
有源降噪头靠是小尺度空间ANC的一种典型应用，引起了大量的研究和讨论［2-3］。通过引入次级噪声来抵消某些位置的初级噪声，在初级噪声场中创建静音区［4-6］。静音区通常指次级声场中噪声衰减超过10.0 dB的降噪区域，主要集中在误差传声器附近。静音区往往很小，特别是当初级声场的噪声包含较高频率时［7］。Elliott等［8］计算出局部空间中静音区的大小一般是以降噪目标噪声频率1/10波长为直径的球形区域。因此，误差传声器应放置在靠近用户耳朵的位置［9］，实际应用中往往难以实现。为此，学者提出了虚拟误差传感［10-12］来克服此类限制。
在虚拟误差传感的ANC系统中，实际布置的传声器称为物理误差传声器，降噪目标区域预测得到的误差信号视为从虚拟布置在该区域的传声器中获得，称为虚拟误差传声器。如何使用物理误差传声器检测到的误差信号来精确估计降噪目标区域的误差信号非常重要［13］。随着研究的深入，远程传声器技术（Remote Microphone Technique，RMT） ［14］、自适应LMS虚拟传声器技术［15］以及卡尔曼滤波虚拟误差传感技术［16-17］都得到了较大的发展。这些技术主要用于解决复杂声场下局部有源噪声控制中误差传声器布放位置的限制，在控制目标不移动的情况下可以在小尺度空间内取得较好的降噪效果。其技术特点是物理和虚拟传声器的布放位置距离较近，不能大于初级噪声目标降噪频率的1/4波长，以便于在人耳处更好地产生静音区。邹海山等［18］使用虚拟声屏障技术，采用立体结构的声源和传感器阵列，在传感器阵列围成的封闭空间内产生静音区，使用多通道扩大了静音区，并分析了采用不同代价函数时的性能表现［19］。
在大尺度空间（空间尺度在3~5个波长以上）复杂声场中（如机车、直升机和涡浆飞机舱室），因空间限制，ANC系统中的误差传声器可布放位置距目标降噪区域较远，即物理传声器和虚拟误差传声器的距离大于1/4波长，加之需要实现静音区的范围也随人员活动范围增大而增大，使用虚拟误差传感的技术实现较为困难。目前，国内外对大尺度空间中使用虚拟误差传感进行有源降噪的研究极少，距解决实际问题仍有较大差距。
基于上述分析，本文在目标降噪区域中放置多个虚拟误差传声器，将静音区由人耳局部区域扩展到更大的空间范围，使之尽可能覆盖目标降噪区域，实现空间降噪，同时对其降噪性能及影响因素进行研究。首先使用FxLMS并参考RMT对原理及算法进行分析，明确算法原理及控制流程；然后分别在自由场和大尺度封闭空间中对虚拟误差传感的降噪性能、物理虚拟通路模型估计方法、物理和虚拟误差传声器的数量及布放等因素对降噪性能的影响进行仿真及分析；最后在涡桨飞机舱室内对降噪性能与影响因素进行实验验证，证明所提方法在大尺度空间中的可行性。
1　原理及算法
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1.1　原理
实现基于虚拟误差传感的大尺度空间ANC系统的主要组成部件包括次级声源、误差传声器和有源噪声控制器，与小尺度空间使用RMT相比，区别在于降噪性能的影响因素较多，通路模型更为复杂，估计精度要求更高。
在虚拟误差传感ANC系统中，误差传声器包括物理误差传声器和虚拟误差传声器。与小尺度空间的ANC系统相比，次级声源与物理误差传声器和物理与虚拟误差传声器布置的距离更远，物理和虚拟误差传声器的数量更多，通路模型更为复杂。
系统的实现包含建模和控制两个过程。建模过程为系统工作前的准备过程，需要对物理次级通路、虚拟次级通路和物理虚拟通路模型进行估计，将次级声源至物理误差点、次级声源至虚拟误差点和物理至虚拟误差点的传递函数分别记为，和。虚拟误差传声器处仅在建模过程布放物理传声器，用于通路传递函数估计。通过采集和处的噪声信号计算得到上述通路模型估计值，和。
控制过程为系统的降噪过程，将参考信号及物理误差传声器处的噪声信号输入至有源噪声控制器，结合通路模型，和估计虚拟误差点的噪声信号，系统以为控制目标计算次级声源驱动信号，利用声波相消原理在虚拟误差点处形成静音区。
1.2　算法
设系统包含个次级声源，个物理误差传感器，个虚拟误差点，其控制滤波器长度为，次级通路长度为，物理虚拟通路长度为。第个次级声源到第个虚拟误差点的次级通路脉冲响应中的第个值为，为其估计值。已知第个虚拟误差点期望信号估计值为，参考信号为，则时刻第个虚拟误差点噪声信号估计值为：
式中　 ，。其中，为第个次级声源的驱动信号，有：
式中　 为参考信号矢量；为第l个次级声源对应控制滤波器的权系数。则有：
将式（1）写为矩阵形式有：
式中　 ，
式（1）中，虚拟误差点期望信号由物理误差点处的期望信号估计得到。设第个物理误差点到第个虚拟误差点的物理虚拟通路脉冲响应的第个值为，为其估计值。初级声场环境下，第个物理误差点处的期望信号估计为，第个虚拟误差点处的期望信号估计为，则时刻虚拟误差点与物理误差点处期望信号有以下关系：
式中　 ，。
将式（4）写成矩阵形式有：
式中　 ，
控制算法运行过程中，物理误差点处的期望信号（初级声场）由物理误差点处的噪声信号（次级声场）计算得到。设第个次级声源到第个物理误差传感器的次级通路脉冲响应中的第个值为，为其估计值。已知第个物理误差传感器处的噪声信号为，则时刻第个物理误差传感器处的期望信号为：
式中　 。
将式（6）写为矩阵形式有：
式中　 ，
2　计算机仿真及结果分析
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为分析虚拟误差传感在大尺度空间中的降噪性能，以及初级声场噪声频率、虚拟误差传声器数量和布放等因素对降噪性能的影响，仿真模型设置为某型涡桨飞机的舱段空间有源降噪。该模型舱长10.0 m，内径4.0 m，舱段内有4个操作台及座椅，降噪的目标空间为人员坐姿时头部可移动区域。该飞机噪声能量主要集中在基频108 Hz（1BPF）及其2，3阶谐波（2~3BPF）频率处，仿真中频率分析范围为80~500 Hz，初级声场为真机实录的飞行声场。
结合工程实际，由于座椅需要经常性移动、拆卸等因素导致不能安装误差传声器，仿真模型中使用8个物理误差传声器E1~E8，8个虚拟误差传声器Ev1~Ev8，以及8个次级声源S1~S8。每个操作台上各布放2个物理误差传声器；每个操作台下方各布放2个次级声源；每个操作台对应的座椅靠背中心位置布放1个虚拟误差传声器；每个操作台台面边沿中心正上方人耳位置布放1个虚拟误差传声器。次级声源和误差传声器在舱段内的布放如图1所示。仿真所用的通路模型均来源于飞机等比例舱段模型中的实测值。
根据1.2节算法，所需的三种通路模型为，和，其中和可通过次级声源依次发出一定幅度的白噪声，离线完成通路模型估计。虚拟误差传声器新增的物理虚拟通路，虚拟误差点能否精准得到噪声信号的全部特性，直接影响ANC系统的降噪效果。因此，使用维纳滤波方法得到初级声场下物理和虚拟误差传声器之间的通路模型。
为便于进行降噪效果的对比，仿真参考信号选用相干性较高的电信号，分别使用3种控制方式对8个物理误差点E1~E8和8个虚拟误差点Ev1~Ev8降噪前后的噪声值进行估计。控制虚拟误差时，在8个虚拟误差点各放置1个物理误差传声器，其中虚拟误差点处降噪前后计权频谱以及降噪量如图2所示。使用8个物理误差传声器和8个虚拟误差传声器实现的虚拟误差传感降噪，其中虚拟误差点处降噪前后计权频谱以及降噪量如图3所示。
由图2和图3对比可知，1BPF降噪量分别为20.8和20.6 dB，1~2BPF降噪量也基本相同。这表明，使用虚拟误差传感对虚拟误差点进行降噪等同在虚拟误差点处直接放置物理误差传声器的降噪效果，频率越低，降噪效果越好。3种控制方式物理和虚拟误差点平均降噪量对比如表1所示。
由表1可知，控制目标点即实际误差点的降噪量最大，物理和虚拟误差点之间平均降噪量差值最大为13.3 dB（A），最小为11.1 dB（A）。使用虚拟误差传感时物理和虚拟误差点之间平均降噪量差值变小，分析认为这是由于使用虚拟误差传感技术时，虽然物理误差传声器没有直接参与控制，但虚拟误差传声器的噪声信号估计信息来源于物理误差传声器，降噪过程中误差信号实际间接包含了物理误差点处的噪声信号，因此物理误差点也间接得到了控制。
仿真结果表明，降噪效果是以误差传声器点为中心形成的静音区，远离误差点降噪效果变差。使用虚拟误差传感时物理和虚拟误差点之间的平均降噪量差值变小，同时这也有利于增大目标降噪区域的平均降噪量及静音区范围。
3　实验验证
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3.1　实验环境
实验在某型涡桨飞机等比例模型舱中进行，模型舱与第2节仿真所用环境相同。有源降噪系统为自研的高性能数字信号处理（Digital Signal Processing，DSP）实验平台。验证实验使用8个物理误差传声器E1~E8、8个虚拟误差传声器Ev1~Ev8和8个次级声源S1~S8，初级声场为80~500 Hz的真机噪声，在实验室进行声场重构，重构目标点即误差点处1~3BPF声级及总声级重构误差绝对值均小于2.0 dB，平均误差为1.2 dB。次级声源、物理和虚拟误差点均按图1所示布放，模型舱内测量传声器、物理和虚拟误差点的设备布置如图4所示。
降噪实验分别记录物理和虚拟误差点以及坐姿人耳高度（离地板1.2 m，与虚拟误差点同高）平面网格划分测量点处的1~3BPF声级和总声级，以便于进行降噪性能对比。网格划分时以第1个座椅和显控台边缘交点为xyz轴原点，形成一个长320.0 cm、宽120.0 cm的平面，单个网格长30.0 cm、宽20.0 cm，共70个网格测量点。网格划分及坐标如图1所示，划定x［0，320.0］，y［0，100］的区域为目标降噪区域。
模型舱初级声场噪声分布云图如图5所示。图5中给出了坐姿人耳高度平面1~3BPF及总声级分布云图，坐标单位为cm，通过对网格点的噪声值进行线性插分得到噪声云图。由图5可知，该模型舱重构声场中的总声压级约大于79.6 dB（A）、小于89.5 dB（A），平均噪声值约为85.3 dB（A）。1BPF噪声对总声级贡献最大，2BPF次之，3BPF最小声级接近65.0 dB（A）。由图5对比1~3BPF分布规律可知，1BPF声场呈带状分布，随着噪声频率的增大，噪声波长变小，声场特性更为复杂，因此3BPF相较1BPF噪声明显呈碎块状分布。
降噪对比实验共分6组，每组实验采用相同数量和布放位置的8个次级声源，实验分组如表2所示，分组名中以E表示物理误差传声器、Ev表示虚拟误差传声器，如E4Ev4-1表示为使用4个物理误差传声器和4个虚拟误差传声器做的第1组布局实验。
实验E4Ev4-1和E4Ev4-2使用相同数量的物理和虚拟误差传声器，区别在于选用的物理误差传声器布放位置不同；实验E8Ev4-3和E8Ev8-4是在上组实验前提下分别增加4个物理和虚拟误差传声器；实验E8Ev0-5为直接控制物理误差点，虚拟误差传声器数量为0；实验E0Ev8-6为在8个虚拟误差点处各放置1个物理误差传声器，对虚拟误差点直接进行降噪。
3.2　结果及分析
对表2所示6组实验数据进行处理。各实验分组次级声场的总声级云图如图6所示，图中标注了物理和虚拟误差传声器的布放位置，坐标轴单位为cm，以颜色表示该点处的声压级值。总降噪量云图如图7所示，图中以颜色表示该点处的降噪量值。
由图6可知，在虚拟误差传声器附近的噪声明显降低，次级声场的最大噪声值约为80.4 dB（A），最小噪声值约为65.3 dB（A）。由图6和图7可知，降噪效果较好的区域均在控制目标点附近，围绕误差点形成静音区，对比实验E4Ev4-1和E4Ev4-2可知，虽然物理误差点没有直接作为误差信号参与降噪，但物理误差传声器的布放直接影响虚拟误差点的降噪效果及静音区范围。合理布放物理误差传声器，虚拟误差传声器周围更容易产生静音区。
对比图6和7中实验E4Ev4-2和E8Ev4-3可知，增加物理误差传声器的数量，可以改善空间降噪效果，增大静音区范围。相较于实验E8Ev8-4，增加虚拟误差传声器的数量比增加物理误差传声器的数量更能直接地增大降噪目标区域的平均降噪量和静音区范围。实验E8Ev0-5和E0Ev8-6分别在虚拟误差点和物理误差点未布放误差传声器，因此降噪区域明显呈带状分布，靠近误差传声器的区域降噪效果较好。
对比图6和7中实验E8Ev8-4和E0Ev8-6可知，静音区分布近似相同，均100%覆盖了降噪目标区域，使用虚拟误差传感能够很好地将静音区迁移至目标降噪区域，解决了降噪目标区域不能布放物理传声器的问题，使用虚拟误差传感等同于在虚拟误差点布置了物理误差传声器的降噪效果。同时在不考虑DSP处理性能，使用相同数量的次级声源和误差传声器情况下，使用虚拟误差传感实现的降噪效果更优，次级声场计算结果误差较小，满足降噪需求。
为分析物理和虚拟误差传声器的数量和布放对初级声场中不同频率噪声的降噪性能与其影响因素，图8~10分别给出了1~3BPF降噪量云图。
对比图8~10可知，1BPF噪声降噪效果最好，1BPF由于频率较低，容易在降噪目标区域产生覆盖范围为100%的静音区。由图9中2BPF降噪量云图可知，静音区相较于1BPF明显减小，但静音区和降噪量最优区域仍在误差传声器附近。
由图10中3BPF降噪量云图可知，虽然降噪量最优区域仍在误差传声器附近，但很难产生较大区域的静音区，部分目标降噪区域的噪声甚至不降反增。对比图5，9和10可知，目标降噪区域中降噪效果较差甚至噪声增加的区域，其初级声场往往较低，部分区域由于初级声场噪声明显低于其他区域次级声场噪声，导致了该区域噪声不降反增。结合图7可知，虽然部分区域初级声场噪声较低，降噪量为负值，但该区域噪声增加值及初级声场较小，因此并不影响目标降噪区域整体的降噪效果和静音区。对比图10中是否使用虚拟误差传感的实验结果可知，使用虚拟误差传感虽未能实现大范围的静音区，但降噪效果仍相对最优。
通过计算，3BPF噪声波长约为1.05 m，图10中误差传声器点处静音区直径平均约为0.10 m，分析认为，如要实现3BPF更好的降噪效果和扩大静音区，应增加更多的物理和虚拟误差传声器。
由图6~10分析可得，无论是否使用虚拟误差传感，均围绕误差传声器附近形成静音区，因此误差点的降噪效果也可直观反映系统的降噪性能。6组实验中物理和虚拟误差监测点的平均降噪量对比如表3所示。
由表3可知，控制目标点即误差传声器点的降噪量最大，物理和虚拟误差点之间平均降噪量最大差值为13.9 dB（A），最小为5.5 dB（A）。远离误差点降噪效果会明显变差，使用虚拟误差传感时物理和虚拟误差点之间的平均降噪量差值变小，分析认为，降噪过程中误差信号实际间接包含了物理误差点处的噪声信号，因此物理误差点也间接实现了控制，同时这也有利于增大目标降噪区域的平均降噪量。
4　结论
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本文对大尺度空间中使用虚拟误差传感的多通道ANC算法进行了原理及算法分析，通过计算机仿真，分析了使用虚拟误差传感在飞机模型舱段中的控制方式、物理和虚拟误差传声器的数量及布放等因素对降噪性能的影响。在模型舱内对其降噪性能与影响因素进行验证，结果表明：
（1）物理误差传声器的布放直接影响虚拟误差点的降噪效果及静音区范围，物理误差传声器布放合理，虚拟误差传声器周围更容易产生静音区；
（2）相同数量的误差传声器，使用虚拟误差传感的降噪效果更优，有利于增大目标降噪区域的静音区及空间平均降噪量；
（3）合理的物理与虚拟误差传声器数量及布放可以扩大静音区使其100%覆盖降噪目标区域，最优数量与初级声场噪声频率特性相关。
基金
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  • 国家自然科学基金资助项目(11974287)
文献
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2024年第37卷第4期
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doi: 10.16385/j.cnki.issn.1004-4523.2024.04.014
  • 接收时间：2022-10-08
  • 首发时间：2026-02-09
  • 出版时间：2024-04-28
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  • 收稿日期：2022-10-08
  • 修回日期：2022-12-14
基金
国家自然科学基金资助项目(11974287)
作者信息
    1西北工业大学航海学院，陕西　西安　710072
    2西安艾科特声学科技有限公司，陕西　西安　710075

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陈克安（1965—），男，博士，教授。电话： （029） 88494183； E-mail： 。
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https://castjournals.cast.org.cn/joweb/zdgcxb/CN/10.16385/j.cnki.issn.1004-4523.2024.04.014
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2种不同金属材料的力学参数
科
Family		 属数
Number of
genus		 种数
Number of
species		 占总种数比例
Percentage of
total species (%)		 属
Genus		 种数
Number of
species		 占总种数比例
Percentage of total
species (%)
鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
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