基于主动噪声控制技术改善车内声品质
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摘要
为达到改善某款SUV匀速工况下车内声品质的目的,以驾驶员右耳旁的稳态噪声为研究对象,建立GA-BP声品质预测模型,对声品质客观参量和主观烦恼度进行一元线性回归,选取与主观烦恼度显著相关的响度和粗糙度作为控制目标,利用Zwicker计算模型对响度进行分析,利用小波变换对粗糙度进行分析,根据分析结果确定最优控制频带,并设计基于FELMS算法的主动噪声控制系统对样本噪声进行主动控制。仿真结果表明,控制后噪声的响度、粗糙度分别降低了33.5%、23.1%,烦恼度等级下降了2.76个等级,车内声品质得到大幅改善。
In order to improve SUV sound quality under uniform speed condition, the steady-state noise next to the driver's right ear was studied and the GA-BP sound quality prediction model was established. The objective parameters of sound quality and subjective annoyance were analyzed by linear regression.In this paper, the loudness and roughness which are significantly related to subjective annoyance were selected as the control objectives and were analyzed respectively by using Zwicker calculation model and wavelet transform.According to the analysis results, the optimal control frequency band was determined, and an active noise control system based on FELMS algorithm was designed to actively control the sample noise.The simulation results show that loudness and roughness of the sample noise are reduced by 33.5 % and 23.1 %, respectively, and the annoyance level is reduced by 2.76 grades.The sound quality inside vehicle has been improved.
In order to improve SUV sound quality under uniform speed condition, the steady-state noise next to the driver's right ear was studied and the GA-BP sound quality prediction model was established. The objective parameters of sound quality and subjective annoyance were analyzed by linear regression.In this paper, the loudness and roughness which are significantly related to subjective annoyance were selected as the control objectives and were analyzed respectively by using Zwicker calculation model and wavelet transform.According to the analysis results, the optimal control frequency band was determined, and an active noise control system based on FELMS algorithm was designed to actively control the sample noise.The simulation results show that loudness and roughness of the sample noise are reduced by 33.5 % and 23.1 %, respectively, and the annoyance level is reduced by 2.76 grades.The sound quality inside vehicle has been improved.
引文
[1] 陈克安.有源噪声控制[M].北京:国防工业出版社,2014.
[2] 曾文杰.基于FXLMS算法的车内噪声主动控制技术研究[D].镇江:江苏大学,2017.
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[4] 刘宗巍,王登峰,姜吉光.用主动噪声控制法改善车内声品质[J].吉林大学学报(工学版),2008,38(2):774-776.
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[7] GB1496-79,机动车辆噪声测量方法[S].北京:中国标准出版社,2003.
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[9] 谢文阁,王福全,伶玉军,等.一种GA-BP算法的研究及性能分析[J].大众科技,2014(4):24-26.
[10] 严静,刘瑞军,丁玲,等.基于小波变换的车窗防夹系统电流降噪与特性分析[J].广西大学学报(自然科学版),2017,42(2):602-610.
[11] 卢家暄,熊荆州.基于改进的Daubechies小波变换的电网谐波检测研究[J].现代制造,2016(36):40-41.
[12] KUO S M,TSAI J.Residual noise shaping technique for active noise control systems[J].The Journal of the Acoustical Society of America,1994,95(3):1665-1668.
[2] 曾文杰.基于FXLMS算法的车内噪声主动控制技术研究[D].镇江:江苏大学,2017.
[3] BLAUERT J,JEKOSCH U.Sound-quality evaluation-a mufti-layered problem[J].Acta acustica united with acustica,1997,83(5):747-753.
[4] 刘宗巍,王登峰,姜吉光.用主动噪声控制法改善车内声品质[J].吉林大学学报(工学版),2008,38(2):774-776.
[5] DE M,GONZALEZ A,PINERO G,et al.Subjective evaluation of actively controlled interior car noise[C]//2001 IEE International Conference on Acoustics,Speech,and Signal Processing.Florence,Italy:IEEE,2001:3225-3228.
[6] LIN J H,TANG S T,HAN W R,et al.Evaluation of speech intelligibility for feedback adaptive active noise cancellation headset[C]//International Conference on Biomedical and Pharmaceutical Engineering,Singapore:IEEE,2006:24-29.
[7] GB1496-79,机动车辆噪声测量方法[S].北京:中国标准出版社,2003.
[8] 申秀敏,左曙光,李林,等.车内噪声声品质神经网络预测.声学技术[J].2009,28(3):264-268.
[9] 谢文阁,王福全,伶玉军,等.一种GA-BP算法的研究及性能分析[J].大众科技,2014(4):24-26.
[10] 严静,刘瑞军,丁玲,等.基于小波变换的车窗防夹系统电流降噪与特性分析[J].广西大学学报(自然科学版),2017,42(2):602-610.
[11] 卢家暄,熊荆州.基于改进的Daubechies小波变换的电网谐波检测研究[J].现代制造,2016(36):40-41.
[12] KUO S M,TSAI J.Residual noise shaping technique for active noise control systems[J].The Journal of the Acoustical Society of America,1994,95(3):1665-1668.