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基于MICA的声级计频率计权数字IIR滤波器设计

2020-04-17唐求吴娟邱伟沈洁滕召胜

湖南大学学报·自然科学版 2020年2期

唐求 吴娟 邱伟 沈洁 滕召胜

摘   要:针对双线性变换法在设计声级计频率计权数字滤波器时存在固有频率失真问题,提出一种基于改进帝国竞争算法的数字IIR滤波器设计方法. 为避免帝国竞争算法出现早熟收敛而陷入局部最优的问题,在帝国竞争算法同化阶段引入混沌函数来增大搜索范围,与此同时,在帝国竞争阶段引入克隆进化算子,引导算法向IIR滤波器参数最优解方向搜索,得到改进帝国竞争算法. 在研究声级计A、C计权的IIR滤波器误差来源的基础上,利用改进帝国竞争算法对声级计频率计权数字IIR滤波器系数进行寻优求解,构建基于改进帝国竞争算法的频率计权数字IIR滤波器优化模型. 仿真与实验结果表明,本文提出的数字滤波器设计方法精度较高,且滤波器的误差能控制在10-3 dB数量级范围内. 在噪声环境下不同声信号级进行的频率计权测试结果表明,改进帝国竞争算法测试的声信号级的计权误差能维持在10-2 dB数量级范围内,完全满足国家标准GB/T 3241—2010对1级声级计的设计要求.

关键词:声级计;频率计权;数字IIR滤波器设计;帝国竞争算法;混沌函数;克隆进化

中图分类号:TB52                                    文献标志码:A

Abstract:Aiming at the frequency distortion problem in the design of frequency weighting digital filter based on bilinear transformation,an evolutionary method based on Modified Imperialist Competitive Algorithm(MICA)has been proposed to design digital IIR filter. In order to help the algorithm to escape from local minima,this paper introduced a chaotic function to make the search range wider in the assimilation operation of Imperialist Competitive Algorithm (ICA). Meanwhile,a clone evolution operator was introduced in the competition operation,guiding the search for global optimization efficiently. Then,the optimization model of modified ICA of the filter in sound-level meter was designed based on the research of the source of error in IIR filter. The coefficients of frequency weighted were searched based on the MICA. The results of both simulation and application show the performance of the design method to find better solution,indicating that the proposed method can significantly improve the precision and the error can be controlled within the order of 10-3 dB. Finally,the test of frequency weighting under different acoustic signal level with noise verifies that the error of the MICA test can be maintained in the order of 10-2 dB,which fully meets the design requirements of sound level meter (Class 1) in the national standard of GB/T 3241-2010.

Key words:sound level meter;frequency weighting;digital IIR filter design;Imperialist Competitive Algorithm(ICA);chaotic function;clone evolution

人耳對响度相同、频率成分不同的声音产生不同的听觉感受,为了模拟人耳的听觉特性,需在声级计中设计一种频率计权网络修正声音信号,使其对不同频率信号具有与人耳相同的灵敏度[1]. 因此,频率计权是声级计实现噪声测量的一项重要计量指标[2]. IEC 61672规定1级声级计必须实现A、C频率计权功能[3].

近年来,全数字式声级计得到广泛应用[4],但针对声级计频率计权数字滤波器的设计研究较少. 频率计权数字滤波器的实现可以选择无限冲激响应(IIR)数字滤波器和有限冲激响应(FIR)数字滤波器[5]. 对于相同的滤波精度,与FIR滤波器相比,IIR滤波器所用的阶数少,存储单元也较少[6].

由于声级计的频率计权算法采用嵌入式系统实现,要求计算量小,占用存储空间少,故本文选用数字IIR滤波器设计频率计权. 其中,常用双线性变换(Bilinear Transformation,BT)设计数字IIR滤波器[7]. 但双线性变换是一种近似变换,存在固有的频率失真[8],导致误差较大. 为此,文献[9]采用粒子群优化算法(Particle Swarm Optimization,PSO)对A计权的数字IIR滤波器系数进行搜索优化,取得了明显成效. 但PSO算法在优化过程中容易出现早熟收敛而陷入局部极值点,从而得不到全局最优解[10-11],尤其在加噪环境下,误差更为明显.

帝国竞争算法(Imperialist Competitive Algorithm,ICA)在滤波器的优化设计中,全局搜索能力和信息不依赖能力均高于其他智能优化算法[12]. 但该算法在系数搜索过程中也同样存在早熟收敛等不足,导致优化结果存在误差[13]. 据此,本文提出一种改进帝国竞争算法(Modified Imperialist Competitive Algorithm,MICA)的声级计频率计权数字滤波器设计方案. MICA在标准ICA算法的同化过程中添加混沌函数来增强算法的搜索可能性,引入克隆进化算子来有效引导算法向最优解方向搜索,最终得到滤波器的最优系数. 相比标准ICA,MICA具有搜索范围广,寻优精度高和优化性能好等特点.

本文针对双线性变换法实现声级计频率计权存在的误差,通过在ICA算法中添加混沌函数和引入克隆算子,设计MICA算法,并将MICA应用到频率计权数字IIR滤波器设计中. 仿真与实验数据表明,在加噪环境下,不同声信号级进行的頻率计权误差均能维持在10-2 dB数量级范围内,符合1级声级计的设计要求,证明了该方法的有效性.

4   结   论

本文针对双线性变换法设计声级计频率计权数字滤波器时出现误差较大的问题,提出了一种基于改进帝国竞争算法的声级计频率计权数字IIR滤波器设计方法. 为避免标准ICA早熟收敛而陷入局部最优,在同化阶段加入混沌函数以及帝国竞争阶段引入克隆进化算子,进一步提高算法的收敛精度. 对A计权的测试结果表明,本文提出的改进ICA算法,有效改善了双线性变换法的误差,优化效果明显. 且在加噪环境下,不同声信号级的计权误差均能维持在10-2 dB数量级范围内,符合1级声级计设计要求. 本文提出的方法不仅适用于声级计的频率计权优化设计,也适用于其他采用双线性变换设计数字滤波器引起的频率特性失真问题,具有较高的实际应用价值.

参考文献

[1]   ANSI Sl.42-2001  Design response of weighting networks for acoustical measurements [S]. New York:Acoustical Society of America,2001.

[2]    钟波,孙庆生,王雪晶,等. 声级计频率计权特性自动检定系统研究与实现[J]. 电声技术,2010,34(5):37—40.

ZHONG B,SUN Q S,WANG X J,et al. Design and realization of automatic calibration system on frequency weighting of sound level meter[J]. Audio Engineering,2010,34(5):37—40. (In Chinese)

[3]    IEC 61672-1  Sound level meters-Part 1:Specifications [S]. Geneva:International Electrotechnical Commission,2003.

[4]    杨昌棋,秦树人,张跃俊. 虚拟式噪声分析仪的数字计权与开发[J]. 重庆大学学报(自然科学版),2001,24 (5):59—61,66.

YANG C Q,QIN S R,ZHANG Y J. Digit weight and development of a virtual noise analyzer[J]. Journal of Chongqing University (Natural Science Edition),2001,24 (5):59—61,66. (In Chinese)

[5]    姚佳旭,朱磊,潘杨,等. 基于STM32的级联型IIR数字滤波器设计[J]. 电子测量技术,2018,41(17):95—99.

YAO J X,ZHU L,PAN Y,et al. Design of cascaded IIR digital filters based on STM32[J]. Electronic Measurement Technology,2018,41(17):95—99. (In Chinese)

[6]    刘强,陈仁义,刘琳,等. 改进的前馈FIR振动控制器[J].  振动与冲击,2009,28(2):107—110.

LIU Q,CHEN R Y,LIU L,et al. Improved feed forward FIR vibration controller [J]. Vibration and Shock,2009,28(2):107—110. (In Chinese)

[7]    金晖,何洁. 频率计权的全数字实现[J]. 仪器仪表学报,2006,27(S2):1495—1496.

JIN H,HE J. Digital design method of the frequency weighting [J]. Chinese Journal of Scientific Instrument,2006,27(S2):1495—1496.

[8]    KRISHNA B T. Design of fractional order differentiators using novel s to z transform[C]// Proceedings of the 2012 International Conference on Radar,Communication and Computing. Tiruvannamalai:IEEE,2012:268—271.

[9]    唐求,贾杨威,滕召胜,等. 基于粒子群优化的声级计A计权设计[J]. 仪器仪表学报,2015,36(4):856—862.

TANG Q,JIA Y W,TENG Z S,et al. Design of A-weighting in sound-level meters based on PSO algorithm[J]. Chinese Journal of Science Instrument,2015,36(4):856—862. (In Chinese)

[10]  LUITEL B,VENAYAGAMOORTHY G K. Differential evolution particle swarm optimization for digital filter design [C]// 2008 IEEE Congress on Evolutionary Computation. Hong Kong:IEEE,2008:3954—3961.

[11]  胡瑾秋,郭放,張来斌. 结合改进PSO算法和LSSVM的化工异常工况超早期监测预警研究[J]. 电子测量与仪器学报,2018,32(2):36—41.

HU J Q,GUO F,ZHANG L B. Study on ultra-early prediction of chemical abnormal situation based on improved PSO algorithm and LSSVM[J]. Journal of Electronic Measurement and Instrumentation,2018,32(2):36—41. (In Chinese)

[12]  ZHANG Y,WEI H,LIAO R,et al. A new support vector machine model based on improved imperialist competitive algorithm for fault diagnosis of oil-immersed transformers[J]. Journal of Electrical Engineering & Technology,2017,12(2):830—839.

[13]  邵永亮,常军. 运用改进帝国竞争算法识别结构模态参数[J]. 噪声与振动控制,2017,37(2):152—157.

SHAO Y L,CHANG J. Structural modal parameter identification based on improved imperialist competitive algorithm [J]. Noise and Vibration Control,2017,37(2):152—157. (In Chinese)

[14]  ANDRZEJ M,ANDRZEJ P. Digital-filter-based compensation of case effect in sound-level meters[J]. International Journal of electronics and telecommunications,2010,56(3):263—266.

[15]  ATASHPAZ G E,LUCAS C. Imperialist competitive algorithm:an algorithm for optimization inspired by imperialistic competition[C]// 2007 IEEE Congress on Evolutionary Computation. Singapore:IEEE,2007:4661—4667.

[16]  何存富,王志,刘秀成,等. 基于GA-PSO混合算法的钢杆磁特性参数识别方法[J]. 仪器仪表学报,2017,38(4):838—843.

HE C F,WANG Z,LIU X C,et al. Magnetic property parameter identification of steel pole based on GA-PSO hybrid algorithm [J]. Chinese Journal of Science Instrument,2017,38(4):838—843. (In Chinese)