Active control of workspace noise based on ChFxLMS algorithm

LI Fei; HUANG Shuang

doi:10.12299/jsues.22-0013

Volume 36 Issue 3

Jun. 2022

Turn off MathJax

Article Contents

Article Navigation > Journal of Shanghai University of Engineering Science > 2022 > 36(3): 284-289

LI Fei, HUANG Shuang. Active control of workspace noise based on ChFxLMS algorithm[J]. Journal of Shanghai University of Engineering Science, 2022, 36(3): 284-289. doi: 10.12299/jsues.22-0013

Citation:

LI Fei, HUANG Shuang. Active control of workspace noise based on ChFxLMS algorithm[J]. Journal of Shanghai University of Engineering Science, 2022, 36(3): 284-289. doi: 10.12299/jsues.22-0013

LI Fei, HUANG Shuang. Active control of workspace noise based on ChFxLMS algorithm[J]. Journal of Shanghai University of Engineering Science, 2022, 36(3): 284-289. doi: 10.12299/jsues.22-0013

Citation:

LI Fei, HUANG Shuang. Active control of workspace noise based on ChFxLMS algorithm[J]. Journal of Shanghai University of Engineering Science, 2022, 36(3): 284-289. doi: 10.12299/jsues.22-0013

PDF( 2931 KB)

Active control of workspace noise based on ChFxLMS algorithm

doi: 10.12299/jsues.22-0013

LI Fei,
HUANG Shuang^,

School of Mechanical and Automotive Engineering, Shanghai University of Engineering Science, Shanghai 201620, China

Received Date: 2022-01-19
Publish Date: 2022-06-30

Abstract

Abstract

To improve the deficiency that the traditional filter-x least mean square (FxLMS) algorithm can not take into account the steady-state error and convergence speed, a variable step size FxLMS (Cosh-FxLMS, ChFxLMS) algorithm based on cosh function was proposed. The relationship between the error signal and the step factor was established by using the cosh function, so that step factor could adjust continuously according to the characteristics of the cosh function. The influence of different parameters on the performance of ChFxLMS algorithm was analyzed to provide guidance for the selection of algorithm parameters. And the sinusoidal signal and measured loom signal were used as input signals to verify the performance of ChFxLMS algorithm. It was compared with FxLMS algorithm and variable step size FxLMS algorithm based on sigmoid function (Sigmoid-FXLMS, SFFxLMS algorithm). The simulation results show that the performance of ChFxLMS algorithm has achieved good control results in time domain and frequency domain. Through comparative analysis, the algorithm can greatly reduce the steady-state error and improve the convergence speed. The research results will provide a new idea for active noise control in workspace.
- active noise control,
- ChFxLMS algorithm,
- steady-state error,
- convergence speed

FullText(HTML)

References(13)

References

[1]	胡异丁, 王凤森, 杨敏, 等. 一种改进变步长LMS自适应滤波算法[J] . 计算机仿真,2020,37(7):291 − 295. doi: 10.3969/j.issn.1006-9348.2020.07.057
[2]	韩啸, 陈钟荣. 一种改进反正切函数的变步长LMS算法[J] . 中国科技论文,2019,14(7):759 − 764,772. doi: 10.3969/j.issn.2095-2783.2019.07.010
[3]	吴瑶, 张海霞. 一种变步长LMS自适应滤波的改进算法[J] . 通信技术,2021,54(2):307 − 311.
[4]	洪丹枫, 苗俊, 苏健, 等. 一种变步长凸组合LMS自适应滤波算法改进及分析[J] . 电子学报,2014,42(11):2225 − 2230. doi: 10.3969/j.issn.0372-2112.2014.11.015
[5]	陆森林, 默超. 车内ANC系统次级通道辨识及仿真研究[J] . 重庆理工大学学报(自然科学),2016,30(3):22 − 27.
[6]	GUO H, WANG Y S, LIU N N, et al. Active interior noise control for rail vehicle using a variable step-size median-LMS algorithm[J] . Mechanical Systems and Signal Processing,2018,109:15 − 26. doi: 10.1016/j.ymssp.2018.02.040
[7]	束建华, 付志浩. 改进FxLMS算法在主动振动控制中的应用[J] . 计算机工程与应用,2015,51(12):230 − 234. doi: 10.3778/j.issn.1002-8331.1411-0325
[8]	张帅, 王岩松, 张心光. 汽车车内噪声主动控制变步长NFB−LMS算法[J] . 声学技术,2019,38(6):680 − 685.
[9]	HUANG B Y, XIAO Y G, SUN J W, et al. A variable step-size FXLMS algorithm for narrowband active noise control[J] . Speech & language processing,2013,21(2):301 − 312.
[10]	MENG H, CHEN S M. A modified adaptive weight-constrained FxLMS algorithm for feedforward active noise control systems[J] . Applied Acoustics,2020,164:1 − 8.
[11]	褚轶景, 麦卓明, 蔡陈之, 等. 一种新型基于分布式FxLMS的主动噪声控制算法与空间平滑[J] . 南京大学学报(自然科学),2021,54(4):683 − 688.
[12]	ZHU W Z, LUO L, XIE A T, et al. A novel FELMS-based narrowband active noise control system and its convergence analysis[J] . Applied Acoustics,2019,156:229 − 245. doi: 10.1016/j.apacoust.2019.07.003
[13]	徐洋, 张晓蕾, 盛晓伟, 等. 基于MEEMD−AIC的簇绒地毯织机噪声源识别方法[J] . 振动、测试与诊断,2018,38(6):1176 − 1181,1292.