摘要
为改善滤波-x最小均方(filtered-x least mean square,FxLMS)算法在噪声主动控制时无法兼顾收敛速度和稳态误差的问题,提出了基于sigmoid-sinh分段函数的FxLMS(SSFxLMS)算法,并引入蚁狮算法对SFxLMS(sigmoid filtered-x least mean square)、ShFxLMS(sinh filtered-x least mean square)、SSFxLMS算法的参数进行优化。分别采用高斯白噪声和实测簇绒地毯织机噪声为输入信号,采用FxLMS、SFxLMS、ShFxLMS、SSFxLMS算法进行噪声主动控制仿真,对比分析这4种算法的性能。结果表明:与其他3种算法相比,采用SSFxLMS算法对高斯白噪声和簇绒地毯织机噪声进行控制时,误差信号的平均绝对值更小,平均降噪量与收敛速度也有大幅度提升。由此可知,SSFxLMS算法有效改善了FxLMS算法无法兼顾收敛速度和稳态误差的问题,研究结果为噪声主动控制算法设计提供了一定的参考。
In order to improve the problem that the filtered-x least mean square(FxLMS)algorithm can not give consideration to both the convergence speed and the steady-state error in active noise control,the SSFxLMS algorithm based on sigmoid-sinh subsection function was proposed,and the ant lion algorithm was introduced to optimize the parameters of sigmoid filtered-x least mean square(SFxLMS),sinh filtered-x least mean square(ShFxLMS),and SSFxLMS algorithms.Gaussian white noise and actual tufted carpet loom noise were used as input signals respectively,and FxLMS,SFxLMS,ShFxLMS,SSFxLMS algorithms were used for active noise control simulation,and the performance of these four algorithms was compared and analyzed.The results show that compared with the other three algorithms,when SSFxLMS algorithm is used to control Gaussian white noise and tufted carpet loom noise,the average absolute value of error signal is smaller,and the average noise reduction and convergence speed are also greatly improved.It can be seen that SSFxLMS algorithm effectively improves the problem that FxLMS algorithm can not give consideration to both the convergence speed and the steady-state error.The research results provide a certain reference for the design of active noise control algorithm.
作者
李飞
黄双
郭辉
徐洋
傅伟
LI Fei;HUANG Shuang;GUO Hui;XU Yang;FU Wei(School of Mechanical and Automotive Engineering,Shanghai University of Engineering Science,Shanghai 201620,China;College of Mechanical Engineering,Donghua University,Shanghai 201620,China;Zibo Technician College,Zibo 255000,Shandong,China)
出处
《东华大学学报（自然科学版）》
CAS
北大核心
2024年第1期93-100,共8页
Journal of Donghua University(Natural Science)
基金
国家自然科学基金资助项目(51905331,51675094)
上海市优秀学术/技术带头人计划资助项目(21XD1401100)
上海市新能源汽车振动噪声测试与评价技术专业服务平台基金资助项目(18DZ2295900)
上海工程技术大学青年科研团队培育计划(QNTD202112)。
关键词
噪声主动控制
变步长
滤波-x最小均方算法
蚁狮算法
active noise control
variable step-size
filtered-x least mean square algorithm
ant lion algorithm
