摘要
针对复杂环境下破碎机衬板超声测厚的回波信号噪声难以压制的问题,提出一种基于粒子群算法(Particle Swarm Optimization,PSO)寻优变分模态分解(Variational Mode Decomposition,VMD)的噪声压制方法。首先研究分解尺度[K]和惩罚因子[α]两个初始参数对VMD算法分解效果的影响;然后通过PSO算法对VMD算法中的最佳参数组合进行寻优;再将该组最佳参数组合代入VMD算法中进行信号分解,通过互相关系数法选取本征模态函数(Intrinsic Mode Function,IMF)进行信号重构,得到降噪后的信号。仿真与实测结果表明,PSO寻优VMD的噪声压制方法在提高信噪比、降低均方误差、提高波形相似系数等性能指标方面效果显著,能有效压制衬板超声回波信号中的噪声,提高破碎机衬板测厚超声回波信号的可靠性。
Aiming at the difficulty to suppress the echo signal noise of ultrasonic thickness measurement of crusher liner in complex environment,a noise suppression method based on PSO optimized VMD is proposed.First of all,the influence of decomposition scale K and penalty factorαin variational mode decomposition algorithm on the decomposition effect of VMD algorithm is analyzed.And then,PSO algorithm is used to optimize the parameter combination of VMD algorithm,the optimal parameter combination is substituted into VMD algorithm for signal decomposition,and the effective intrinsic mode component is selected by the correlation coefficient method to reconstruct the signal to get the final denoising signal.The simulation and test results show that the noise suppression method of the PSO optimized VMD can improve the signal-to-noise ratio,reduce the mean square error and improve the waveform similarity factor significantly.This method can suppress the noise in the liner echo signal and improve the reliability of the thickness measurement of the lining plate of the crushers.
作者
蔡改贫
阮辽
赵鑫
郁慧
CAI Gaipin;RUAN Liao;ZHAO Xin;YU Hui(School of Mechanical and Electrical Engineering,Jiangxi University of Science and Technology,Ganzhou 341000,Jiangxi,China;Jiangxi Engineering Research Center of Mining and Metallurgy,Ganzhou 341000,Jiangxi,China)
出处
《噪声与振动控制》
CSCD
北大核心
2024年第3期67-74,共8页
Noise and Vibration Control
基金
江西省科技厅重点研发计划资助项目(20181ACE50034)。
关键词
声学
噪声压制
变分模态分解
粒子群算法
信号重构
超声测厚
acoustics
noise suppression
variational mode decomposition
particle swarm optimization
signal reconstruction
ultrasonic thickness measurement
