摘要
为对水轮机空化声发射信号进行降噪并提取其时频特征,提出一种基于改进哈里斯鹰算法(IHHO)和波动散布熵(FDE)的降噪和特征提取方法。首先,利用秃鹰搜索算法(BES)的螺旋搜索机制改进哈里斯鹰算法(HHO)的全局搜索阶段。然后,以散布熵差异互相关系数为适应度函数,利用IHHO对VMD进行参数寻优,对信号进行最优VMD分解和相关系数阈值重构从而实现降噪。最后,提取其能量和波动散布熵特征,分析其随空化系数变化的关系。结果表明:相较于灰狼-布谷鸟(GWO-CS)和HHO算法,IHHO对VMD寻优的降噪效果更好;随着空化系数减小,声发射信号能量呈现先增加、再减小、再增加、再减小的趋势,波动散布熵值呈现先减小后增大的趋势。
In order to reduce the noise and extract time-frequency features of acoustic emission signals induced by hydraulic turbine cavitation,a denoising and feature extraction method based on Improved Harris Hawks Optimization algorithm(IHHO)and Fluctuation-Based Dispersion Entropy(FDE)was proposed.Firstly,the global search stage of the Harris Hawks Optimization algorithm(HHO)was improved by utilizing the spiral search mechanism of the Bald Eagle Search algorithm(BES).Then,with the dispersion entropy difference correlation coefficient as the objective function,IHHO was used to find the optimal parameters of VMD.The optimal parameters of VMD were used to decompose the signal,and then the signal was reconstructed based on the correlation coefficient threshold to achieve noise reduction.Finally,the energy and fluctuation-based dispersion entropy features of the acoustic emission signal were extracted,and the relationship between the variation of cavitation coefficient and the features was analyzed.The results show that compared to the Grey Wolf-Cuckoo algorithm(GWO-CS)and HHO,the IHHO has a better denoising effect on optimizing VMD parameters.The energy of the acoustic emission signal increases first and subsequently decreases as the cavitation coefficient decreases,and with continuous decreasing of the cavitation coefficient,the energy of sound emission signals fluctuates.The fluctuation-based dispersion entropy shows a trend of decreasing first and then increasing when the cavitation coefficient decreases.
作者
刘忠
刘圳
邹淑云
周泽华
乔帅程
LIU Zhong;LIU Zhen;ZOU Shuyun;ZHOU Zehua;QIAO Shuaicheng(School of Energy and Power Engineering,Changsha University of Science and Technology,Changsha 410114,China)
出处
《噪声与振动控制》
北大核心
2025年第2期70-75,111,共7页
Noise and Vibration Control
基金
国家自然科学基金资助项目(52079011)
湖南省自然科学基金资助项目(2023JJ30032)。
关键词
声学
水轮机
空化
声发射
降噪
哈里斯鹰优化算法
秃鹰搜索算法
acoustics
hydraulic turbine
cavitation
acoustic emission
noise reduction
Harris hawks optimization algorithm
bald eagle search algorithm
