摘要
针对强背景噪声下微弱的脉冲涡流检测信号的特征量难以准确提取的问题,提出一种基于维纳自适应滤波和主成分分析的脉冲涡流信号降噪方法。该方法首先利用自适应维纳滤波在最小均方误差意义上所具有的最优特性,对脉冲涡流信号进行预处理;再将预处理信号与参考信号进行差分以消除部分系统噪声;最后利用主成分分析提取差分信号的主成分特征,通过设定阈值选取合适数目的主成分量进行重构,得到了具有高信噪比的脉冲涡流差分信号。在Q235阶梯板试件上进行脉冲涡流检测实验,运用该方法对被噪声干扰严重的检测信号进行处理,结果表明所提方法能够有效的消除强噪声对检测信号的干扰,大幅提高信噪比,是一种有效的脉冲涡流检测信号降噪方法。
Pulsed eddy current( PEC) testing signals are rather weak and often interfered by strong background noises,which make it difficult to efficiently extract signal features. In this paper,a novel PEC signal de-noising method is proposed based on the Wiener filtering and principal component analysis( PCA). Firstly,PEC signals are preprocessed by the adaptive Wiener filtering to generate a preliminary result based on the criteria of Minimum Mean Square Error( MMSE). Then,the preprocessed signals are subtracted by a reference signal to partly eliminate the system noise. Afterwards,the principal component features of differential signals are extracted by using PCA,and adequate number of principle components at a given threshold is selected to perform the signal reconstruction scheme. Following the above de-noising procedures,a PEC signal with high signal-to-noise ratio( SNR) is finally obtained. Validation experiment is also carried out on a step wedge Q235 steel plate. The presented method is applied to process experimental PEC signals severely interfered by noises. The results show that strong noises in experimental signals are effectively eliminated and the SNR is significantly improved,proving the presented de-nosing method to be effective and reliable.
作者
徐志远
伍权
XU Zhiyuan;WU Quan(Engineering Research Center for Complex Path Processing Technology and Equipment,Ministry of Education,Xiangtan University,Xiangtan Hu’nan 411105,China;School of Mechanical Engineering,Xiangtan University,Xiangtan Hu’nan 411105,China)
出处
《传感技术学报》
CAS
CSCD
北大核心
2019年第3期411-417,共7页
Chinese Journal of Sensors and Actuators
基金
国家自然科学基金项目(51505406)
关键词
信号去噪
维纳滤波
主成分分析
脉冲涡流
signal de-noising
Wiener filter
principal component analysis
pulsed eddy current
