中文摘要：

为实现圆轴中损伤缺陷的识别与量化,解决超声信号处理过程中信号模式混叠和信号处理过程复杂的问题,以波动理论为基础,结合主动传感技术,利用快速集成经验模式分解（Fast Ensemble Empirical Mode Decomposition,FEEMD）算法对接收的导波信号进行分解,从分解的模式分量中提取出特征分量,提出基于FEEMD的透射系数并用于表征损伤严重程度。有限元仿真与实验结果表明,随着损伤程度的增加,透射系数单调递减,据此可检测出轴中所存在的缺陷并判定缺陷严重程度,可为轴类构件的结构健康监测提供一定依据。

英文摘要：

In order to realize the identifwation and quantification of damage defects in circular shaft,and solve the problem of signal mode mixing and signal processing efficiency in ultrasonic signal processing, based on wove theory and active seusing technology,the paper uses Fast Ensemble Empirical Mode Decomposition （FEEMD） algorithm for data processing,extract the feature component from the decomposition of the pattern component,and the severity of damage was defined by the transmission coefficient.The simulation and experimental results show that：with the increase of damage degree, the transmission coeffwient has changed according to some certain rules, thus can effectively detect the existing defect of the shaft, and characterization of the defect size ,it provides a certain basis for the shaft component of the structural health monitoring.