中文摘要：

为解决声发射检测中信号采集时间长、信号量大、存储成本高的问题,提出了一种应用压缩感知理论（CS）的声发射信号采集方法,实现了应用匹配追踪算法（MP）和正交匹配追踪算法（OMP）对声发射信号进行重构,利用Matlab软件对原信号和重构信号进行参数化分析,同时对比MP算法和OMP算法对原信号的重构效果。实验结果表明：应用CS能够实现远低于传统Nyquist采样定律所要求的采样频率进行信号采样,同时实现数据的压缩;MP算法和OMP算法都能实现声发射信号的重构恢复,且OMP算法比MP算法恢复效果更好;对信号进行参数化分析,OMP算法对原信号的平均重构误差为5.56%,重构信号参数误差不到1%,表明通过压缩采样约30%的数据便可获取原声发射信号的主要信息。重构信号降低了采样率,节省存储空间,且信号不失真,CS理论在声发射无损检测领域有着广阔的应用前景。

英文摘要：

In order to solve the problem of long acquisition time,large quantity of data,and high cost in acoustic emission signal acquisition,a theory of compressed sensing（ CS） applied acoustic emission signal acquisition method was developed. The matching pursuit algorithm（ MP） and orthogonal matching pursuit algorithm（ OMP） to reconstruct the acoustic emission signal were applied to realize parametric analysis of the original signal and the reconstructed signal by using Matlab software,and to compare reconstruction effect of MP and OMP on the original signal. The experimental results show that applying CS can achieve far lower sampling frequency than conventional Nyquist sampling theorem sampling and data compression. MP and OMP can reconstruct acoustic emission signal,but the OMP is better than MP on recovery effect. Signal parametric analysis show that the average reconstruction error is 5. 56% by the OMP,signal reconstruction parametric error is less than 1% and the main information of the original acoustic emission signal can be obtain by compressing about 30% of sampling data. Reconstruction signal reduces signal sampling rate and saves storage spacewithout signal distortion,the CS has broad application prospects on acoustic emission nondestructive testing field.