摘要
采用声发射技术评估疲劳裂纹扩展状态时,评估结论会受到其它类型声发射信号和噪声的干扰。针对上述问题,在分析经验模态分解和独立分量分析特点的基础上,提出集合导数优化经验模态分解与独立分量分析相结合的声发射信号去噪盲分离方法,用于疲劳裂纹扩展声发射信号的处理。分别进行模拟声发射信号和疲劳裂纹扩展试验,采用上述方法对采集声发射信号进行去噪盲分离,结果表明:基于集合导数优化经验模态分解与独立分量分析的声发射信号去噪方法可有效去除噪声信号的干扰,准确分离出疲劳裂纹扩展声发射信号,为进行含裂纹结构的疲劳损伤状态评估和剩余寿命预测奠定基础。
This paper proposed a new method for signal denoising and blind separation for fatigue crack propagation acoustic emission,combined ensemble derivative optimization empirical mode decomposition with independent component analysis,based on the analysis of the characteristics of empirical mode decomposition and independent component analysis.Simulated acoustic emission signal and fatigue crack growth test are respectively carried out,the collected acoustic emission signals are de-noised and blind separated by the proposed method,the results show that the interference signals are removed effectively by the method based on ensemble derivative optimization empirical mode decomposition and independent component analysis,the fatigue crack propagation acoustic emission signal is separated accurately.This study lays a foundation of fatigue damage evaluation and residual life prediction.
作者
王兴路
贺利乐
贺瑞
石嘉堃
柴健湣
WANG Xinglu;HE Lile;HE Rui;SHI Jiakun;CAI Jianmin(School of Vehicle Engineering,Xi′an Aeronautical University,Xi′an 710077,China;School of Mechanical and Electrical Engineering,Xi′an University of Architecture and Technology,Xi′an 710055,China)
出处
《机械科学与技术》
CSCD
北大核心
2021年第10期1608-1613,共6页
Mechanical Science and Technology for Aerospace Engineering
基金
陕西省自然科学基础研究计划项目(2020JQ-908)
陕西省教育厅专项科研计划项目(20JK0695)
西安航空学院2020年省级大学生创新创业训练计划项目(S202011736079)。
关键词
声发射信号
去噪盲分离
集合导数优化经验模态分解
独立分量分析
疲劳裂纹扩展
acoustic emission signal
de-noising and blind separation
ensemble derivative-optimized empirical mode decomposition
independent components analysis
fatigue crack propagation
