摘要
针对飞行器结构系统声发射信号的非线性与非平稳特征,为实现飞行器结构部件的有效健康监测,提出了基于经验模态分解包络谱的飞行器健康诊断方法。该法首先对由声发射传感器募集到的飞行器关键部件原始声发射信号进行经验模态分解(EMD),提取其固有频率段的固有模态函数(IMF)信息,然后运用Hilbert变换对其进行处理得到各IMF的包络信号,由此可得其包络谱。通过包络谱的特征信息便可实现对飞行器结构部件的健康诊断。将该方法应用于某飞机真实水平尾翼疲劳试验所募集的声发射信号,结果表明,该法可监测出飞行器水平尾翼的健康状态,适用于飞行器结构部件的健康监测。
According to the non-linearity and non-stationary of the aircraft acoustic emission （AE） signals,a health diagnosis approach based on empirical mode decomposition （EMD） envelope spectrum was proposed to effectivly monitor the aircraft structural components＇ health. In this approach,the AE signals of the aircraft key parts were decomposed into number of IMF,and then the envelope spectrum was obtained by Hilbert transform. Finally,the aircraft structural components＇ health monitoring can be implemented through the fault signal characteristic information. This method was used to analyze the AE signal in the fatigue test of the horizontal tail,and the results showed that this method can highlight the aircraft fault signal characteristics and increase the accuracy of fault diagnosis.
出处
《压电与声光》
CSCD
北大核心
2009年第6期807-810,共4页
Piezoelectrics & Acoustooptics
基金
国家航空科学基金资助项目(2007ZD54006)
中国博士后科学基金资助项目(20070421062)
辽宁省教育厅科研基金资助项目(2008544)
沈阳航空工业学院博士启动基金资助项目(06YB19)
关键词
声发射
经验模态分解
包络谱
健康诊断
acoustic emission EMD envelope spectrum health diagnosis
