摘要
为了有效地对飞行器的健康状况进行诊断,将EMD-ARMA模型引入到飞行器健康诊断中,提出基于AR-MA(n,n-1)模型参数的健康诊断方法.采用EMD模型将飞行器关键部件的声发射信号进行分解,得到多个内禀模态分量IMF,选取包含主要信息的IMF分量建立ARMA(n,n-1)模型,采用长自回归模型法进行参数估计,得到模型主要的自回归参数,绘出模型参数的细化图用以健康诊断.对某型号真实飞行器关键结构部件的健康监测实验表明,该方法可以有效地诊断出飞行器关键结构部件的疲劳裂纹.
To effectively diagnose the aircraft structure components health status,a new kind of health diagnosis approach for the aircraft,based on EMD and ARMA model,is proposed in this paper.The advanced acoustic emission technique is used to monitor the aircraft stabilizer health state and get the AE information.And the AE signal is decomposed into the limited IMF by the EMD.Then the first two IMF components were used to set up ARMA (n,n-1) model with the method of long autoregressive model.Then we can get the auto-regressive parameters of the ARMA model,further we can draw the thinned figures of the auto-regressive parameters to diagnose the health status of aircraft.Experiments show that this method can effectively monitor the fatigue crack of the aircraft structure components.
出处
《大庆石油学院学报》
CAS
北大核心
2010年第2期108-112,共5页
Journal of Daqing Petroleum Institute
基金
航空科学基金资助项目(2007ZD54006)
