考虑不确定测量和个体差异的非线性随机退化系统剩余寿命估计

发布时间：2019-03-21 15:27

【摘要】：剩余寿命估计是预测与健康管理的基础,是降低系统运行风险、提高系统安全性与可靠性的有效途径.针对工程实际中大量存在的非线性随机性退化系统,现有方法仅单独考虑了不确定测量或系统间个体差异对剩余寿命的影响,尚未实现同时考虑不确定测量和个体差异的剩余寿命估计.因此,本文首先建立了一种基于扩散过程的非线性退化模型,进一步通过建立的状态空间模型和Kalman滤波实现了同时考虑不确定测量和个体差异下的随机退化系统剩余寿命自适应估计,同时对漂移系数进行自适应估计,以获取非线性退化系统更加精确的剩余寿命估计.最后,将所提方法应用于疲劳裂纹和陀螺仪的监测数据,结果表明本文方法显著优于仅考虑不确定测量或仅考虑个体差异的寿命估计方法,具有潜在的工程应用价值.
[Abstract]:The remaining life estimation is the basis of the prediction and health management, which is an effective way to reduce the system running risk and improve the safety and reliability of the system. In view of the large number of non-linear stochastic degradation systems in the engineering practice, the existing method only considers the influence of the individual difference between the measurement or the system on the remaining life, and has not realized the estimation of the remaining life of the measurement and the individual difference. In this paper, a non-linear degradation model based on the diffusion process is firstly established, and the residual life-adaptive estimation of the random degradation system under uncertainty measurement and individual difference is further considered through the established state space model and the Kalman filter. At the same time, the self-adaptive estimation of the drift coefficient is carried out to obtain a more accurate residual life estimate of the non-linear degradation system. Finally, the method is applied to the monitoring data of the fatigue crack and the gyroscope, and the results show that the method is superior to the method of estimating the life span of only the measurement or the individual difference, and has the potential engineering application value.
【作者单位】：火箭军工程大学控制工程系;
【基金】：国家自然科学基金(61174030,61374126,61473094,61573365,61573366)资助~~
【分类号】：O213.2

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