具有不确定测量的非线性随机退化系统剩余寿命预测

摘要/Abstract

摘要：

摘要：提出了一类同时考虑不确定测量和非线性随机退化的退化建模方法，通过Kalman滤波技术对受不确定测量影响的潜在退化状态进行实时估计；基于此，通过首达时间的概念得到了同时考虑退化非线性特征、退化状态不确定性及测量不确定性的剩余寿命分布；此外，提出了一种基于极大似然方法的退化模型参数估计方法，并通过陀螺仪的退化测量数据验证了所提方法可以提高剩余寿命估计的准确性.

关键词: 预测与健康管理, 寿命预测, 退化建模, Kalman滤波, 不确定测量

Abstract:

Abstract： A class of degradation modeling approach was proposed, in which the nonlinear stochastic deterioration and uncertain measurements of the system were considered simultaneously, and the Kalman filtering technique was utilized to estimate the underlying degradation state. Based on the estimated degradation state, the analytical RUL distribution was derived according to the concept of the first passage time which accounted for the uncertainties in the estimated degradation state and measurements, and the effect of the degradation nonlinearity. Additionally, a parameter estimation method for the developed model was presented based on the maximum likelihood method. Finally, a case study of the gyros verified that the proposed method could improve the accuracy of the predicted RUL.

Key words: prognostics and health management, life prediction, degradation modeling, Kalman filter, uncertain measurements

中图分类号:

TP 273

司小胜1,胡昌华1,李娟2,孙国玺3,张琪1. 具有不确定测量的非线性随机退化系统剩余寿命预测[J]. 上海交通大学学报（自然版）, 2015, 49(06): 855-860.

SI Xiaosheng1,HU Changhua1,LI Juan2,SUN Guoxi3,ZHANG Qi1. Remaining Useful Life Prediction of Nonlinear Stochastic Degrading Systems Subject to Uncertain Measurements[J]. Journal of Shanghai Jiaotong University, 2015, 49(06): 855-860.

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