Reliability Assessment from Performance Degradation Data Based on Time Series Model

被引:0
|
作者
You Qi [1 ]
Ma Xiaobing [1 ]
Zhao Yu [1 ]
机构
[1] Beijing Univ Aeronaut & Astronaut, Dept Syst Engn Engn Technol, Beijing 100083, Peoples R China
关键词
Degradation Measure Distribution; Time-Dependent Parameters; Time Series Model; Reliability Assessment;
D O I
暂无
中图分类号
O29 [应用数学];
学科分类号
070104 ;
摘要
To evaluate reliability and predict lifetime for products from performance degradation data. a new method based oil degradation measure distribution is proposed. Assume that the degradation measure follows the same distribution family but its parameters may change with time, dynamic data of time-dependent parameters can be modeled by autoregressive integrated moving average (ARIMA), and the corresponding reliability functions are then developed. The method has the advantages of self-adjustment with time series model for stochastic process and high precision for prediction. and effectively overcomes human factors influences caused by the hypothesis of time-dependent parameter distributions, so the method has better robustness. An example of reliability assessment is given at last, which can illustrate the validity and feasibility of the presented method.
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页码:236 / 240
页数:5
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