摘要
针对航空航天产品高可靠性、长寿命的特点,通过综合时序模型对随机序列自拟合性强与短期预测精度高的优点,提出了两类基于性能退化数据的产品可靠性评估时序模型方法.首先,从性能退化量分布的角度出发,在假设退化量分布类型不随时间变化的前提下,利用时间序列建立了性能退化分布参数的分析模型,进而根据可靠度与性能退化量分布的关系进行可靠性评估.然后,从退化轨迹的角度出发,对所有样本的退化轨迹进行时序分析与建模,外推伪失效区间与伪失效寿命值,进而采用完全寿命试验数据的统计方法进行可靠性评估.最后,对某金属材料疲劳裂纹扩展数据进行可靠性评估与寿命预测,结果表明该方法具有良好的稳健性.
Time series model has the advantage of strong self-adjustment for stochastic process and high precision for prediction. For the high-reliability and long-life products in the field of aeronautics and astronau- tics, two methods based on time series model were proposed to evaluate reliability and predict lifetime using performance degradation data. Firstly, assuming that the degradation measure follows the same distribution family but its parameters may change with time. Non-stationary time series were used to fit distribution parameters. According to the relation between reliability and degradation measure distribution, the corresponding reliability functions were developed. Then, degradation paths of all samples were described by time series mod- el. False failure interval and the false lifetime value could be predicted and reliability was obtained by statistical method from complete lifetime test data. Finally, the alloy fatigue crack data was used to evaluate reliability and predict lifetime, and the reasonable results show that the proposed method has better robustness.
出处
《北京航空航天大学学报》
EI
CAS
CSCD
北大核心
2009年第5期644-648,共5页
Journal of Beijing University of Aeronautics and Astronautics
基金
国家部委基金资助项目(914A19039106HK0108)
关键词
可靠性
时序模型
退化量分布
退化轨迹
reliability
time series model
degradation measure distribution
degradation paths
作者简介
龙琦（1982-），女，安徽六安人，硕士生，oiuybz@hotmail．com.
