摘要
针对滚动轴承的磨损这一时变随机退化过程,采用Gamma过程进行建模,开展了多组定时递进的加速寿命试验,按照标准GB T 25769—2010测量得到了对应不同试验时长轴承的游隙数据,通过极大似然法与遗传算法对该过程的尺度参数与形状参数进行了最优估计,参数估计的结果验证了Gamma过程的非齐次性质。最后,将建立的退化过程模型与原始数据进行对比,模型拟合一致性较好。
Aimed at the time-varying random degradation process of rolling bearing wear,Gamma process was adopted to model and we carried out multiple groups of timed progressive accelerated life tests.According to the standard GB/T 25769-2010,clearance data of bearings with different test durations were obtained.The maximum likelihood method and genetic algorithm were used to estimate the scale parameters and shape parameters of the Gamma process.The results of parameter estimation verified the non-homogeneous nature of the Gamma process.Finally,the established degradation process model was compared with the original data,and the model fit was consistent.
作者
王延忠
鄂世元
谢斌
WANG Yanzhong;E Shiyuan;XIE Bin(School of Mechanical Engineering&Automation,Beihang University,Beijing 100191,China)
出处
《新技术新工艺》
2023年第4期74-76,共3页
New Technology & New Process
基金
国家重点研发计划项目(2019YFB2004400)。
关键词
随机过程
滚动轴承
磨损
参数估计
Gamma过程
随机退化
stochastic process
rolling bearing
wear
parameter estimation
Gamma process
random degradation
