Reliability Evaluating Theory for Data Sample with Unknown Priori Information

摘要：

　　Hierarchical maximum entropy Bayesian method is proposed to establish the reliability evaluation model for data sample with unknown priori information.The probability density functions are calculated for different time series using the maximum entropy principles and the Bayesian method is utilized to obtain the posterior sample information for different time intervals.The values of performance continuity relative reliability for time series data sample can be calculated during the corresponding time intervals and the failure degree maintaining optimum performance status in the future can be predicted.

关键词： data sample hierarchical maximum entropy Bayesian method unknown priori information intrinsic time series probability density function

作者: Liang Ye Xintao Xia Zhen Chang

作者单位: School of Mechanical Engineering,Northwestern Polytechnical University,Xian,China Mechatronical Engineering College,Henan University of Science and Technology,Luoyang,China Hangzhou Bearing Test & Research Center,Hangzhou,China

会议类型: 国际会议

会议名称: 2018 3rd International Conference on Computer Science and Information Engineering (ICCSIE 2018) 2018第三届计算机科学与信息工程国际会议(ICCSIE 2018)

会议地点: 西安

会议语种:英文

页码: 402-406

在线出版日期: 2018-09-21（万方平台首次上网日期，不代表论文的发表时间）