文献详情
Degradation reliability modeling based on an independent increment process with quadratic variance
文献类型期刊
作者Wang, Zhihua[1];Zhang, Yongbo[2];Wu, Qiong[3];Fu, Huimin[4];Liu, Chengrui[5];Krishnaswamy, Sridhar[6]
机构
通讯作者Zhang, YB (reprint author), Beihang Univ, Sch Aeronaut Sci & Engn, Beijing 100191, Peoples R China.
来源信息年:2016  卷:70-71  页码范围:467-483  
期刊信息MECHANICAL SYSTEMS AND SIGNAL PROCESSING影响因子和分区  ISSN:0888-3270
关键词Degradation test; Reliability analysis; Failure time distribution; Independent increment process; One-stage parameter estimation; Quadratic variance function
增刊正刊
摘要Degradation testing is an important technique for assessing life time information of complex systems and highly reliable products. Motivated by fatigue crack growth (FCG) data and our previous study, this paper develops a novel degradation modeling approach, in which degradation is represented by an independent increment process with linear mean and general quadratic variance functions of test time or transformed test time if necessary. Based on the constructed degradation model, closed-form expressions of failure time distribution (FED) and its percentiles can be straightforwardly derived and calculated. A one-stage method is developed to estimate model parameters and FTD. Simulation studies are conducted to validate the proposed approach, and the results illustrate that the approach can provide reasonable estimates even for small sample size situations. Finally, the method is verified by the FCG data set given as the motivating example, and the results show that it can be considered as an effective degradation modeling approach compared with the multivariate normal model and graphic approach. (C) 2015 Elsevier Ltd. All rights reserved.
收录情况SCIE(WOS:000366765500028)  EI(20153801295401)  
所属部门航空科学与工程学院
DOI10.1016/j.ymssp.2015.08.021
学科工程:机械
百度学术Degradation reliability modeling based on an independent increment process with quadratic variance
语言外文
被引频次4
人气指数28
浏览次数28
基金National Natural Science Foundation of China [11202011]; Fundamental Research Funds for the Central Universities [YWK13HK11]; Beijing Natural Science Foundation [3154034]; National Basic Research Program of China (973 Program) [2012CB720000]
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