期刊文献+

系统健康管理中的寿命模型仿真研究 被引量:1

Research on Life Model Simulation of the System Health Management
下载PDF
导出
摘要 在航空、航天、通信等领域,高可靠性和长寿命设计的产品所占比重逐渐增大;性能退化状态评估和剩余使用寿命预测技术在提高该类产品安全性和维护效率、降低全寿命周期成本等方面意义重大;针对当前国内健康管理研究中缺乏寿命及可靠性基础数据的现状,介绍了系统寿命预测的典型过程,重点分析了寿命模型研究和仿真中存在的若干问题,旨在建立实现简单且与实际系统运行过程相似度高的寿命模型的建模方法,为后续系统性能状态评估提供有效的数据支持。 In the areas such as aviation,aerospace and communication,high reliability and tong life design products are widely used.Assess of the performance degradation status or prediction of the remaining useful life have great significance in enhancing system safety,increasing maintenance efficiency and reducing total life cycle cost of the system.To cover the shortage of life and reliability data in domestic health management,the system representative modeling process is presented.Especially,the existent problems for further research of life model and modeling simulation are investigated,which is to obtain the life model easy to fulfill and with high-fidelity.Then it can be hoped to provide efficient data support for further performance degradation status assessment.
出处 《计算机测量与控制》 2016年第5期279-283,共5页 Computer Measurement &Control
基金 学校基金(2015QDJ045)
关键词 性能退化 寿命模型 系统仿真 performance degradation life model system simulation
  • 相关文献

参考文献17

  • 1Tuchhand Brian A. Implementation of Prognostics and Health Man- agement for Electronic Systems [D]. Park: University of Mary- land. 2007.
  • 2Bhaskar Saha. A Bayesian Framework for Remaining Useful Life Estimation [J]. Association for the Advancement of Artificial Intel- ligence. 2007.
  • 3周月阁,叶雪荣,翟国富.基于性能退化和Monte-Carlo仿真的系统性能可靠性评估[J].仪器仪表学报,2014,35(5):1185-1191. 被引量:20
  • 4王玉明.基于性能退化数据的电子产品可靠性分析研究[D].石家庄:军械工程学院博士论文,2009.
  • 5Patrick W. Kalgren. Defining PHM, A Lexical Evolution of Main- tenance and Logistics [A]. IEEE Autotestcon [C], Anaheim, CA. 2006. 9, 18-21: 357.
  • 6Van Tung Trana. Machine Performance Degradation Assessment and Remaining Useful Prediction using Proportional Hazard Model- ing and Support Vector Machine [J]. Mechanical Systems and Sig- nal Processing, 2012, 32: 320-330.
  • 7Gu J. Prognostics Implementation Methods for Electronics [A]. Reliability and Maintainability Symposium. Annual [C]. 2007. 1. Orlando: 101 - 106.
  • 8Michael J. Roemer. An Overview of Selected Prognostic Technolo- gies with Application to Engine Health Management [A]. ASME Turbo Expo [C]. Barcelona, Spain. 2006. 5. 8-11: 2.
  • 9Pradeep Shetty. A Hybrid Prognostic Model Formulation System Iden- tification and Health Estimation of Auxiliary Power Units [A]. IEEE Aerospace Conference [C]. Big Sky, MT. 2006 : 2 - 5.
  • 10Philip L. Dussauh. Field Data Evaluation and Continuous Health Assessment of Critical Avionics Subsystem Degradation [A]. Aer- ospace Conference [C]. IEEE, 2006:1 - 8.

二级参考文献17

  • 1SANKALITA S,JOSE R C,VLADISLAV V,et al.accelerated aging with electrical overstress and prognostics for power MOSFETs[C].IEEE Energytech.2011:1-6.
  • 2NISHAD P,JOSE C,DIGANTA D,et al.Precursor parameter identification for insulated gate bipolar transistor(IGBT) prognostics[J].IEEE Transactions on Reliability,2009,58(2):271-276.
  • 3ZHOUYG,YEXR,ZHAIGF.Degradation model and maintenance strategy of the electrolytic capacitors for electronics applications[C].2011 Prognostics and System Health Management Conference,2011:1-6.
  • 4YE Z S,WANG Y,TSUI K L,et al.Degradation data analysis using wiener processes with measurement errors[J].IEEE Transactions on Reliability,2013,62(4):772-780.
  • 5YUAN X X,PANDEY M D.A nonlinear mixed-effects model for degradation data obtained from in-service inspections[J].Reliability Engineering and System Safety,2009,94:509-519.
  • 6LAURENCIU N C,COTOFANA S D.A nonlinear degradation path dependent end-of-life estimation framework from noisy observations[J].Microelectronics Reliability,2013,53:1213-1217.
  • 7FAN J J,YUNG K C,MICHAEL P.Lifetime estimation of high-power white LED using degradation data driven method[J].IEEE Transactions on Device and Materials Reliability,2012,12(2):470-477.
  • 8CHIEN-YU P,SHENG-TSAING T.Mis-specification snalysis of linear degradation Models[J].IEEE Transactions on Reliability,2009,58(3):444-455.
  • 9YOUNG K S,GORDON J S.A new sample based ap proach to predict system performance reliability[J].IEEE Transaction on Reliability,2008,57(2):322-330.
  • 10何英,周东华,俞容.一种基于性能退化数据的电子设备缓变故障预报方法[J].仪器仪表学报,2008,29(7):1526-1529. 被引量:8

共引文献19

同被引文献8

引证文献1

二级引证文献6

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部