期刊文献+

基于设备状态振动特征的比例故障率模型可靠性评估 被引量:49

Reliability Assessment Based on Equipment Condition Vibration Feature Using Proportional Hazards Model
下载PDF
导出
摘要 基于概率统计的传统可靠性评估方法一般依赖于失效寿命数据。但失效寿命数据需要通过寿命试验和加速寿命试验获取,对于大量的实时工作设备采用这种方法是不适宜的。这种情况下,基于设备状态的性能退化数据能够提供可靠性评估的重要信息。在集成失效数据可靠性建模技术和基于设备状态的振动信号特征提取的基础上,提出设备状态振动特征的比例故障率模型可靠性评估的新方法。该方法可以把底层信息(如设备运行状态特征的方均根、峭度)与高层信息(如可靠性统计学)之间建立联系,适合设备运行可靠性参数的估计,并能够提供有效的可靠性评估,为设备以可靠性为中心的基于状态的预防维修提供技术支持。通过在铁路机车轮对轴承上的应用实例说明该方法的合理性和有效性。 The traditional reliability assessment methods based on probability statistics depend on failure lifetime data which have to be obtained through life test and accelerated life test. It is not suitable to utilize this method for the real-time operating equipment. In such a case, the performance degradation data based on equipment condition can provide useful information about the reliability assessment for the equipment. By integrating traditional reliability modeling techniques with vibration signal feature extraction of equipment condition, a new method of reliability assessment based on equipment condition vibration feature by using proportional hazards model has been is proposed for the first time. This method can establish relationship between low-level information (such as condition parameters) and high-level information (like reliability statistics) to build relation. It is suitable for estimating reliability parameter of the equipment operation, and providing effective reliability assessment. Thereby providing technical support for the preventive maintenance of equipment based on condition with reliability as center. A practice example of locomotive wheel set bearing is given to demonstrate the rationality and effectiveness of this method.
出处 《机械工程学报》 EI CAS CSCD 北大核心 2009年第12期89-94,共6页 Journal of Mechanical Engineering
基金 国家重点基础研究发展计划资助项目(973计划 2005CB724106)
关键词 可靠性评估 比例故障率模型 设备状态 振动特征 Reliability assessment Proportional hazards model Equipment condition Vibration feature
  • 相关文献

参考文献22

  • 1JARDINE A K S, LIN D, BANJEVIC D. A review on machinery diagnostics and prognostics implementing condition-based maintenance[J]. Mechanical Systems and Signal Processing, 2006, 20(7): 1 483-1 510.
  • 2HESS S M, BITER W J, HOLLINGSWORTH S D. An evaluation method for application of cond/tion-based maintenance technologies[C]//IEEE Proceedings Annual Reliability and Maintainability Symposium, 2001: 240-245.
  • 3SARANGA H, KNEZEVIC J. Reliability prediction for condition-based maintained systems[J]. Reliability Engineering and System Safety, 2001, 71(2): 219-224.
  • 4LIAO Haitao, ZHAO Wenbiao, GUO Huairui. Predicting remaining useful life of an individual unit using proportional hazards model and logistic regression model[C]// IEEE Proceedings Annual Reliability and Maintainability Symposium, 2006: 127-132.
  • 5CHINNAM R B. On-line reliability estimation of individual components using degradation signal models[J]. IEEE Transactions on Reliability, 1999, 48(4): 403-412.
  • 6LU H, KOLARIK W J, LU S S. Real-time performance reliability rrediction[J]. IEEE Transactions on Reliability, 2001, 50(4): 353-357.
  • 7LU S S, LU H, KOLARIK W J. Multivariate performance reliability prediction in real-time[J]. Reliability Engineering and System Safety, 2001, 72 (1): 39-45.
  • 8LIN Changching, TSENG Hsienyu. A neural network application for reliability modeling and condition-based predictive maintenance[J]. The International Journal of Advanced Manufacturing Technology, 2005, 25(1): 174-179.
  • 9YONG Suna, LIN Maa, JOSEPH Mathew, et al. Mechanical systems hazard estimation using condition monitoring[J]. Mechanical Systems and Signal Processing, 2006, 20(5): 1 189-1 201.
  • 10COX D R. Regression models and life-tables(with discussion)[J]. Journal of the Royal Statistical Society, Series B (Methodological), 1972, 34(2): 187-220.

同被引文献419

引证文献49

二级引证文献445

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