Whitmore G A
McGill University, Faculty of Management, Montreal, Quebec, Canada.
Lifetime Data Anal. 1995;1(3):307-19. doi: 10.1007/BF00985762.
Most materials and components degrade physically before they fail. Engineering degradation tests are designed to measure these degradation processes. Measurements in the tests reflect the inherent randomness of degradation itself as well as measurement errors created by imperfect instruments, procedures and environments. This paper describes a statistical model for measured degradation data that takes both sources of variation into account. The degradation process in the model is taken to be a Wiener diffusion process. The measurement errors are assumed to be independent normal random outcomes that are independent of the degradation process. The paper describes inference procedures for the model and discusses some practical issues that must be considered in dealing with the statistical problem. A case study is presented.
大多数材料和部件在失效前会发生物理降解。工程降解测试旨在测量这些降解过程。测试中的测量反映了降解本身固有的随机性以及由不完善的仪器、程序和环境产生的测量误差。本文描述了一种针对测量的降解数据的统计模型,该模型考虑了这两种变异来源。模型中的降解过程被视为维纳扩散过程。假设测量误差是独立的正态随机结果,且与降解过程无关。本文描述了该模型的推断程序,并讨论了在处理统计问题时必须考虑的一些实际问题。还给出了一个案例研究。