分段确定性马尔可夫过程的疲劳裂纹增长预测应用
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摘要
分段确定性的马尔可夫过程(PDMP)是扩散过程的一种替换物,它实质上给出了是确定性运动和随机跳跃混合物的任意随机过程的表示,因而PDMP的样本轨迹能够包括确定性的退化过程和偶然的外伤性事件。在本研究中发现该过程到达一个确定性阈值的首达时的拉普拉斯变换满足Fredholm方程,通过指数快速收敛Neumann级数给出了此方程的解。将PDMP引入到具有退化的可靠性分析中,通过疲劳裂纹增长分析,研究了基于PDMP实行退化建模的可行性。
Piecewise Deterministic Markov Processes(PDMP) is an alternative to diffusion processes.It virtually gives a representation of any stochastic process being the mixture of deterministic motions and random jumps.Hence,the sample paths of PDMP contain deterministic degradation process and accidental traumatic events.The Laplace transform of the first crossing time of a fixed threshold by the process is shown to satisfy a Fredholm equation of second kind.Solution to this equation is given by exponentially fast converging Neumann series.The PDMP is introduced into reliability analysis of product with degradation.With the analysis of fatigue crack growth data,the feasibility of degradation modeling based on PDMP is studied.
引文
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