Title :
Dynamic modeling of degradation data
Author :
Jiang, Mingxiao ; Zhang, Yongcang
Author_Institution :
GE Corporate R&D, Niskayuna, NY, USA
Abstract :
In applications with few or no failures, degradation data can provide more reliability information than traditional censored failure-time data. In this paper, the authors present a dynamic model of degradation data comparing to the general ones available in literature. Random fatigue crack growth is illustrated in detail as an example of degradation data problem. The proposed model is ready to be generalized to accelerated life testing (ALT) analysis under various testing conditions
Keywords :
failure analysis; fatigue cracks; reliability; accelerated life testing; degradation data; degradation data dynamic modeling; failure analysis; random fatigue crack growth; reliability information; testing conditions; Data analysis; Failure analysis; Fatigue; Life estimation; Life testing; Markov processes; Research and development; Stochastic processes; Thermal degradation; Thermal stresses;
Conference_Titel :
Reliability and Maintainability Symposium, 2002. Proceedings. Annual
Conference_Location :
Seattle, WA
Print_ISBN :
0-7803-7348-0
DOI :
10.1109/RAMS.2002.981709