Title :
Baysian Reliability Assessment of Avionic Device Based on Markov Chain Monte Carlo Method
Author :
Yin Zong-run ; Mu Xiao-dong ; Shi De-Qin ; Zhao Peng
Author_Institution :
Dept. of Comput. Sci. & Technol., Xi´an Res. Inst. of Hi-Tech Hongqing Town, Xi´an
Abstract :
This paper studies the computation problem involving Bayesian reliability assessment of avionic device. A method based on Markov Chain Monte Carlo is proposed to the issue. The non- informative prior distribution of the life distribution parameter is built at first, the kernel function of full conditional density function is figured out according to Bayesian theory, and sample scheme is chosen on the basis of the kernel function, at last, an example is given as an illustration. Test shows that, this method can simplify the computation greatly, and the result is in accordance with the engineering experience. It is a simple and effective approach in reliability assessment applications.
Keywords :
Markov processes; Monte Carlo methods; Weibull distribution; avionics; reliability; Bayesian reliability assessment; Markov Chain Monte Carlo method; avionic device; computation problem; full conditional density function; kernel function; Aerospace electronics; Bayesian methods; Distributed computing; Electronic equipment; Kernel; Monte Carlo methods; Sampling methods; Shape; Testing; Weibull distribution;
Conference_Titel :
Testing and Diagnosis, 2009. ICTD 2009. IEEE Circuits and Systems International Conference on
Conference_Location :
Chengdu
Print_ISBN :
978-1-4244-2587-7
DOI :
10.1109/CAS-ICTD.2009.4960790