Dynamic reliability model updating method based on Bayes factor optimization
A technology for model updating and model optimization, applied in special data processing applications, instruments, electrical and digital data processing, etc., can solve problems such as the need for updated information and reliability prediction accuracy that have not yet been carried out, shorten the development cycle, reduce maintenance costs, The effect of strong engineering significance
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[0017] General method of the present invention is described below in conjunction with accompanying drawing:
[0018] Such as figure 1 As shown, a dynamic reliability model update method based on Bayesian factor optimization includes the following steps:
[0019] Step 1: Analyze the failure physics of the product, establish the failure physics reliability model of the product (the full name is the dynamic reliability approximation model based on failure physics), use Monte Carlo simulation to conduct dynamic reliability analysis on the failure physics reliability model, and estimate that in a certain some given time t i Reliability R at (i=1,2,...,l) point 0 (t i ), l is a natural number;
[0020] Reliability R 0 (t i ) is calculated as formula (1):
[0021] R 0 ( t i ) = Pr { g ( d ...
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