Low efficiency and accuracy problem is serious when analyzing the rare event using Monte Carlo methods, a reliability analysis method was proposed based on the adaptive importance sampling (AIS). Finding the failure points is difficult when the failure equation is not explicit. Firstly a conditioned recursion algorithm was used to search the failure point which was as close as possible to failure surface. Then the failure point was selected as the new sample center, and the center point was adjusted iteratively to get a failure sample nearby the design point. The failure sample was used to predict the parameters of importance sampling density function; iteration will be performed during the process until the deviation of failure probability met the requirement. Finally, two typical cases were used to verify the method; simulation results show that the failure point can be searched quickly through simulation method without an explicit failure equation, which means it is applicable to the situation where failure equation is implicit. Comparison results with Monte Carlo methods prove that simulation efficiency is increased obviously, especially for the application condition with very small failure probability.
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