| Abstract:Function failure in product development is a complex systematic engineering, and the failure process contains a lot of uncertain factors. To this end, this paper constructs an adaptive Kriging algorithm for uncertain reliability function optimization, carries out product overall function failure analysis, cognitive set reliability, sample point generation, adaptive Kriging calculation and optimal function combination, and obtains the optimal solution under the specified probability constraint. Based on the law of large numbers and the limit theorem, the convergence conditions of the sample points in important regions and Kriging model are guaranteed. Taking the energy storage system of construction machinery as an example, the iteration, convergence, accuracy and stability of the algorithm are illustrated. The results show that the algorithm can get accurate sensitivity, save computing time and improve computing efficiency. |
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