Abstract
In this paper, aiming at the reliability analysis and optimization of jth series marine low-speed diesel engine supercharger of Chongqing JIANGZENG Shipbuilding Heavy Industry Co., Ltd., a response surface mathematical model is constructed by using 62 groups of dispersive simulation analysis data to verify the accuracy and effectiveness of the mathematical model. Based on this, Monte Carlo sampling is carried out to obtain the reliability of turbine disk is 0.943, and the reliability of turbine blade is 0.96 Reliability optimization space. Based on NSGA-II multi-objective genetic algorithm, the reliability of turbine disk and turbine blade is optimized by taking the stress value and machining cost of turbine disk and turbine blade as the objective function. The reliability of turbine disk and turbine blade is 1, the stress value of turbine blade is optimized by 4.7941%, the stress value of turbine disk is optimized by 3.0136%, the machining cost of turbine blade is optimized by 15.5087%, and the machining cost of turbine disk is optimized by 3.9907%. Finally, the results of genetic algorithm and simulation analysis are compared, the difference is less than 5%, which shows that the data based on NSGA-II multi-objective genetic algorithm has practical application reference value.
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