会议专题

Tolerance Optimization Design Based on Neural Network and Genetic Algorithm

  Aiming at the characteristics of highly non-linear relationship between tolerance and cost in product manufacturing,a tolerance optimization method based on neural network and genetic algorithm is proposed.This method uses genetic algorithm to obtain global optimal solution with strong robustness by probability search strategy in a wide range of solution space,and the advantages of neural network in solving highly non-linear problems.The function relationship of tolerance cost with black box characteristics is obtained by simulating tolerance cost with neural network.Then genetic algorithm is used in tolerance allocation to minimize total cost,and optimization is carried out under the constraints of meeting assembly tolerance requirements and meeting standard tolerance grade.At the same time,tolerance optimization system is developed based on VC and Matlab,and the object of tolerance allocation is the locker mechanism of aircraft cabin door.The results show that the results of comprehensive allocation using neural network and genetic algorithm are superior to those of traditional methods.

tolerance cost relationship tolerance optimization neural network genetic algorithm

Jinwei Fan Ning Ma Peitong Wang Jian Yin Hongliang Zhang Miaomiao Wang

BeijingUniversity of Technology,Beijing 10024,China

国际会议

2019 2nd International Conference on Mechanical Engineering, Industrial Materials and Industrial Electronics (MEIMIE 2019)2019年第二届机械工程、工业材料和工业电子国际会议(Meimie 2019)

大连

英文

293-301

2019-03-29(万方平台首次上网日期,不代表论文的发表时间)