自适应模糊遗传算法在轮胎花纹降噪中的应用

Application of tread patterns noise-reduction based on self-adaptive fuzzy genetic algorithm

为了进一步优化轮胎花纹结构参数,提高轮胎花纹降噪的效果,在现有模糊遗传算法的基础上,提出了一种自适应模糊遗传降噪算法(Self-adaptive Fuzzy Genetic Noise-Reduction Algorithm,SFGNRA)。引入变换算子和对非法个体的贪婪处理,能够随时间和个体的适应度大小自动调整变换概率、变异概率,不需要人为设定。利用轮胎噪声仿真分析优化软件进行轮胎花纹结构设计,验证了该算法能进一步降低轮胎的噪声,得到了低噪声轮胎花纹结构方案。研究成果为低噪声轮胎花纹设计规范与方法提供了新的路径。

In order to optimize the structure parameters of tread pattern and improve the efficiency of noise-reduction,Serfadaptive Fuzzy Genetic Noise-Reduction Algorithm（SFGNRA） has been proposed,which is also based on the prior Fuzzy Genetic Algorithm （FGA）.In the improved algorithm,the relationship between crossover probability and mutation probability and individual＇s fitness is adopted,operators of Simple Genetic Algorithms（SGA） are improved,and simulated annealing methods are introduced after crossover to improve enhance the local search ability of genetic algorithm.Some experiments have been done by means of the software of TNT and ODS simulation,and the results show that the tread patterns noise should be reduced,and the merit project of structure parameters may be found.The research is successfully applied to the design of way for the lownoise tread patterns.