Abstract: To solve the problems of low precision and slow convergence speed in scribing path optimization of complex hull assembly lines,and thus improve the operation efficiency of CNC scriber gun,an adjustable parameters immune optimization algorithm of scribing path of hull assembly lines based on free path and direction was proposed.The objective function was established based on the scribing order and the scribing direction of the assembly lines.Then a new immune optimization algorithm was designed based on the virtual-real imaging principle of convex lens.The crossover and mutation probabilities were adaptively adjusted based on evolutionary algebra and population concentration,and vaccine operation was introduced to solve the scribing path of hull assembly lines.The convergence of immune optimization algorithm was proved by Markov chain theory.The test results of six groups of high-dimensional functions showed that the proposed algorithm achieved 100% optimization by comparing with the Genetic Algorithm(GA),the Immune Genetic Algorithm(IGA)and the Adaptive Improved Genetic Algorithm(AIGA),and the minimum convergence algebra,average convergence algebra and iterative algebra standard deviation were reduced by an average of 29.63%,28.96% and 18.33%.The results of optimization tests on the scribing path of assembly lines on four hull structures showed that the path planning performance of the proposed algorithm was the best by comparing with the other three algorithms,and the minimum and mean of the objective function were reduced by an average of 1.38% and 2.39% respectively.Furthermore,the average convergent algebra and iterative algebra standard deviation were reduced by an average of 17.19% and 13.08% respectively,which further verified the effectiveness and superiority of adjustable parameters immune optimization of scribing path of hull assembly lines.

Key words: hull assembly lines, scribing path, empty travel, virtual-real imaging, immune optimization

摘要： 为解决复杂船体装配线划线路径优化时精度低和收敛速度慢的问题,进而提高数控划线枪的作业效率,提出了基于空程和方向的船体装配线划线路径的调参免疫优化。首先以装配线的划线顺序和划线方向建立目标函数;然后借鉴凸透镜虚实成像原理设计了新免疫优化算法,基于进化代数和种群浓度自适应调节交叉和变异概率,并引入疫苗操作实现了船体装配线划线路径求解;最后基于马尔科夫链理论证明了免疫优化算法的收敛性。六组高维函数测试结果表明,与遗传算法、免疫遗传算法和自适应改进遗传算法相比,所提算法实现了100%寻优,且最小收敛代数、平均收敛代数、迭代代数标准差分别平均减少了29.63%、28.96%和18.33%。四种船体结构的装配线划线路径优化测试结果表明,相比起其他三种算法,所提算法的路径规划性能最佳,其最小值和平均值分别平均减少了1.38%和2.39%,平均收敛代数和迭代代数标准差分别平均减少了17.19%和13.08%,从而进一步验证了船体装配线划线路径调参免疫优化的有效性和优越性。

关键词: 船体装配线, 划线路径, 空走行程, 虚实成像, 免疫优化