基于云蚁群算法的高效节能氩弧焊工艺参数优化研究

为在氩弧焊加工过程中提升效率的同时降低能耗,研究了一种氩弧焊高效节能工艺参数的多目标优化模型及算法。首先确定了以焊接速度及焊接电流为优化变量,在综合考虑焊接设备、工件特性、操作方法及焊接质量等约束的前提下,建立了以最小电能消耗以及最短加工时长为优化目标的多目标工艺参数优化模型;提出一种基于云模型的蚁群算法(CBACO)以对所构建的优化模型进行求解,其中包含一种适当的编码方式、一种局部与全局相结合的探索策略、一种基于云模型的变异因子、传统的单点交叉因子、单形交叉因子以及适当的选择策略;通过一个针对某航空器油箱的焊接实例,对所提出的优化模型及算法的实用性进行了验证,结果表明优化参数可在保证加工质量的前提下有效地节省时间60.41%~69.05%,节省电能34.88%~46.30%。

Optimization of Argon Arc Welding Parameters Based on Cloud Ant Colony Algorithm for High Efficiency and Energy Saving

To improve the efficiency of argon arc welding and reduce the energy consumption,a multi-objective optimization model and algorithm of high efficiency and energy saving process parameters were studied.Firstly,taking welding speed and welding current as optimization variables,and considering the constraints of welding equipment,workpiece characteristics,operation method and welding quality,a multi-objective process parameter optimization model with the minimum power consumption and the shortest processing time as optimization objectives was established.Put forward a kind of ant colony algorithm based on cloud model(CBACO)to solve the optimization of the constructed model,which contains an appropriate encoding method,a combination of local and global exploration strategy,a mutation factor based on cloud model,the traditional single point crossover factor,simplex crossover factor and the choice of appropriate strategies;Through a welding example of an aircraft fuel tank,the practicability of the optimization model and algorithm proposed in this paper is verified.The results show that the optimized parameters can effectively save time 60.41%-69.05%and energy 34.88%-46.30%under the premise of guaranteeing the processing quality.