摘要
长度为1.6~8 m的大型曲轴在制造加工过程中,由于热变形和冷却不均等原因会造成二次弯曲,需要通过圆角滚压矫直工艺进一步改善主轴颈和连杆颈中心的跳动量。为了解决大型曲轴跳动量超差现象并提高加工效率,旨在以16V型大型曲轴为研究对象,基于已有结论和建立优化数学模型,运用NSGA-Ⅲ算法和PlatEMO平台对圆角滚压矫直工艺实行了多目标优化,并结合TOPSIS决策方法计算了Pareto解集的贴近度指数,根据指数排序结果进一步选择每次滚压矫直的最佳方案,实现了工艺参数(滚压力、滚压角度范围)的优化。优化结果与有限元仿真结果具有较高的一致性,有效降低了16V型大型曲轴各主轴颈的矫后跳动量和减少了滚压矫直的次数,确保曲轴性能达到要求。
During the manufacturing process of large crankshafts with lengths ranging from 1.6 m to 8 m,secondary bending can occur due to thermal distortion and uneven cooling.This necessitates the use of fillet rolling straightening to further improve the runout of the main journal and connecting rod journal centers.To address the issue of excessive runout in large crankshafts and enhance processing efficiency,this paper focuses on the 16V-type large crankshaft,building on existing conclusions and establishing an optimized mathematical model.The NSGA-Ⅲ algorithm and the PlatEMO platform were used to perform multi-objective optimization of the fillet rolling straightening process.By integrating the TOPSIS decision-making method,the closeness index of the Pareto solution set was calculated.Based on the index ranking results,the best scheme for each rolling straightening was selected,optimizing the process parameters(rolling pressure,rolling angle range).The optimization results showed high consistency with finite element simulation results,effectively reducing the post-straightening runout of each main journal of the 16V-type large crankshaft and decreasing the number of rolling straightening operations,ensuring that the crankshaft performance meets the required standards.
作者
罗远新
曹锋
易丽群
杨昊
周赟
LUO Yuanxin;CAO Feng;YI Liqun;YANG Hao;ZHOU Yun(College of Mechanical and Vehicle Engineering,Chongqing University,Chongqing 400030,China;Chongqing Chang′an Wangjiang Industry Group Co.,Ltd.,Chongqing 401120,China;Guilin Fuda Alfing Large Crankshaft Co.,Ltd.,Guiling 541199,China)
出处
《重型机械》
2024年第4期25-32,共8页
Heavy Machinery
基金
广西科技重大专项资助项目(桂科AA21077002)。
关键词
大型曲轴
滚压矫直
数学模型
矫后跳动量优化
NSGA-Ⅲ算法
large crankshaft
rolling straightening
mathematical model
post-straightening runout optimization
NSGA-Ⅲ algorithm