中国机械工程2026，Vol.37Issue(2)：476-486,11.DOI:10.3969/j.issn.1004-132X.2026.02.022
基于多策略改进复合麻雀搜索算法的自冲铆成形质量预测
Prediction of Self-piercing Riveting Quality Based on Multi-strategy Improved Composite Sparrow Search Algorithm
摘要
Abstract
To efficiently predict the forming quality of self-piercing riveted joints,a finite element model of self-piercing riveting for AA5754 aluminum alloys was established,and the effectiveness of the simulation model was verified through experiments.Based on the simulation analysis,176 sets of effective cross-sectional data of the joints were obtained.By integrating the sparrow search algorithm and the butter-fly algorithm,a composite optimization algorithm was constructed.The algorithm's convergence speed and solution quality were improved by employing population initialization and lens reverse learning strategies.Multidirectional learning and Levy flight strategies were introduced to enhance the algorithm's ability to es-cape local optima,thereby improving the global search capabilities.Research indicates that the prediction results of the established model have a MAPE of less than 10%,a correlation coefficient R2 higher than 0.99,and a mean square error MSE consistently less than 0.001.Therefore,the proposed improved model has high predictive accuracy and robustness.关键词
自冲铆/神经网络/优化算法/成形质量预测/仿真Key words
self-piercing riveting/neural network/optimization algorithm/forming quality predic-tion/simulation分类
矿业与冶金引用本文复制引用
刘洋,吴庆军,郭浩,祁凯飞,庄蔚敏,伏广省..基于多策略改进复合麻雀搜索算法的自冲铆成形质量预测[J].中国机械工程,2026,37(2):476-486,11.基金项目
国家自然科学基金(52272364) （52272364）
山东省自然科学基金(ZR2025MS888,ZR2022QE264) （ZR2025MS888,ZR2022QE264）
