Due to the significant differences in the chemical and physical properties of aluminum and copper,numerous defects can arise at the welded joint during the welding process,severely affecting the joint's performance.High-entropy alloys provide significant advantages in enhancing the welding performance of dissimilar metals.Therefore,this study employed FeCoNiCrTi high-entropy alloy powder as a filler material.Additionally,the study proposed an optimization method for welding parameters using a gradient boosting regression tree model optimized by the black-winged kite algorithm,combined with a multi-objective stochastic paint optimizer.The results indicate that under the conditions of a laser power of 677.2 W,a welding speed of 639.3 mm/min,a defocusing amount of 2.75 mm,and a high-entropy alloy addition of 0.05 g,the optimization objectives reached optimal levels.The warp deformation of the welded part decreased by 20.14%,the maximum tensile strength of the welded part increased by 49.72%,and the cost was reduced by 10.90%.
关键词
异种金属焊接/高熵合金/优化算法/GBRT模型/多目标参数优化
Key words
dissimilar metal welding/high-entropy alloys/optimization algorithms/GBRT model/multi-objective parameter optimization
维普
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