激光冲击强化对异型材焊接接头性能的影响

为了研究激光冲击强化对异型材焊接接头性能的影响,对5 mm厚40Cr钢与45钢焊接接头进行激光冲击处理,分析了冲击后凹坑形貌以及冲击前后焊接接头残余应力、显微硬度的变化情况。结果表明,焊接接头不同区域产生不同程度的压塑性变形;焊缝区和热影响区的残余拉应力变为压应力,且在焊缝中心处有最大平均残余压应力396 MPa;冲击后焊接接头的显微硬度也得到一定程度的提高。激光冲击强化有效地提高了异型材焊接接头的性能。

Prediction about residual stress and microhardness of material subjected to multiple overlap laser shock processing using artificial neural network

In this work,the nickel-based powder metallurgy superalloy FGH95 was selected as experimental material,and the experimental parameters in multiple overlap laser shock processing(LSP)treatment were selected based on orthogonal experimental design.The experimental data of residual stress and microhardness were measured in the same depth.The residual stress and microhardness laws were investigated and analyzed.Artificial neural network(ANN)with four layers(4-N-(N-1)-2)was applied to predict the residual stress and microhardness of FGH95 subjected to multiple overlap LSP.The experimental data were divided as training-testing sets in pairs.Laser energy,overlap rate,shocked times and depth were set as inputs,while residual stress and microhardness were set as outputs.The prediction performances with different network configuration of developed ANN models were compared and analyzed.The developed ANN model with network configuration of 4-7-6-2 showed the best predict performance.The predicted values showed a good agreement with the experimental values.In addition,the correlation coefficients among all the parameters and the effect of LSP parameters on materials response were studied.It can be concluded that ANN is a useful method to predict residual stress and microhardness of material subjected to LSP when with limited experimental data.