Deep learning-based optimization and mechanism study of dual-wavelength laserwelding for aluminum alloys
A multi‑input deep neural network prediction model is built by us. Its input parameters include laser power, welding speed, defocus amount, and the power ratio between the two wavelengths. We obtain 156 groups of welding sample data through an orthogonal experimental design. Then a hybrid CNN‑LSTM architecture is used...