Based on the basic platform of BP neural network

a BP network model was founded to predict the bending angle in the process of laser bending of aluminum alloy sheet to optimize laser bending parameter control. The sample data obtained from experiment were used to train BP network. The nonlinear regularities of sample data were fitted through trained BP network

the predicted results include laser bending angles and laser bending parameters. Experimental results indicate the prediction allowance is controlled less than 5~8 %

it can provide effective foundation both theory and experiment for industry purpose.