Research of the Curve Radius of Shape Formed in Profile Cold Forming with BP Neural Networks Approach Based on Experiment
During the processing of frame part forming in ship production, the prediction of the curve radius of shape formed is of great significance for the quality and efficiency of forming work. The experiment method is used to conduct the research. Because the profile forming is affected by various factors, this article used orthogonal experiment designing method to draw up the forming experiment scheme. In the experiment researches, the angle steel is chosen as study object. Using the data recorded in the experiments as training sample, this article established a model based on the Bayesian regularization back propagation (BP) neural network to predict the curve radius of shape formed. With this model and the test sample recorded in the experiment, the calculation results showed that the model could reflect the relationship between the technical parameters and the curve radius correctly. Using the above model, this article predicts the curve radius with a series of variables of the influence factors, studies the rules of the influence of the factors to the curve radius, and obtains meaningful conclusions. These conclusions have been applied to guide the development of the three fulcrum frame bender successfully.