Prediction and control method of nickel-base super alloy microstructure on the basis of BP (Back Propagation) neural network
A nickel-based superalloy, BP neural network technology, applied in neural learning methods, biological neural network models, special data processing applications, etc., can solve problems such as difficult to control microstructures
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[0081] The present invention will be described in detail below in conjunction with the accompanying drawings and specific embodiments.
[0082] The invention is a method for predicting and controlling the microstructure of a nickel-based superalloy, the flow chart of which is as follows figure 1 shown. Below in conjunction with the finite element simulation software DEFORM-3D, introduce in detail the implementation details of the nickel-base superalloy microstructure predictive control involved in the present invention, its method comprises:
[0083] Step 1: Initialize the parameters in the training prediction neural network model and the control neural network model, and train the prediction neural network model and the control neural network model offline according to the historical die forging process parameters and microstructure information;
[0084] The initialization parameters mainly include: learning rate η = 0.01, feedback correction weight coefficient h = 1, soften...
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