The invention relates to the technical field of aluminum profile heat treatment control, in particular to an aluminum profile heat
treatment system based on multi-parameter feedback and LSTM, which comprises a
server and an execution terminal, and the
server comprises a multi-dimensional parameter acquisition module, a
feature fusion preprocessing module, an LSTM prediction optimization module, a deviation hierarchical control module and a dynamic iterative storage module. The multi-dimensional parameter acquisition module acquires real-time heat treatment temperature, profile thickness,
cooling medium flow velocity and finished product tensile strength; the
feature fusion preprocessing module purifies and optimizes the data and then outputs a
state parameter vector; the LSTM prediction optimization module predicts the tensile strength based on the vector, and outputs the parameter adjustment amount in combination with the deviation value and the profile thickness; the deviation grading control module executes differential adjustment according to deviation grades; and the dynamic iteration storage module stores data, regularly and incrementally trains the model, and optimizes a parameter mapping relation. According to the method, through multi-parameter cooperation, LSTM nonlinear
adaptation and dynamic iteration, the heat
treatment quality stability and self-adaptability of the aluminum profile are improved.