The invention provides a bidirectional
tension control withdrawal and straightening method for loose edge defects of a cold-rolled 2B plate, which comprises the following steps of: S1, acquiring
transverse strain distribution data of the plate in real time through a distributed
optical fiber strain sensor array at the sampling frequency of more than or equal to 10kHz; s2, inputting the strain data and the process parameters into a physical-data
hybrid drive prediction model, and generating an optimized combination matrix of longitudinal tension sigma long and transverse tension sigma trans by the model through a neural network constrained by an embedded Hollomon elastic-plastic equation; s3, the
magnetic field intensity of the
magnetorheological fluid clamping roller is dynamically adjusted according to the optimization matrix, so that the transverse tension is continuously adjustable within the range of 0.1-50 N / mm < 2 >; s4, a multi-target
reinforcement learning algorithm is adopted,
model parameters are updated on line based on real-time defect detection data, and the loose edge
elimination rate and the
energy consumption index are balanced. The method has the advantages that longitudinal and transverse tension coordinated regulation and control are realized, the loose edge defect
elimination precision is improved, and the real-time adaptability of the model is enhanced.