Method for controlling thickness of cold rolled steel strip capable of conducting dynamic compensation of thermal expansion of rollers

Abstract

The invention relates to a method for controlling the thickness of cold rolled band steel which can process roller thermal expansion dynamic compensation, wherein the invention is characterized in that: it has roller thermal expansion dynamic compensation module, based on position and thickness detection; said module based on expansion theory, dynamically corrects and compensates the preset position value. The invention leads said thermal expansion dynamic compensation into AGC system, which can analyze the data based on the tested signal to obtain present thermal expansion information, and calculate out the compensated value to correct the position setting value, to hold the roller seam constant. Therefore, the roller length will be uniform.

Description

technical field [0001] The invention relates to a thickness control method capable of compensating the thermal expansion of rolls in the process of rolling metal thin plates, especially thin steel strips. Background technique [0002] In the production process of rolled metal sheet strip, people are more concerned about whether its thickness is uniform, especially whether the thickness of the strip is uniform along the length direction of the strip or along the rolling direction. [0003] The strip cold rolling equipment should include at least one or several rolling mill stands arranged continuously, and the strip enters the gap defined by the rolls, that is, the roll gap, after passing through each stand. The rolling control system adjusts the roll pressing of each stand or the front and rear of the stand according to the exit thickness, entrance thickness, displacement of the pressing cylinder, rolling force, and front and rear tension measured by the sensors distributed ...

AI Technical Summary

Problems solved by technology

Due to the complexity of practical problems, theoretical models are established on the basis of simplification and assumptions. The neural network model is limited by structure and parameters. It is based on several process parameters to estimate the thermal expansion process of the roll that will occur, and can only reflect thermal expansion. The general law of the macro, but for each specific pass due to various accidental factors (such as the change of belt threading time, the length of acceleration and deceleration time, the change of coolant flow rate, etc.), the local specific changes cannot be effectively reflected.

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