The present application relates to the technical field of
float glass preparation, and specifically discloses a method for precisely controlling the thickness difference of
float glass, comprising the following steps: S10, constructing a multi-layer composite heat preservation structure outside the water tank in the high-temperature zone of the
tin tank of a
float glass production line; S20, collecting the process parameters of the
tin tank in real time, including the temperature field distribution, pressure parameters and the geometric parameters of the glass ribbon; S30,
processing the process parameters using a field-adaptive
deep learning algorithm to generate a
control signal for the edge puller; S40, adjusting the angle, speed, strength and position parameters of the edge puller according to the
control signal; S50, repeating steps S20 to S40 to form a closed-
loop control cycle, and when the thickness difference of the glass is stabilized within the required range, entering a
maintenance mode to reduce the calculation load. A stable temperature environment is provided by the heat preservation structure, the
algorithm fully learns the special rules of
glass forming, the glass process characteristics are deeply integrated into the
control system design, and the precise control of the thickness difference is achieved.