This invention relates to the field of
automatic control technology, and more particularly to an AI-based prefabricated
data center cooling control method and
system. The method includes the following steps: acquiring a texture map and a
depth map of the rack under test; analyzing the material information of the texture map to determine the theoretical
heat capacity benchmark of the equipment and the geometric features of the
depth map to determine the equivalent volumetric
heat capacity of the rack under test; calculating the
tortuosity index of the rack under test based on the spatial gradient features of the
depth map to characterize heat exchange efficiency; constructing a feedforward
cooling power curve by combining the equivalent volumetric
heat capacity, the
tortuosity index, the geometric volume of the rack under test, and the
initial heat dissipation
temperature difference; and controlling the operation of a precision
air conditioning unit based on this curve. This invention, through intelligent
perception of the appearance of the rack under test, predicts its actual
heat load and heat dissipation characteristics, realizing a shift from passive feedback to active feedforward
temperature control mode, improving
temperature control accuracy and operating efficiency.