This invention discloses a centralized control method and
system for hot gas
defrosting. Through
data acquisition,
frost layer prediction and triggering,
defrosting execution, and optimization feedback steps, it achieves intelligent and precise control of the
defrosting process. The
system includes a sensor group, an edge
data acquisition module, a local controller, a communication module, a cloud-based centralized control platform, and actuators. This invention employs a fusion prediction model, combining rule-based rapid scoring with
machine learning-based accurate prediction to dynamically assess
frost risk and trigger defrosting, avoiding the
blindness of traditional timed defrosting. Simultaneously, it ensures
system stability through grouped
sequential control and
safety monitoring, and utilizes a cloud platform to aggregate multi-site data for
global optimization scheduling and model iteration. This invention effectively reduces defrosting
energy consumption, maintains
stable storage / cabinet temperatures, and improves the operating efficiency and
intelligent management level of the
refrigeration system.