Abstract: In the context of the big data era, the traditional home appliance industry is undergoing a historical transformation of interweaving and integrating new technologies and business needs. Through statistical analysis of a large amount of user refrigerator data, rules for extracting time temperature difference big data indicators and defrosting decision rules have been developed to indirectly identify the degree of evaporator frost, and initiate defrosting when refrigerator performance begins to deteriorate. With the help of big data technology, a time temperature difference big data intelligent defrosting system has been deployed on the big data platform. A standard temperature difference value has been established for each defrosting cycle of each refrigerator to make judgments and decisions. Through comparison before and after optimization, the defrosting cycle has been significantly extended after optimization, which brings multiple performance improvements to the refrigerator.

Key words: Refrigerator defrosting, Big data, Temperature difference value