大数据驱动的冰箱智能除霜应用研究
Research on the application of big data driven air cooled refrigerator defrosting on demand
陈峰峰 1杨昀松 1任飞 1曹代华1
作者信息
- 1. 四川虹美智能科技有限公司 四川 绵阳 621000
- 折叠
摘要
在大数据时代背景下,传统家电行业正经历新技术和业务需求交织融合的历史变革.通过对大量用户冰箱数据统计分析,制定了时间-温差-大数据指标提取规则和除霜决策规则,间接辨识蒸发器凝霜程度,在冰箱性能开始恶化时刻启动除霜.借助于大数据技术,在大数据平台部署了时间-温差-大数据智能化霜系统,针对每台冰箱的每次化霜周期建立标准温差值进行判断决策,通过对优化前后的对比,优化后除霜周期明显得到延长,可对冰箱带来多方面的性能提升.
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.
关键词
冰箱除霜/大数据/温差值Key words
Refrigerator defrosting/Big data/Temperature difference value引用本文复制引用
出版年
2024
国家科技期刊平台
NSTL
万方数据