家电科技 ›› 2025, Vol. 0 ›› Issue (zk): 127-133.doi: 10.19784/j.cnki.issn1672-0172.2025.99.027

• 第一部分 优秀论文 • 上一篇    下一篇

基于数据驱动的冰箱门未关严检测方法

尚靖, 蒋婉, 李甜甜, 李云涛, 王远燊   

  1. 四川虹美智能科技有限公司 四川绵阳 621011
  • 发布日期:2025-12-30
  • 通讯作者: 蒋婉,E-mail:wan.jiang@changhong.com。
  • 作者简介:尚靖,本科学历。研究方向:大数据、机器学习、家电故障诊断等。地址:四川省绵阳市涪城区四川虹美智能科技有限公司。E-mail:jing1.shang@changhong.com。

Data-driven detection method of refrigerator door-ajar events

SHANG Jing, JIANG Wan, LI Tiantian, LI Yuntao, WANG Yuanshen   

  1. Sichuan Hongmei Intelligent Technology Co., LTD Mianyang 621011
  • Published:2025-12-30

摘要: 针对智能冰箱门体关闭状态实时监测需求日益增长,而传统门磁或机械开关存在装配复杂、低温凝露易失效、成本高等问题,提出一种完全基于冰箱运行大数据的门未关严检测方法。该方法无需新增硬件,而是利用大数据平台离线构建门关不严异常数据库,以压缩机状态位、蒸发器温度、冷藏温度、冷冻室温度、化霜周期等相关多源运行数据为输入,为冰箱智能化运维提供了低成本、可落地的检测解决方案。

关键词: 冰箱, 门未关严, 大数据, 运行数据, 异常检测

Abstract: In view of the increasing demand for real-time monitoring of the closed state of the smart refrigerator door, and the traditional door magnetic or mechanical switch has some problems, such as complex assembly, easy failure of low-temperature condensation and high cost, etc., a door ajar detection method based on refrigerator operation big data is proposed. This method does not need to add new hardware, but uses a big data platform to build an off-line abnormal database with compressor status bit, evaporator temperature, refrigeration temperature, freezing room temperature, defrosting cycle and other related multi-source operation data as inputs, which provides a low-cost and landing detection solution for intelligent operation and maintenance of refrigerators.

Key words: Refrigerator, Door not closed tightly, Big data, Operation data, Anomaly detection

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