家电科技 ›› 2023, Vol. 0 ›› Issue (2): 52-55.doi: 10.19784/j.cnki.issn1672-0172.2023.02.008

• 论文 • 上一篇    下一篇

洗鞋机洗涤参数优化研究

田海东1,2, 刘玉春1,2, 薛威海1,2, 周之运1,2   

  1. 1.海信家电集团股份有限公司 广东佛山 528300;
    2.海信冰箱有限公司 山东青岛 266100
  • 出版日期:2023-04-01 发布日期:2023-06-27
  • 作者简介:田海东,硕士学位。研究方向:洗衣机结构设计、洗涤研究。地址:山东省青岛市崂山区松岭路399号。E-mail:1123088745@qq.com。

Research on optimization of washing parameters of shoe washing machine

TIAN Haidong1,2, LIU Yuchun1,2, XUE Weihai1,2, ZHOU Zhiyun1,2   

  1. 1. Hisense Appliance Group Co., Ltd Foshan 528300;
    2. Hisense Refrigerator Co., Ltd. Qingdao 266100
  • Online:2023-04-01 Published:2023-06-27

摘要: 为了确定波轮洗鞋机的最佳洗涤参数,提升洗涤性能,以波轮洗鞋机为研究对象,选取浸泡时间、洗涤时间、转停比、漂洗时间等影响洗涤性能的关键因子进行洗涤参数优化研究。通过设计正交试验和极差分析,研究结果表明,各因素对洗净比影响显著性由大到小排序为:漂洗时间>洗涤时间>浸泡时间>转停比;各因素对磨损率影响显著性由大到小排序为:洗涤时间>浸泡时间>漂洗时间>转停比;洗涤时的最佳参数组合为:洗涤时间11.5 min,浸泡时间6 min,转停比1.5:1.0,漂洗时间2 min。参数优化后,洗净比提高了18%,磨损率降低了22%,显著提高了洗鞋机的洗涤性能。

关键词: 洗鞋机, 洗涤性能, 参数优化

Abstract: In order to determine the optimal washing parameters of the wave wheel shoe washing machine and improve its washing performance, the wave wheel shoe washing machine was selected as the research object to optimize the washing parameters by selecting key factors that affect washing performance, such as soaking time, washing time, turn-stop ratio, and rinsing time. Through the design of orthogonal experiments and range analysis, the research results show that the significance of various factors on the washing ratio is ranked in descending order: rinsing time>washing time>soaking time>turn-stop ratio. The significance of various factors on wear rate is ranked in descending order: washing time>soaking time>rinsing time>turn-stop ratio. The optimal parameter combination for washing is: washing time 11.5 min, soaking time 6 min, turn-stop ratio 1.5:1.0, and rinsing time 2 min. After parameter optimization, the washing ratio increased by 18% and the wear rate decreased by 22%, significantly improving the washing performance of the shoe washing machine.

Key words: Shoe washing machine, Washing performance, Parameter optimization

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