Split learning machine
CN224696405UActive Publication Date: 2026-08-28JIANGSU SHUHE INTELLIGENT TECHNOLOGY CO LTD
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Patent Information
- Application Number
- CN202522132364.1
- Authority / Receiving Office
- CN · China
- Patent Type
- Utility models(China)
- Current Assignee / Owner
- Filing Date
- 2025-10-09
- Publication Date
- 2026-08-28
- Estimated Expiration
- 2035-10-09
AI Technical Summary
Technical Problem
[0003]在分体式学习机主机与屏幕组件的连接操作中，设计有特定流程，安装时，可借助屏幕组件背面的导轨实现快速定位，之后利用磁吸或卡扣结构完成固定，然而，该导轨结构存在明显缺陷，即缺少防呆设计，这使得在安装过程中，用户很容易因疏忽或操作不当，导致主机安装错位，一旦出现错位情况，就需要重新取下主机再次装配，这一过程不仅繁琐，还耗费时间和精力，极大地降低了分体式学习机原本应有的便捷性，影响用户的使用体验
Benefits of technology
在本例中，通过安装第一定位杆和第二定位杆，将主机主体靠近触控屏主体，主机主体进入定位座内部，主机主体背面与触控屏主体背面相对，第一定位杆才能进入主机主体的侧面，第二定位杆进入主机主体的另一个侧面，主机主体定位安装时，进行防呆保护，提高了分体式学习机的便捷性。
✦ Generated by Eureka AI based on patent content.
Smart Images
Figure CN224696405U_ABST
Abstract
The utility model relates to a split type learning machine. The structure includes: touch screen main body, host computer main body, positioning seat and foolproof positioning mechanism, the back of touch screen main body is provided with host computer main body, the back of touch screen main body is fixedly connected with positioning seat, the bottom of host computer main body is opened with data transmission hole symmetry, the inner wall of positioning seat is fixedly connected with data plug symmetry, data plug and data transmission hole slide and connect, the inside of positioning seat is installed with foolproof positioning mechanism, through installing first positioning rod and second positioning rod, host computer main body is close to touch screen main body, host computer main body enters the inside of positioning seat, the back of host computer main body is opposite to the back of touch screen main body, first positioning rod can enter the side of host computer main body, second positioning rod enters the other side of host computer main body, when host computer main body positioning installation, carry out foolproof protection, have improved the convenience of split type learning machine.
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