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Intelligent memory and automatic positioning method based on big data platform

A big data platform and automatic positioning technology, applied in the field of component position, intelligent memory of lifting equipment and automatic positioning of materials, can solve problems such as error-prone and low efficiency, and achieve the effect of improving efficiency and avoiding manual recording and search.

Pending Publication Date: 2021-11-26
北京市机械施工集团有限公司
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0002] At present, in large-scale steel structure processing enterprises, it is still in a relatively primitive stage to find the storage location of raw materials and components, that is, it needs to be manually recorded and searched. When the quantity is small and the storage area is small and concentrated, this method is acceptable. However, when the quantity is large and the storage area is large and scattered, it will be powerless and the disadvantages will appear, that is, low efficiency, error-prone, and continuous communication between workers.

Method used

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  • Intelligent memory and automatic positioning method based on big data platform
  • Intelligent memory and automatic positioning method based on big data platform
  • Intelligent memory and automatic positioning method based on big data platform

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0080] According to attached figure 1 As shown, the embodiment of the present invention provides a method for intelligent memory and automatic positioning based on a big data platform, which is characterized in that it includes:

[0081] Grid the storage area of ​​raw materials and components, and determine the grid code;

[0082] Import the grid code into the big data platform for intelligent memory, and determine the initial position of each raw material and component;

[0083] According to the initial position, control the optimal driving equipment to automatically drive to the position of raw materials and components.

[0084] The working principle and beneficial effects of the above-mentioned technical scheme are:

[0085] In the embodiment of the present invention, the storage areas of raw materials and components are divided into grid areas, and the grids in the grid areas are numbered to determine the coding information. The storage areas of raw materials and compone...

Embodiment 2

[0087] This technical solution provides an embodiment, the storage area of ​​raw materials and components is gridded, and the grid code is determined, including:

[0088] Access to storage areas for raw materials and components;

[0089] Determining the division grid according to the preset length and width, performing grid division on the storage area according to the division grid, and numbering the grids in the grid area to determine the grid number;

[0090] Find the area boundary of the storage area according to the grid number, and make a boundary sign on the area boundary;

[0091] Determine the grid code according to the grid number and the boundary sign.

[0092] The working principle and beneficial effects of the above-mentioned technical scheme are:

[0093] The storage area of ​​raw materials and components of this technical solution is divided into several grids with a certain length (such as 10m) according to the length and width, and each grid is numbered, and...

Embodiment 3

[0095] This technical solution provides an embodiment,

[0096] The step of importing the grid code into the big data platform for intelligent memory and determining the initial position of each raw material and component also includes the following steps:

[0097] Obtain the warehousing information of raw materials and components, and determine the use time of raw materials and components according to the warehousing information;

[0098] According to the use time, plan the raw materials and components, and generate a storage planning code; wherein,

[0099] The warehousing planning code is the storage code generated in the order of use when raw materials and components are put into storage;

[0100] Using the preset lifting equipment, the raw materials and components are placed in the corresponding storage location according to the storage planning code.

[0101] The working principle and beneficial effects of the above-mentioned technical scheme are:

[0102] When the ra...

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Abstract

The invention provides an intelligent memory and automatic positioning method based on a big data platform, and the method comprises the steps of carrying out the meshing of a storage region of a raw material and a component, and determining a grid code; importing the grid codes into a big data platform for intelligent memory, and determining the initial position of each raw material and component; and according to the initial position, controlling the optimal driving equipment to automatically drive to the positions of the raw materials and the components.

Description

technical field [0001] The present invention relates to the technical field of intelligent memory of hoisting equipment of a big data platform and a high-precision positioning system and a method for automatically locating materials and component positions, in particular to a method for intelligent memory and automatic positioning based on a big data platform. Background technique [0002] At present, in large-scale steel structure processing enterprises, it is still in a relatively primitive stage to find the storage location of raw materials and components, that is, it needs to be manually recorded and searched. When the quantity is small and the storage area is small and concentrated, this method is acceptable. However, when the quantity is large and the storage area is large and scattered, it will appear powerless, and the disadvantages will appear, that is, low efficiency, error-prone, and continuous communication between workers. Contents of the invention [0003] Th...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06K17/00G06F16/29H04W4/029
CPCG06K17/0029G06F16/29H04W4/029
Inventor 庄会云韩朋张剑杨玲玲杨富海倪超李永马翠娟戚建民艾建中刘洋马亚龙孟令占李明良肖振楠武亚光赵玉明宋磊
Owner 北京市机械施工集团有限公司
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