Textile image identifying and cutting control system based on big data

Abstract

The invention discloses a big data-based textile image identification cutting control system, which comprises a base and a data management module, and is characterized in that the data management module comprises a data detection module and a data processing module, the data detection module is used for detecting data information in an equipment operation process, and the data processing module is used for processing the data information; the detection module is used for detecting the detected data information and transmitting the detected data information to the data processing module, the data processing module is used for analyzing and processing the received data information and processing the cloth according to the processing result, a supporting frame is arranged at the top of the base, and a conveying belt is arranged at the bottom of the supporting frame; sliding rails are arranged on the inner side and the outer side of the supporting frame correspondingly, sliding blocks are slidably connected to the tops of the sliding rails, sliding grooves are fixedly formed in the tops of the two sets of sliding blocks, and laser cutters are slidably connected to the tops of the sliding grooves.

Description

technical field [0001] The invention relates to the technical field of cloth cutting, in particular to a textile image recognition and cutting control system based on big data. Background technique [0002] When the existing textile image recognition and cutting control system based on big data cuts the cloth, when the distance between the cut images of the cloth is relatively close, the cutting will cause certain damage to the image, and the cloth required When the distance between the cropped images is far, cutting them with lower output power will result in lower cutting efficiency. At the same time, when the existing textile image recognition and cutting control system based on big data cuts the cloth, the cloth When the height is low, cutting it with higher output power will cause certain damage to the fabric and the processing table, and when there are many images to be cut on the surface of the fabric, multiple cuttings will generate a certain temperature. Higher tem...

AI Technical Summary

Problems solved by technology

[0002] When the existing textile image recognition and cutting control system based on big data cuts the cloth, when the distance between the cut images of the cloth is relatively close, the cutting will cause certain damage to the image, and the cloth required When the distance between the cropped images is far, cutting them with lower output power will result in lower cutting efficiency. At the same time, when the existing textile image recognition and cutting control system based on big data cuts the cloth, the cloth When the height is low, cutting it with higher output power will cause certain damage to the fabric and the processing table, and when there are many images to be cut on the surface of the fabric, multiple cuttings will generate a certain temperature. Higher temperature will cause certain damage to the fabric and the processing table, reduce the quality of the cut cloth, and shorten the service life of the processing table. Therefore, a textile map based on big data is designed to protect the cloth and improve the cutting efficiency. It is necessary for the object recognition and clipping control system

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