Digital twin model construction system based on image recognition and dynamic matching

Abstract

The invention relates to a digital twin model construction system based on image recognition and dynamic matching, which is used for carrying out automatic recognition and twin model dynamic self-adaptive matching on tested production equipment, and comprises a design image acquisition module, a dynamic matching module and a dynamic matching module, the shot original image is pre-processed and then is output to the image identification module; the image recognition module is used for recognizing the type of the equipment according to the image information and sending the type of the tested production equipment to the three-dimensional model assembly module; and the three-dimensional visualization module is used for visually displaying the category information of the tested production equipment. Compared with the prior art, the method is oriented to production line equipment model construction, automatic identification and twinborn model dynamic adaptive matching can be carried out on tested equipment, and finally production line digital twinborn model construction and three-dimensional visual display are achieved.

Description

technical field [0001] The invention relates to the field of dynamic matching of production line image recognition, in particular to a digital twin model construction system based on image recognition and dynamic matching. Background technique [0002] With the development of artificial intelligence, image recognition technology is also becoming more and more perfect, from the original text recognition to the current object recognition, however, one of the shortcomings of modern image recognition technology is the poor adaptive performance, once the target image is polluted by strong noise or It is because the target image has a large defect that often cannot get the ideal result. This shortcoming makes the application of image recognition greatly limited, and it is still impossible to accurately find its position in the manufacturing process. [0003] The digital twin technology realizes the feedback of the real physical system to the cyberspace digital model. Once it is pr...

AI Technical Summary

Problems solved by technology

[0002] With the development of artificial intelligence, image recognition technology is also becoming more and more perfect, from the initial text recognition to the current object recognition. However, one of the shortcomings of modern image recognition technology is poor adaptive performance. Once the target image is polluted by strong noise or If the target image has a large defect, the ideal result is often not obtained. This shortcoming restricts the application of image recognition to a large extent, and it is still impossible to accurately find its position in production and manufacturing.

[0003] The digital twin technology realizes the feedback from the real physical system to the cyberspace digital model. Once it is proposed, it is widely used in manufacturing. It can truly ensure the coordination between the digital and the physical world within the entire life cycle. The current Twin technology is suitable for the virtual and reality mapping of a single production line, and it is difficult to realize the common use or multi-use of production models and production modes. Therefore, a digital twin model combined with a dynamic matching method is needed to realize various simulations, Analysis, data accumulation, mining and other information sharing, so as to improve the applicability of digital twins

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