Random curve modeling method based on image processing

Abstract

The invention discloses a random curve modeling method based on image processing. The method comprises the following steps: 1) reading an image shot by an SEM; 2) performing related image processing on the image to obtain image data; 3) drawing a plurality of random B-sample curves in a layer with the same size as the SEM through Matlab, and endowing each curve with a width; 4) drawing the edges of all curves in each layer through picture processing software to form a curve wireframe diagram; 5) storing the curve wireframe diagram in a DWG format through an Illustrator; and 6) importing the curve wireframe diagram into modeling software for modeling. Generation of a random three-dimensional fiber structure grid is realized through image processing of an SEM image, generation of a random curve, extraction of a curve contour and curve contour modeling. The problem that a Matlab two-dimensional model is difficult to import into modeling software is solved.

Description

technical field [0001] The invention relates to the technical field of two-dimensional curve modeling, in particular to a random curve modeling method based on image processing. Background technique [0002] As a natural polymer with large reserves and large output in nature, cellulose has many advantages, such as complete biodegradation, non-toxicity, non-polluting, easy modification, good biocompatibility, etc. It is the future world energy, chemical industry It can be widely used in the fields of papermaking, fibers and textiles, and cellulose derivatives. [0003] Papermaking technology has a long heritage in my country, and it has extended to many fields from papermaking. For example, in the field of lithium batteries, the separator, one of the four key materials of lithium-ion batteries, can be prepared through papermaking technology. Paper structures have different requirements in different situations, so research on different scales of paper structures has been goin...

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Problems solved by technology

However, the models established by these two methods cannot truly reflect the structure of the fiber, and even differ greatly from the actual structure, so they can only be applied to some simple qualitative simulation analysis

Among the reasons for this result, in addition to the inability to obtain enough and relatively accurate statistical data in the processing of fiber microscopic pictures and parameter statistics, part of the reason is that the establishment of random curves is unreasonable, and the establishment of Matlab The fiber model is imported into solidworks and other modeling software for modeling. This operation is difficult to achieve, making two-dimensional woven mesh models more common, while multi-layer random fiber meshes are relatively rare (Peng Yujian "Lithium-ion Battery Cellulose Separator Research on multi-scale structures and mechanical properties")

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