Multiphase flow dispersed phase identification and completion method based on a SAM neural network
AssigneesInstitute of Process Engineering, Chinese Academy of Sciences, Nanjing Jiuzhang Chemical Technology Co., Ltd.
InventorsChao Yang, Xin Feng, Haohan Xu, Xiaoxia Duan, Jie Chen, Weipeng Zhang
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Abstract
A multiphase flow dispersed phase identification and completion method includes preprocessing an image to filter out noise and a non-key frequency component; identifying and segmenting the preprocessed image by using a SAM neural network to obtain a segmentation mask; post-processing the segmentation mask to output a precise bubble mask; and reconstructing the shape of a bubble by using a bubble reconstruction algorithm.
Claims6
A multiphase flow dispersed phase identification and completion method based on a SAM neural network, comprising the following steps:
- preprocessing an image to filter out noise and a non-key frequency component;
- identifying and segmenting the preprocessed image by using a SAM neural network to obtain a segmentation mask;
- post-processing the segmentation mask to output a precise bubble mask;
- and
- reconstructing a shape of a bubble by using a bubble reconstruction algorithm;
- wherein the post-processing of the image comprises:
- identifying and excluding a mask that represents a background and that is deficient in size and a mask having a deficiency in fill rate;
- and
- removing a mask that causes under-segmentation and a mask nested inside another mask;
- and
- wherein the bubble reconstruction algorithm comprises:
- extracting boundary contour points from the precise bubble mask;
- extracting a relationship between a target and a surrounding by using global information, identifying a shared boundary, determining boundary attribution, and mapping an identified bubble contour into a polar coordinate system;
- and
- completing an overall contour of the bubble by fitting a missing part by using a cubic spline curve;
- wherein the boundary contour points are extracted from the bubble mask by using an edge extraction algorithm;
- wherein identifying the shared boundary includes identifying the shared boundary between an occluding bubble and an occluded bubble;
- wherein the shared boundary is determined based on an analysis of a mask intersection between the occluding bubble and the occluded bubble;
- and
- wherein the boundary contour points of the shared boundary are attributed to the occluding bubble and removed from a mask of the occluded bubble.
Dependencies are inferred from the claim text.