The patent badge is an abbreviated version of the USPTO patent document. The patent badge does contain a link to the full patent document.

The patent badge is an abbreviated version of the USPTO patent document. The patent badge covers the following: Patent number, Date patent was issued, Date patent was filed, Title of the patent, Applicant, Inventor, Assignee, Attorney firm, Primary examiner, Assistant examiner, CPCs, and Abstract. The patent badge does contain a link to the full patent document (in Adobe Acrobat format, aka pdf). To download or print any patent click here.

Date of Patent:
Jan. 17, 2023

Filed:

Jan. 13, 2022
Applicant:

Nanjing University of Aeronautics and Astronautics, Nanjing, CN;

Inventors:

Zhongde Shan, Nanjing, CN;

Jun Wang, Nanjing, CN;

Anyi Huang, Nanjing, CN;

Qian Xie, Nanjing, CN;

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G06T 7/00 (2017.01); G06T 7/50 (2017.01); G06T 7/11 (2017.01); G06V 10/77 (2022.01); G06V 10/774 (2022.01); G06V 20/70 (2022.01); G06T 7/30 (2017.01); G06V 10/776 (2022.01); G06V 10/25 (2022.01); G06V 10/26 (2022.01);
U.S. Cl.
CPC ...
G06T 7/0004 (2013.01); G06T 7/11 (2017.01); G06T 7/30 (2017.01); G06T 7/50 (2017.01); G06V 10/776 (2022.01); G06V 10/7715 (2022.01); G06V 10/7747 (2022.01); G06V 20/70 (2022.01); G06T 2200/04 (2013.01); G06T 2207/10024 (2013.01); G06T 2207/10028 (2013.01); G06T 2207/20021 (2013.01); G06T 2207/20081 (2013.01); G06T 2207/30108 (2013.01);
Abstract

A method for detecting and recognizing surface defects of an automated fiber placement composite based on an image converted from point clouds, including: acquiring a surface point cloud of the automated fiber placement composite; fitting a plane to surface point data; calculating a distance from each point of the surface point cloud to a fitted plane; enveloping the surface point cloud by OBB, and generating a grayscale image according to the OBB and the distance; constructing a pre-trained semantic segmentation network for defect of fiber placement, and inputting the grayscale image to segment and recognize defect areas thereon; mapping a segmentation result output by the semantic segmentation network to the point cloud followed by defect evaluation and visualization.


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