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公开(公告)号：US11787051B2
公开(公告)日：2023-10-17
申请号：US18058845
申请日：2022-11-25
发明人： Jun Wang , Anyi Huang , Cheng Yi , Zeyong Wei , Hao Yan
CPC分类号： B25J9/1664 , B25J9/1694 , B25J11/0055
摘要： A method for automatically processing a structure-reinforcing member of an aircraft, including: (S1) acquiring, by a handheld laser scanner, data of an area to be reinforced of the aircraft; (S2) controlling a robotic arm to automatically grab the reinforcing member for automatic scanning; (S3) setting a cutting path in a computer aided design (CAD) digital model followed by registration with real data to obtain an actual cutting path, and cutting the reinforcing member; (S4) controlling the robotic arm to guide a cut reinforcing member to a scanning area for automatic scanning; and (S5) subjecting point cloud data of the cut reinforcing member and the area to be reinforced to virtual assembly and calculating a machining allowance to determine whether an accuracy requirement is met; if yes, ending a task; otherwise, grinding the reinforcing member automatically, and repeating steps (S4)-(S5).
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公开(公告)号：US11535400B2
公开(公告)日：2022-12-27
申请号：US17169505
申请日：2021-02-07
发明人： Jun Wang , Xiaoge He , Yuanpeng Liu , Yuan Zhang
摘要： A fairing skin repair method based on measured wing data includes fairing skin registration. Data set P1 through denoising and filtering wing point cloud data is reorganized to obtain a key point set P. A histogram feature descriptor in a normal direction of any key point in set P and a skin point cloud data Q is calculated. Euclidean distance between feature descriptors of two points is calculated through K-nearest neighbor algorithm, and points with high similarity are added into a set M. A clustering is performed on set M using a Hough voting algorithm to obtain a local point cloud set P′ in set P. The method includes fairing skin repair. The boundary line of the point frame is projected onto Q, and a distance between a projection line on the point cloud and the boundary line is calculated to obtain an amount of skin to be repaired.
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公开(公告)号：US11514555B2
公开(公告)日：2022-11-29
申请号：US17169534
申请日：2021-02-07
摘要： The present disclosure provides a point cloud denoising method based on deep learning for an aircraft part, in which different degrees of Gaussian noise are added based on a theoretical data model of the aircraft part, a heightmap for each point in the theoretical data model is generated, and a deep learning training set is constructed. A deep learning network is trained based on the constructed deep learning training set, to obtain a deep learning network model. A real aircraft part is scanned via a laser scanner to obtain measured point cloud data. The normal information of the measured point cloud is predicted based on the trained deep learning network model. Based on the predicted normal information, a position of each point in the measured point cloud data is further updated, thereby completing denoising of the measured point cloud data.
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4.发明授权公开(公告)号：US11938636B2
公开(公告)日：2024-03-26
申请号：US18321840
申请日：2023-05-23
发明人： Jun Wang , Hangbin Zeng , Yuanpeng Liu , Zhengshui Kang , Jianping Yang
CPC分类号： B25J9/1664 , G01B21/20 , B25J19/02
摘要： A feature-guided scanning trajectory optimization method for a 3D measurement robot, including: building a 3D digital model of an aircraft surface; obtaining a size of the 3D digital model; extracting features to be measured; classifying the features to be measured; calculating a geometric parameter of each type of features to be measured; generating an initial scanning trajectory of each type of features to be measured; building a constraint model of the 3D measurement robot; optimizing the initial scanning trajectory into a local optimal scanning trajectory; and planning a global optimal scanning trajectory of each type of features to be measured on the aircraft surface by using a modified ant colony optimization algorithm.
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公开(公告)号：US11823425B2
公开(公告)日：2023-11-21
申请号：US18316326
申请日：2023-05-12
发明人： Jun Wang , Zhongde Shan , Shiyan Hua , Dawei Li
IPC分类号： G06V10/774 , G06T7/00 , G06V10/764 , G06T7/73 , G06V10/77 , G06V10/82
CPC分类号： G06V10/774 , G06T7/0004 , G06T7/73 , G06V10/764 , G06V10/7715 , G06V10/82 , G06T2207/20021 , G06T2207/20081 , G06T2207/20084 , G06T2207/30164
摘要： A few-shot defect detection method based on metric learning, including: (S1) performing data enhancement on a to-be-detected few-shot defect data set through a G2-Generative adversarial network (G2-GAN); (S2) extracting features of a defect data set similar to the to-be-detected few-shot defect data set based on an adaptive convolution kernel-based convolutional neural network (SKM-CNN) to generate a pre-training model; and (S3) transferring the pre-training model to a few-shot defect detection network (S2D2N) based on metric learning; and performing target feature extraction and metric learning in sequence to realize rapid identification and location of defects.
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公开(公告)号：US11544837B2
公开(公告)日：2023-01-03
申请号：US17574843
申请日：2022-01-13
发明人： Zhongde Shan , Jun Wang , Zhengyuan Wei , Honghua Chen , Qian Xie
IPC分类号： G06K9/00 , G06T7/00 , G06T7/55 , G06T7/70 , G06V10/74 , G06V10/75 , G06V10/24 , G06V10/10 , G01B11/16 , G01B11/00
摘要： A method for dynamically measuring deformation of a rotating-body mold, including: (S1) subjecting an overall outer surface of the rotating-body mold to three-dimensional measurement to acquire an initial point cloud data; (S2) shooting, by a multi-camera system, the mold from different angles to obtain three-dimensional coordinates of marking points and coding points on the overall outer surface of the rotating-body mold; (S3) rotating the mold, and repeatedly photographing the marking points and the coding points on the mold surface under different angle poses; and calculating three-dimensional coordinates of the marking points and the coding points; and (S4) predicting a point cloud data of the outer surface under different angle poses based on a conversion relationship among the marking points to analyze a deformation degree of the mold during a rotation process.
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公开(公告)号：US11538181B2
公开(公告)日：2022-12-27
申请号：US17026206
申请日：2020-09-19
发明人： Jun Wang , Qian Xie , Dening Lu , Yuan Zhang
摘要： A method for automated flushness measurement of point cloud rivets, including: extracting a rivet outline by adopting an RANSAC circle fitting algorithm, and determining a center, a radius and a normal vector of an outline circle; extracting point cloud of a rivet head for a single rivet outline; extracting point cloud around the rivet for the single rivet outline; and generating a distance color difference map reflecting rivet flushness according to the point cloud of the rivet head and the point cloud around the rivet. According to the present invention, the point cloud of the rivet head and the point cloud around the rivet can be respectively extracted, and the distance color difference map reflecting the rivet flushness is generated according to the point cloud of the rivet head and the point cloud around the rivet, so that the rivet flushness is rapidly and effectively measured.
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公开(公告)号：US11532121B2
公开(公告)日：2022-12-20
申请号：US17169527
申请日：2021-02-07
摘要： A method for measuring a seam on aircraft skin based on a large-scale point cloud is disclosed. A point cloud density of each point in an aircraft skin point cloud is calculated. Seam and non-seam point clouds are divided according to a discrepancy of the calculated point cloud density. A point is selected from the point cloud of the seam area, and a section at the point is extracted. A certain range of the seam and non-seam point clouds is projected to the section and a projected point cloud is acquired. A calculation model of flush and gap is constructed, and the flush and the gap of the aircraft skin seam at the measuring point is calculated according to the projected point cloud and the calculation model.
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公开(公告)号：US11308632B2
公开(公告)日：2022-04-19
申请号：US17169513
申请日：2021-02-07
发明人： Jun Wang , Zeyong Wei , Qian Xie
摘要： Disclosed herein is a code point-driven three-dimensional (3D) point cloud deformation method. In the method, movable code points and fixed code points are respectively pasted on a moving structure and a static structure. Reference poses of the movable code points and fixed code points are obtained by a dual-camera measurement system, and a 3D point cloud reference model containing the moving structure and the static structure is obtained by 3D laser scanning. A transformation matrix of each code point is calculated, and a real-time point cloud model is established based on the transformation matrix to complete the real-time and dynamic measurement of the moving structure.
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公开(公告)号：US11790517B2
公开(公告)日：2023-10-17
申请号：US18306166
申请日：2023-04-24
发明人： Jun Wang , Zhongde Shan , Shuyi Jia , Dawei Li , Yuxiang Wu
CPC分类号： G06T7/0004 , G06T7/73 , G06T2207/20016 , G06T2207/20081
摘要： A subtle defect detection method based on coarse-to-fine strategy, including: (S1) acquiring data of an image to be detected via a charge-coupled device (CCD) camera; (S2) constructing a defect area location network and preprocessing the image to be detected to initially determine a defect position; (S3) constructing a defect point detection network; and training the defect point detection network by using a defect segmentation loss function; and (S4) subjecting subtle defects in the image to be detected to quantitative extraction and segmentation via the defect point detection network.
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