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21.发明授权公开(公告)号：US11359945B2
公开(公告)日：2022-06-14
申请号：US17169529
申请日：2021-02-07
Inventor： Jun Wang , Dawei Li , Yuxiang Wu , Cheng Yi , Xu Xu
Abstract: An inspection device for subway tunnel based on three-dimensional laser scanning includes a three-dimensional laser scanner, an adaptive structure of a track trolley, a power control module for the track trolley, a photoelectric sensor and a body of the track trolley. The power control module is arranged on the body. A support rod is vertically arranged on the power control module, and the three-dimensional laser scanner is mounted at a top of the support rod. The adaptive structure is symmetrically arranged at two sides of the body of the track trolley, and the photoelectric sensor is arranged in the body of the track trolley. The inspection device is designed to be modular, which is convenient to carry and repair, and easy to mount. In addition, the inspection device has low labor cost due to less manual intervention, and the inspection efficiency can be improved.
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22.发明授权公开(公告)号：US11836896B2
公开(公告)日：2023-12-05
申请号：US18320280
申请日：2023-05-19
Inventor： Jun Wang , Kun Xiao , Zikuan Li , Tianchi Zhong
CPC classification number: G06T3/60 , G06T3/4038
Abstract: A semantic segmentation method for aircraft point cloud based on voxelization and three views, including: filtering a collected point cloud followed by centralization to obtain a centralized point cloud; inputting the centralized point cloud into a T-Net rotation matrix network; rotating the centralized point cloud to a front side followed by voxelization to obtain a voxelized point cloud; subjecting the voxelized point cloud to voxel filling to obtain a voxel-filled point cloud; calculating thickness maps of three views of the voxel-filled point cloud, followed by sequentially stitching and inputting to the point cloud semantic segmentation network to train the point cloud semantic segmentation network; inputting the collected point cloud into the trained point cloud semantic segmentation network; and predicting a result semantic segmentation of a 3D point cloud of the aircraft.
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公开(公告)号：US11830164B2
公开(公告)日：2023-11-28
申请号：US18316317
申请日：2023-05-12
Inventor： Jun Wang , Zhongde Shan , Kaijun Zhang , Zikuan Li , Chao Li
IPC: G06T3/40
CPC classification number: G06T3/4046
Abstract: This application discloses a semantic learning-based down-sampling method of point cloud data of an aircraft, including: (S1) constructing a multi-input encoder based on feature learning according to point cloud semantic learning principle; inputting the point cloud data of the aircraft and feature point data into the multi-input encoder for feature fusion followed by decoding using a decoder the multi-input feature fused data to obtain to-be-measured data; (S2) constructing and training a point cloud feature weight calculation network based on semantic learning to acquire a feature weight of each point in the to-be-measured data; and (S3) performing spatial weighted sampling on the feature weight of each point in the to-be-measured data followed by down-sampling based on Gaussian distribution-based spatial sampling principle.
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Patent Agency Ranking
公开(公告)号：US11661686B2
公开(公告)日：2023-05-30
申请号：US17702145
申请日：2022-03-23
Inventor： Zhongde Shan , Jun Wang , Yaoyao Wang , Haoqin Yang , Chao Li
Abstract: A mechanism for radially inserting a yarn into a 3D braided preform, including a first bracket, an upper linear actuator, a support mechanism, an upper yarn insertion device, a yarn carrying device, an upper gear ring, a lower yarn insertion device, a lower linear actuator, a second bracket, a lower gear ring, a lower gear, a lower motor, a lower circular track, an upper circular track, a base, an upper gear, a pneumatic transmission and control device and an upper motor.
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公开(公告)号：US11557029B2
公开(公告)日：2023-01-17
申请号：US17574827
申请日：2022-01-13
Inventor： Zhongde Shan , Jun Wang , Anyi Huang , Qian Xie
IPC: G06T7/00 , G06T7/50 , G06T7/11 , G06V10/77 , G06V10/774 , G06V20/70 , G06T7/30 , G06V10/776 , G06V10/25 , G06V10/26
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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公开(公告)号：US11543795B2
公开(公告)日：2023-01-03
申请号：US17026262
申请日：2020-09-20
Inventor： Jun Wang , Zeyong Wei , Honghua Chen
IPC: G05B19/402 , G01M5/00
Abstract: The present invention relates to an airplane structure stiffener repair method based on measured data guidance. The method includes: respectively measuring point cloud data on a surface of a structure stiffener and point cloud data on a surface of a to-be-assembled position of a body; respectively extracting all assembly plane features in two point cloud data based on an RANSAC algorithm; performing pre-alignment according to the plane features; performing accurate alignment based on a signed distance constraint according to repair tolerance requirements; and calculating a repair allowance, and generating a machining path to serve as an accurate machining basis. According to the method in the present invention, a repair amount can be accurately calculated by virtue of an alignment algorithm of the signed distance constraint, and an envelope relationship during model matching is met.
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公开(公告)号：US11532123B2
公开(公告)日：2022-12-20
申请号：US17574796
申请日：2022-01-13
Inventor： Jun Wang , Zikuan Li , Anyi Huang , Qian Xie
IPC: G06T17/00
Abstract: A method for visualizing a large-scale point cloud based on normal, including: (S1) according to a spatial structure of a point cloud data, constructing a balanced octree structure of a node point cloud; (S2) according to the balanced octree structure and normal information of a point cloud, constructing an octree structure with the normal information; and constructing a normal level-of-detail (LOD) visualization node through downsampling; and (S3) determining a node scheduling strategy according to a relationship between a viewpoint, a viewing frustum and a normal of a render node; and respectively calling a reading thread and a rendering thread to simultaneously perform reading and rendering according to the node scheduling strategy.
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28.发明授权公开(公告)号：US11037346B1
公开(公告)日：2021-06-15
申请号：US17026260
申请日：2020-09-20
Inventor： Jun Wang , Yan Wang , Yuanpeng Liu , Qian Xie
Abstract: Disclosed a multi-station scanning global point cloud registration method based on graph optimization, including acquiring multi-station original three-dimensional point cloud data; based on initial registration of targets, completing initial registration of point cloud data at adjacent stations by virtue of the target at each angle of view; calculating a point cloud overlap area at adjacent angles of view, and calculating areas of overlap regions of adjacent point cloud by a gridded sampling method; constructing a fine registration graph structure, and constructing a fine registration graph by taking point cloud data of each station as a node of the graph and taking an overlap area of the point cloud data of adjacent stations as a side of adjacent nodes of the graph structure; and based on loop closure fine registration based on graph optimization, gradually completing point cloud fine registration of the whole aircraft according to a specific closure sequence.
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