Distortion quantifier for analyzing surfaces
US-9429421-B2 · Aug 30, 2016 · US
US11544837B2 · US · B2
| Field | Value |
|---|---|
| Publication number | US-11544837-B2 |
| Application number | US-202217574843-A |
| Country | US |
| Kind code | B2 |
| Filing date | Jan 13, 2022 |
| Priority date | Feb 10, 2021 |
| Publication date | Jan 3, 2023 |
| Grant date | Jan 3, 2023 |
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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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What is claimed is: 1. A method for dynamically measuring deformation of a rotating-body mold, comprising: (S 1 ) subjecting an overall outer surface of the rotating-body mold to three-dimensional measurement to acquire an initial point cloud data; (S 2 ) shooting, by a multi-camera system, the rotating-body mold from different angles to obtain three-dimensional coordinates of marking points and three-dimensional coordinates of coding points on the overall outer surface of the rotating-body mold; (S 3 ) rotating the rotating-body mold, and repeatedly photographing the marking points and the coding points on the overall outer surface under different angle poses; and respectively calculating three-dimensional coordinates of the marking points and three-dimensional coordinates of the coding points under different angle poses; and (S 4 ) predicting point cloud data of the overall outer surface under different angle poses based on a conversion relationship among the marking points to analyze a deformation degree of the rotating-body mold during a rotation process; wherein the step (S 2 ) is performed through steps of: (S 21 ) planning a plurality of stations for photogrammetry followed by photographing; wherein each of the plurality of stations is configured to contain as many of the marking points as possible; and adjacent stations are configured to contain at least four common marking points; (S 22 ) recognizing coding marks in images respectively taken in the plurality of stations; (S 23 ) subjecting images with common coding marks to matching; unifying the images respectively taken in the plurality of stations into a photogrammetric coordinate system using the coding marks; and obtaining an exterior orientation element of each image; (S 24 ) based on known exterior orientation elements of the images respectively taken in the plurality of stations, subjecting other non-coding mark points to correspondence points matching using an epipolar matching method; and (S 25 ) calculating the three-dimensional coordinates of the marking points through bundle adjustment to obtain marking point data t 1 ={t 1_1 , t 2_1 , . . . , t n_1 } of a total of n marking points in a first pose; wherein the step (S 4 ) is performed through steps of: (S 41 ) based on a rigid-body transformation of coding points on a chuck, unifying marking point data obtained under multiple angle poses into a common coordinate system; (S 42 ) calculating a transformation relationship between marking points adjacent to outer surface points under multiple angle poses to reversely obtain a three-dimensional coordinate set P 1 , P 2 , . . . , P i of the overall outer surface under a corresponding pose, wherein i is a number of poses corresponding to a rotation angle; and (S 43 ) analyzing the deformation degree of the rotating-body mold during the rotation process based on three-dimensional coordinates of the overall outer surface under multiple angle poses; wherein the step (S 43 ) is performed through steps of: (S 431 ) calculating a distance between surface points of adjacent stations, wherein a distance between P 1 and P 2 is d 1 , a distance between P 2 and P 3 is d 2 , and so on, and a distance between P i-1 and P i is d i-1 ; and a distance array is expressed as d={d 1 , d 2 , . . . , d i-1 }; and (S 432 ) calculating an average value and a variance of the distance array d={d 1 , d 2 , . . . , d i-1 } to evaluate the deformation degree of the rotating-body mold. 2. The method of claim 1 , wherein the step (S 1 ) is performed through steps of: (S 11 ) pasting the coding points on the overall outer surface and cylindrical surfaces of chucks on both sides of the rotating-body mold at a certain density, and pasting the marking points randomly on the overall outer surface; wherein the coding points are configured for construction of a global coordinate system and a data alignment reference; and the marking points are configured for sampling increase and subsequent conversion and calculation of a surface data; (S 12 ) placing a reference ruler and a benchmark; taking multiple sets of overlapping photos using MaxShot, and performing three-dimensional calculation of the coding points via image triangulation to establish a measurement coordinate system; and (S 13 ) measuring three-dimensional point cloud data P 1 ={p 1 , p 2 , . . . , p m } of the overall outer surface of the rotating-body mold through binocular C-Track transformation using MetraScan. 3. The method of claim 1 , wherein the step (S 3 ) is performed through steps of: rotating the rotating-body mold, and repeating the step (S 2 ) to shoot and calculate marking point data t 2 ={t 1_2 , t 2_2 , . . . , t n_2 }, . . . , t i ={t 1_i , t 2_i , . . . , t n_i } under different angle poses, wherein i is the number of poses corresponding to a rotation angle. 4. The method of claim 1 , wherein the step (S 41 ) is performed through steps of: (S 411 ) recognizing coding points on cylindrical surfaces of chucks on both sides of the rotating-body mold in a captured image; and (S 412 ) taking the marking point data t 1 ={t 1_1 , t 2_1 , . . . , t n_1 } measured for the first pose as a reference to calculate a rotation matrix among coordinates of coding points with a same serial number; and subjecting the marking point data obtained under multiple angle poses to alignment; wherein the marking point data after alignment are s 1 ={s 1_1 , s 2_1 , . . . , s n_1 }, s 2 ={s 1_2 , s 2_2 , . . . , s n_2 }, . . . , s i ={s 1_i , s 2_i , . . . , s n_i }; and s 1 =t 1 . 5. The method of claim 1 , wherein the step (S 42 ) is performed throughs steps of: (S 421 ) finding k neighboring marking points {(s 1_1 , s 2_1 , . . . , s k_1 ), (s 1_2 , s 2_2 , . . . , s k_2 ), . . . , (s 1_i , s 2_i , . . . , s k_i )} of outer surface points p j in an initial station in a marking point data set {s 1 , s 2 , . . . , s i }; (S 422 ) calculating three-dimensional coordinates of points on the overall outer surface of the rotating-body mold at a second station, expressed as p j_2 =p j_1 +(θ 1 (s 1_2 −s 1_1 )+θ 2 (s 2_2 −s 2_1 )+ . . . +θ k (s k_2 −s k_1 ))/k; wherein θ k is a weight of each neighboring marking point; and the closer a marking point is to p j_1 , the greater its weight is; and (S 423 ) repeating the step (S 422 ) to calculate a three-dimensional coordinate set P 1 , P 2 , . . . , P i of the overall outer surface under multiple angle poses.
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