CN106780721A - Three-dimensional laser spiral scanning point cloud three-dimensional reconstruction method - Google Patents
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Abstract
The invention discloses a three-dimensional laser spiral scanning point cloud three-dimensional reconstruction method, which comprises the following steps: establishing a point cloud data structure containing three-dimensional coordinates of points, relevant angle information and rotation times; storing the scanned spiral line point cloud data according to the established point cloud data structure, and reordering the spiral line point cloud data according to the relevant angle information and the rotation times of each point; sectioning the reordered spiral line point cloud data according to the rotation times to obtain single-contour line point clouds with the same number as the rotation times; and optimizing each single contour line point cloud, and connecting according to the principle that whether the relevant angles of the upper and lower single contour line point clouds are the same or not to form a three-dimensional solid model. According to the method, all point cloud data participate in calculation, the three-dimensional form of the point cloud is reserved to the maximum extent, and finally, the three-dimensional reconstruction entity is matched with the three-dimensional form of the point cloud without holes, so that an accurate three-dimensional reconstruction entity is formed, and a foundation is provided for subsequent data utilization.
Description
Technical field
The present invention relates to Point Cloud Processing technical field, more particularly to a kind of three-dimensional laser spiral scanning spot cloud Three-dimensional Gravity
Construction method.
Background technology
There are many approach in cloud data source, such as by three-dimensional laser scanner, photogrammetric, three coordinate measuring machine
Deng.Cloud data is topological structure at random, is a kind of dispersion point cloud, and inorganization data set is can be described as again, between points milli
Without inner link.The purpose of cloud data three-dimensional reconstruction is to find certain mathematical description form, construction one with summit and
The triangular mesh model of topological relation is connected with each other, and grid is analyzed, optimized, changed and painted in itself on this basis
System.It is popular research direction how dispersion point cloud to be reconstructed into threedimensional model, but measurand is scanned through the point for obtaining
Cloud huge number, reaches hundreds of thousands point, even more than millions of points, and point cloud is distributed sparse inequality, to dispersion point cloud
Three-dimensional reconstruction brings very big challenge and difficulty, there is presently no a kind of general point cloud three-dimensional rebuilding method.For at random
Point cloud three-dimensional reconstruction, many researchers propose various solutions, and common point cloud three-dimensional rebuilding method has：
1st, the three-dimensional reconstruction algorithm based on Delaunay Triangulation.
Curve reestablishing based on Delaunay Triangulation is also referred to as engraving method, that is, first pass through the convex closure for calculating point cloud, so
The triangular facet relevant with a cloud surface configuration is found out according to the rule of setting afterwards, then constantly being removed from convex closure need not
Tetrahedron carry out curve reestablishing.As Boissonnat took the lead in proposing the curved surface based on Delaunay Triangulation in 1984
Algorithm for reconstructing, first does Delaunay trigonometric ratios to a cloud, and such as point in fruit dot cloud is not located on the convex closure of point cloud, then constantly deletes entirely
Except the tetrahedron in convex closure, until the point in a cloud is all located on the surface of body, this individual surface is exactly to need to rebuild curved surface
One it is approximate；Bajaj etc. proposes, using signed distance function reconstruction curved surface is constructed, to achieve good effect in nineteen ninety-five.
Amenta et al. proposed the Crust algorithms based on three-dimensional Voronoi diagram in 1998, then had also been proposed Cocone algorithms,
Further optimize Crust algorithms, but this kind of algorithm amount of calculation all cause greatly very much it is inefficient；Adamy et al. proposes to be based on
The UmbrellaFilter methods of Delaunay subdivisions.Such algorithm be directed to a cloud Delaunay trigonometric ratios or
The calculating of Voronoi diagram, amount of calculation is inefficient than larger.
However, still there is following defect in such scheme：1) the Time ＆ Space Complexity problem of algorithm, that is, efficiency
Problem, for the flood tide cloud data that laser scanning is obtained, carries out three-dimensional reconstruction by the way of triangulation, does not examine
The logical relation between scanning element cloud is considered, it is necessary to travel through a cloud and carried out triangle to it and cut open and to take a significant amount of time, in reality
Cannot often receive in the application of border.2) three-dimensional reconstruction is carried out by the way of triangulation, it is necessary to calculate a cloud convex closure, Ran Houzai
Step wise approximation point cloud exterior three dimensional form, the physical model of last three-dimensional reconstruction depends on the distributed in three dimensions situation of point cloud, if
There is the situation for being recessed or putting the sparse inequality of cloud in point cloud, then the physical model of three-dimensional reconstruction will not conform to the actual conditions.
2nd, three-dimensional reconstruction algorithm based on RBF etc..
Three-dimensional reconstruction based on RBF is that three-dimensional reconstruction problem is converted into function Solve problems, and then realizes three
Dimension is rebuild.Typical method has：Hoppe proposes the three-dimensional reconstruction algorithm based on vector distance function, this side in its thesis for the doctorate
Although method practice effect is good, complexity also than relatively low, is only applicable to uniform, the intensive situation of sampling, and presence cannot be extensive
Sharp features of appearing again and the curved surface that recovers without original point set shortcoming；Kazhdan introduces Fast Fourier Transform (FFT)
To in three-dimensional reconstruction, but the method takes more internal memory, and cannot be applied to largely put the situation of cloud；Subsequent Kazhdan
Et al. Problems of Reconstruction is converted into space Poisson's equation Solve problems and then three-dimensional surface is obtained, the method obtains good effect
Really；Method based on region extension is general first since a seed triangle, and the side of triangle is added into wavefront side chain table
In, for chained list in every a line an optimum point is determined in a cloud according to the optimum point selection criterion on side, with this edge
The new triangle of composition, and current extensions side is deleted from wavefront side chain table, newly-generated side is added, until wavefront side chain table is
Space-time terminates.This method it is critical only that the optimal summit what kind of criterion to determine side according in a cloud.
However, still there is following defect in such scheme：Using the three-dimensional rebuilding method based on RBF, Three-dimensional Gravity
Can there is the situation of hole in the physical model built, especially when the sparse inequality of three-dimensional point cloud of collection, then the reality of three-dimensional reconstruction
Body Model will show riddled with gaping wounds state, differ too big with real body surface, and cannot recover sharp features.
The content of the invention
It is an object of the invention to provide a kind of three-dimensional laser spiral scanning spot cloud three-dimensional rebuilding method, can obtain scanning
Scattered point cloud data fast and accurately three-dimensional reconstruction is follow-up data using providing basis into physical model.
The purpose of the present invention is achieved through the following technical solutions：
A kind of three-dimensional laser spiral scanning spot cloud three-dimensional rebuilding method, including：
Set up the cloud data structure of three-dimensional coordinate and related angle information comprising point and number of revolutions；
The helix cloud data for obtaining will be scanned to be stored according to the cloud data structure set up, and according to each
The related angle information of point is resequenced with number of revolutions to helix cloud data；
Cutting is carried out to the helix cloud data after rearrangement according to number of revolutions, number identical with number of revolutions is obtained
The single-wheel profile point cloud of amount；
Treatment is optimized to each single-wheel profile point cloud, according still further to upper and lower single-wheel profile point cloud related angle whether
Principle of identity is attached, and forms three-dimensional entity model.
Related angle information in foregoing cloud data structure includes：Axial angle θ, radial angle α；Number of revolutions is
Axial-rotation frequency n.
The foregoing related angle information put according to each is resequenced to helix cloud data with number of revolutions and is wrapped
Include：
Traversal helix cloud data, the helix cloud data of traversal puts in order by axial-rotation frequency n and axial direction
Angle is arranged；If number of revolutions n1<N2, then the corresponding all cloud datas of number of revolutions n1 are all arranged in rotation time
Before the corresponding all cloud datas of number n2；If cloud data number of revolutions is identical, then cloud data is according to axial angle θ
Size is arranged, and the small point of axial angle is arranged in front, after the big point of axial angle is arranged in；Ensure spiral shell through the above way
Spin line cloud data is arranged according to helix tandem.
Foregoing carries out cutting to the helix cloud data after rearrangement according to number of revolutions, obtains and number of revolutions
The single-wheel profile point cloud of equal number includes：
Subdivision is carried out according to axial-rotation frequency n, a whole piece helix cloud data is cut into n bar single-wheel profile points
Cloud, forms n bar single-wheel profile cloud datas, makes a kind of helix cloud data from dispersion point cloud condition conversion without logical construction
Into a kind of contour line point cloud form for having a logical construction.
It is foregoing treatment is optimized to each single-wheel profile point cloud to include：
One parameter γ is set, then is 360/ γ equal portions by the cutting of each single-wheel profile point cloud, each equal portions is interval
Corresponding is an angular interval；
Assuming that m-th equal portions interval is P, according to the corresponding equal portions interval angular range of cloud data axial angle, if
A point is only existed inside the P of equal portions interval, then as the starting point coordinate of equal portions interval P；If inside exist one with
On point, just take center-of-mass coordinate a little as equal portions interval P starting point coordinate；If inside is without point, just equal portions
In bar single-wheel profile point cloud where interval P axial angle less than equal portions interval P start angles and angle difference absolute value most
In bar single-wheel profile point cloud where small point coordinates, with equal portions interval P axial angle more than equal portions interval P termination points and
The minimum point coordinates of the difference absolute value of angle is attached by straight line, then separates this according to equal portions interval P start angle value differences
The starting point coordinate of equal portions interval P；According to this data processing method, then each single-wheel profile point cloud is corresponding to count out
It is fixed, is 360/ γ point, and each corresponding axial angle angle value of point is also fixed, is m*360/ γ °, and point cloud is sat
Mark is according to above computational methods it has been determined that each single-wheel profile point cloud is reorganized into a cloud number according to equal portions compartmention
According to the new n bar single-wheel profile point clouds of formation.
Whether principle of identity is attached the foregoing related angle according to upper and lower single-wheel profile point cloud, forms solid object surface
Including：
With a series of tri patch of interconnections according to corresponding identical equal portions angle value between contour line by upper and lower two
Bar single-wheel profile point cloud is coupled together；Numerous triangular facets that each point is formed on upper and lower two single-wheel profiles point cloud are connected, is constituted
The three-dimensional surface of interconnection, and can not intersect in tri patch each other, so as to form three-dimensional entity model.
As seen from the above technical solution provided by the invention, three-dimensional laser helical scanning cloud data has been taken into full account
Between logical construction, on this basis to cloud data subdivision be a plurality of single-wheel profile point cloud, while every single-wheel of optimization processing
Profile point cloud, makes upper and lower single-wheel profile point cloud corresponding points radial angle (equal portions angle) consistent, can allow every in this way
Individual point is known is attached with specific which point, without being traveled through to whole cloud data, when having saved a large amount of
Between, efficiency of algorithm is very high, and whole scheme allows all cloud datas to participate in calculating, and at utmost remains the three-dimensional of a cloud
Form, last three-dimensional reconstruction entity coincide with point cloud three-dimensional configuration, does not have hole, accurate three-dimensional reconstruction entity is formed, after being
The application of aspects such as the calculating of continuous volume, Feature matching provide reliable data basis.
Brief description of the drawings
Technical scheme in order to illustrate more clearly the embodiments of the present invention, below will be to that will use needed for embodiment description
Accompanying drawing be briefly described, it should be apparent that, drawings in the following description are only some embodiments of the present invention, for this
For the those of ordinary skill in field, on the premise of not paying creative work, other can also be obtained according to these accompanying drawings
Accompanying drawing.
Fig. 1 is three-dimensional laser scanner helical scanning schematic diagram provided in an embodiment of the present invention；
Fig. 2 is a kind of three-dimensional laser spiral scanning spot cloud three-dimensional rebuilding method flow chart provided in an embodiment of the present invention；
Fig. 3 is illustrated by the three-dimensional laser helical scanning cloud data gathered in confirmatory experiment provided in an embodiment of the present invention
Figure；
Fig. 4 is the three-dimensional reconstruction result schematic diagram in confirmatory experiment provided in an embodiment of the present invention.
Specific embodiment
With reference to the accompanying drawing in the embodiment of the present invention, the technical scheme in the embodiment of the present invention is carried out clear, complete
Ground description, it is clear that described embodiment is only a part of embodiment of the invention, rather than whole embodiments.Based on this
Inventive embodiment, the every other implementation that those of ordinary skill in the art are obtained under the premise of creative work is not made
Example, belongs to protection scope of the present invention.
The present invention proposes that one kind is applied to three-dimensional laser spiral scanning spot cloud three-dimensional rebuilding method, is mainly used in three-dimensional laser
Scanner carries out reconstructing three-dimensional model after obtaining three-dimensional point cloud.There are many approach in cloud data source, such as by three-dimensional laser
Scanner, photogrammetric, three coordinate measuring machine etc..
In the embodiment of the present invention, three-dimensional laser scanner carries out form scanning using helical scanning mode, uses
A kind of moving interpolation control mode, axial direction electric machine is continuously rotated, and radial motor is back and forth transported according to interpolated point position
It is dynamic, a whole piece helix point cloud is ultimately formed, if these clouds are attached according to context one such as Fig. 1 will be formed
Shown helix.
Scheme computational efficiency provided in an embodiment of the present invention is very high, three-dimensional reconstruction physical model with actually match, and
And physical model is not in hole, three-dimensional spiral scanning element cloud three-dimensional reconstruction can be solved with solving the problems, such as very well.
As shown in Fig. 2 be a kind of three-dimensional laser spiral scanning spot cloud three-dimensional rebuilding method provided in an embodiment of the present invention, its
Mainly comprise the following steps：
Step 1, the cloud data structure for setting up the three-dimensional coordinate comprising point and related angle information and number of revolutions.
In the embodiment of the present invention, the related angle information in cloud data structure includes：Axial angle θ, radial angle α,
Axial angle represents the corresponding angle of axial direction electric machine rotation, radial angle and represents radial motor rotation corresponding angle；Number of revolutions
It is axial-rotation frequency n.
Step 2, the helix cloud data for obtaining scanning are stored according to the cloud data structure set up, and according to
The related angle information of each point is resequenced with number of revolutions to helix cloud data.
In the embodiment of the present invention, the process to the rearrangement of helix cloud data is as follows：Traversal helix cloud data,
The helix cloud data of traversal puts in order and arranged by axial-rotation frequency n and axial angle；If number of revolutions n1<
N2, then before the corresponding all cloud datas of number of revolutions n1 are all arranged in the corresponding all cloud datas of number of revolutions n2；
If cloud data number of revolutions is identical, then cloud data is arranged according to axial angle θ sizes, the small point of axial angle
It is arranged in front, after the big point of axial angle is arranged in；Before and after ensureing helix cloud data according to helix through the above way
Order is arranged.
Step 3, cutting is carried out to the helix cloud data after rearrangement according to number of revolutions, obtained and number of revolutions
The single-wheel profile point cloud of equal number.
In the embodiment of the present invention, subdivision is carried out according to axial-rotation frequency n, a whole piece helix cloud data is cut into
N bar single-wheel profile point clouds, form n bar single-wheel profile cloud datas, make a kind of helix cloud data from dissipating without logical construction
Disorderly point cloud form state changes into a kind of contour line point cloud form for having a logical construction.
Step 4, treatment is optimized to each single-wheel profile point cloud, according still further to the related angle of upper and lower single-wheel profile point cloud
Whether principle of identity is attached degree, forms three-dimensional entity model.
In the embodiment of the present invention, optimization process is as follows：One parameter γ is set (for example, can be set between 0.1 ° -1 °
Any one value), then be 360/ γ equal portions by the cutting of each single-wheel profile point cloud, it is one that each equal portions interval is corresponding
Angular interval；Assuming that parameter γ is set to 1 °, then the interval corresponding angle initial range of the 10th equal portions is 9 ° -10 °.Due to all
Cloud data is sorted according to axial angle size, it is assumed that m-th equal portions interval is P, according to cloud data axial direction
The corresponding equal portions interval angular range of angle, if inside only exists a point, as the starting point of equal portions interval P
Coordinate；If there is more than one point in inside, just take center-of-mass coordinate a little sat as the starting point of equal portions interval P
Mark；If inside is without point, then just that axial angle in the bar single-wheel profile point cloud where the P of equal portions interval is interval less than equal portions
In the minimum point coordinates of the difference absolute value of P start angles and angle, with the bar single-wheel profile point cloud where the P of equal portions interval axially
The angle point coordinates minimum more than the difference absolute value of equal portions interval P termination points and angle is attached by straight line, Ran Hougen
The starting point coordinate of equal portions interval P is separated according to equal portions interval P start angle value differences；According to this data processing method, then
Each single-wheel profile corresponding the counting out of point cloud is fixed, is 360/ γ point, and each corresponding axial angle of point
Value is also fixed, is m*360/ γ °, and point cloud coordinate is according to above computational methods it has been determined that each single-wheel profile point cloud
Cloud data is reorganized into according to equal portions compartmention, new n bar single-wheel profile point clouds are formed.
Form three-dimensional entity model process as follows：With a series of tri patch of interconnections according to correspondence between contour line
Identical equal portions angle value upper and lower two single-wheel profiles point cloud is coupled together；Connect each on upper and lower two single-wheel profiles point cloud
Numerous triangular facets that point is formed, constitute the three-dimensional surface being connected with each other, and can not intersect in tri patch each other,
So as to form three-dimensional entity model.
The such scheme of the embodiment of the present invention, has taken into full account the logic knot between three-dimensional laser helical scanning cloud data
Structure, is on this basis a plurality of single-wheel profile point cloud to cloud data subdivision, while every single-wheel profile point cloud of optimization processing, makes
Upper and lower single-wheel profile point cloud corresponding points axial angle (equal portions angle) is consistent, and each point can be allowed to know in this way should
It is attached with specific which point, without being traveled through to whole cloud data, has been saved the plenty of time, efficiency of algorithm is non-
Chang Gao, and whole scheme allows all cloud datas to participate in calculating, and at utmost remains the three-dimensional configuration of a cloud, it is last three-dimensional
Rebuild entity to be coincide with point cloud three-dimensional configuration, there is no hole, form accurate three-dimensional reconstruction entity, be follow-up volume calculate, it is real
The application of aspects such as body cutting provide reliable data basis.
On the other hand, associated verification experiment has also been carried out in order to verify the effect of such scheme.
Beijing Mine and Metallurgy General Inst B411 laboratories three-dimensional laser helical scanning cloud data is used in this confirmatory experiment
(as shown in Figure 3), point cloud number is 246501, and cloud data is cut into 180 single-wheel profiles, and parameter γ is set to 1 °.
Scanning element cloud is a progressively abducent helix point cloud since scan start point as can be seen from Figure 3, and point cloud
There is sparse uneven situation in data.Fig. 4 is using a kind of three-dimensional laser spiral scanning spot cloud three-dimensional reconstruction side proposed by the present invention
Method carries out three-dimensional reconstruction result to scanning element cloud, and three-dimensional reconstruction entity and the scanning element cloud form of formation are coincide very much, point cloud point
Sharp feature is retained, and three-dimensional reconstruction entity, without cavity situation, point cloud three-dimensional reconstruction is time-consuming 11 seconds, and efficiency is very high.
Through the above description of the embodiments, those skilled in the art can be understood that above-described embodiment can
Realized with by software, it is also possible to realized by the mode of software plus necessary general hardware platform.Based on such understanding,
The technical scheme of above-described embodiment can be embodied in the form of software product, and the software product can store non-easy at one
The property lost storage medium (can be CD-ROM, USB flash disk, mobile hard disk etc.) in, including some instructions are used to so that a computer sets
Standby (can be personal computer, server, or network equipment etc.) performs the method described in each embodiment of the invention.
The above, the only present invention preferably specific embodiment, but protection scope of the present invention is not limited thereto,
Any one skilled in the art in the technical scope of present disclosure, the change or replacement that can be readily occurred in,
Should all be included within the scope of the present invention.Therefore, protection scope of the present invention should be with the protection model of claims
Enclose and be defined.
Claims (6)
1. a kind of three-dimensional laser spiral scanning spot cloud three-dimensional rebuilding method, it is characterised in that including：
Set up the cloud data structure of three-dimensional coordinate and related angle information comprising point and number of revolutions；
The helix cloud data for obtaining will be scanned to be stored according to the cloud data structure set up, and put according to each
Related angle information is resequenced with number of revolutions to helix cloud data；
Cutting is carried out to the helix cloud data after rearrangement according to number of revolutions, is obtained and number of revolutions equal number
Single-wheel profile point cloud；
Treatment is optimized to each single-wheel profile point cloud, whether the related angle according still further to upper and lower single-wheel profile point cloud is identical
Principle is attached, and forms three-dimensional entity model.
2. a kind of three-dimensional laser spiral scanning spot cloud three-dimensional rebuilding method according to claim 1, it is characterised in that point cloud
Related angle information in data structure includes：Axial angle θ, radial angle α；Number of revolutions is axial-rotation frequency n.
3. a kind of three-dimensional laser spiral scanning spot cloud three-dimensional rebuilding method according to claim 2, it is characterised in that described
The related angle information put according to each includes with number of revolutions to the rearrangement of helix cloud data：
Traversal helix cloud data, the helix cloud data of traversal puts in order by axial-rotation frequency n and axial angle
Arranged；If number of revolutions n1<N2, then the corresponding all cloud datas of number of revolutions n1 are all arranged in number of revolutions n2
Before corresponding all cloud datas；If cloud data number of revolutions is identical, then cloud data is according to axial angle θ sizes
Arranged, the small point of axial angle is arranged in front, after the big point of axial angle is arranged in；Ensure helix through the above way
Cloud data is arranged according to helix tandem.
4. a kind of three-dimensional laser spiral scanning spot cloud three-dimensional rebuilding method according to claim 1 and 2, it is characterised in that
It is described that cutting is carried out to the helix cloud data after rearrangement according to number of revolutions, obtain and number of revolutions equal number
Single-wheel profile point cloud includes：
Subdivision is carried out according to axial-rotation frequency n, a whole piece helix cloud data is cut into n bar single-wheel profile point clouds, shape
Into n bar single-wheel profile cloud datas, make helix cloud data from a kind of dispersion point cloud condition conversion without logical construction into one
Plant the contour line point cloud form for having logical construction.
5. a kind of three-dimensional laser spiral scanning spot cloud three-dimensional rebuilding method according to claim 1 and 2, it is characterised in that
It is described treatment is optimized to each single-wheel profile point cloud to include：
One parameter γ is set, then is 360/ γ equal portions, the interval correspondence of each equal portions by the cutting of each single-wheel profile point cloud
Be an angular interval；
Assuming that m-th equal portions interval is P, according to the corresponding equal portions interval angular range of cloud data axial angle, if equal portions
A point is only existed inside interval P, then as the starting point coordinate of equal portions interval P；If inside exists more than one
Point, just take center-of-mass coordinate a little as equal portions interval P starting point coordinate；If inside is without point, just equal portions interval P
The axial angle point minimum less than the difference absolute value of equal portions interval P start angles and angle in the bar single-wheel profile point cloud at place
In bar single-wheel profile point cloud where coordinate, with equal portions interval P axial angle more than equal portions interval P termination points and angle it
The minimum point coordinates of difference absolute value is attached by straight line, then separates the equal portions area according to equal portions interval P start angle value differences
Between P starting point coordinate；According to this data processing method, then each single-wheel profile corresponding the counting out of point cloud is fixed
, be 360/ γ point, and each corresponding axial angle angle value of point is also fixed, is m*360/ γ °, point cloud coordinate according to
Above computational methods are it has been determined that each single-wheel profile point cloud is reorganized into cloud data, shape according to equal portions compartmention
The n bar single-wheel profile point clouds of Cheng Xin.
6. a kind of three-dimensional laser spiral scanning spot cloud three-dimensional rebuilding method according to claim 5, it is characterised in that described
According to the related angle of upper and lower single-wheel profile point cloud, whether principle of identity is attached, and forming solid object surface includes：
With a series of tri patch of interconnections according to corresponding identical equal portions angle value between contour line by upper and lower two lists
Contour line point cloud is coupled together；Numerous triangular facets that each point is formed on upper and lower two single-wheel profiles point cloud are connected, is constituted mutual
The three-dimensional surface of connection, and can not intersect in tri patch each other, so as to form three-dimensional entity model.
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| CN108257222A (en) * | 2018-01-31 | 2018-07-06 | 杭州中科天维科技有限公司 | The automatic blending algorithm of steel stove converter three-dimensional laser point cloud |
| CN108642750A (en) * | 2018-04-27 | 2018-10-12 | 江苏东方生态清淤工程有限公司 | A kind of bionical screw high-pressure nozzle and its design method for the cleaning of board and frame machine filter cloth |
| CN111649694A (en) * | 2020-06-04 | 2020-09-11 | 四川大学 | Implicit phase-parallax mapping binocular measurement missing point cloud interpolation method |
| CN111649694B (en) * | 2020-06-04 | 2021-05-04 | 四川大学 | Implicit phase-parallax mapping binocular measurement missing point cloud interpolation method |
| CN112147037A (en) * | 2020-10-09 | 2020-12-29 | 中国电建集团贵阳勘测设计研究院有限公司 | Method for detecting density of rockfill body through three-dimensional imaging |
| CN116021161A (en) * | 2022-12-30 | 2023-04-28 | 惠州洋瑞印刷包装有限公司 | Hard plastic product processing device and control method thereof |
| CN116021161B (en) * | 2022-12-30 | 2023-09-01 | 广州富星电声科技股份有限公司 | Hard plastic product processing device and control method thereof |
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