CN108673899A - A kind of networking 3D printer monitoring system and monitoring method - Google Patents
A kind of networking 3D printer monitoring system and monitoring method Download PDFInfo
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- CN108673899A CN108673899A CN201810328291.5A CN201810328291A CN108673899A CN 108673899 A CN108673899 A CN 108673899A CN 201810328291 A CN201810328291 A CN 201810328291A CN 108673899 A CN108673899 A CN 108673899A
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Classifications
-
- B—PERFORMING OPERATIONS; TRANSPORTING
- B29—WORKING OF PLASTICS; WORKING OF SUBSTANCES IN A PLASTIC STATE IN GENERAL
- B29C—SHAPING OR JOINING OF PLASTICS; SHAPING OF MATERIAL IN A PLASTIC STATE, NOT OTHERWISE PROVIDED FOR; AFTER-TREATMENT OF THE SHAPED PRODUCTS, e.g. REPAIRING
- B29C64/00—Additive manufacturing, i.e. manufacturing of three-dimensional [3D] objects by additive deposition, additive agglomeration or additive layering, e.g. by 3D printing, stereolithography or selective laser sintering
- B29C64/30—Auxiliary operations or equipment
- B29C64/386—Data acquisition or data processing for additive manufacturing
- B29C64/393—Data acquisition or data processing for additive manufacturing for controlling or regulating additive manufacturing processes
-
- B—PERFORMING OPERATIONS; TRANSPORTING
- B22—CASTING; POWDER METALLURGY
- B22F—WORKING METALLIC POWDER; MANUFACTURE OF ARTICLES FROM METALLIC POWDER; MAKING METALLIC POWDER; APPARATUS OR DEVICES SPECIALLY ADAPTED FOR METALLIC POWDER
- B22F3/00—Manufacture of workpieces or articles from metallic powder characterised by the manner of compacting or sintering; Apparatus specially adapted therefor ; Presses and furnaces
- B22F3/115—Manufacture of workpieces or articles from metallic powder characterised by the manner of compacting or sintering; Apparatus specially adapted therefor ; Presses and furnaces by spraying molten metal, i.e. spray sintering, spray casting
-
- B—PERFORMING OPERATIONS; TRANSPORTING
- B29—WORKING OF PLASTICS; WORKING OF SUBSTANCES IN A PLASTIC STATE IN GENERAL
- B29C—SHAPING OR JOINING OF PLASTICS; SHAPING OF MATERIAL IN A PLASTIC STATE, NOT OTHERWISE PROVIDED FOR; AFTER-TREATMENT OF THE SHAPED PRODUCTS, e.g. REPAIRING
- B29C64/00—Additive manufacturing, i.e. manufacturing of three-dimensional [3D] objects by additive deposition, additive agglomeration or additive layering, e.g. by 3D printing, stereolithography or selective laser sintering
- B29C64/30—Auxiliary operations or equipment
- B29C64/386—Data acquisition or data processing for additive manufacturing
-
- B—PERFORMING OPERATIONS; TRANSPORTING
- B33—ADDITIVE MANUFACTURING TECHNOLOGY
- B33Y—ADDITIVE MANUFACTURING, i.e. MANUFACTURING OF THREE-DIMENSIONAL [3-D] OBJECTS BY ADDITIVE DEPOSITION, ADDITIVE AGGLOMERATION OR ADDITIVE LAYERING, e.g. BY 3-D PRINTING, STEREOLITHOGRAPHY OR SELECTIVE LASER SINTERING
- B33Y50/00—Data acquisition or data processing for additive manufacturing
-
- B—PERFORMING OPERATIONS; TRANSPORTING
- B33—ADDITIVE MANUFACTURING TECHNOLOGY
- B33Y—ADDITIVE MANUFACTURING, i.e. MANUFACTURING OF THREE-DIMENSIONAL [3-D] OBJECTS BY ADDITIVE DEPOSITION, ADDITIVE AGGLOMERATION OR ADDITIVE LAYERING, e.g. BY 3-D PRINTING, STEREOLITHOGRAPHY OR SELECTIVE LASER SINTERING
- B33Y50/00—Data acquisition or data processing for additive manufacturing
- B33Y50/02—Data acquisition or data processing for additive manufacturing for controlling or regulating additive manufacturing processes
Abstract
The invention belongs to 3D printing field, a kind of networking 3D printer monitoring system and monitoring method are disclosed, is provided with 3D printing module, the 3D printing module is connect with input module, power plant module control module；The monitoring module is connect with analysis module；The analysis module is connect with control module and alarm modules；The control module is connect with network module.The device, which possesses alarm modules, can make one to realize manipulation long-range realizing the prompting to staff, network module, facilitate the printing of people, can pass through the unmanned printing of real-time performance；The present invention overcomes must carry out region segmentation and grid discrete the problem of could completing target three-dimensional reconstruction in the prior art, it fundamentally avoids cumbersome region segmentation and grid is discrete, the reconstruction process for simplifying optical 3-dimensional imaging realizes accurate, efficient, easy-to-use optical 3-dimensional imaging.
Description
Technical field
The invention belongs to 3D printing field more particularly to networking 3D printer monitoring systems and monitoring method.
Background technology
Currently, the prior art commonly used in the trade is such：
It is one kind based on digital model file currently, 3D printing, material can be bonded with powdery metal or plastic etc.
Material constructs the technology of object by layer-by-layer printing.With the increase of the number of plies and height, the area and shape of synusia profile
Shape can all change, and when shape has greatly changed, be susceptible to fault condition, cause the inclined of model and actual product
Difference leads to the reduction of printout quality, and tradition monitoring printout quality is kept by printer for a long time by operating personnel, is needed
Check printing conditions, this kind of mode of operation intensity is big and time-consuming and laborious, existing in printing when operating personnel midway is left
When failure, then can not immediately it understand.
Optical 3-dimensional imaging be a kind of emerging optical image technology, it by merge measure multi-angle optical signal,
Structure and area optical parameter information, position and intensity based on the optical transport Model Reconstruction target image in accurate region point
Cloth information.The prior art is poor for the solving precision with a variety of scattering properties regions, it is difficult to accurately obtain the position of target
And strength distributing information.Meanwhile there is also uncontrollable factors for grid discrete, which results in the discrete quality of grid to mould
Type solves and rebuilds the uncontrollable influence brought.
In conclusion problem of the existing technology is：
Operating personnel keep by printer for a long time, need to check printing conditions, and this kind of mode of operation intensity is big,
And it is time-consuming and laborious, when operating personnel midway is left, and failure is showed in printing, then can not immediately understand.
It needs to carry out cumbersome region segmentation in the prior art and grid is discrete could obtain optical 3-dimensional imaging reconstruction knot
The problem of fruit.
Invention content
In view of the problems of the existing technology, the present invention provides a kind of networking 3D printer monitoring system and monitoring sides
Method.
The invention is realized in this way a kind of networking 3D printer monitoring system and monitoring method, the networking 3D
Printer monitor system and monitoring method include：Input module, power plant module, 3D printing module, network module, control module,
Alarm modules, analysis module, monitoring module.
The 3D printing module is connect with input module, power plant module control module；
The monitoring module is connect with analysis module；
The analysis module is connect with control module and alarm modules；
The control module is connect with network module.
Monitoring module monitoring method includes：
According to magnetic resonance or the gray scale or texture features of computer tomography voxel data, 3D printing picture appearance is drawn
Boundary contour and interior zone edge line；In voxel data and label based on magnetic resonance or computed tomography reconstruction
Portion's edges of regions line, construction inner boundary node are enriched with function；The structural heterogeneity and optical specificity for considering 3D printing image, are adopted
Transmission process of the light particle in 3D printing image is described with the adaptive optical transmission mathematical model based on mixing photon transport equation；
In view of application advantage of the finite volume method on hexahedron voxel grid, number is transmitted to adaptive optical using extension finite volume method
It learns model and carries out numerical discretization and solution, establish the system equation of linear relationship between target and body surface measurement value in Description；
Consider the imperfection of the sparsity and body surface measurement data of 3D printing image distribution, establish based on sparse Regularization Strategy and melts
Close the object function that priori tentatively marks positioning result；Using suitable Optimization Method object function, 3D printing image is realized
Accurate, the quick reconstruction of target image.
Further, monitoring module monitoring method specifically includes：
Step 1: data acquisition and pretreatment, using multi-mode molecule imaging system, successively acquisition for optical 3-dimensional at
Multi-angle fluorescence data, the magnetic resonance for building voxel physical model or the computer tomography data of picture；Utilize multimode
Pretreatment software in state molecular imaging system is removed ambient noise, extraction area-of-interest pretreatment to fluorescence data；
Bad point bad line, bright field correction, geometric correction pretreatment and said three-dimensional body are compensated to magnetic resonance or computer tomography data
Plain data reconstruction；
Step 2: building voxel-based physical model；
Step 3: structure adaptive optical transmits mathematical model；
Step 4: fusion enrichment function establishes system equation；
Step 5: establishing object function；
Step 6: solving object function, suitable optimization algorithm is selected to solve the object function of foundation, obtains 3D
The spatial position of print image target image and concentration distribution；
Step 7: three-dimensional reconstruction result is shown, the three-dimensional voxel data of target image reconstructed results and acquisition to acquisition
Image co-registration is carried out, the Target space position of reconstruction and concentration distribution are subjected to Three-dimensional Display in 3D printing image.
Further, monitoring module monitoring method specifically includes：
Voxel-based physical model is built to specifically include：
The first step, using the registration software in multi-mode molecule imaging system, by magnetic resonance or computer tomography weight
The three-dimensional voxel Registration of Measuring Data built is drawn with this to being disclosed in digital mouse collection of illustrative plates and marks 3D printing picture appearance wheel
The boundary line of profile and internal image；
Second step, the interior zone boundary line based on three-dimensional voxel data and label, tectonic boundary node are enriched with function：
Wherein, j is voxel node；
ψj(r) it is the inner boundary node enrichment function defined；
vj(r) it is interpolation function；
It is symbolic measurement, is defined as node to the distance away from nearest neighbours Close edges：
Wherein, sign (r) is used for indicating the subordinate relation of point r and boundary Γ：Value is negative if putting inside region, in area
Overseas portion then be just, be then zero on boundary；
It is value of the symbolic measurement on voxel node j；
Third walks, using the internal image boundary line of label as interface, by the conjunction that 3D printing picture breakdown is multiple regions
Collection, and area optical characterisitic parameter is assigned to corresponding region, build voxel-based optical 3-dimensional Imaging physics model.
Further, the structure adaptive optical transmission mathematical model specifically includes：
The first step, according to multiple and corresponding area optical characterisitic parameters of decomposition, by region be divided into high scattering, cavity and
Other three classes, classification foundation are：
Wherein, Ω is the solution domain of 3D printing image construction；ΩhsIt is high scattering region；ΩvIt is cavity area；ΩlsIt is it
His region；μs' it is image reduced scattering coefficient；ζ and χ is classification thresholds, is taken as ζ=10 and χ=0.2mm respectively-1；
Second step considers accuracy and computation complexity, and it is suitable to select different types of region adaptivity
Optical transport model is described；Wherein, transmission process of the light in high scattering region is described using diffusion approximation equation, using certainly
The transmission process of light in the cavities is described by space optical transmission equation, and simplifies ball harmonic approximation equation using three ranks and describes light
Transmission process in other regions；
Third walks, and by the boundary coupling condition of physical quantity between the different optical transport models of construction, structure adaptive optical passes
Defeated mathematical model：
Wherein, φi(r) (i=1,2) is node luminous flux, and S (r) is the energy density point of 3D printing imagery optical probe
Cloth, μa(r) and μaj(r) (j=1,2,3) is that 3D printing image absorbs relevant parameter, and D (r) is 3D printing image diffusion coefficient, βi
(i=1,2) and α is SP3The factor is mismatched with DA equation by boundary, G (r ', r) is the transmission letter for describing radiation transfer theory concept
Number, for describing diffused light from the transmission process in cavity area, B is the interface of scattering region and cavity, and σ (r) is description
The indicator of solution point position is：
High scattering and the photon transport equation of other scattering regions are coupled using following formula:
Wherein, φ0(r) be diffusion approximation equation solution node luminous flux；
Using the photon transport equation in following formula coupling scattering region and cavity:
Wherein, q0(r) it is the graceful luminous flux of promise formed on cavity and scattering region interface；
The fusion enrichment function is established system equation and is specifically included：
Using the voxel-based physical model of structure as domain is solved, function is enriched with using the inner boundary node of fusion constructs
Finite volume method is carried out by numerical discretization and is solved for the adaptive optical of structure transmission mathematical model, establish description 3D printing image
The system equation of linear relationship between measured value：
J=AS；
Wherein, A is sytem matrix, the distribution dependent on three classes biotic district in 3D printing image and corresponding optical characteristics
Parameter；J is the emergent light flow rate of 3D printing image body surface acquisition；S is targeting target energy Density Distribution；
The object function of establishing specifically includes：
The first step considers the imperfection of the sparse characteristic and body surface measurement data of the distribution of body target image, the base of foundation
In lp(0<p<1) the sparse regularization object function of norm：
Wherein, Θ (S) is to be based on lp(0<p<1) object function that the sparse Regularization Strategy of norm is established, SinfIt is that 3D is beaten
The lower limit of watermark image energy density, SsupIt is the upper limit of 3D printing image energy density, JmIt is the luminous flux on outer boundary node
Measured value can will be obtained by the 3D printing imaging surface three-dimensional energy reconstruction technique in non-contact type optical sectioning imaging method
Multi-angle fluorescence data be mapped to acquisition three-dimensional voxel data outer boundary and obtain；λ is sparse regularization parameter；
Second step, using the testing result of target in magnetic resonance or computer tomography data as the preliminary target of priori
Positioning result, limits the feasible zone range of system equation, and feasible zone range limits matrix P and is defined as：
Wherein, R is the feasible zone range obtained by magnetic resonance or computer tomography data reconstruction；
Third walks, and will establish feasible zone range and limits the sparse regularization object function that matrix P is brought into foundation, finally builds
Be based on lpThe object function of sparse Regularization Strategy and fusion structure prior information：
Another object of the present invention is to provide a kind of networking 3D printer monitoring methods to include：It is defeated by input module
Entering to need the article that prints, power is provided by power plant module, monitoring module, which is monitored, to be passed to analysis module and is analyzed,
Analysis result is transferred to control module, control module makes corresponding control, then carries out remote transmission by network module,
If there is wrong data, alarm modules are alarmed.
Advantages of the present invention and good effect are：
The device, which possesses alarm modules, can be made one long-range real realizing the prompting to staff, network module
It now manipulates, facilitates the printing of people, the unmanned printing of real-time performance can be passed through.
The present invention directly on the voxel data of magnetic resonance or computed tomography reconstruction due to carrying out optical 3-dimensional weight
It builds, region segmentation and grid discrete the problem of could completing target three-dimensional reconstruction must be carried out in the prior art by overcoming, from root
Cumbersome region segmentation is avoided in sheet and grid is discrete, is simplified the reconstruction process of optical 3-dimensional imaging, is realized accurate, high
Effect, the imaging of easy-to-use optical 3-dimensional.
The present invention due to simultaneously consider that the difference in terms of structural and optical characteristic parameter establishes optical transport combined mathematics model,
Overcome the optical 3-dimensional imaging method in the prior art based on single approximate equation or mixing photon transport equation is rebuilding essence
Limitation in terms of degree and efficiency, can be accurate to being carried out with irregular structure and the complex target in a variety of scattering properties regions
Really, fast imaging.
Positioning result in the present invention using the testing result of magnetic resonance or computer tomography data as priori, limit
The feasible zone range for determining system equation solution, overcomes the inaccurate problem for directly being positioned and being rebuild in the prior art, has
Effect realize the accurate positionin of target with it is quantitative.
Description of the drawings
Fig. 1 is networking 3D printer monitoring system structural schematic diagram provided in an embodiment of the present invention；
In figure：1, input module；2, power plant module；3,3D printing module；4, network module；5, control module；6, alarm
Module；7, analysis module；8, monitoring module.
Specific implementation mode
In order to further understand the content, features and effects of the present invention, the following examples are hereby given, and coordinate attached drawing
Detailed description are as follows.
The structure of the present invention is explained in detail below in conjunction with the accompanying drawings.
As shown in Figure 1, networking 3D printer monitoring system provided in an embodiment of the present invention includes：Input module 1, power
Module 2,3D printing module 3, network module 4, control module 5, alarm modules 6, analysis module 7, monitoring module 8.
The 3D printing module 3 is connect with input module 1, power plant module 2, control module 5；
The monitoring module 8 is connect with analysis module 7；
The analysis module 7 is connect with control module 5 and alarm modules 6；
The control module 5 is connect with network module 4.
Further, the monitoring module 8 monitors 3D printing module 3.
The operation principle of the present invention：
The article printed is needed by the input of input module 1, provides power by power plant module 2, monitoring module 8 is supervised
Control is passed to analysis module 7 and is analyzed, and analysis result is transferred to control module 5, and control module 5 makes corresponding control,
Then remote transmission is carried out by network module 4, if there is wrong data, alarm modules 6 will sound.
The device, which possesses alarm modules, can be made one long-range real realizing the prompting to staff, network module
It now manipulates, facilitates the printing of people, the unmanned printing of real-time performance can be passed through.
With reference to concrete analysis, the invention will be further described.
Monitoring module monitoring method includes：
According to magnetic resonance or the gray scale or texture features of computer tomography voxel data, 3D printing picture appearance is drawn
Boundary contour and interior zone edge line；In voxel data and label based on magnetic resonance or computed tomography reconstruction
Portion's edges of regions line, construction inner boundary node are enriched with function；The structural heterogeneity and optical specificity for considering 3D printing image, are adopted
Transmission process of the light particle in 3D printing image is described with the adaptive optical transmission mathematical model based on mixing photon transport equation；
In view of application advantage of the finite volume method on hexahedron voxel grid, number is transmitted to adaptive optical using extension finite volume method
It learns model and carries out numerical discretization and solution, establish the system equation of linear relationship between target and body surface measurement value in Description；
Consider the imperfection of the sparsity and body surface measurement data of 3D printing image distribution, establish based on sparse Regularization Strategy and melts
Close the object function that priori tentatively marks positioning result；Using suitable Optimization Method object function, 3D printing image is realized
Accurate, the quick reconstruction of target image.
Further, monitoring module monitoring method specifically includes：
Step 1: data acquisition and pretreatment, using multi-mode molecule imaging system, successively acquisition for optical 3-dimensional at
Multi-angle fluorescence data, the magnetic resonance for building voxel physical model or the computer tomography data of picture；Utilize multimode
Pretreatment software in state molecular imaging system is removed ambient noise, extraction area-of-interest pretreatment to fluorescence data；
Bad point bad line, bright field correction, geometric correction pretreatment and said three-dimensional body are compensated to magnetic resonance or computer tomography data
Plain data reconstruction；
Step 2: building voxel-based physical model；
Step 3: structure adaptive optical transmits mathematical model；
Step 4: fusion enrichment function establishes system equation；
Step 5: establishing object function；
Step 6: solving object function, suitable optimization algorithm is selected to solve the object function of foundation, obtains 3D
The spatial position of print image target image and concentration distribution；
Step 7: three-dimensional reconstruction result is shown, the three-dimensional voxel data of target image reconstructed results and acquisition to acquisition
Image co-registration is carried out, the Target space position of reconstruction and concentration distribution are subjected to Three-dimensional Display in 3D printing image.
Further, monitoring module monitoring method specifically includes：
Voxel-based physical model is built to specifically include：
The first step, using the registration software in multi-mode molecule imaging system, by magnetic resonance or computer tomography weight
The three-dimensional voxel Registration of Measuring Data built is drawn with this to being disclosed in digital mouse collection of illustrative plates and marks 3D printing picture appearance wheel
The boundary line of profile and internal image；
Second step, the interior zone boundary line based on three-dimensional voxel data and label, tectonic boundary node are enriched with function：
Wherein, j is voxel node；
ψj(r) it is the inner boundary node enrichment function defined；
vj(r) it is interpolation function；
It is symbolic measurement, is defined as node to the distance away from nearest neighbours Close edges：
Wherein, sign (r) is used for indicating the subordinate relation of point r and boundary Γ：Value is negative if putting inside region, in area
Overseas portion then be just, be then zero on boundary；
It is value of the symbolic measurement on voxel node j；
Third walks, using the internal image boundary line of label as interface, by the conjunction that 3D printing picture breakdown is multiple regions
Collection, and area optical characterisitic parameter is assigned to corresponding region, build voxel-based optical 3-dimensional Imaging physics model.
Further, the structure adaptive optical transmission mathematical model specifically includes：
The first step, according to multiple and corresponding area optical characterisitic parameters of decomposition, by region be divided into high scattering, cavity and
Other three classes, classification foundation are：
Wherein, Ω is the solution domain of 3D printing image construction；ΩhsIt is high scattering region；ΩvIt is cavity area；ΩlsIt is it
His region；μs' it is image reduced scattering coefficient；ζ and χ is classification thresholds, is taken as ζ=10 and χ=0.2mm respectively-1；
Second step considers accuracy and computation complexity, and it is suitable to select different types of region adaptivity
Optical transport model is described；Wherein, transmission process of the light in high scattering region is described using diffusion approximation equation, using certainly
The transmission process of light in the cavities is described by space optical transmission equation, and simplifies ball harmonic approximation equation using three ranks and describes light
Transmission process in other regions；
Third walks, and by the boundary coupling condition of physical quantity between the different optical transport models of construction, structure adaptive optical passes
Defeated mathematical model：
Wherein, φi(r) (i=1,2) is node luminous flux, and S (r) is the energy density point of 3D printing imagery optical probe
Cloth, μa(r) and μaj(r) (j=1,2,3) is that 3D printing image absorbs relevant parameter, and D (r) is 3D printing image diffusion coefficient, βi
(i=1,2) and α is SP3The factor is mismatched with DA equation by boundary, G (r ', r) is the transmission letter for describing radiation transfer theory concept
Number, for describing diffused light from the transmission process in cavity area, B is the interface of scattering region and cavity, and σ (r) is description
The indicator of solution point position is：
High scattering and the photon transport equation of other scattering regions are coupled using following formula:
Wherein, φ0(r) be diffusion approximation equation solution node luminous flux；
Using the photon transport equation in following formula coupling scattering region and cavity:
Wherein, q0(r) it is the graceful luminous flux of promise formed on cavity and scattering region interface；
The fusion enrichment function is established system equation and is specifically included：
Using the voxel-based physical model of structure as domain is solved, function is enriched with using the inner boundary node of fusion constructs
Finite volume method is carried out by numerical discretization and is solved for the adaptive optical of structure transmission mathematical model, establish description 3D printing image
The system equation of linear relationship between measured value：
J=AS；
Wherein, A is sytem matrix, the distribution dependent on three classes biotic district in 3D printing image and corresponding optical characteristics
Parameter；J is the emergent light flow rate of 3D printing image body surface acquisition；S is targeting target energy Density Distribution；
The object function of establishing specifically includes：
The first step considers the imperfection of the sparse characteristic and body surface measurement data of the distribution of body target image, the base of foundation
In lp(0<p<1) the sparse regularization object function of norm：
Wherein, Θ (S) is to be based on lp(0<p<1) object function that the sparse Regularization Strategy of norm is established, SinfIt is that 3D is beaten
The lower limit of watermark image energy density, SsupIt is the upper limit of 3D printing image energy density, JmIt is the luminous flux on outer boundary node
Measured value can will be obtained by the 3D printing imaging surface three-dimensional energy reconstruction technique in non-contact type optical sectioning imaging method
Multi-angle fluorescence data be mapped to acquisition three-dimensional voxel data outer boundary and obtain；λ is sparse regularization parameter；
Second step, using the testing result of target in magnetic resonance or computer tomography data as the preliminary target of priori
Positioning result, limits the feasible zone range of system equation, and feasible zone range limits matrix P and is defined as：
Wherein, R is the feasible zone range obtained by magnetic resonance or computer tomography data reconstruction；
Third walks, and will establish feasible zone range and limits the sparse regularization object function that matrix P is brought into foundation, finally builds
Be based on lpThe object function of sparse Regularization Strategy and fusion structure prior information：
The above is only the preferred embodiments of the present invention, and is not intended to limit the present invention in any form,
Every any simple modification made to the above embodiment according to the technical essence of the invention, equivalent variations and modification, belong to
In the range of technical solution of the present invention.
Claims (5)
1. a kind of networking 3D printer monitoring system, which is characterized in that the networking 3D printer monitoring system and monitoring
Method is provided with：3D printing module；
The 3D printing module is connect with input module, power plant module control module；
The monitoring module is connect with analysis module；
The analysis module is connect with control module and alarm modules；
The control module is connect with network module；
Monitoring module monitoring method includes：
According to magnetic resonance or the gray scale or texture features of computer tomography voxel data, 3D printing picture appearance boundary is drawn
Contour line and interior zone edge line；The inner area of voxel data and label based on magnetic resonance or computed tomography reconstruction
Domain edge line, construction inner boundary node are enriched with function；The structural heterogeneity and optical specificity for considering 3D printing image, using base
Transmission process of the light particle in 3D printing image is described in the adaptive optical transmission mathematical model of mixing photon transport equation；In view of
Application advantage of the finite volume method on hexahedron voxel grid transmits mathematical modulo using extension finite volume method to adaptive optical
Type carries out numerical discretization and solution, establishes the system equation of linear relationship between target and body surface measurement value in Description；Consider
The imperfection of the sparsity and body surface measurement data of 3D printing image distribution is established first based on sparse Regularization Strategy and fusion
Test the object function of preliminary mark positioning result；Using suitable Optimization Method object function, 3D printing image object is realized
Accurate, the quick reconstruction of image.
2. networking 3D printer monitoring system as described in claim 1, which is characterized in that monitoring module monitoring method is specifically wrapped
It includes：
Step 1: data acquisition and pretreatment, using multi-mode molecule imaging system, acquisition is for optical 3-dimensional imaging successively
Multi-angle fluorescence data, the magnetic resonance for building voxel physical model or computer tomography data；Utilize multi-modal point
Pretreatment software in sub- imaging system is removed ambient noise, extraction area-of-interest pretreatment to fluorescence data；To magnetic
Resonance or computer tomography data compensate bad point bad line, bright field correction, geometric correction pretreatment and said three-dimensional body prime number
According to reconstruction；
Step 2: building voxel-based physical model；
Step 3: structure adaptive optical transmits mathematical model；
Step 4: fusion enrichment function establishes system equation；
Step 5: establishing object function；
Step 6: solving object function, suitable optimization algorithm is selected to solve the object function of foundation, obtains 3D printing
The spatial position of image object image and concentration distribution；
Step 7: three-dimensional reconstruction result is shown, the three-dimensional voxel data of target image reconstructed results and acquisition to acquisition carry out
The Target space position of reconstruction and concentration distribution are carried out Three-dimensional Display by image co-registration in 3D printing image.
3. networking 3D printer monitoring system as claimed in claim 2, which is characterized in that monitoring module monitoring method is specifically wrapped
It includes：
Voxel-based physical model is built to specifically include：
The first step is obtained magnetic resonance or computed tomography reconstruction using the registration software in multi-mode molecule imaging system
To three-dimensional voxel Registration of Measuring Data to being disclosed in digital mouse collection of illustrative plates, drawn with this and mark 3D printing picture appearance contour line
With the boundary line of internal image；
Second step, the interior zone boundary line based on three-dimensional voxel data and label, tectonic boundary node are enriched with function：
Wherein, j is voxel node；
ψj(r) it is the inner boundary node enrichment function defined；
vj(r) it is interpolation function；
It is symbolic measurement, is defined as node to the distance away from nearest neighbours Close edges：
Wherein, sign (r) is used for indicating the subordinate relation of point r and boundary Γ：Value is negative if putting inside region, outside region
Portion then be just, be then zero on boundary；
It is value of the symbolic measurement on voxel node j；
Third walks, using the internal image boundary line of label as interface, by the intersection that 3D printing picture breakdown is multiple regions, and
Area optical characterisitic parameter is assigned to corresponding region, builds voxel-based optical 3-dimensional Imaging physics model.
4. networking 3D printer monitoring system as claimed in claim 2, which is characterized in that the structure adaptive optical transmits number
Model is learned to specifically include：
The first step, according to multiple and corresponding area optical characterisitic parameters of decomposition, by region be divided into high scattering, cavity and other
Three classes, classification foundation are：
Wherein, Ω is the solution domain of 3D printing image construction；ΩhsIt is high scattering region；ΩvIt is cavity area；ΩlsIt is other areas
Domain；μs' it is image reduced scattering coefficient；ζ and χ is classification thresholds, is taken as ζ=10 and χ=0.2mm respectively-1；
Second step considers accuracy and computation complexity, and suitable light is selected different types of region adaptivity to pass
Defeated model is described；Wherein, transmission process of the light in high scattering region is described using diffusion approximation equation, using free sky
Between photon transport equation the transmission process of light in the cavities described, and simplify ball harmonic approximation equation using three ranks and describe light at it
Transmission process in his region；
Third walks, and by the boundary coupling condition of physical quantity between the different optical transport models of construction, structure adaptive optical transmits number
Learn model：
Wherein, φi(r) (i=1,2) is node luminous flux, and S (r) is the energy density distribution of 3D printing imagery optical probe, μa
(r) and μaj(r) (j=1,2,3) is that 3D printing image absorbs relevant parameter, and D (r) is 3D printing image diffusion coefficient, βi(i=
1,2) and α is SP3The factor is mismatched with DA equation by boundary, G (r ', r) is the transmission function for describing radiation transfer theory concept, is used
In description diffused light from the transmission process in cavity area, B is the interface of scattering region and cavity, and σ (r) is description solution point
The indicator of position is：
High scattering and the photon transport equation of other scattering regions are coupled using following formula:
Wherein, φ0(r) be diffusion approximation equation solution node luminous flux；
Using the photon transport equation in following formula coupling scattering region and cavity:
Wherein, q0(r) it is the graceful luminous flux of promise formed on cavity and scattering region interface；
The fusion enrichment function is established system equation and is specifically included：
Using the voxel-based physical model of structure as domain is solved, having for function is enriched with using the inner boundary node of fusion constructs
It limits volumetric method the adaptive optical transmission mathematical model of structure is carried out numerical discretization and solved, establishes description 3D printing image and survey
The system equation of linear relationship between magnitude：
J=AS；
Wherein, A is sytem matrix, the distribution dependent on three classes biotic district in 3D printing image and corresponding optical characteristics ginseng
Number；J is the emergent light flow rate of 3D printing image body surface acquisition；S is targeting target energy Density Distribution；
The object function of establishing specifically includes：
The first step, consider body target image distribution sparse characteristic and body surface measurement data imperfection, foundation based on lp(0
<p<1) the sparse regularization object function of norm：
Wherein, Θ (S) is to be based on lp(0<p<1) object function that the sparse Regularization Strategy of norm is established, SinfIt is 3D printing figure
As the lower limit of energy density, SsupIt is the upper limit of 3D printing image energy density, JmIt is the luminous flux measurement on outer boundary node
Value, can be by the 3D printing imaging surface three-dimensional energy reconstruction technique in non-contact type optical sectioning imaging method by the more of acquisition
Angle fluorescent data are mapped to the outer boundary of the three-dimensional voxel data of acquisition and obtain；λ is sparse regularization parameter；
Second step is positioned the testing result of target in magnetic resonance or computer tomography data as the preliminary target of priori
As a result, limiting the feasible zone range of system equation, feasible zone range limits matrix P and is defined as：
Wherein, R is the feasible zone range obtained by magnetic resonance or computer tomography data reconstruction；
Third walks, and will establish feasible zone range and limits the sparse regularization object function that matrix P is brought into foundation, finally establishes base
In lpThe object function of sparse Regularization Strategy and fusion structure prior information：
5. a kind of networking 3D printer monitoring method of networking 3D printer monitoring system as described in claim 1, special
Sign is that the networking 3D printer monitoring method includes：The article printed is needed by input module input, passes through power
Module provides power, and monitoring module, which is monitored, to be passed to analysis module and analyzed, and analysis result is transferred to control module,
Control module makes corresponding control, then by network module carry out remote transmission, if there is wrong data, alarm modules into
Row alarm.
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| CN113787719A (en) * | 2021-09-13 | 2021-12-14 | 珠海赛纳三维科技有限公司 | Three-dimensional object printing failure positioning method, device, equipment and storage medium |
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