CN113688545A - Visualization method and system for finite element post-processing result and data processing terminal - Google Patents
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Abstract
The invention belongs to the technical field of computer aided manufacturing and computer aided engineering, and discloses a method and a system for visualizing a finite element post-processing result and a data processing terminal, wherein the method for visualizing the finite element post-processing result comprises the following steps: modeling a part or a component to be analyzed by using CAE software, and generating nodes and topological information containing a finite element analysis model; constructing a primitive through OpenGL to form a finite element mesh model; finite element analysis is carried out in CAE software to obtain a variable field needing to be output; performing RGB calculation by using scalar variables output after CAE analysis, and giving corresponding nodes; calling a camera by utilizing an ARToolKit system, and displaying a finite element analysis result in a real-time scene on a screen; and adjusting the calibration position to enable the analysis result to be overlapped with the finite element processing scene. According to the invention, the primitive construction is carried out through OpenGL, the obtained cloud picture is smoother, and a relatively ideal three-dimensional visualization effect is realized.
Description
Technical Field
The invention belongs to the technical field of computer aided manufacturing and computer aided engineering, and particularly relates to a method and a system for visualizing a finite element post-processing result and a data processing terminal.
Background
At present, the finite element analysis technology is an effective means for improving the product quality, shortening the design period and improving the product competitiveness, and is widely applied in the fields of mechanical manufacturing, material processing, aerospace and the like which need to save the analysis time and the experiment cost. Computer Aided Engineering (CAE) software for finite element methods currently in use, such as ABAQUS, ANSYS, MARC, etc.
For the CAE software currently in use, the display after the finite element analysis is completed is generally based on the virtual model created before the analysis. The deformation of the part in the processing and assembling process can cause the part to have certain shape deviation with the theoretical model, and the display mode is not visual enough for finite element analysis of the part with the produced model in the assembling or experiment process and has poor visualization degree.
The invention patent with the patent number of CN 110688801A discloses a method for optimizing keel fittings based on finite element analysis, which can optimize FUU keel fittings, improve the bearing capacity of the FUU keel, and is convenient in operation process, but finite element simulation has errors, grid division is not reasonable, so that the simulation result has larger difference from reality, and the visual analysis of the processing result is not realized; the invention patent with patent number CN 101982837 a discloses a fast three-dimensional visualization method based on a finite element analysis post-processing result, which provides a way for combining the finite element technology and the virtual reality technology, but because the method is to perform operation processing on the grid unit bodies, the generated three-dimensional model has a lower visualization degree and has a larger difference with the real object model. In summary, the combined use of numerical simulation technology and virtual reality technology is not mature at present in China, and the combination of the logic accuracy of numerical simulation and the reality of virtual reality is difficult. On one hand, the finite element analysis post-processing technology has limitations, so that the simulation result deviates from reality, and the finite element analysis result is difficult to apply to a virtual reality system due to the difference between the model specification of the finite element analysis and the virtual reality model interface; on the other hand, the diversity of the data processing methods of the virtual reality technology causes the visualization effect displayed after processing to be different. Therefore, a new method for visualizing the finite element post-processing result is needed.
Through the above analysis, the problems and defects of the prior art are as follows:
(1) the deformation of the part in the processing and assembling process can cause the part to have certain shape deviation with a theoretical model, and the existing display mode is not visual enough for finite element analysis of the part with the produced model in the assembling or experiment process and has poor visualization degree.
(2) In the prior art, finite element simulation has errors, the simulation result is greatly different from reality due to improper grid division, and the visual analysis of the processing result is not realized; the grid unit bodies are subjected to operation processing, so that the generated three-dimensional model is low in visualization degree and has a large difference with a real object model.
(3) At present, the combination use of a numerical simulation technology and a virtual reality technology is not mature at home, the logic accuracy of numerical simulation and the reality of virtual reality are difficult to combine, and the visualization effect displayed after the processing is different due to the diversity of data processing methods of the virtual reality technology.
(4) The finite element analysis post-processing technology has limitations, so that a simulation result has deviation from reality, and a model specification of the finite element analysis is different from a virtual reality model interface, so that the finite element analysis result is difficult to apply to a virtual reality system.
The difficulty in solving the above problems and defects is:
(1) the difficulty of visualization of the finite element lies in visual derivation of a simulation result after a finite element simulation process) to a required display platform and interact with the virtual reality, and a model specification output by the finite element is different from a virtual reality model interface, so that an extra platform needs to be constructed to convert and be compatible with the virtual reality model interface.
(2) The finite element simulation error is caused by the fact that the establishment of a finite element model is difficult to have complete consistency with an actual part, the precision of finite element simulation analysis depends on the division of grids to a great extent, the division of the grids is limited by computer computing power, and the complete and real assembly or experiment process cannot be achieved.
The significance of solving the problems and the defects is as follows:
(1) the problem of interaction between a finite element result model and virtual reality is solved, the finite element analysis can be displayed on a part to be analyzed in real time, and errors can be judged and corrected quickly and intuitively.
(2) The technical field of the existing finite element analysis is difficult to obtain a larger breakthrough in a short period, so that the limitation problem of the finite element technology is difficult to obtain a larger improvement, but a more accurate finite element simulation result can be obtained by improving a model, improving the accuracy of the model and reasonably dividing a grid in a key point mode.
Disclosure of Invention
Aiming at the problems in the prior art, the invention provides a method and a system for visualizing a finite element post-processing result and a data processing terminal, and particularly relates to a method and a system for visualizing a finite element analysis processing result based on augmented reality.
The invention is realized in such a way that a visualization method for finite element post-processing results comprises the following steps:
the method comprises the following steps that firstly, CAE software is used for modeling parts or components needing to be analyzed, and nodes and topology information containing a finite element analysis model are generated; the step is not only to carry out corresponding component modeling on the entity, but also to transfer the extracted nodes and topology information to the virtual reality part, which is a data bridge forming the visualization process, and to transfer the initial information of the model in the process.
Step two, carrying out primitive construction through OpenGL to form a finite element grid model; this step receives the data information of step one and converts it into visible primitive information.
Step three, carrying out finite element analysis in CAE software to obtain a variable field needing to be output; the method comprises the core step of analyzing stress strain change through CAE software
Step four, performing RGB calculation by using scalar variables output after CAE analysis, and endowing corresponding nodes with the scalar variables; this step is similar to step one, in which model result data and node stress-strain data are transferred.
Step five, calling a camera by using an ARToolKit system, and displaying a finite element analysis result in a real-time scene on a screen; the step realizes interaction of the finite element analysis result and the virtual reality.
And step six, adjusting the calibration position to enable the analysis result to be superposed with the finite element processing scene.
Further, in the first step, the CAE software is Abaqus, a modeling system of the Abaqus or other CAD modeling software compatible with the Abaqus is selected for modeling, and an inp file is read after modeling; analyzing the structure by a finite element method, discretizing a continuous solution domain, namely dividing the solution domain into finite units which are mutually connected by nodes, analyzing and calculating the field quantity on a network point on the basis, and finishing the visual processing of drawing the cloud picture;
nodes control the geometry of the data, while cells control the geometry of the data; the unit data and the node data form finite element analysis data, a voxel network is constructed during modeling, and the finite element analysis data and the node data are processed by using a mesh division function of an Abaqus system or other point cloud data and mesh division software after modeling;
and performing network modeling by using the 8-Node 6-plane monomer unit, reading a Node part and an Element part in a file, respectively storing the Node part and the Element part in a Node list and a unit topology list, and defining the unit by using the Node and topology data so as to divide a grid.
Further, in the second step, the constructing the primitive through OpenGL includes:
determining a construction method according to the element type used for the finite element analysis: sequentially connecting each point to the plane unit and the axisymmetric unit; for the space unit, the space unit is decomposed into a plurality of planes, the combined nodes of all the planes are analyzed and are respectively connected in sequence to form all the plane nodes, and drawing is finished;
drawing primitives in OpenGL through programming, wherein the common functions for constructing geometric primitives in OpenGL comprise glBegin (mode) and glend (); where a mode creates the type of primitive, the three values most commonly used by a mode are: GL _ POINTS, GL _ LINES, and GL _ POLYGON;
constructing the geometric primitive by using different mode types according to different unit types; for an 8-node 6-surface unit as an example, selecting a mode parameter GL _ LINES, and sequentially drawing twelve edges of each hexahedron to construct geometric primitives so as to form a finite element mesh model.
Further, the GL _ poits is configured to treat the defined vertex as an independent point unit; if n points are defined at one time, n independent vertexes are defined; GL _ LINES, if reading n vertexes at a time, representing and defining n/2 line segments, and connecting two points between each point in sequence to form a line segment; GL _ POLYGON, when reading n points at a time, represents a convex POLYGON with the n points as vertices.
Further, in the third step, performing finite element analysis by using Abaqus, endowing material attributes, section attributes and grid attributes of the model besides the existing grid model, giving a load state and a boundary state according to the analyzed environment state, performing visual analysis on created operation and submitted operation, and exporting node data; and the Python script is used for operation in engineering, and the finite element analysis process is rapidly and automatically completed.
Further, in the fourth step, reconstructing the stress cloud image obtained by the finite element analysis by using OpenGL, including:
reading node data derived from the Abaqus operation, wherein the node data gives a stress strain value corresponding to each node, and the read file is an rpt file; drawing the cloud picture by a scalar drawing method;
the read file firstly obtains the maximum value and the minimum value of a scalar, and a color lookup table is established through the two maximum values; selecting an RGB mode as a color value, and using a short Rainbow algorithm which is more consistent with a color lookup table used by Abaqus as a color lookup table; the short Rainbow algorithm takes the minimum scalar value as blue and the maximum scalar value as red;
establishing a corresponding relation between a scalar value and a color, namely an RGB value by using a short Rainbow algorithm; for any scalar value, converting the scalar value into RGB color according to the size of the scalar value and a color lookup table; acquiring three-dimensional information of nodes and corresponding field values, filling until all grids are filled, and finishing the visualization of a scalar cloud chart;
after converting the three-dimensional scalar into the corresponding color in the color comparison table, calling OpenGL related functions, and completing cloud picture filling and drawing by using a Lagrange linear interpolation mode; the call function glColor3f (r, g, b) is chosen to set the color for each point, with the rgb values for glColor3f ranging from a floating point number between 0 and 1.
Further, in the fifth step, the invoking the camera by using the ARToolKit system includes:
the method comprises the following steps of calling a camera by utilizing the ARToolkit, identifying by utilizing the camera, directly selecting a marker provided by the ARToolkit to make an identification, printing and pasting the identification on a part or a component to be displayed, calling an ARToolkit program to perform virtual-real fusion of a finite element postprocessing result and a real environment, wherein the flow of an augmented reality virtual-real fusion algorithm of the finite element postprocessing result is as follows:
binarization of a video image: because the identification points are black and white, the binaryzation simplifies the image without influencing the characteristics of the pattern of the identification points, and a black and white image only containing 0 and 1 is obtained;
connecting the area identifiers: obtaining a connected domain in the image by adopting a connected domain marking algorithm to obtain a candidate connected domain set;
and thirdly, tracking the boundary of the connected region: obtaining the region boundary of each candidate region by using a region boundary tracking algorithm;
finding candidate quadrilateral areas: obtaining a candidate quadrilateral area by using a quadrilateral detection algorithm;
extracting the mark points: four vertexes of a quadrangle are used as characteristic points in the ARToolkit, linear regression algorithm is adopted for the four sides of the quadrangle to carry out linear fitting, and intersection points of the four linear are extracted to obtain the four vertexes of the quadrangle;
sixthly, identification point coding and decoding: the decoding process of the identification point actually compares the internal pattern of the current identification point with all the identification point patterns stored in the system one by one to find out a consistent match;
estimation of the posture: the camera directly acquires the projection coordinates of the identification point to the camera, and the identification point matrix under the world coordinates can be calculated according to the internal parameters of the camera and the artificially given rotation and translation matrix;
and adopting OpenGL to reconstruct the cloud picture, wherein the OpenGL and the ARToollit have the same working environment, so that the reconstructed cloud picture model can be directly called in the ARToollit to complete virtual fusion. After the virtual-real fusion is completed, repeated template training is carried out on the camera, the most appropriate coverage effect is selected by changing the translation and rotation matrixes, and the most appropriate coverage effect is stored, so that the expected virtual-real fusion effect can be obtained.
Another object of the present invention is to provide a visualization system for a finite element post-processing result, which applies the visualization method for a finite element post-processing result, the visualization system for a finite element post-processing result comprising:
the finite element analysis model building module is used for modeling a part or a component to be analyzed by using CAE software and generating a node containing a finite element analysis model and topological information;
the finite element mesh model construction module is used for constructing the primitives through OpenGL to form a finite element mesh model;
the finite element analysis module is used for carrying out finite element analysis in CAE software to obtain a variable field to be output;
the scalar variable calculation module is used for performing RGB calculation by using the scalar variables output after CAE analysis and endowing the calculated scalar variables to corresponding nodes;
the analysis result display module is used for calling the camera by utilizing an ARToolKit system and displaying a finite element analysis result in a real-time scene on a screen;
and the virtual-real fusion module is used for enabling the analysis result to be overlapped with the finite element processing scene by adjusting the calibration position.
It is a further object of the invention to provide a computer device comprising a memory and a processor, the memory storing a computer program which, when executed by the processor, causes the processor to perform the steps of:
modeling a part or a component to be analyzed by using CAE software, and generating nodes and topological information containing a finite element analysis model; constructing a primitive through OpenGL to form a finite element mesh model; finite element analysis is carried out in CAE software to obtain a variable field needing to be output;
performing RGB calculation by using scalar variables output after CAE analysis, and giving corresponding nodes; calling a camera by utilizing an ARToolKit system, and displaying a finite element analysis result in a real-time scene on a screen; and adjusting the calibration position to enable the analysis result to be overlapped with the finite element processing scene.
The invention also aims to provide an information data processing terminal, which is used for realizing the finite element post-processing result visualization system.
By combining all the technical schemes, the invention has the advantages and positive effects that: according to the method for visualizing the finite element post-processing result, the pixel construction is carried out through OpenGL, and the cloud image obtained after the finite element network model is subjected to finite element analysis through CAE software is smoother. The invention also combines CAE analysis with ARTookKit system, so that the finite element analysis result realizes ideal three-dimensional visualization effect.
According to the method for visualizing the finite element analysis processing result, a post-processing module technology in CAE software is not directly applied to grid division, node information containing a finite element analysis model is generated after modeling, and a cloud picture generated after the established finite element network model is subjected to finite element analysis is more accurate through OpenGL primitive construction processing; according to the method, an ARToolkit system is used, node data which are output and processed after CAE analysis are combined, RGB calculation is carried out on an output scalar variable, corresponding nodes are given, the state change of a model is easier to observe, the visualization of a finite element analysis result is achieved through a virtual reality technology, the visualization degree of a three-dimensional model generated after the virtual reality technology is processed is higher due to the generation of an accurate finite element analysis cloud diagram, the visualization effect is more consistent with a real object, the visualization effect can be calibrated on the real object, the finite element model is accurately projected onto the real object through the identification of the ARToolkit, and the state change of the object under a real-time scene under load is observed through a screen.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings needed to be used in the embodiments of the present invention will be briefly described below, and it is obvious that the drawings described below are only some embodiments of the present invention, and it is obvious for those skilled in the art that other drawings can be obtained according to the drawings without creative efforts.
FIG. 1 is a flowchart of a method for visualizing a finite element post-processing result according to an embodiment of the present invention.
Fig. 2 is a schematic diagram of an architecture of an ARToolKit-based finite element post-processing augmented reality on-site display technology according to an embodiment of the present invention.
FIG. 3 is a block diagram of a system for visualizing a finite element post-processing result according to an embodiment of the present invention;
in the figure: 1. a finite element analysis model building module; 2. a finite element mesh model building module; 3. a finite element analysis module; 4. a scalar variable calculation module; 5. an analysis result display module; 6. and a virtual-actual fusion module.
Fig. 4 is a flowchart of a mesh model rendering process according to an embodiment of the present invention.
Fig. 5 is a flowchart of scalar cloud mapping according to an embodiment of the present invention.
Fig. 6 is an identification diagram of ARToolkit provided by the embodiment of the present invention.
Fig. 7 is a flowchart of ARToolKit algorithm development provided by the embodiment of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention is further described in detail with reference to the following embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.
Aiming at the problems in the prior art, the invention provides a visualization method, a visualization system and a data processing terminal for finite element post-processing results, and the invention is described in detail below with reference to the accompanying drawings.
As shown in fig. 1, a method for visualizing a finite element post-processing result according to an embodiment of the present invention includes the following steps:
s101, modeling a part or a component to be analyzed by using CAE software, and generating nodes and topological information containing a finite element analysis model;
s102, carrying out primitive construction through OpenGL to form a finite element mesh model;
s103, carrying out finite element analysis in CAE software to obtain a variable field needing to be output;
s104, performing RGB (red, green and blue) calculation by using a scalar variable output after CAE (computer aided engineering) analysis, and giving corresponding nodes;
s105, calling a camera by using an ARToolKit system, and displaying a finite element analysis result in a real-time scene on a screen;
and S106, adjusting the calibration position to enable the analysis result to be overlapped with the finite element processing scene.
As shown in fig. 3, a system for visualizing a finite element post-processing result according to an embodiment of the present invention includes:
the finite element analysis model building module 1 is used for modeling a part or a component to be analyzed by using CAE software and generating a node containing a finite element analysis model and topological information;
the finite element mesh model construction module 2 is used for constructing the primitives through OpenGL to form a finite element mesh model;
the finite element analysis module 3 is used for carrying out finite element analysis in CAE software to obtain a variable field to be output;
the scalar variable calculation module 4 is used for performing RGB calculation by using the scalar variables output after CAE analysis and endowing the calculated scalar variables to corresponding nodes;
the analysis result display module 5 is used for calling a camera by utilizing an ARToolKit system and displaying a finite element analysis result in a real-time scene on a screen;
and the virtual-real fusion module 6 is used for enabling the analysis result to be superposed with the finite element processing scene by adjusting the calibration position.
The technical solution of the present invention will be further described with reference to the following examples.
The technical problems to be solved by the invention are as follows:
(1) errors exist in finite element simulation, and a more accurate modeling method needs to be adopted to obtain a more accurate cloud picture;
(2) the combination of numerical simulation technology and virtual reality technology needs to be solved;
(3) reasonable virtual reality technology is needed to enable the visualization effect of the processed model display to be better.
The invention provides a finite element analysis processing result visualization method based on augmented reality, wherein the element construction is carried out through OpenGL, and the cloud image obtained after finite element analysis of a formed finite element network model is carried out through CAE software is smoother. The invention also combines CAE analysis with ARTookKit system, so that the finite element analysis result realizes ideal three-dimensional visualization effect.
In order to achieve the purpose, the invention adopts the technical scheme that: a visualization method for processing results of finite element analysis in augmented reality comprises the following steps:
(1) modeling a part or a component to be analyzed, and generating nodes and topology information containing a finite element analysis model;
(2) constructing a primitive through OpenGL to form a finite element mesh model;
(3) finite element analysis is carried out in CAE software to obtain a variable field needing to be output;
(4) performing RGB calculation by using scalar variables output after CAE analysis, and giving corresponding nodes;
(5) using an ARToolKit system to call a camera, and displaying a finite element analysis result in a real-time scene on a screen;
(6) and adjusting the calibration position to enable the analysis result to be overlapped with the finite element processing scene.
The augmented reality site display technology architecture based on ARToolKit provided by the embodiment of the invention is shown in fig. 2, and the specific operation steps are as follows:
(1) the CAE finite element software is selected as Abaqus, a modeling system of the Abaqus or other CAD modeling software compatible with the Abaqus is selected for modeling, and the inp file is read after modeling. For the finite element method to analyze the structure, firstly, a continuous solution domain is discretized, namely, the solution domain is divided into a finite number of units which are mutually connected by nodes, and on the basis, the field quantity on a network point can be analyzed and calculated, so that the visualization processing such as cloud picture drawing is completed. Nodes control the geometry of the data, and cells control the geometry of the data. The element data and the node data constitute finite element analysis data, for example, displacement and speed which are generally scattered on the node belong to the node data, and stress and strain which are generally scattered on the element belong to the element data. Therefore, a voxel network is required to be constructed during modeling, and after modeling, the voxel network is required to be processed by using a meshing function of an Abaqus system or other point cloud data and meshing software, such as geomagic. And carrying out network modeling by using 8-node 6-plane monomer units. The partitioning of the mesh model is shown in fig. 4. And reading a Node part and an Element part in the file, respectively storing the Node part and the Element part into a Node list and a unit topology list, and defining units by using the nodes and topology data so as to divide grids.
(2) Primitive construction in OpenGL is required. First, the construction method needs to be determined according to the type of element used for finite element analysis: sequentially connecting each point to the plane unit and the axisymmetric unit; for the space unit, the space unit needs to be decomposed into a plurality of planes, then the combined nodes of all the planes are analyzed and sequentially connected to form all the plane nodes respectively, and drawing is completed. Programming is required for drawing primitives in OpenGL. Commonly used functions for constructing geometric primitives in OpenGL are glBegin (mode) and glend (), where mode creates primitive types such as: points, lines, independent triangles, etc. The following are the three values most commonly used by mode: GL _ POINTS: the defined vertices are treated as independent point units. If n points are defined at one time, n independent vertexes are defined; GL _ LINES: if n vertexes are read in at a time, n/2 line segments are defined, and the two points are sequentially connected into a line segment between each point; GL _ POLYGON: if n points are read in at a time, a convex polygon with the n points as vertexes is defined. And according to different unit types, different mode types are used for constructing the geometric primitive. For an 8-node 6-surface unit as an example, selecting a mode parameter GL _ LINES, and sequentially drawing twelve edges of each hexahedron to construct geometric primitives so as to form a finite element mesh model.
(3) The finite element analysis is carried out by utilizing the Abaqus, material attributes, section attributes and grid attributes of the model are required to be given besides the existing grid model, a load state and a boundary state are given according to the analyzed environment state, finally, visual analysis is carried out on creating operation and submitting operation, and node data are exported. In order to improve the analysis speed, the Python script can be used for operation in engineering, and the finite element analysis process is rapidly and automatically completed.
(4) And reconstructing the stress cloud picture obtained by the finite element analysis by utilizing OpenGL. First, node data derived from the Abaqus job needs to be read, and stress strain values corresponding to each node are given in the node data. Since the CAE finite element software is ABAQUS, the file to be read is the rpt file. For drawing the cloud picture, a scalar drawing method is selected. The scalar cloud rendering flow is shown in fig. 5. The read file firstly obtains the maximum value and the minimum value of a scalar, and then a color lookup table is established through the two maximum values (the color value is selected from an RGB or BGR mode, and the color value is uniformly selected as an RGB mode). The RGB color scheme is a color standard in the industry, and various colors are obtained by changing three color channels of red (R), green (G) and blue (B) and superimposing the three color channels on each other, where RGB represents colors of the three channels of red, green and blue, and the color standard almost includes all colors that can be perceived by human vision, and is one of the most widely used color systems at present. Commonly used color lookup tables include gradycale, shortrainbow, long rainbow, yellowtore, and the like. The short Rainbow algorithm is chosen to be more consistent with the color look-up table used by Abaqus. The short Rainbow algorithm takes the minimum scalar value as blue and the maximum scalar value as red. And establishing a corresponding relation between the scalar value and the color, namely the RGB value by using a short Rainbow algorithm. For any scalar value, it can be converted to RGB colors according to its size against a color look-up table. And then acquiring three-dimensional information of the nodes and corresponding field values, and filling until all grids are filled, and finishing the visualization process of the scalar cloud picture. And after converting the three-dimensional scalar into the corresponding color in the color comparison table, calling an OpenGL related function, and completing filling and drawing of the cloud picture by using a Lagrange linear interpolation mode. Here we choose to call the function glColor3f (r, g, b) to set the color for each point. The rgb values used by glColor3f range from floating point numbers between 0 and 1.
(5) The camera is called by utilizing the ARToollit, and the marker provided by the ARToollit toolkit can be directly selected to make the marker by utilizing the camera identification, and the marker provided by the ARToollit is shown in fig. 6. And printing and pasting the printing and pasting on parts or components needing to be displayed, and calling an ARToolkit program to perform virtual-real fusion of a finite element post-processing result and a real environment. The development flow of the ARToolkit algorithm is shown in fig. 7, and the main flow of the finite element post-processing result augmented reality virtual-real fusion algorithm is as follows:
binarization of a video image: because the identification points are black and white, the binaryzation simplifies the image without influencing the characteristics of the pattern of the identification points, and a black and white image only containing 0 and 1 is obtained;
connecting the area identifiers: and obtaining a connected domain in the image by adopting a connected domain marking algorithm to obtain a candidate connected domain set.
And thirdly, tracking the boundary of the connected region: the region boundary of each candidate region is obtained using a region boundary tracking algorithm.
Finding candidate quadrilateral areas: and obtaining a candidate quadrilateral area by using a quadrilateral detection algorithm.
Extracting the mark points: four vertexes of a quadrangle are used as characteristic points in the ARToolkit, linear regression algorithm is adopted for the four sides of the quadrangle to carry out linear fitting, and then intersection points of the four linear are extracted to obtain the four vertexes of the quadrangle.
Sixthly, identification point coding and decoding: the decoding process of the identification point is actually to compare the internal pattern of the current identification point with all the patterns of the identification point stored in the system one to one, and find a consistent match.
Estimation of the posture: the camera needs to identify the position of the identification point in the real world, a series of matrix operations need to be carried out, the camera can directly acquire the projection coordinate of the identification point to the camera, and the identification point matrix under the world coordinate can be calculated according to the internal parameters of the camera and the artificially given rotation and translation matrix.
After the steps are completed, virtual-real fusion operation can be started, and since OpenGL is adopted to reconstruct the cloud picture and the working environment of OpenGL and ARToolkit is the same, the reconstructed cloud picture model can be directly called in ARToolkit to complete virtual fusion.
(6) After the virtual-real fusion is completed, repeated debugging is needed to ensure that the model and the real object are more closely attached, repeated template training is needed to be carried out on the camera, for example, calibration training is carried out by using a black and white checkerboard, in continuous experiments, the most appropriate coverage effect is selected by changing a translation matrix and a rotation matrix, and the most appropriate coverage effect is stored, so that the expected virtual-real fusion effect can be obtained.
In the above embodiments, the implementation may be wholly or partially realized by software, hardware, firmware, or any combination thereof. When used in whole or in part, can be implemented in a computer program product that includes one or more computer instructions. When loaded or executed on a computer, cause the flow or functions according to embodiments of the invention to occur, in whole or in part. The computer may be a general purpose computer, a special purpose computer, a network of computers, or other programmable device. The computer instructions may be stored in a computer readable storage medium or transmitted from one computer readable storage medium to another, for example, the computer instructions may be transmitted from one website site, computer, server, or data center to another website site, computer, server, or data center via wire (e.g., coaxial cable, fiber optic, Digital Subscriber Line (DSL), or wireless (e.g., infrared, wireless, microwave, etc.)). The computer-readable storage medium can be any available medium that can be accessed by a computer or a data storage device, such as a server, a data center, etc., that includes one or more of the available media. The usable medium may be a magnetic medium (e.g., floppy Disk, hard Disk, magnetic tape), an optical medium (e.g., DVD), or a semiconductor medium (e.g., Solid State Disk (SSD)), among others.
The above description is only for the purpose of illustrating the present invention and the appended claims are not to be construed as limiting the scope of the invention, which is intended to cover all modifications, equivalents and improvements that are within the spirit and scope of the invention as defined by the appended claims.
Claims (10)
1. A visualization method for finite element post-processing results is characterized by comprising the following steps:
the method comprises the following steps that firstly, CAE software is used for modeling parts or components needing to be analyzed, and nodes and topology information containing a finite element analysis model are generated;
step two, carrying out primitive construction through OpenGL to form a finite element grid model;
step three, carrying out finite element analysis in CAE software to obtain a variable field needing to be output;
step four, performing RGB calculation by using scalar variables output after CAE analysis, and endowing corresponding nodes with the scalar variables;
step five, calling a camera by using an ARToolKit system, and displaying a finite element analysis result in a real-time scene on a screen;
and step six, adjusting the calibration position to enable the analysis result to be superposed with the finite element processing scene.
2. The method for visualizing finite element post-processing results as claimed in claim 1, wherein in the first step, the CAE software is Abaqus, a modeling system of the Abaqus itself or other CAD modeling software compatible with the Abaqus is selected for modeling, and the inp file is read after modeling; analyzing the structure by a finite element method, discretizing a continuous solution domain, namely dividing the solution domain into finite units which are mutually connected by nodes, analyzing and calculating the field quantity on a network point on the basis, and finishing the visual processing of drawing the cloud picture;
nodes control the geometry of the data, while cells control the geometry of the data; the unit data and the node data form finite element analysis data, a voxel network is constructed during modeling, and the finite element analysis data and the node data are processed by using a mesh division function of an Abaqus system or other point cloud data and mesh division software after modeling;
and performing network modeling by using the 8-Node 6-plane monomer unit, reading a Node part and an Element part in a file, respectively storing the Node part and the Element part in a Node list and a unit topology list, and defining the unit by using the Node and topology data so as to divide a grid.
3. The method for visualizing the finite element post-processing result as claimed in claim 1, wherein in the second step, the constructing the primitive by OpenGL comprises:
determining a construction method according to the element type used for the finite element analysis: sequentially connecting each point to the plane unit and the axisymmetric unit; for the space unit, the space unit is decomposed into a plurality of planes, the combined nodes of all the planes are analyzed and are respectively connected in sequence to form all the plane nodes, and drawing is finished;
drawing primitives in OpenGL through programming, wherein the common functions for constructing geometric primitives in OpenGL comprise glBegin (mode) and glend (); where a mode creates the type of primitive, the three values most commonly used by a mode are: GL _ POINTS, GL _ LINES, and GL _ POLYGON;
constructing the geometric primitive by using different mode types according to different unit types; for an 8-node 6-surface unit as an example, selecting a mode parameter GL _ LINES, and sequentially drawing twelve edges of each hexahedron to construct geometric primitives so as to form a finite element mesh model.
4. The method for visualizing finite element post-processing results as in claim 3, wherein said GL POINTS is used for defining the vertices as independent point units; if n points are defined at one time, n independent vertexes are defined; GL _ LINES, if reading n vertexes at a time, representing and defining n/2 line segments, and connecting two points between each point in sequence to form a line segment; GL _ POLYGON, when reading n points at a time, represents a convex POLYGON with the n points as vertices.
5. The method for visualizing finite element post-processing results as claimed in claim 1, wherein in step three, the finite element analysis is performed by using Abaqus, material properties, cross-sectional properties, and mesh properties are given to the model in addition to the existing mesh model, and load states and boundary states are given according to the analyzed environment states, and the visualization analysis is performed on the creation job and the submission job, and node data is derived; and the Python script is used for operation in engineering, and the finite element analysis process is rapidly and automatically completed.
6. The method for visualizing finite element post-processing results as claimed in claim 1, wherein in step four, reconstructing the stress cloud obtained by finite element analysis using OpenGL comprises:
reading node data derived from the Abaqus operation, wherein the node data gives a stress strain value corresponding to each node, and the read file is an rpt file; drawing the cloud picture by a scalar drawing method;
the read file firstly obtains the maximum value and the minimum value of a scalar, and a color lookup table is established through the two maximum values; selecting an RGB mode as a color value, and using a short Rainbow algorithm which is more consistent with a color lookup table used by Abaqus as a color lookup table; the short Rainbow algorithm takes the minimum scalar value as blue and the maximum scalar value as red;
establishing a corresponding relation between a scalar value and a color, namely an RGB value by using a short Rainbow algorithm; for any scalar value, converting the scalar value into RGB color according to the size of the scalar value and a color lookup table; acquiring three-dimensional information of nodes and corresponding field values, filling until all grids are filled, and finishing the visualization of a scalar cloud chart;
after converting the three-dimensional scalar into the corresponding color in the color comparison table, calling OpenGL related functions, and completing cloud picture filling and drawing by using a Lagrange linear interpolation mode; the call function glColor3f (r, g, b) is chosen to set the color for each point, with the rgb values for glColor3f ranging from a floating point number between 0 and 1.
7. The method for visualizing finite element post-processing results as claimed in claim 1, wherein in step five, said invoking a camera with ARToolKit system comprises:
the method comprises the following steps of calling a camera by utilizing the ARToolkit, identifying by utilizing the camera, directly selecting a marker provided by the ARToolkit to make an identification, printing and pasting the identification on a part or a component to be displayed, calling an ARToolkit program to perform virtual-real fusion of a finite element postprocessing result and a real environment, wherein the flow of an augmented reality virtual-real fusion algorithm of the finite element postprocessing result is as follows:
binarization of a video image: because the identification points are black and white, the binaryzation simplifies the image without influencing the characteristics of the pattern of the identification points, and a black and white image only containing 0 and 1 is obtained;
connecting the area identifiers: obtaining a connected domain in the image by adopting a connected domain marking algorithm to obtain a candidate connected domain set;
and thirdly, tracking the boundary of the connected region: obtaining the region boundary of each candidate region by using a region boundary tracking algorithm;
finding candidate quadrilateral areas: obtaining a candidate quadrilateral area by using a quadrilateral detection algorithm;
extracting the mark points: four vertexes of a quadrangle are used as characteristic points in the ARToolkit, linear regression algorithm is adopted for the four sides of the quadrangle to carry out linear fitting, and intersection points of the four linear are extracted to obtain the four vertexes of the quadrangle;
sixthly, identification point coding and decoding: the decoding process of the identification point actually compares the internal pattern of the current identification point with all the identification point patterns stored in the system one by one to find out a consistent match;
estimation of the posture: the camera directly acquires the projection coordinates of the identification point to the camera, and the identification point matrix under the world coordinates can be calculated according to the internal parameters of the camera and the artificially given rotation and translation matrix;
adopting OpenGL to reconstruct the cloud picture, wherein the OpenGL and ARToollit have the same working environment, so that the reconstructed cloud picture model can be directly called in the ARToollit to complete virtual fusion;
after the virtual-real fusion is completed, repeated template training is carried out on the camera, the most appropriate coverage effect is selected by changing the translation and rotation matrixes, and the most appropriate coverage effect is stored, so that the expected virtual-real fusion effect can be obtained.
8. A finite element post-processing result visualization system for implementing the method of visualizing a finite element post-processing result of any one of claims 1 to 7, the system comprising:
the finite element analysis model building module is used for modeling a part or a component to be analyzed by using CAE software and generating a node containing a finite element analysis model and topological information;
the finite element mesh model construction module is used for constructing the primitives through OpenGL to form a finite element mesh model;
the finite element analysis module is used for carrying out finite element analysis in CAE software to obtain a variable field to be output;
the scalar variable calculation module is used for performing RGB calculation by using the scalar variables output after CAE analysis and endowing the calculated scalar variables to corresponding nodes;
the analysis result display module is used for calling the camera by utilizing an ARToolKit system and displaying a finite element analysis result in a real-time scene on a screen;
and the virtual-real fusion module is used for enabling the analysis result to be overlapped with the finite element processing scene by adjusting the calibration position.
9. A computer device, characterized in that the computer device comprises a memory and a processor, the memory storing a computer program which, when executed by the processor, causes the processor to carry out the steps of:
modeling a part or a component to be analyzed by using CAE software, and generating nodes and topological information containing a finite element analysis model; constructing a primitive through OpenGL to form a finite element mesh model; finite element analysis is carried out in CAE software to obtain a variable field needing to be output;
performing RGB calculation by using scalar variables output after CAE analysis, and giving corresponding nodes; calling a camera by utilizing an ARToolKit system, and displaying a finite element analysis result in a real-time scene on a screen; and adjusting the calibration position to enable the analysis result to be overlapped with the finite element processing scene.
10. An information data processing terminal, characterized in that the information data processing terminal is configured to implement the finite element post-processing result visualization system of claim 8.
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