CN116049941B - Method for extracting and analyzing multidimensional state of assembled ring truss structural member before assembly - Google Patents
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Abstract
The application discloses a method for extracting and analyzing a multidimensional state of an assembled ring truss structure component before assembly, which comprises the steps of thresholding and stepwise rotating an assembled component physical model to a state that the length direction is perpendicular to a horizontal reference plane based on a three-dimensional iterative algorithm of a matrix; after gridding treatment, dispersing two-dimensional sections with uniform spacing or set unequal spacing; extracting a two-dimensional section centroid, a radial length and a design physical model by using a multi-dimensional physical description extraction algorithm; utilizing a multi-dimensional data processing algorithm to obtain a V, W-plane projection data set of a space shape core line and a radial length difference data set of a design and physical model; and counting the general rule of the data set through a multidimensional physical analysis algorithm, and obtaining the multidimensional state expression before component assembly after signaling processing. The application can rapidly, efficiently and accurately extract and analyze the multidimensional state of the components before assembly, and promote the intelligent digital development of the building structure.
Description
Technical Field
The invention belongs to the technical field of civil engineering, and relates to a method for extracting and analyzing a multidimensional state of an assembled ring truss structure member before assembly.
Background
The intelligent and industrialized construction is a great demand for the transformation and upgrading of the building industry in China, and industrialization, greenization, intellectualization and digitalization are the necessary trend of the development of the building engineering field under new situation. Because the assembled ring truss has the advantages of high construction efficiency, low pollution, reasonable stress and the like, and is mainly used for the lower supporting structures of large-span space structures such as cable dome structures, cable net structures and the like, the development of an assembled ring truss structure system tends to push the intelligent construction technology in the field of structural engineering to advance. However, the attention of the new fabricated ring truss is directed to the safety and reliability thereof, and the multi-dimensional state of the fabricated members is an important factor affecting the safety and reliability of the structure.
Because the research of the assembled ring truss is basically in a starting state, the research results are relatively few, and the research of the multi-dimensional state extraction and analysis method before assembling the assembled ring truss structure member is in a blank state. Therefore, it is necessary to develop a fast, efficient, practical and accurate method to extract the multidimensional state of the assembled ring truss structure assembly member before assembly, provide necessary bottom data for the emerging high-precision technologies such as dynamic growth of the structure and twin of the structure numbers, and facilitate the establishment of the digital structure of the original structure high-fidelity mapping for the purpose of evaluating the safety and stability of the structure, and promote the intelligent and digital development of the building structure.
Disclosure of Invention
The invention aims to overcome the defects, and provides a multi-dimensional state extraction and analysis method before assembling an assembled ring truss structure member, which solves the problem of filling the blank state in the related technical field.
In order to achieve the above purpose, the technical scheme adopted by the invention is as follows: a method for extracting and analyzing a multidimensional state of an assembled ring truss structure member before assembly, comprising the steps of:
S1: the three-way iterative algorithm based on the matrix rotates the assembly component physical model in a thresholding step by step until the length direction is perpendicular to the horizontal reference plane;
s2: the step-by-step rotated component physical model is subjected to gridding treatment, and two-dimensional XOY sections with uniform spacing or unequal spacing are discretized through a multi-dimensional physical discretization algorithm;
s3: processing a discrete two-dimensional XOY section by utilizing a multi-dimensional physical description extraction algorithm, and extracting a centroid, a radial length and a design physical model of a two-dimensional section of the physical model of the assembly member;
s4: obtaining a V-plane projection data set { V }, { W } of a space shape core line and a data set { R } of a radial length difference value of an assembly member physical model and a design physical model through a multi-dimensional data processing algorithm;
s5: and counting the general rules of { V }, { W }, and { R }, and obtaining the multidimensional state function expression before component assembly after signaling processing.
Further, in step S1, the physical model of the assembly member is a physical model composed of three-dimensional coordinates of x, y and z space and direction vectors thereof, and is used for completely reflecting the actual state of the assembly ring truss assembly member before assembly.
Further, in step S1, the three-way iterative algorithm based on the matrix is used to rotate relative to a certain spatial coordinate axis respectively, until the threshold is reached, and then the three-way iterative algorithm is ended.
Further, in step S1, the horizontal reference plane is an H plane or an XOY plane of the spatial coordinate system or any plane parallel to the XOY plane.
Further, in step S2, the two-dimensional cross section in which the pitch in the longitudinal direction is uniform or the non-uniform pitch is set is composed of a series of points which are generated in such a manner that: and a plane P perpendicular to the length direction of the assembly member, wherein the plane P and the assembly member are intersected at each preset interval Z m by moving the assembly member at the bottommost end of the assembly member, namely at the position z=0, with the preset uniform interval or the preset unequal interval as a step length, and all the intersected points form the two-dimensional section, wherein Z is a space coordinate axis Z-axis coordinate value, and Z m is the preset uniform interval or the preset unequal interval.
Further, in step S2, the intersection point of the plane P and the assembly member is the intersection point of the plane P and the regular triangle formed by gridding the assembly member.
Further, in step S3, the multidimensional physical description extraction algorithm performs feature description, that is, fitting of centroids and radial lengths, on discrete two-dimensional sections, fitting of an assembly member design physical model corresponding to the assembly member physical model, and sorting the centroids of the two-dimensional sections according to discrete distances to combine into an actual spatial shape core line of the assembly member physical model.
Further, in step S3, the centroid coordinates and the radial length of the two-dimensional cross section of the physical model of the assembly member are fitted by an average method, a weighted average method, or a least square method.
Further, in step S5, the data sets { V }, { W } and { R } are subjected to coordinate conversion, i.e., from cartesian coordinates to polar coordinates, by a multidimensional physical analysis algorithm, and then their general rule is counted.
Further, in step S5, a function F is fitted to the data sets { V }, { W }, and then a signaling process is performed to obtain frequency domain data, and the energy size is quantized, and an expression G V、GW about the component height z is fitted; the dataset { R } is directly signaled to obtain frequency domain data, the energy magnitude is quantized, and the expression G R of the data about the component height z is fitted.
The beneficial effects of the invention are as follows:
The method is simple to realize, and the premise of data authenticity is ensured by introducing the assembly component physical model and the design model; meanwhile, corresponding data are obtained through space centroid line projection, radial length comparison and other modes, so that data regularization analysis is realized; the data rule signaling processing breaks through the bottleneck of low fitting precision of the traditional data, so that the multidimensional state of the components before assembly is truly reflected and is represented in a common mathematical expression form. In addition, the three-dimensional iterative algorithm, the multi-dimensional physical discrete algorithm, the multi-dimensional physical description extraction algorithm, the multi-dimensional data processing algorithm and the multi-dimensional physical analysis algorithm can be used for realizing high speed, high efficiency, practicability and accuracy, and universal software and program autonomy are eliminated. The invention fills the blank of high-precision extraction of multidimensional state before assembly of the assembly type ring truss structure assembly member, provides data with higher precision for reliability analysis of the structure and the member, establishes digital twin, dynamic growth and other models of a highly restored real structure, and promotes intelligent digital development of the building structure, in particular to the assembly type ring truss structure.
Drawings
FIG. 1 is a flow chart of a method of multi-dimensional state extraction and analysis prior to assembly of an assembled ring truss structure member of the invention;
FIG. 2 is a schematic view of a physical model of a fitting member prior to fitting in accordance with an embodiment of the present invention;
FIG. 3 is a schematic view of an assembly member after stepwise rotation of a physical model in accordance with an embodiment of the present invention;
FIG. 4 is a diagram of meshing of a physical model of an assembly member according to an embodiment of the present invention;
FIG. 5 is a schematic view of a discrete two-dimensional cross-section of a physical model of an assembly member according to an embodiment of the invention;
FIG. 6 is a schematic view of a spatial centroid of a physical model of an assembly member according to an embodiment of the present invention;
FIG. 7 is a schematic illustration of a physical model of an assembly according to an embodiment of the present invention after projection of a spatial centroid line;
FIG. 8 is a two-dimensional cross-sectional comparison of a physical model of an assembled component and a designed physical model of an embodiment of the present invention;
FIG. 9 is a statistical diagram of the data sets { V }, { W } rule according to an embodiment of the present invention;
FIG. 10 is a graph showing the curves and fitting results after the data sets { V }, { W }, and { R } are signaled according to the embodiment of the present invention.
Detailed Description
Certain terms are used throughout the description and claims to refer to particular components. Those of skill in the art will appreciate that a hardware manufacturer may refer to the same component by different names. The description and claims do not take the form of an element differentiated by name, but rather by functionality. As used throughout the specification and claims, the word "comprise" is an open-ended term, and thus should be interpreted to mean "include, but not limited to. By "substantially" is meant that within an acceptable error range, a person skilled in the art is able to solve the technical problem within a certain error range, substantially achieving the technical effect. The description hereinafter sets forth a preferred embodiment for practicing the application, but is not intended to limit the scope of the application, as the description is given for the purpose of illustrating the general principles of the application. The scope of the application is defined by the appended claims.
Referring to fig. 1, the present invention provides a method for extracting and analyzing a multidimensional state of an assembled ring truss structure member before assembly, comprising:
S1: the three-way iterative algorithm based on the matrix rotates the assembly component physical model in a thresholding step by step until the length direction is perpendicular to the horizontal reference plane;
S2: the step-by-step rotated component physical model is subjected to gridding treatment, and two-dimensional (XOY) sections with uniform spacing or unequal spacing are discretized through a multi-dimensional physical discretization algorithm;
s3: processing discrete two-dimensional sections by utilizing a multi-dimensional physical description extraction algorithm, and extracting the centroid, radial length and design physical model of the two-dimensional section of the physical model of the assembly member;
s4: obtaining a V-plane projection data set { V }, { W } of a space shape core line and a data set { R } of a radial length difference value of an assembly member physical model and a design physical model through a multi-dimensional data processing algorithm;
s5: and counting the general rules of { V }, { W }, and { R }, and obtaining the multidimensional state function expression before component assembly after signaling processing.
In one possible implementation manner, in the method for extracting and analyzing the multidimensional state before assembling the assembled ring truss structure member provided by the invention, step S1 specifically includes:
and (3) taking the physical model of the assembly type ring truss assembly component as an object, and using a three-way iterative algorithm based on a matrix to rotate the assembly component physical model step by step until the length direction is perpendicular to a horizontal reference plane.
The physical model of the assembly member mainly refers to a physical model formed by three-dimensional coordinates of x, y and z space and direction vectors thereof, and the physical model has the main function of completely reflecting the actual state of the assembly ring truss assembly member before assembly. The model can be obtained through vision technologies such as panoramic depth vision, three-dimensional laser mapping and the like.
The three-way iterative algorithm based on the matrix is an algorithm which is developed by taking actual needs as guidance and has a thresholding function, and the main function is thresholding and step-by-step rotation, namely, rotation relative to a certain space coordinate axis respectively until the threshold is reached, and then the three-way iterative algorithm is ended. The main mathematical expressions are as shown in (1) to (6):
When (when) Or/>And when the step rotation is completed, the step rotation is considered to be completed.
Wherein x, y and z represent coordinate values of an assembly component physical model space x axis, y axis and z axis; x, Y, Z represents the coordinate values of the space x-axis, y-axis and z-axis after step rotation; m represents the number of iterations; alpha, beta and gamma respectively represent rotation angles relative to an x axis, a y axis and a z axis; representing a rotation matrix; /(I) Representing a rotation matrix iterated m times relative to the x-axis, the y-axis, and the z-axis, respectively; /(I)Representing the component length direction vector after m iterations; epsilon, delta represents the iteration threshold; /(I)Representing a z-direction vector of a space coordinate system; /(I)Representing the horizontal plane vector after m iterations.
The length direction refers to the length direction of the fitting member, i.eThe horizontal reference plane refers to the H-plane or XOY-plane of the spatial coordinate system or any plane parallel to the XOY-plane.
Further, in the preferred embodiment provided by the present invention, step S2 is continuously performed, specifically: all types of assembly component physical models after step-by-step rotation in the embodiment S1 of the invention are selected to carry out gridding treatment, namely, the assembly is formed by combining regularly arranged triangles on the premise of not changing the original state, and the gridding treatment result is shown in figure 4. The method aims at eliminating redundant data expression, so that the model is lighter and the processing speed of subsequent data is increased. And setting uniform spacing or nonuniform spacing in a multidimensional physical discrete algorithm, and deriving the section data of the discrete assembly components as a result after the uniform spacing or nonuniform spacing is set.
Specifically, the multidimensional physical discrete algorithm is to discrete the assembly member physical model of the embodiment of the invention into two-dimensional sections with uniform spacing along the length direction or set unequal spacing, namely an XOY plane.
Specifically, in the embodiment of the present invention, the two-dimensional section with uniform or unequal intervals along the length direction is composed of a series of points, and the manner of generating the points is that: a plane P perpendicular to the length direction of the assembly member, wherein the plane P intersects with the assembly member at a position of a preset distance Z m, and all the intersection points form the two-dimensional section, wherein the position at the bottommost end of the assembly member, i.e. z=0, moves along the Z >0 direction with the uniform distance or the preset unequal distance as step length. Wherein Z is a Z-axis coordinate value of the space coordinate axis, and Z m is a set uniform interval or a set unequal interval.
Specifically, the intersection point of the plane P and the assembly member, that is, the intersection point of the plane P and the regular triangle formed by gridding the assembly member, is specifically implemented as follows: the total number of triangles intersected by the plane P at the interval Z m is n, the vertex of the ith triangle is [ t i],Xij、Yij、Zij ] which represents the vertex coordinate value, two intersection points of the plane P and the ith triangle are { P k}(k＝1,2),PXk、PYk、PZk which represents the coordinate value of the intersection point, and { P k } is calculated by the formula (9), wherein ζ ij represents the proportionality coefficient, so that all the intersection points { P n } can be obtained.
Still preferably, the embodiment of the present invention targets the type (b) assembly member in fig. 4, and the two-dimensional cross section with uniform spacing along the length direction is discretized by using a multidimensional physical discretization algorithm, and the result is shown in fig. 5. The result is calculated by adopting an independently written algorithm program, and an effect graph of the length of the assembly member, all the two-dimensional sections and even intervals is automatically reflected.
Further, in the preferred embodiment provided by the present invention, step S3 is continuously performed, specifically: and (3) carrying out batch analysis processing on the discrete section data of the further preferred embodiment by utilizing a multi-dimensional physical description extraction algorithm, and firstly fitting and extracting the two-dimensional section centroid coordinates and the radial length of the physical model of the assembly component by utilizing the algorithm. The fitting component design physical model corresponding to the fitting component physical model is then extracted from the intersection point { P n } described above. And meanwhile, sorting the two-dimensional section centroids according to discrete distances, and combining the two-dimensional section centroids into an actual space centroids of the assembly member physical model.
Specifically, the multi-dimensional physical description extraction algorithm is a fitting of a physical model of the fitting member design corresponding to the physical model of the fitting member by characterizing discrete two-dimensional cross sections, i.e., centroid, radial length, in a further preferred embodiment of the invention. And sequencing the centroids of the two-dimensional sections according to discrete distances, and combining the centroids into the actual space shape line of the physical model of the assembly member.
Preferably, the embodiment of the present invention targets the type (b) assembly component in fig. 4, and the actual spatial shape core line is extracted by using a multidimensional physical description extraction algorithm, and the result is shown in fig. 6. The result reflects that the centroid change before assembly of the assembly member is complex and is not unidirectional bending in an ideal sense, so that the result obtained by the multidimensional physical description extraction algorithm has the advantage of highly reflecting reality, the reliability of subsequent structural safety analysis is improved, and the defects of complicated and complex measurement of the traditional caliper are overcome.
Specifically, the centroid coordinates and the radial length of the two-dimensional section of the physical model of the assembly member are important parameters for describing the state of the assembly member before assembly, and the assembly member can be fitted by means of an average method, a weighted average method, a least square method and the like.
Specifically, the physical model of the assembly member is designed in accordance with the centroid of the physical model of the assembly member in the embodiment of the present invention, and the data points constituting the cross section thereof are fitted according to { P n } and the direction angles thereof, as shown in equations (10) to (12).
Where phi denotes the direction angle, ρ denotes the radial length, P Xi、PYi denotes the X, y coordinate values of the two-dimensional cross-section data point, (X i',Yi'), i=1, 2, and n represents data points of a cross section of a physical model of the design of the assembly member, and X c、Yc represents X and y coordinate values of a centroid of the two-dimensional cross section.
Further, in the preferred embodiment provided by the present invention, step S4 is continuously performed, specifically: projection data sets { V } and { W } of the actual space shape core line of the assembly member physical model on the V surface (namely the XOZ surface) and the W surface (namely the YOZ surface) are obtained through a multi-dimensional data processing algorithm, and meanwhile, the difference value of the radial lengths of the assembly member physical model and the design physical model is obtained according to comparison, and is defined as a data set { R }.
Specifically, the multidimensional data processing algorithm has the function of processing the actual spatial centroid line of the physical model of the assembly member obtained in step S3 of the embodiment of the present invention, calculating projection data of the actual spatial centroid line on the V-plane (i.e., XOZ-plane) and the W-plane (i.e., YOZ-plane), and storing the projection data in the data sets { V } and { W }. Next, the difference in radial length of the fitting member physical model and the design physical model is calculated and stored in the data set { R }. And finally, exporting and storing the data set.
Specifically, the data sets { V } and { W } in the embodiment of the present invention are calculated mainly by equations (13) - (15), and the results are shown in fig. 7 (a) and fig. 7 (b), where fig. 7 (a) is a projection of the actual spatial centerline in the embodiment of the present invention on the V plane (i.e., XOZ plane), and fig. 7 (b) is a projection of the actual spatial centerline in the embodiment of the present invention on the W plane (i.e., YOZ plane). Fig. 7 (a) and 7 (b) respectively reflect the offset of the x and y coordinates with respect to the z axis, and the maximum value is between 0.45 and 0.5mm, and the result is reflected to measure the change of the centroid initial state in the sub-millimeter data.
(XV',YV')＝[XV,YV]ηV (14)
(XW',YW')＝[XW,YW]ηW (15)
Wherein η denotes a rotation matrix, θ denotes a direction angle, [ X V,YV ] denotes a point coordinate matrix after V-plane projection of the centroid, (X V',YV ') denotes a point coordinate matrix after V-plane projection of the centroid, (X W,YW ') denotes a point coordinate matrix after W-plane projection of the centroid, (X W',YW ') denotes a coordinate matrix after W-plane projection of the centroid, η V denotes a V-plane rotation matrix, η W denotes a W-plane rotation matrix.
Specifically, the difference in radial length between the assembly physical model and the design physical model in the embodiment of the present invention is obtained by equation (16), Δr i constituting the dataset { R }.
Wherein Δr represents the difference in radial length between the physical model of the fitting member and the designed physical model, ρ represents the radial length design value, and P Xi、PYi represents the x, y coordinate values of the two-dimensional cross-section data point of the physical model of the fitting member.
Preferably, a two-dimensional cross-sectional comparison of the fitting member physical model and the design physical model of an embodiment of the present invention is given, as shown in fig. 8. As can be seen from the figure, the radial length of the designed physical model is a design value, the two-dimensional section of the physical model shows periodic variation around the designed model, the result more vividly shows the difference of the radial lengths of the physical model of the assembly component and the designed physical model, and the method can obtain the radial length difference with high precision more efficiently.
Further, in the preferred embodiment provided by the present invention, step S5 is continuously performed, specifically: the data sets { V }, { W } and { R } of the embodiments of the present invention are transformed by a multidimensional physical analysis algorithm, i.e., from cartesian coordinates to polar coordinates, and then their general rules are counted. As shown in fig. 9 (a) and 9 (b), the statistical data sets { V }, and { W } respectively are general rules, and from the statistical results, it can be seen that the data sets { V }, and { W } conform to the sine wave rule, whereas the conventional method can only simulate the rule by means of probability assumption due to the limitation of measurement accuracy.
Further, a function F is fitted to the data sets { V }, { W }, and then signal processing is carried out to obtain frequency domain data, the energy size is quantized, and an expression G V、GW of the energy size about the component height z is fitted; the data set { R } in the embodiment of the invention is directly subjected to signaling processing to obtain frequency domain data, the energy size is quantized, and an expression G R of the data set { R } about the component height z is fitted. Wherein, possible forms of the G V、GW、GR mathematical expression are shown in (17) to (20).
Where G denotes an expression concerning the member height z, a, b, c, d, e denotes a fitting coefficient, G V、GW、GR denotes expressions concerning the member height z of the datasets { V }, { W }, and { R }, respectively, and a multi-dimensional state before assembly of the assembly member is expressed.
Preferably, the embodiment of the present invention utilizes the above method to regularly fit the function F to the data sets { V }, { W }, and then performs the signaling process, and simultaneously directly performs the signaling process to the data set { R }, and the results are shown in fig. 10 (a), fig. 10 (b), and fig. 10 (c). The data sets { V }, { W }, and { R } are all represented by curves, and mathematical expressions are directly given, and from the results, it can be seen that the multi-dimensional state amplitude change before the assembly of the component has a certain rule and can be expressed mathematically, and the mathematical expressions are in accordance with one of the above formulas (17) - (20). The method is also a method for representing the multi-dimensional state of the fabricated ring truss structural member before assembly through amplitude variation fitting.
The multi-dimensional state before the assembly of the assembly type ring truss structure component is extracted, the multi-dimensional state of the assembly component is represented by analyzing and obtaining a function G V、GW、GR, and the multi-dimensional state before the assembly of the assembly component is perfectly described and used for bottom data of technologies such as structural growth, digital twinning and the like.
The invention has the beneficial effects that:
The method is simple to realize, and the premise of data authenticity is ensured by introducing the assembly component physical model and the design model; meanwhile, corresponding data are obtained through space centroid line projection, radial length comparison and other modes, so that data regularization analysis is realized; the data rule signaling processing breaks through the bottleneck of low fitting precision of the traditional data, so that the multidimensional state of the components before assembly is truly reflected and is represented in a common mathematical expression form. In addition, the three-dimensional iterative algorithm, the multi-dimensional physical discrete algorithm, the multi-dimensional physical description extraction algorithm, the multi-dimensional data processing algorithm and the multi-dimensional physical analysis algorithm can be used for realizing high speed, high efficiency, practicability and accuracy, and universal software and program autonomy are eliminated. The invention fills the blank of high-precision extraction of multidimensional state before assembly of the assembly type ring truss structure assembly member, provides data with higher precision for reliability analysis of the structure and the member, establishes digital twin, dynamic growth and other models of a highly restored real structure, and promotes intelligent digital development of the building structure, in particular to the assembly type ring truss structure.
While the foregoing description illustrates and describes the preferred embodiments of the present application, it is to be understood that the application is not limited to the forms disclosed herein, but is not to be construed as limited to other embodiments, and is capable of numerous other combinations, modifications and environments and is capable of changes or modifications within the scope of the inventive concept as expressed herein, either as a result of the foregoing teachings or as a result of the knowledge or technology of the relevant art. And that modifications and variations which do not depart from the spirit and scope of the application are intended to be within the scope of the appended claims.
Claims (6)
1. A method for extracting and analyzing a multidimensional state of an assembled ring truss structure member before assembly, comprising the steps of:
S1: the three-way iterative algorithm based on the matrix rotates the assembly component physical model in a thresholding step by step until the length direction is perpendicular to the horizontal reference plane; the three-way iterative algorithm based on the matrix is used for rotating relative to a certain space coordinate axis respectively until reaching a threshold value and ending;
S2: the component physical model after step rotation is subjected to gridding treatment, and two-dimensional XOY sections with uniform spacing or unequal spacing are discretized through a multidimensional physical discretization algorithm, namely: a two-dimensional cross-section with uniform or unequal spacing along the length is composed of a series of points that are produced in a manner that: a plane P perpendicular to the length direction of the assembly member, wherein the plane P and the assembly member intersect at a distance Z m from the bottommost end of the assembly member, i.e., z=0, with the uniform distance or the set unequal distance as a step length, and each of the planes is moved along the Z > 0 direction, and all the intersecting points form the two-dimensional cross section, wherein Z is a Z-axis coordinate value of a spatial coordinate axis, and Z m is the set uniform distance or the set unequal distance;
S3: processing a discrete two-dimensional XOY section by using a multi-dimensional physical description extraction algorithm, and extracting a centroid, a radial length and a design physical model of a two-dimensional section of an assembly member physical model, wherein the multi-dimensional physical description extraction algorithm is used for carrying out characteristic description on the discrete two-dimensional section, namely fitting of the centroid and the radial length, fitting of the design physical model of the assembly member corresponding to the assembly member physical model, and sequencing the centroid of the two-dimensional section according to discrete distances to form an actual space shape core line of the assembly member physical model;
s4: obtaining a V-plane projection data set { V }, { W } of a space shape core line and a data set { R } of a radial length difference value of an assembly member physical model and a design physical model through a multi-dimensional data processing algorithm; the multidimensional data processing algorithm is used for processing the actual space centroid line of the assembly component physical model obtained in the step S3, calculating projection data of the assembly component physical model on a V plane and a W plane, and storing the projection data in a data set { V } and { W }; secondly, calculating the difference value of the radial length of the physical model of the assembly component and the designed physical model, storing the difference value in a data set { R }, and finally exporting and storing the data set;
S5: the general rules of { V }, { W }, and { R }, are counted through a multidimensional physical analysis algorithm, and a multidimensional state function expression before component assembly is obtained after signaling processing, namely: fitting a function F to the data set { V }, { W }, then performing signaling processing to obtain frequency domain data, quantifying the energy size, and fitting an expression G V、GW of the frequency domain data about the component height z; the dataset { R } is directly signaled to obtain frequency domain data, the energy magnitude is quantized, and the expression G R of the data about the component height z is fitted.
2. The method for extracting and analyzing the multidimensional state of the fabricated ring truss structure member before assembly according to claim 1, wherein in step S1, the physical model of the fabricated member is a physical model composed of x, y, z space three-dimensional coordinates and direction vectors thereof, and is used for completely reflecting the actual state of the fabricated ring truss structure member before assembly.
3. The method for extracting and analyzing the multidimensional state of the fabricated ring truss structure member before assembly according to claim 1, wherein in the step S1, the horizontal reference plane is an H plane or an XOY plane of a space coordinate system or any plane parallel to the XOY plane.
4. The method for extracting and analyzing a multidimensional state before assembling an assembled ring truss structure member according to claim 1, wherein in step S2, the intersection point of the plane P and the assembled member is the intersection point of the plane P and the regular triangle of the assembled member after meshing.
5. The method for extracting and analyzing the multidimensional state of the assembled ring truss structure member before assembly according to claim 1, wherein in the step S3, the physical model of the assembled member is fitted by an average method, a weighted average method and a least square method by two-dimensional cross-section centroid coordinates and radial lengths.
6. The method of claim 4, wherein in step S5, the data sets { V }, { W }, and { R } are subjected to coordinate transformation from cartesian coordinates to polar coordinates by a multidimensional physical analysis algorithm, and then their general rule is counted.
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