CN115588082A - Method, device and equipment for displaying space digital model in real time and storage medium - Google Patents
Method, device and equipment for displaying space digital model in real time and storage medium Download PDFInfo
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Abstract
The invention relates to an artificial intelligence technology, and discloses a real-time display method of a space digital model, which comprises the following steps: the method comprises the steps of obtaining a space digital elevation model, calculating trend data of space coordinates in a preset direction in the space digital elevation model, performing space correlation characteristic representation on the space coordinates in the preset direction in the space digital elevation model by utilizing the trend data to obtain characteristic data, obtaining real-time dynamic displacement data of a monitoring range, performing space interpolation on the real-time dynamic displacement data based on the characteristic data to obtain displacement interpolation data, performing graphic processing and rendering on the displacement interpolation data and the real-time dynamic displacement data to obtain a digital three-dimensional model, and performing real-time visual display on the digital three-dimensional model by utilizing a preset front end view assembly. The invention also provides a device, equipment and a storage medium for displaying the space digital model in real time. The invention can improve the real-time performance of space digital model display, establish a three-dimensional digital twin model and realize three-dimensional visual simulation deduction display.
Description
Technical Field
The invention relates to the technical field of artificial intelligence, in particular to a method and a device for displaying a space digital model in real time, electronic equipment and a computer readable storage medium.
Background
The digital twin is a technical means for creating a virtual entity of a physical entity in a digital manner, simulating, verifying, predicting and controlling the whole life cycle process of the physical entity by means of historical data, real-time data, algorithm models and the like, and is a novel digital model display technology which is established on the basis of a Building Information Model (BIM) and combines a Geographic Information System (GIS) and an Internet of Things technology (Internet of Things, ioT). The digital twin is gradually applied to various industries, and particularly, the digital twin is more applied to the field of engineering construction. For example, in a slope monitoring project, the displacement monitoring information of the slope can present dynamic information display through a digital twin platform, so that a user can observe and evaluate the safety state of the slope intuitively.
However, in the slope monitoring technology based on the internet of things, sensing monitoring equipment is mainly adopted to obtain dynamic data of monitoring points, and then analysis is performed according to the increment and the change rate of the dynamic data to predict the slope stability state. However, the arrangement of the monitoring points (i.e. the collection points of the dynamic data) is often sparse, the related characteristic parameters of the spatial data are extracted directly from the dynamic data generated by the monitoring points, such an operation mode is constrained by the sparse monitoring points, and the accuracy of the obtained spatial related characteristic parameters is poor, so that it is difficult to obtain an accurate dynamic displacement data interpolation result. Meanwhile, the workload required for extracting the spatial correlation characteristic parameters of the dynamic data each time is large, the required calculation time is long, and the real-time efficiency and accuracy of digital model display are poor.
Disclosure of Invention
The invention provides a method and a device for displaying a space digital model in real time, electronic equipment and a readable storage medium, and mainly aims to improve the real-time performance of displaying the space digital model, establish a three-dimensional digital twin model and realize three-dimensional visual simulation deduction display.
In order to achieve the above object, the present invention provides a method for displaying a space digital model in real time, which comprises:
acquiring a space digital elevation model, and calculating trend data of space coordinates in a preset direction in the space digital elevation model based on space coordinate data in the space digital elevation model;
performing spatial correlation characteristic representation on the spatial coordinates in the preset direction in the spatial digital elevation model by using the trend data to obtain characteristic data;
acquiring real-time dynamic displacement data of a monitoring range, and performing spatial interpolation on the real-time dynamic displacement data based on the characteristic data to obtain displacement interpolation data;
and performing graphic processing and rendering on the displacement interpolation data and the real-time dynamic displacement data to obtain a digital three-dimensional model, and performing real-time visual display on the digital three-dimensional model by using a preset front end view component.
Optionally, the calculating trend data of the spatial coordinates in the preset direction in the space digital elevation model based on the spatial coordinate data in the space digital elevation model includes:
calculating cross validation indexes and fitting indexes of the space coordinates in the preset direction;
and performing polynomial regression processing on the space coordinate in the preset direction based on the cross validation index and the fitting index until the regression order meets the preset regression condition, and obtaining a regression coefficient containing the trend data through a least square method.
Optionally, the performing polynomial regression processing on the spatial coordinate in the preset direction based on the cross validation index and the fitting index until the regression order satisfies a preset regression condition, and obtaining a regression coefficient including the trend data by a least square method includes:
initializing an original regression order, and determining a cross validation index and a fitting index under the original regression order;
if the fitting index of the original regression order is less than or equal to a preset fitting threshold value, performing order raising processing on the original regression order, determining whether the cross validation index and the fitting index under the regression order after order raising meet a preset regression condition, and if not, continuing to raise the order until the cross validation index and the fitting index under the regression order after order raising meet the preset regression condition to obtain a standard regression order;
constructing a polynomial regression equation by using the standard regression order, and calculating a regression coefficient of the polynomial regression equation by using a least square method;
and if the fitting index of the original regression order is larger than the preset fitting threshold, performing order reduction on the original regression order, and returning to the step of determining the cross validation index and the fitting index under the original regression order.
Optionally, the performing, by using the trend data, spatial correlation feature representation on the spatial coordinates in a preset direction in the spatial digital elevation model to obtain feature data includes:
calculating a spatial autocorrelation equation of the spatial coordinates by using a Materen covariance method;
and determining the spatial autocorrelation parameters of the spatial autocorrelation equation based on a maximum likelihood estimation method, and taking the spatial autocorrelation parameters as characteristic data.
Optionally, the spatial autocorrelation equation is as follows:
wherein,
is the spatial distance of any two coordinates in the space digital elevation model,
the equation of the spatial autocorrelation is expressed,
a smoothing parameter ranging from 0 to infinity,
in order to be a parameter of the range,
in order to be the gamma equation,
is composed of
Bessel formula of the second kind of order.
Optionally, the performing spatial interpolation on the real-time dynamic displacement data based on the feature data to obtain displacement interpolation data includes:
constructing a horizontal covariance matrix based on the real-time dynamic displacement data of the monitoring range and the unmonitored space coordinates;
and calculating an interpolation weighting coefficient by using the horizontal covariance matrix and the characteristic data, and calculating displacement interpolation data of the spatial coordinates which are not monitored in the spatial digital elevation model based on the interpolation weighting coefficient and a regression kriging interpolation method.
Optionally, the performing graphics processing and rendering on the displacement interpolation data and the real-time dynamic displacement data to obtain a digital three-dimensional model includes:
generating a vertex coordinate set based on the space digital elevation model, the displacement interpolation data and the real-time dynamic displacement data;
carrying out graph source assembly on the vertex coordinate set to obtain a primitive set;
and rasterizing the primitives in the primitive set to obtain a fragment set, and performing geometric transformation on the fragments in the fragment set to obtain the digital three-dimensional model.
In order to solve the above problems, the present invention further provides a device for displaying a space digital model in real time, wherein the device comprises:
the spatial trend calculation module is used for acquiring a spatial digital elevation model and calculating trend data of spatial coordinates in a preset direction in the spatial digital elevation model based on spatial coordinate data in the spatial digital elevation model;
the spatial feature representation module is used for performing spatial correlation feature representation on the spatial coordinates in the preset direction in the spatial digital elevation model by using the trend data to obtain feature data;
the spatial interpolation module is used for acquiring real-time dynamic displacement data of a monitoring range, and carrying out spatial interpolation on the real-time dynamic displacement data based on the characteristic data to obtain displacement interpolation data;
and the model display module is used for carrying out graphic processing and rendering on the displacement interpolation data and the real-time dynamic displacement data to obtain a digital three-dimensional model, and carrying out real-time visual display on the digital three-dimensional model by utilizing a preset front end view component.
In order to solve the above problem, the present invention also provides an electronic device, including:
a memory storing at least one computer program; and
and the processor executes the computer program stored in the memory to realize the space digital model real-time display method.
In order to solve the above problem, the present invention further provides a computer-readable storage medium, in which at least one computer program is stored, and the at least one computer program is executed by a processor in an electronic device to implement the method for real-time presentation of a space digital model described above.
In the embodiment, the trend data of the spatial coordinates in the preset direction in the spatial digital elevation model is calculated, and the spatial correlation characteristic representation is performed on the spatial coordinates in the preset direction in the spatial digital elevation model by using the trend data to obtain the characteristic data. Meanwhile, the real-time dynamic displacement data in the monitoring range are subjected to spatial interpolation based on the characteristic data, so that more accurate displacement interpolation data can be obtained, in the real-time dynamic data display, the spatial correlation characteristic data do not need to be repeatedly calculated, the operation time is saved, and finally, the displacement interpolation data and the real-time dynamic displacement data are subjected to graphic processing and rendering to obtain a digital three-dimensional model, so that the real-time performance of the space digital model display is improved. Therefore, the method, the device, the electronic equipment and the computer readable storage medium for displaying the space digital model in real time can improve the real-time performance of displaying the space digital model, establish a three-dimensional digital twin model and realize three-dimensional visual simulation deduction display.
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Fig. 1 is a schematic flow chart of a method for displaying a space digital model in real time according to an embodiment of the present invention;
FIG. 2 is a functional block diagram of a device for displaying a space-time digital model in real time according to an embodiment of the present invention;
fig. 3 is a schematic structural diagram of an electronic device for implementing the method for displaying a space digital model in real time according to an embodiment of the present invention.
The implementation, functional features and advantages of the present invention will be further described with reference to the accompanying drawings.
Detailed Description
It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.
The embodiment of the application provides a real-time display method of a space digital model. The execution subject of the space digital model real-time presentation method includes, but is not limited to, at least one of electronic devices, such as a server and a terminal, which can be configured to execute the method provided by the embodiments of the present application. In other words, the space digital model real-time presentation method may be performed by software or hardware installed in a terminal device or a server device, and the software may be a block chain platform. The server includes but is not limited to: a single server, a server cluster, a cloud server or a cloud server cluster, and the like. The server may be an independent server, or may be a cloud server that provides basic cloud computing services such as a cloud service, a cloud database, cloud computing, a cloud function, cloud storage, a Network service, cloud communication, a middleware service, a domain name service, a security service, a Content Delivery Network (CDN), a big data and artificial intelligence platform, and the like.
Fig. 1 is a schematic flow chart of a method for displaying a space digital model in real time according to an embodiment of the present invention. In this embodiment, the method for displaying the space digital model in real time includes:
s1, a space digital elevation model is obtained, and trend data of space coordinates in a preset direction in the space digital elevation model are calculated based on space coordinate data in the space digital elevation model.
In the embodiment of the present invention, the spatial Digital Elevation model is a DEM (Digital Elevation Mode) model, which is a Digital representation of a terrain and a landform, and is generally stored in a grid or grid form, and records three-dimensional coordinates of the earth, that is, (x, y) coordinates of a two-dimensional plane and an Elevation z corresponding to the coordinates. The space digital elevation model can be obtained by the technical means of the existing digital elevation model database, manual surveying and mapping, unmanned aerial vehicle surveying and mapping, photogrammetry and laser radar technology (LIDAR) and the like.
In detail, the calculating trend data of the spatial coordinates in the preset direction in the space digital elevation model based on the spatial coordinate data in the space digital elevation model includes:
calculating a cross validation index and a fitting index of the space coordinate in the preset direction;
and performing polynomial regression processing on the space coordinate in the preset direction based on the cross validation index and the fitting index until the regression order meets the preset regression condition, and obtaining a regression coefficient containing the trend data through a least square method.
Practice of the inventionIn the example, the trend data of the spatial coordinates can be obtained by a polynomial regression mode, and the determination of the regression order needs to follow two principles of accurate regression and over-fitting avoidance and respectively uses cross validation indexes
And fitting index
And (6) judging.
In an optional embodiment of the invention, the fitting index is obtained by subtracting the statistical quantity of Wald and the statistical F distribution of observed spatial data (namely, spatial coordinates in a preset direction) to obtain
Calculating the cross validation index by the following formula
：
Wherein,
is the residual value vector of the space coordinate, is equal to the displacement observed quantity of each space coordinate minus the corresponding trend structure value,
is the total number of spatial coordinates observed.
In detail, the performing polynomial regression processing on the spatial coordinate in the preset direction based on the cross validation index and the fitting index until the regression order satisfies a preset regression condition obtains a regression coefficient including the trend data by a least square method, including:
initializing an original regression order, and determining a cross validation index and a fitting index under the original regression order;
if the fitting index of the original regression order is less than or equal to a preset fitting threshold value, performing order raising processing on the original regression order, determining whether the cross validation index and the fitting index under the regression order after order raising meet a preset regression condition, and if not, continuing to raise the order until the cross validation index and the fitting index under the regression order after order raising meet the preset regression condition to obtain a standard regression order;
constructing a polynomial regression equation by using the standard regression order, and calculating a regression coefficient of the polynomial regression equation by using a least square method;
and if the fitting index of the original regression order is larger than the preset fitting threshold, performing order reduction on the original regression order, and returning to the step of determining the cross validation index and the fitting index under the original regression order.
In an alternative embodiment of the present invention, a smaller original regression order is first determined
Wherein
the decision being based on the order of a natural number
In the case of
And
value, if
Then the order is reduced, otherwise the order is increased to
Comparing the results after the upgrade
A value if
A value is raised and it
When the preset value is reached, the step is continuously increased until the preset value is reached
Or PF>Until 0.05, after determining the standard regression order, the polynomial form of the regression equation is known.
Furthermore, the formula in the invention is calculated by
For example, the calculating the regression coefficient of the polynomial regression equation by using the least square method includes:
calculating the regression coefficient by using the following formula
：
Wherein,
the matrix of trend data, containing trend structure and coordinate information,
is a covariance matrix of the spatial coordinates,
to represent
Spatial coordinates of the direction.
In the embodiment of the present invention, the trend data mainly includes trend structure information in three directions x, y, and z, for example, a trend structure in the x direction is determined, and a structural equation of the trend structure is x = f (y, z); determining a trend structure in the y direction, wherein the structural equation is y = f (x, z); and determining a trend structure in the z direction, wherein the structural equation is z = f (x, y). Meanwhile, when trend structures in the x and y directions are determined, the corresponding trend structures are solved on the left and right sides of the corresponding x and y directions by taking the middle of the object slope as a reference, and the corresponding trend structures are 5 groups, namely, z, y-, y +, x-, and x +, when trend data are determined, the coordinate of the repeated point is the minimum value of the coordinate.
And S2, performing spatial correlation characteristic representation on the spatial coordinates in the preset direction in the spatial digital elevation model by using the trend data to obtain characteristic data.
In the embodiment of the invention, the spatial correlation characteristic of the spatial data can be characterized by a spatial autocorrelation function and a spatial autocorrelation parameter.
In detail, the performing spatial correlation feature representation on the spatial coordinates in the preset direction in the spatial digital elevation model by using the trend data to obtain feature data includes:
calculating a spatial autocorrelation equation of the spatial coordinates by using a Materen covariance method;
and determining the spatial autocorrelation parameters of the spatial autocorrelation equation based on a maximum likelihood estimation method, and taking the spatial autocorrelation parameters as characteristic data.
In an optional embodiment of the present invention, the manten covariance approach uses matern equations to characterize the data features.
In an optional embodiment of the present invention, the spatial autocorrelation equation is as follows:
wherein,
is the spatial distance of any two coordinates in the space digital elevation model,
the equation of the spatial autocorrelation is expressed,
a smoothing parameter ranging from 0 to infinity,
in order to be a parameter of the range,
in order to be the gamma equation,
is composed of
Bessel formula of the second kind of order.
In an optional embodiment of the present invention, the determining a spatial autocorrelation parameter of the spatial autocorrelation equation based on a maximum likelihood estimation method includes:
calculating a spatial autocorrelation parameter of the spatial autocorrelation equation using the following formula:
wherein,
，
，
is a matrix of trend data that is,
is a covariance matrix of the spatial coordinates,
，
is a matrix of the unit, and is,
to represent
The spatial coordinates of the direction of the light,
is a parameter vector composed of the spatial autocorrelation parameters in the spatial autocorrelation equation,
is composed of
The number of the elements in (1) is,
is the total number of spatial coordinates observed.
In the embodiment of the invention, the parameter vector is calculated
The spatial autocorrelation parameters can be used for representing spatial features, corresponding to trend structures in 5 directions, the spatial autocorrelation parameters are also divided into five directions of z, y-, y +, x-, and x + for extraction, and the obtained spatial autocorrelation parameters are also 5 groups.
And S3, acquiring real-time dynamic displacement data of the monitoring range, and performing spatial interpolation on the real-time dynamic displacement data based on the characteristic data to obtain displacement interpolation data.
In the embodiment of the invention, the real-time dynamic displacement data refers to dynamic displacement data of a side slope monitored by monitoring equipment, for example, the horizontal displacement, settlement displacement, inclination angle, vibration, underground water level and other side slope displacement data of the side slope acquired by an internet of things sensor. The real-time dynamic displacement data is the displacement data of the space monitored by the monitoring equipment, the space digital elevation model also comprises unmonitored space coordinates, and the regression Krigin interpolation method considers the relationship between the position of the monitored point and the position of the unmonitored point, so that the distribution rule of the real-time displacement of the space can be objectively reflected.
Specifically, the performing spatial interpolation on the real-time dynamic displacement data based on the feature data to obtain displacement interpolation data includes:
constructing a horizontal covariance matrix based on the real-time dynamic displacement data of the monitoring range and the unmonitored space coordinates;
and calculating an interpolation weighting coefficient by using the horizontal covariance matrix and the characteristic data, and calculating displacement interpolation data of the spatial coordinates which are not monitored in the spatial digital elevation model based on the interpolation weighting coefficient and a regression kriging interpolation method.
In an optional embodiment of the present invention, the horizontal covariance matrix is as follows:
wherein,
horizontal coordinates representing n monitoring points and
a horizontal covariance matrix composed of the horizontal coordinates of the unmonitored points,
in order to fix the parameters of the device,
、
represents the interval between any two points on the x, y axes,
representing a spatial autocorrelation equation.
In an alternative embodiment of the present invention, the interpolation weighting factor is calculated using the following formula:
wherein,
for the purpose of the characteristic data, it is,
is a vector of all 1's,
for the purpose of the interpolation weighting coefficients,
in order to be a lagrange multiplier,
first to represent the horizontal covariance matrix
And (4) columns.
In an optional embodiment of the present invention, the calculating, based on the interpolation weighting coefficient and the regression kriging interpolation method, displacement interpolation data of an unmonitored spatial coordinate in the spatial digital elevation model includes:
calculating displacement interpolation data for the non-monitored spatial coordinates using the following formula:
wherein,
displacement interpolation data representing a prediction of the jth unmonitored point in the z direction,
representing monitored spatial coordinates
The value of the displacement of (a) is,
trend data for displacement values.
According to the method, the coordinate values of the digital elevation model of the slope body are extracted, the spatial correlation characteristic parameters of the slope elevation data are obtained through the obtained coordinate values, the obtained spatial correlation characteristic parameters are combined with the dynamic displacement data of the monitoring points and applied to the interpolation of the dynamic displacement data of the slope, and finally the displacement data of the whole range of the slope body can be obtained.
And S4, performing graphic processing and rendering on the displacement interpolation data and the real-time dynamic displacement data to obtain a digital three-dimensional model, and performing real-time visual display on the digital three-dimensional model by using a preset front end view component.
In the embodiment of the invention, the webGL technology can be used for carrying out graphic processing and rendering on the displacement interpolation data and the real-time dynamic displacement data, and the VUE view component is used for carrying out page display.
In detail, the performing graphics processing and rendering on the displacement interpolation data and the real-time dynamic displacement data to obtain a digital three-dimensional model includes:
generating a vertex coordinate set based on the space digital elevation model, the displacement interpolation data and the real-time dynamic displacement data;
performing graph source assembly on the vertex coordinate set to obtain a primitive set;
and rasterizing the primitives in the primitive set to obtain a fragment set, and performing geometric transformation on the fragments in the fragment set to obtain the digital three-dimensional model.
In another alternative embodiment of the present invention, the predetermined front end view component may be a Vue component, and the basic process of packaging is as follows:
1. create a component using vue.extensing ();
2. component () component registration using vue;
3. if a subcomponent requires data, the definition is accepted at the props;
4. and after the sub-component modifies the data, the data is transmitted to the parent component through an emit () method.
In an optional embodiment of the invention, a vertex coordinate set is derived through three-dimensional software or a framework, a vertex shader (written by opengles, defined by java in a character string form and used for transmitting vertex coordinates) is used for converting the vertex coordinates to generate a primitive (namely a triangle), so that three-dimensional world coordinates are converted into screen coordinates, after the primitive is generated, the model is colored, and the texture (color, diffuse reflection mapping and the like) of the model, light and the like are changed through the fragment shader. And meanwhile, a level of Detail (LOD) model is adopted to carry out geometric transformation to obtain the digital three-dimensional model.
The invention renders the updated spatial data in real time through the webGL technology and displays the updated spatial data in real time through the front end view component, so that the real-time performance of digital model display can be improved.
In the embodiment, the trend data of the spatial coordinates in the preset direction in the spatial digital elevation model is calculated, and the spatial correlation characteristic representation is performed on the spatial coordinates in the preset direction in the spatial digital elevation model by using the trend data to obtain the characteristic data. Meanwhile, the real-time dynamic displacement data in the monitoring range are subjected to spatial interpolation based on the characteristic data, so that more accurate displacement interpolation data can be obtained, in the real-time dynamic data display, the spatial correlation characteristic data do not need to be repeatedly calculated, the operation time is saved, and finally, the displacement interpolation data and the real-time dynamic displacement data are subjected to graphic processing and rendering to obtain a digital three-dimensional model, so that the real-time performance of the space digital model display is improved. Therefore, the real-time display method of the space digital model provided by the invention can improve the real-time performance of the display of the space digital model, establish the three-dimensional digital twin model and realize the three-dimensional visual simulation deduction display.
Fig. 2 is a functional block diagram of a device for displaying a space digital model in real time according to an embodiment of the present invention.
The device 100 for displaying a space digital model in real time of the invention can be installed in an electronic device. According to the realized functions, the spatial digital model real-time display device 100 can comprise a spatial trend calculation module 101, a spatial feature representation module 102, a spatial interpolation module 103 and a model display module 104. The module of the present invention, which may also be referred to as a unit, refers to a series of computer program segments that can be executed by a processor of an electronic device and that can perform a fixed function, and that are stored in a memory of the electronic device.
In the present embodiment, the functions regarding the respective modules/units are as follows:
the spatial trend calculation module 101 is configured to obtain a spatial digital elevation model and real-time dynamic displacement data of a monitoring range in the spatial digital elevation model, and calculate trend data of spatial coordinates in a preset direction in the spatial digital elevation model based on spatial coordinate data of the spatial digital elevation model;
the spatial trend calculation module 101 is configured to obtain a spatial digital elevation model, and calculate trend data of spatial coordinates in a preset direction in the spatial digital elevation model based on spatial coordinate data in the spatial digital elevation model;
the spatial feature representation module 102 is configured to perform spatial correlation feature representation on spatial coordinates in a preset direction in the spatial digital elevation model by using the trend data to obtain feature data;
the spatial interpolation module 103 is configured to obtain real-time dynamic displacement data of a monitoring range, and perform spatial interpolation on the real-time dynamic displacement data based on the feature data to obtain displacement interpolation data;
the model display module 104 is configured to perform graphics processing and rendering on the displacement interpolation data and the real-time dynamic displacement data to obtain a digital three-dimensional model, and perform real-time visual display on the digital three-dimensional model by using a preset front end view component.
In detail, the specific implementation of each module of the space digital model real-time displaying apparatus 100 is as follows:
the method comprises the steps of firstly, obtaining a space digital elevation model, and calculating trend data of space coordinates in a preset direction in the space digital elevation model based on space coordinate data in the space digital elevation model.
In the embodiment of the present invention, the spatial Digital Elevation model is a DEM (Digital Elevation Mode) model, which is a Digital representation of topography, and is generally stored in a grid or grid form, and records three-dimensional coordinates of the earth, that is, (x, y) coordinates of a two-dimensional plane and an Elevation z corresponding to the coordinates. The space digital elevation model can be obtained by the technical means of the existing digital elevation model database, manual surveying and mapping, unmanned aerial vehicle surveying and mapping, photogrammetry and laser radar technology (LIDAR) and the like.
In detail, the calculating trend data of the spatial coordinates in the preset direction in the space digital elevation model based on the spatial coordinate data in the space digital elevation model includes:
calculating cross validation indexes and fitting indexes of the space coordinates in the preset direction;
and performing polynomial regression processing on the space coordinate in the preset direction based on the cross validation index and the fitting index until the regression order meets the preset regression condition, and obtaining a regression coefficient containing the trend data through a least square method.
In the embodiment of the invention, the trend data of the space coordinate can be obtained by a polynomial regression mode, the determination of the regression order of the trend data needs to follow two principles of accurate regression and over-fitting avoidance, and cross validation indexes are respectively used
And fitting index
And (6) judging.
In an optional embodiment of the invention, the fitting index is obtained by subtracting the statistical quantity of Walld and the statistical F distribution of observed spatial data (namely the spatial coordinates in the preset direction), and the cross validation index is calculated by the following formula
：
Wherein,
is the residual value vector of the space coordinate, is equal to the displacement observed quantity of each space coordinate minus the corresponding trend structure value,
is the total number of spatial coordinates observed.
In detail, the performing polynomial regression processing on the spatial coordinate in the preset direction based on the cross validation index and the fitting index until the regression order satisfies a preset regression condition obtains a regression coefficient including the trend data by a least square method, including:
initializing an original regression order, and determining a cross validation index and a fitting index under the original regression order;
if the fitting index of the original regression order is less than or equal to a preset fitting threshold value, performing order raising processing on the original regression order, determining whether the cross validation index and the fitting index under the regression order after order raising meet a preset regression condition, and if not, continuing to raise the order until the cross validation index and the fitting index under the regression order after order raising meet the preset regression condition to obtain a standard regression order;
constructing a polynomial regression equation by using the standard regression order, and calculating a regression coefficient of the polynomial regression equation by using a least square method;
and if the fitting index of the original regression order is larger than the preset fitting threshold, performing order reduction on the original regression order, and returning to the step of determining the cross validation index and the fitting index under the original regression order.
In an alternative embodiment of the present invention, a smaller original regression order is first determined
Wherein
the decision being based on the order of a natural number
In the case of
And
value, if
Then the order is reduced, otherwise the order is increased to
Comparing the results after the upgrade
A value if
A value is raised and it
When the preset value is reached, the step is continuously increased until the preset value is reached
Or PF>Until 0.05, after determining the standard regression order, the polynomial form of the regression equation is known.
Furthermore, the formula in the invention is calculated by
For example, the calculating the regression coefficient of the polynomial regression equation by using the least square method includes:
calculating the regression coefficient using the following formula
：
Wherein,
the matrix of trend data, containing trend structure and coordinate information,
is a covariance matrix of the spatial coordinates,
to represent
Spatial coordinates of the direction.
In the embodiment of the present invention, the trend data mainly includes trend structure information in three directions x, y and z, for example, a trend structure in the x direction is determined, and a structural equation of the trend structure is x = f (y, z); determining a trend structure in the y direction, wherein the structural equation is y = f (x, z); and determining a trend structure in the z direction, wherein the structural equation is z = f (x, y). Meanwhile, when trend structures in the x and y directions are determined, the corresponding trend structures are solved on the left and right sides of the corresponding x and y directions by taking the middle of the object slope as a reference, and the corresponding trend structures are 5 groups, namely, z, y-, y +, x-, and x +, when trend data are determined, the coordinate of the repeated point is the minimum value of the coordinate.
And secondly, performing spatial correlation characteristic representation on the spatial coordinates in the preset direction in the spatial digital elevation model by using the trend data to obtain characteristic data.
In the embodiment of the invention, the spatial correlation characteristic of the spatial data can be characterized by a spatial autocorrelation function and a spatial autocorrelation parameter.
In detail, the performing spatial correlation feature representation on the spatial coordinates in the preset direction in the spatial digital elevation model by using the trend data to obtain feature data includes:
calculating a spatial autocorrelation equation of the spatial coordinates by using a Materen covariance method;
and determining the spatial autocorrelation parameters of the spatial autocorrelation equation based on a maximum likelihood estimation method, and taking the spatial autocorrelation parameters as characteristic data.
In an optional embodiment of the present invention, the manten covariance approach uses matern equations to characterize the data features.
In an optional embodiment of the present invention, the spatial autocorrelation equation is as follows:
wherein,
is the spatial distance of any two coordinates in the space digital elevation model,
the equation of the spatial autocorrelation is expressed,
a smoothing parameter ranging from 0 to infinity,
in order to be a parameter of the range,
in order to obtain the gamma equation,
is composed of
Bessel formula of the second kind of order.
In an optional embodiment of the present invention, the determining the spatial autocorrelation parameters of the spatial autocorrelation equation based on a maximum likelihood estimation method includes:
calculating a spatial autocorrelation parameter of the spatial autocorrelation equation using the following formula:
wherein,
，
，
is a trend numberAccording to the matrix of the data matrix,
is a covariance matrix of the spatial coordinates,
，
is an identity matrix, representing
The spatial coordinates of the direction of the light,
is a parameter vector composed of the spatial autocorrelation parameters in the spatial autocorrelation equation,
is composed of
The number of elements in (1) is the total amount of observed spatial coordinates.
In the embodiment of the invention, the parameter vector is calculated
The spatial autocorrelation parameters can be used for representing spatial features, corresponding to trend structures in 5 directions, the spatial autocorrelation parameters are also divided into five directions of z, y-, y +, x-, and x + for extraction, and the obtained spatial autocorrelation parameters are also 5 groups.
And thirdly, acquiring real-time dynamic displacement data of the monitoring range, and performing spatial interpolation on the real-time dynamic displacement data based on the characteristic data to obtain displacement interpolation data.
In the embodiment of the invention, the real-time dynamic displacement data refers to dynamic displacement data of a side slope monitored by monitoring equipment, for example, the horizontal displacement, settlement displacement, inclination angle, vibration, underground water level and other side slope displacement data of the side slope are acquired by using an internet of things sensor. The real-time dynamic displacement data is the displacement data of the space monitored by the monitoring equipment, the space digital elevation model also comprises unmonitored space coordinates, and the regression Krigin interpolation method considers the relationship between the position of the monitored point and the position of the unmonitored point, so that the distribution rule of the real-time displacement of the space can be objectively reflected.
Specifically, the performing spatial interpolation on the real-time dynamic displacement data based on the feature data to obtain displacement interpolation data includes:
constructing a horizontal covariance matrix based on the real-time dynamic displacement data of the monitoring range and the unmonitored space coordinates;
and calculating an interpolation weighting coefficient by using the horizontal covariance matrix and the characteristic data, and calculating displacement interpolation data of the spatial coordinates which are not monitored in the spatial digital elevation model based on the interpolation weighting coefficient and a regression kriging interpolation method.
In an optional embodiment of the present invention, the horizontal covariance matrix is as follows:
wherein,
horizontal coordinates representing n monitoring points and
a horizontal covariance matrix composed of the horizontal coordinates of the unmonitored points,
in order to fix the parameters of the device,
、
indicates the interval between any two points on the x and y axes,
representing a spatial autocorrelation equation.
In an alternative embodiment of the present invention, the interpolation weighting factor is calculated using the following formula:
wherein,
in order to be able to determine the characteristic data,
is a vector of all 1's,
for the said interpolation weight-ing factor(s),
in order to be a lagrange multiplier,
first to represent a horizontal covariance matrix
And (4) columns.
In an optional embodiment of the present invention, the calculating, based on the interpolation weighting coefficient and the regression kriging interpolation method, displacement interpolation data of the spatial coordinates that are not monitored in the spatial digital elevation model includes:
calculating displacement interpolation data for the non-monitored spatial coordinates using the following formula:
wherein，
Displacement interpolation data representing a prediction of the jth unmonitored point in the z direction,
representing monitored spatial coordinates
Is the trend data of the displacement value.
According to the method, the coordinate values of the digital elevation model of the slope body are extracted, the spatial correlation characteristic parameters of the slope elevation data are obtained through the obtained coordinate values, the obtained spatial correlation characteristic parameters are combined with the dynamic displacement data of the monitoring points and applied to the interpolation of the dynamic displacement data of the slope, and finally the displacement data of the whole range of the slope body can be obtained.
And fourthly, performing graphic processing and rendering on the displacement interpolation data and the real-time dynamic displacement data to obtain a digital three-dimensional model, and performing real-time visual display on the digital three-dimensional model by using a preset front end view component.
In the embodiment of the invention, the webGL technology can be used for carrying out graphic processing and rendering on the displacement interpolation data and the real-time dynamic displacement data, and the VUE view component is used for carrying out page display.
In detail, the performing graphics processing and rendering on the displacement interpolation data and the real-time dynamic displacement data to obtain a digital three-dimensional model includes:
generating a vertex coordinate set based on the space digital elevation model, the displacement interpolation data and the real-time dynamic displacement data;
carrying out graph source assembly on the vertex coordinate set to obtain a primitive set;
and rasterizing the primitives in the primitive set to obtain a fragment set, and performing geometric transformation on the fragments in the fragment set to obtain the digital three-dimensional model.
In another alternative embodiment of the present invention, the predetermined front end view assembly may be a Vue assembly, and the basic process of packaging is as follows:
1. create a component using vue.extensing ();
2. component () component registration using vue;
3. accepting definitions at the tips if the subcomponents require data;
4. and after the sub-component modifies the data, the data is transmitted to the parent component through an emit () method.
In an optional embodiment of the invention, a vertex coordinate set is derived through three-dimensional software or a framework, a vertex shader (written by opengles, defined by java in a character string form and used for transmitting vertex coordinates) is used for converting the vertex coordinates to generate a primitive (namely a triangle), so that three-dimensional world coordinates are converted into screen coordinates, after the primitive is generated, the model is colored, and the texture (color, diffuse reflection mapping and the like) of the model, light and the like are changed through the fragment shader. And meanwhile, a level of Detail (LOD) model is adopted to carry out geometric transformation to obtain the digital three-dimensional model.
The invention renders the updated spatial data in real time through the webGL technology and displays the updated spatial data in real time through the front end view component, so that the real-time performance of digital model display can be improved.
In the embodiment, the trend data of the spatial coordinates in the preset direction in the spatial digital elevation model is calculated, and the spatial correlation characteristic representation is performed on the spatial coordinates in the preset direction in the spatial digital elevation model by using the trend data to obtain the characteristic data. Meanwhile, the real-time dynamic displacement data in the monitoring range are subjected to spatial interpolation based on the characteristic data, so that more accurate displacement interpolation data can be obtained, in the real-time dynamic data display, the spatial correlation characteristic data do not need to be repeatedly calculated, the operation time is saved, and finally, the displacement interpolation data and the real-time dynamic displacement data are subjected to graphic processing and rendering to obtain a digital three-dimensional model, so that the real-time performance of the space digital model display is improved. Therefore, the real-time display device for the space digital model, provided by the invention, can improve the real-time performance of the display of the space digital model, establish a three-dimensional digital twin model and realize three-dimensional visual simulation deduction display.
Fig. 3 is a schematic structural diagram of an electronic device for implementing the method for real-time displaying a space digital model according to an embodiment of the present invention.
The electronic device may include a processor 10, a memory 11, a communication interface 12 and a bus 13, and may further include a computer program, such as a space digital model real-time presentation program, stored in the memory 11 and executable on the processor 10.
The memory 11 includes at least one type of readable storage medium, which includes flash memory, removable hard disk, multimedia card, card type memory (e.g., SD or DX memory, etc.), magnetic memory, magnetic disk, optical disk, etc. The memory 11 may in some embodiments be an internal storage unit of the electronic device, for example a removable hard disk of the electronic device. The memory 11 may also be an external storage device of the electronic device in other embodiments, such as a plug-in mobile hard disk, a Smart Media Card (SMC), a Secure Digital (SD) Card, a Flash memory Card (Flash Card), and the like, which are provided on the electronic device. Further, the memory 11 may also include both an internal storage unit and an external storage device of the electronic device. The memory 11 may be used to store not only application software installed in the electronic device and various data, such as codes of a space digital model real-time presentation program, but also temporarily store data that has been output or will be output.
The processor 10 may be composed of an integrated circuit in some embodiments, for example, a single packaged integrated circuit, or may be composed of a plurality of integrated circuits packaged with the same or different functions, including one or more Central Processing Units (CPUs), microprocessors, digital Processing chips, graphics processors, and combinations of various control chips. The processor 10 is a Control Unit (Control Unit) of the electronic device, connects various components of the electronic device by using various interfaces and lines, and executes various functions and processes data of the electronic device by running or executing programs or modules (e.g., space digital model real-time presentation programs, etc.) stored in the memory 11 and calling data stored in the memory 11.
The communication interface 12 is used for communication between the electronic device and other devices, and includes a network interface and a user interface. Optionally, the network interface may include a wired interface and/or a wireless interface (e.g., WI-FI interface, bluetooth interface, etc.), which are typically used to establish a communication connection between the electronic device and other electronic devices. The user interface may be a Display (Display), an input unit, such as a Keyboard (Keyboard), and optionally a standard wired interface, a wireless interface. Alternatively, in some embodiments, the display may be an LED display, a liquid crystal display, a touch-sensitive liquid crystal display, an OLED (Organic Light-Emitting Diode) touch device, or the like. The display, which may also be referred to as a display screen or display unit, is suitable, among other things, for displaying information processed in the electronic device and for displaying a visualized user interface.
The bus 13 may be a Peripheral Component Interconnect (PCI) bus, an Extended Industry Standard Architecture (EISA) bus, or the like. The bus 13 may be divided into an address bus, a data bus, a control bus, etc. The bus 13 is arranged to enable connection communication between the memory 11 and at least one processor 10 or the like.
Fig. 3 shows only an electronic device having components, and those skilled in the art will appreciate that the structure shown in fig. 3 does not constitute a limitation of the electronic device, and may include fewer or more components than those shown, or some components may be combined, or a different arrangement of components.
For example, although not shown, the electronic device may further include a power supply (such as a battery) for supplying power to each component, and preferably, the power supply may be logically connected to the at least one processor 10 through a power management device, so that functions of charge management, discharge management, power consumption management and the like are realized through the power management device. The power supply may also include any component of one or more dc or ac power sources, recharging devices, power failure detection circuitry, power converters or inverters, power status indicators, and the like. The electronic device may further include various sensors, a bluetooth module, a Wi-Fi module, and the like, which are not described herein again.
Further, the electronic device may further include a network interface, and optionally, the network interface may include a wired interface and/or a wireless interface (such as a WI-FI interface, a bluetooth interface, etc.), which are generally used to establish a communication connection between the electronic device and other electronic devices.
Optionally, the electronic device may further comprise a user interface, which may be a Display (Display), an input unit, such as a Keyboard (Keyboard), and optionally a standard wired interface, a wireless interface. Alternatively, in some embodiments, the display may be an LED display, a liquid crystal display, a touch-sensitive liquid crystal display, an OLED (Organic Light-Emitting Diode) touch device, or the like. The display, which may also be referred to as a display screen or display unit, is suitable, among other things, for displaying information processed in the electronic device and for displaying a visualized user interface.
It is to be understood that the described embodiments are for purposes of illustration only and that the scope of the appended claims is not limited to such structures.
The space digital model real-time presentation program stored in the memory 11 of the electronic device is a combination of a plurality of instructions, and when running in the processor 10, can realize:
acquiring a space digital elevation model, and calculating trend data of space coordinates in a preset direction in the space digital elevation model based on space coordinate data in the space digital elevation model;
performing spatial correlation characteristic representation on the spatial coordinates in the preset direction in the spatial digital elevation model by using the trend data to obtain characteristic data;
acquiring real-time dynamic displacement data of a monitoring range, and performing spatial interpolation on the real-time dynamic displacement data based on the characteristic data to obtain displacement interpolation data;
and performing graphic processing and rendering on the displacement interpolation data and the real-time dynamic displacement data to obtain a digital three-dimensional model, and performing real-time visual display on the digital three-dimensional model by using a preset front end view component.
Specifically, the specific implementation method of the instruction by the processor 10 may refer to the description of the relevant steps in the embodiment corresponding to the drawings, which is not described herein again.
Further, the electronic device integrated module/unit, if implemented in the form of a software functional unit and sold or used as a separate product, may be stored in a computer readable storage medium. The computer readable storage medium may be volatile or non-volatile. For example, the computer-readable medium may include: any entity or device capable of carrying said computer program code, recording medium, U-disk, removable hard disk, magnetic disk, optical disk, computer Memory, read-Only Memory (ROM).
The present invention also provides a computer-readable storage medium storing a computer program which, when executed by a processor of an electronic device, implements:
acquiring a space digital elevation model, and calculating trend data of space coordinates in a preset direction in the space digital elevation model based on space coordinate data in the space digital elevation model;
performing spatial correlation characteristic representation on the spatial coordinates in the preset direction in the spatial digital elevation model by using the trend data to obtain characteristic data;
acquiring real-time dynamic displacement data of a monitoring range, and performing spatial interpolation on the real-time dynamic displacement data based on the characteristic data to obtain displacement interpolation data;
and performing graphic processing and rendering on the displacement interpolation data and the real-time dynamic displacement data to obtain a digital three-dimensional model, and performing real-time visual display on the digital three-dimensional model by using a preset front end view component.
In the embodiments provided in the present invention, it should be understood that the disclosed apparatus, device and method can be implemented in other ways. For example, the above-described apparatus embodiments are merely illustrative, and for example, the division of the modules is only one logical functional division, and other divisions may be realized in practice.
The modules described as separate parts may or may not be physically separate, and parts displayed as modules may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of the present embodiment.
In addition, functional modules in the embodiments of the present invention may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit. The integrated unit can be realized in a form of hardware, or in a form of hardware plus a software functional module.
It will be evident to those skilled in the art that the invention is not limited to the details of the foregoing illustrative embodiments, and that the present invention may be embodied in other specific forms without departing from the spirit or essential attributes thereof.
The present embodiments are therefore to be considered in all respects as illustrative and not restrictive, the scope of the invention being indicated by the appended claims rather than by the foregoing description, and all changes which come within the meaning and range of equivalency of the claims are therefore intended to be embraced therein. Any reference signs in the claims shall not be construed as limiting the claim concerned.
The embodiment of the application can acquire and process related data based on an artificial intelligence technology. Among them, artificial Intelligence (AI) is a theory, method, technique and application system that simulates, extends and expands human Intelligence using a digital computer or a machine controlled by a digital computer, senses the environment, acquires knowledge and uses the knowledge to obtain the best result.
The artificial intelligence infrastructure generally includes technologies such as sensors, dedicated artificial intelligence chips, cloud computing, distributed storage, big data processing technologies, operation/interaction systems, mechatronics, and the like. The artificial intelligence software technology mainly comprises a computer vision technology, a robot technology, a biological recognition technology, a voice processing technology, a natural language processing technology, machine learning/deep learning and the like.
Furthermore, it is obvious that the word "comprising" does not exclude other elements or steps, and the singular does not exclude the plural. A plurality of units or means recited in the system claims may also be implemented by one unit or means in software or hardware. The terms second, etc. are used to denote names, but not to denote any particular order.
Finally, it should be noted that the above embodiments are only for illustrating the technical solutions of the present invention and not for limiting, and although the present invention is described in detail with reference to the preferred embodiments, it should be understood by those skilled in the art that modifications or equivalent substitutions may be made on the technical solutions of the present invention without departing from the spirit and scope of the technical solutions of the present invention.
Claims (10)
1. A method for displaying a space digital model in real time is characterized by comprising the following steps:
acquiring a space digital elevation model, and calculating trend data of space coordinates in a preset direction in the space digital elevation model based on space coordinate data in the space digital elevation model;
performing spatial correlation characteristic representation on the spatial coordinates in the preset direction in the spatial digital elevation model by using the trend data to obtain characteristic data;
acquiring real-time dynamic displacement data of a monitoring range, and performing spatial interpolation on the real-time dynamic displacement data based on the characteristic data to obtain displacement interpolation data;
and performing graphic processing and rendering on the displacement interpolation data and the real-time dynamic displacement data to obtain a digital three-dimensional model, and performing real-time visual display on the digital three-dimensional model by using a preset front end view component.
2. The method for displaying the space digital model in real time as claimed in claim 1, wherein the calculating trend data of the space coordinates in the preset direction in the space digital elevation model based on the space coordinate data in the space digital elevation model comprises:
calculating a cross validation index and a fitting index of the space coordinate in the preset direction;
and performing polynomial regression processing on the space coordinate in the preset direction based on the cross validation index and the fitting index until the regression order meets the preset regression condition, and obtaining a regression coefficient containing the trend data through a least square method.
3. The method for displaying a space digital model in real time according to claim 2, wherein the performing polynomial regression processing on the space coordinates in the preset direction based on the cross validation index and the fitting index until the regression order satisfies a preset regression condition obtains a regression coefficient including the trend data by a least square method, including:
initializing an original regression order, and determining a cross validation index and a fitting index under the original regression order;
if the fitting index of the original regression order is less than or equal to a preset fitting threshold value, performing order raising processing on the original regression order, determining whether the cross validation index and the fitting index under the regression order after order raising meet a preset regression condition, and if not, continuing to raise the order until the cross validation index and the fitting index under the regression order after order raising meet the preset regression condition to obtain a standard regression order;
constructing a polynomial regression equation by using the standard regression order, and calculating a regression coefficient of the polynomial regression equation by using a least square method;
and if the fitting index of the original regression order is larger than the preset fitting threshold, performing order reduction on the original regression order, and returning to the step of determining the cross validation index and the fitting index under the original regression order.
4. The method for displaying the space digital model in real time according to claim 1, wherein the performing spatial correlation feature representation on the spatial coordinates in the preset direction in the space digital elevation model by using the trend data to obtain feature data comprises:
calculating a spatial autocorrelation equation of the spatial coordinates by using a Materen covariance method;
and determining the spatial autocorrelation parameters of the spatial autocorrelation equation based on a maximum likelihood estimation method, and taking the spatial autocorrelation parameters as characteristic data.
5. The method for displaying the space digital model in real time according to claim 4, wherein the space autocorrelation equation is as follows:
wherein,
is the spatial distance of any two coordinates in the space digital elevation model,
indicates nullThe inter-self-correlation equation is obtained,
a smoothing parameter ranging from 0 to infinity,
in order to be a parameter of the range,
in order to be the gamma equation,
is composed of
Bessel formula of order II.
6. The method for displaying a space digital model in real time according to claim 1, wherein the performing spatial interpolation on the real-time dynamic displacement data based on the feature data to obtain displacement interpolation data comprises:
constructing a horizontal covariance matrix based on the real-time dynamic displacement data of the monitoring range and the unmonitored space coordinates;
and calculating an interpolation weighting coefficient by using the horizontal covariance matrix and the characteristic data, and calculating displacement interpolation data of the spatial coordinates which are not monitored in the spatial digital elevation model based on the interpolation weighting coefficient and a regression kriging interpolation method.
7. The method for displaying a spatial digital model in real time according to claim 1, wherein the step of performing graphic processing and rendering on the displacement interpolation data and the real-time dynamic displacement data to obtain a digital three-dimensional model comprises:
generating a vertex coordinate set based on the space digital elevation model, the displacement interpolation data and the real-time dynamic displacement data;
carrying out graph source assembly on the vertex coordinate set to obtain a primitive set;
and rasterizing the primitives in the primitive set to obtain a fragment set, and performing geometric transformation on the fragments in the fragment set to obtain the digital three-dimensional model.
8. An apparatus for displaying a space digital model in real time, the apparatus comprising:
the space trend calculation module is used for acquiring a space digital elevation model and calculating trend data of space coordinates in a preset direction in the space digital elevation model based on space coordinate data in the space digital elevation model;
the spatial feature representation module is used for performing spatial correlation feature representation on the spatial coordinates in the preset direction in the spatial digital elevation model by using the trend data to obtain feature data;
the spatial interpolation module is used for acquiring real-time dynamic displacement data of a monitoring range, and carrying out spatial interpolation on the real-time dynamic displacement data based on the characteristic data to obtain displacement interpolation data;
and the model display module is used for carrying out graphic processing and rendering on the displacement interpolation data and the real-time dynamic displacement data to obtain a digital three-dimensional model, and carrying out real-time visual display on the digital three-dimensional model by utilizing a preset front end view component.
9. An electronic device, characterized in that the electronic device comprises:
at least one processor; and the number of the first and second groups,
a memory communicatively coupled to the at least one processor; wherein,
the memory stores a computer program executable by the at least one processor to enable the at least one processor to perform the method of real-time presentation of a space digital model according to any one of claims 1 to 7.
10. A computer-readable storage medium, in which a computer program is stored, wherein the computer program, when being executed by a processor, implements the method for real-time presentation of a space digital model according to any one of claims 1 to 7.
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