Digital twinborn multidimensional data visualization method and system based on OGC standard

Abstract

The invention relates to the technical field of multi-dimensional data visualization, in particular to a digital twinborn multi-dimensional data visualization method and system based on an OGC standard, in the system, a visualization special effect signal analysis module is used for calculating a dynamic interpolation position corresponding to a current time key frame state attribute in a WebGPU rendering pipeline; and performing service rule judgment based on the GPU executable instruction of the current time key frame, and outputting a visual special effect signal when the service rule is triggered. According to the method, the limitation of a standard 3D Tiles static data model can be broken through in a manner of newly adding a time sequence slot, and a space-time integrated storage structure oriented to a dynamic object is constructed; according to the method, the dynamic interpolation of the position and the attribute in the key frame state data can be realized, and the rendering delay can be effectively reduced; according to the method, the rule judgment structure can be used as a new key frame to be inserted into or cover the original time sequence slot through the differential update packet, so that the key frame data of the time sequence slot can be self-corrected.

Description

Technical Field

[0001] The present invention relates to the technical field of multidimensional data visualization, and specifically to a digital twin multidimensional data visualization method and system based on the OGC standard. Background Art

[0002] As a virtual representation of the physical world, digital twins must integrate heterogeneous data from multiple sources (such as geospatial, IoT sensors, BIM models, and real-time business data) and support dynamic interaction and high-fidelity visualization. Although OGC standards (such as WMS, WMTS, WFS, and 3D Tiles) provide specifications for geographic data interoperability, they still face limitations in digital twin scenarios. Traditional OGC 3D Tiles only supports static models and focuses on publishing static data, but lacks efficient encoding and transmission mechanisms for real-time streaming data (such as sensor time series data). Dynamic objects often require full tile updates, resulting in wasted bandwidth. Furthermore, W3C semantic rules are typically executed on the CPU, significantly disconnected from the GPU rendering pipeline and resulting in significant rule triggering latency. Furthermore, existing WebGL shaders lack a timed keyframe interpolation mechanism, requiring dynamic attributes to be transmitted frame by frame, increasing the data transmission load. Consequently, existing technologies present significant limitations. Summary of the Invention

[0003] The purpose of the present invention is to provide a digital twin multidimensional data visualization method and system based on the OGC standard to solve the problems raised in the above background technology.

[0004] In order to solve the above technical problems, the present invention provides the following technical solution: a digital twin multidimensional data visualization method based on the OGC standard, the method comprising: S1. Extend the time slots in the batch attribute table of OGC 3D Tiles to store the key frame states of objects within a time window of preset length, and build a dynamic attribute stream in the time-enhanced 3D Tiles data layer; S2. Based on the dynamic attribute flow in the timing-enhanced 3D Tiles data layer, linear interpolation is performed on the key frame state at the current time in the GPU shader to extract the state attributes of the key frame at the current time; S3. Obtain RDF / SPARQL business rules, convert RDF triples or SPARQL query conditions into a logical expression tree, and extract the results based on the state attributes of the current time key frame to obtain GPU executable instructions based on the current time key frame; S4. In the WebGPU rendering pipeline, the dynamic interpolation position corresponding to the state attribute of the current time keyframe is calculated, the business rule determination is performed based on the GPU executable instructions of the current time keyframe, and a visual special effect signal is output when the business rule is triggered; S5. Generate a differential update package according to the rule trigger signal, and return the differential update package to the time series data layer to update the time series slot key frame.

[0005] Furthermore, the key frame state of the object stored in S1 within a time window of a preset length includes a timestamp sequence, a position key frame sequence, and an attribute key frame sequence corresponding to the key frames in the extended time slot; The number of elements in the timestamp sequence, the position key frame sequence, and the attribute key frame sequence is the same, and each element corresponds to a key frame; the elements in the attribute key frame sequence are the service attribute vectors of the corresponding key frame, and the service attribute vector is a matrix composed of attribute values ​​of multiple different service attribute types, and the number of service attribute types is preset; The attribute keyframe sequence in the keyframe state of the stored object within a preset time window is used as a dynamic attribute stream in a timing-enhanced 3D Tiles data layer.

[0006] The present invention extends the Batch Table structure of OGC 3D Tiles and adds time slots to store the key frame states of objects within a time window. This approach can break through the limitations of the standard 3D Tiles static data model and build a spatiotemporal integrated storage structure for dynamic objects.

[0007] Furthermore, the calculation formula involved in extracting the state attribute of the current time key frame in S2 is as follows:

[0008] Among them, BD represents the state attribute of the key frame at the current time; ξ represents the time progress coefficient corresponding to the current time; TD represents the current time; T i Indicates the timestamp in the timestamp sequence that is earlier than the current time and has the smallest time interval with the current time; T i+1 Indicates the timestamp in the timestamp sequence that is later than the current time and has the smallest time interval with the current time; B i Indicates that the corresponding timestamp in the attribute keyframe sequence is T i Business attribute vector of B i+1 Indicates that the corresponding timestamp in the attribute keyframe sequence is T i+1 Business attribute vector.

[0009] In the present invention, the time progress coefficient is calculated in real time in the shader, and dynamic interpolation operations on positions and attributes are implemented based on the time progress coefficient obtained by real-time calculation. Compared with traditional CPU interpolation solutions, this can effectively reduce rendering delays. In essence, the present invention offloads timing calculations to the GPU, thereby achieving hardware-level interpolation acceleration.

[0010] Furthermore, the S3 includes: S31, parsing the input RDF triple or SPARQL query condition into a logical expression tree; S32. Partially evaluate the logical expression tree based on the state attributes of the current time key frame; S33, compile the partially evaluated logical expression tree into a WGSL code snippet executable by the GPU shader; In the process of partial evaluation of the logical expression tree by S32, when the tree node is an attribute type, the attribute of the corresponding tree node is replaced with a preset constant value corresponding to the corresponding attribute type; when all child nodes of the tree node are constant values, the value of the node is calculated and replaced with a constant node; the logical expression tree after partial evaluation is an expression tree that is minimized and includes the attribute type of the tree node and the various attribute types involved in the state attributes of the previous time key frame; if the entire expression tree is a constant after partial evaluation, a WGSL code fragment that returns the constant value is generated; each tree node of the logical expression tree includes 0 or more child nodes of the corresponding tree node, and each child node is a tree node.

[0011] The present invention parses W3C RDF / SPARQL rules into a logical expression tree, and dynamically generates WGSL code snippets (GPU executable instructions based on the current time keyframe) that can be executed by the GPU shader based on the node status within the logical expression tree. The present invention can open up a heterogeneous computing collaborative channel between semantic rules and rendering pipelines.

[0012] Furthermore, the calculation formula involved in calculating the dynamic interpolation position corresponding to the current time key frame state attribute in S4 is as follows:

[0013] Among them, PD represents the dynamic interpolation position corresponding to BD; B i Indicates that the corresponding timestamp in the position keyframe sequence is T i The key frame state position of B i+1 Indicates that the corresponding timestamp in the position keyframe sequence is T i+1 The key frame state position; The visual special effect signal output when the rule is triggered includes the target object of the special effect trigger, the business attribute vector and the timestamp.

[0014] Furthermore, the differential update package in S5 includes the visual special effect signal output when the rule is triggered, the interval between the timestamp in the visual special effect signal and the timestamp corresponding to any element in the corresponding timestamp sequence in the extended timing slot, and the vector difference between the business attribute vector in the visual special effect signal and the business attribute vector corresponding to any element in the corresponding attribute key frame sequence in the extended timing slot; Based on the obtained inserted update package, the update demand evaluation coefficient of the current time key frame is calculated. The calculation formula involved is as follows:

[0015] Among them, PX1 represents the update demand evaluation coefficient of the current time key frame; BC i Indicates BD and B i The modulus length corresponding to the vector difference between them; BC i+1 Indicates BD and B i+1 The modulus length corresponding to the vector difference between them; Compare PX with the first preset evaluation coefficient Y1 respectively, When PX1<Y1, calculate B i The previous key frame of the corresponding key frame and B i+1 Attribute mutation coefficient BS between corresponding key frames （i-1，i+1） , further BS （i-1，i+1） Compared with the preset mutation coefficient, If BS （i-1，i+1） If it is greater than or equal to the preset mutation coefficient, the current time key frame is inserted into B i With B i+1 Between the corresponding key frames, the updated time slot key frame is obtained; if BS （i-1，i+1） If it is less than the preset mutation coefficient, the current time key frame will be overwritten by B i The corresponding key frame obtains the updated timing slot key frame; When Y1≤PX1, insert the current time key frame into B i With B i+1 Between the corresponding key frames, the updated time slot key frames are obtained; The calculation formula for calculating the attribute mutation coefficient between any two key frames is as follows:

[0016] Among them, BS represents the attribute mutation coefficient between the corresponding two key frames; SPQ represents the quotient of the average value of the absolute value of the difference between the attribute value of each business attribute type corresponding to the business attribute vector of the previous key frame in the corresponding two key frames and the attribute value of the same business attribute type in the business attribute vector of the current key frame, divided by the difference between the timestamp of the corresponding key frame and the current time; SPH represents the quotient of the average value of the absolute value of the difference between the attribute value of each business attribute type corresponding to the business attribute vector of the latter key frame in the corresponding two key frames and the attribute value of the same business attribute type in the business attribute vector of the current key frame, divided by the difference between the timestamp of the corresponding key frame and the current time; min{} represents the minimum value function; max{} represents the maximum value function.

[0017] The present invention can insert the rule determination structure as a new key frame into or overwrite the original timing slot through the differential update package, thereby realizing self-correction of the key frame data of the timing slot.

[0018] A digital twin multidimensional data visualization system based on the OGC standard, comprising: A dynamic attribute stream construction module is used to extend the time slots in the batch attribute table of OGC 3D Tiles, store the keyframe states of objects within a time window of preset length, and build a dynamic attribute stream in the time-enhanced 3D Tiles data layer; The state attribute extraction module, based on the dynamic attribute flow in the timing-enhanced 3D Tiles data layer, linearly interpolates the key frame state at the current time in the GPU shader to extract the state attributes of the key frame at the current time; The GPU execution acquisition module is used to obtain RDF / SPARQL business rules, convert RDF triples or SPARQL query conditions into logical expression trees, and extract the results based on the state attributes of the current time key frame to obtain GPU executable instructions based on the current time key frame; The visual effects signal analysis module is used to calculate the dynamic interpolation position corresponding to the current time keyframe state attribute in the WebGPU rendering pipeline, perform business rule determination based on the GPU executable instructions of the current time keyframe, and output visual effects signals when the business rules are triggered; The timing slot key frame update module is used to generate a differential update package according to the rule trigger signal, and return the differential update package to the timing data layer to update the timing slot key frame.

[0019] Furthermore, the GPU execution acquisition module includes a logic expression tree acquisition unit and an execution instruction analysis unit. The logical expression tree acquisition unit is used to acquire RDF / SPARQL business rules and convert RDF triples or SPARQL query conditions into a logical expression tree; The execution instruction analysis unit obtains a GPU executable instruction based on the current time key frame in combination with the state attribute extraction result of the current time key frame.

[0020] Furthermore, the visual special effect signal analysis module includes an interpolation position acquisition unit and a special effect signal output unit. The interpolation position acquisition unit is used to calculate the dynamic interpolation position corresponding to the current time key frame state attribute in the WebGPU rendering pipeline; The special effect signal output unit performs business rule determination based on the GPU executable instructions of the current time key frame, and outputs a visual special effect signal when the business rule is triggered.

[0021] Compared with the prior art, the present invention has the following beneficial effects: (1) The present invention can break through the limitations of the standard 3D Tiles static data model by adding time slots and construct a spatiotemporal integrated storage structure for dynamic objects; (2) The present invention introduces the concept of time progress coefficient to achieve dynamic interpolation of the position and attributes in the key frame state data, which can effectively reduce rendering delay compared to the traditional CPU interpolation solution; (3) The present invention can parse RDF / SPARQL rules into logical expression trees, and then dynamically generate GPU executable instructions for the current time key frame, effectively opening up a heterogeneous computing collaborative channel between semantic rules and rendering pipelines; (4) The present invention can insert the rule judgment structure as a new key frame into or overwrite the original timing slot through the differential update package, thereby realizing self-correction of the key frame data of the timing slot, avoiding the full update of tiles, and saving bandwidth resources. BRIEF DESCRIPTION OF THE DRAWINGS

[0022] The accompanying drawings are used to provide a further understanding of the present invention and constitute a part of the specification. Together with the embodiments of the present invention, they are used to explain the present invention and do not constitute a limitation of the present invention. In the accompanying drawings: Figure 1 It is a structural diagram of the digital twin multidimensional data visualization system based on the OGC standard of the present invention; Figure 2 It is a flow chart of the digital twin multidimensional data visualization method based on the OGC standard of the present invention. DETAILED DESCRIPTION

[0023] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.

[0024] See also Figure 1-Figure 2 , the present invention provides a technical solution: Figure 1 As shown, this embodiment provides a digital twin multidimensional data visualization system based on the OGC standard, and the system includes: A dynamic attribute stream construction module is used to extend the time slots in the batch attribute table of OGC 3D Tiles, store the keyframe states of objects within a time window of preset length, and build a dynamic attribute stream in the time-enhanced 3D Tiles data layer; The state attribute extraction module, based on the dynamic attribute flow in the timing-enhanced 3D Tiles data layer, linearly interpolates the key frame state at the current time in the GPU shader to extract the state attributes of the key frame at the current time; GPU execution acquisition module, the GPU execution acquisition module includes a logic expression tree acquisition unit and an execution instruction analysis unit, The logical expression tree acquisition unit is used to acquire RDF / SPARQL business rules and convert RDF triples or SPARQL query conditions into a logical expression tree; The execution instruction analysis unit obtains a GPU executable instruction based on the current time key frame in combination with the state attribute extraction result of the current time key frame; Visual special effects signal analysis module, which includes an interpolation position acquisition unit and a special effects signal output unit. The interpolation position acquisition unit is used to calculate the dynamic interpolation position corresponding to the current time key frame state attribute in the WebGPU rendering pipeline; The special effect signal output unit performs business rule determination based on the GPU executable instructions of the current time key frame, and outputs a visual special effect signal when the business rule is triggered; The timing slot key frame update module is used to generate a differential update package according to the rule trigger signal, and return the differential update package to the timing data layer to update the timing slot key frame.

[0025] like Figure 2 As shown, this embodiment provides a digital twin multidimensional data visualization method based on the OGC standard, and the method includes: S1. Extend the time slots in the batch attribute table of OGC 3D Tiles to store the key frame states of objects within a time window of preset length, and build a dynamic attribute stream in the time-enhanced 3D Tiles data layer; The key frame state of the object stored in S1 within a time window of a preset length includes a timestamp sequence, a position key frame sequence, and an attribute key frame sequence corresponding to the key frame in the extended time slot; The number of elements in the timestamp sequence, the position key frame sequence, and the attribute key frame sequence is the same, and each element corresponds to a key frame; the elements in the attribute key frame sequence are the service attribute vectors of the corresponding key frame, and the service attribute vector is a matrix composed of attribute values ​​of multiple different service attribute types, and the number of service attribute types is preset; In this embodiment, if there are four preset business attribute types, and the attribute values ​​corresponding to the four business attribute types are recorded as w1, w2, w3 and w4 respectively, the corresponding business attribute vector is ; The attribute keyframe sequence in the keyframe state of the stored object within a preset time window is used as a dynamic attribute stream in a timing-enhanced 3D Tiles data layer.

[0026] S2. Based on the dynamic attribute flow in the timing-enhanced 3D Tiles data layer, linear interpolation is performed on the key frame state at the current time in the GPU shader to extract the state attributes of the key frame at the current time; The calculation formula involved in extracting the state attributes of the current time key frame in S2 is as follows:

[0027] Among them, BD represents the state attribute of the key frame at the current time; ξ represents the time progress coefficient corresponding to the current time; TD represents the current time; T i Indicates the timestamp in the timestamp sequence that is earlier than the current time and has the smallest time interval with the current time; T i+1 Indicates the timestamp in the timestamp sequence that is later than the current time and has the smallest time interval with the current time; B i Indicates that the corresponding timestamp in the attribute keyframe sequence is T i Business attribute vector of B i+1 Indicates that the corresponding timestamp in the attribute keyframe sequence is T i+1 Business attribute vector.

[0028] S3. Obtain RDF / SPARQL business rules, convert RDF triples or SPARQL query conditions into a logical expression tree, and extract the results based on the state attributes of the current time key frame to obtain GPU executable instructions based on the current time key frame; Said S3 includes: S31, parsing the input RDF triple or SPARQL query condition into a logical expression tree; S32. Partially evaluate the logical expression tree based on the state attributes of the current time key frame; S33, compile the partially evaluated logical expression tree into a WGSL code snippet executable by the GPU shader; In the process of partial evaluation of the logical expression tree by S32, when the tree node is an attribute type, the attribute of the corresponding tree node is replaced with a preset constant value corresponding to the corresponding attribute type; when all child nodes of the tree node are constant values, the value of the node is calculated and replaced with a constant node; the logical expression tree after partial evaluation is an expression tree that is minimized and includes the attribute type of the tree node and the various attribute types involved in the state attributes of the previous time key frame; if the entire expression tree is a constant after partial evaluation, a WGSL code fragment that returns the constant value is generated; each tree node of the logical expression tree includes 0 or more child nodes of the corresponding tree node, and each child node is a tree node.

[0029] In this embodiment, the types of tree nodes of the logical expression tree include leaf nodes and non-leaf nodes. Leaf nodes correspond to operation trees, which correspond to attribute types or attribute values ​​corresponding to corresponding attribute types; non-leaf nodes correspond to operators, which correspond to greater than, less than, equal to, and operation, or operation, not operation, etc. S4. In the WebGPU rendering pipeline, the dynamic interpolation position corresponding to the state attribute of the current time keyframe is calculated, the business rule determination is performed based on the GPU executable instructions of the current time keyframe, and a visual special effect signal is output when the business rule is triggered; The calculation formula involved in calculating the dynamic interpolation position corresponding to the current time key frame state attribute in S4 is as follows:

[0030] Among them, PD represents the dynamic interpolation position corresponding to BD; B i Indicates that the corresponding timestamp in the position keyframe sequence is T i The key frame state position of B i+1 Indicates that the corresponding timestamp in the position keyframe sequence is T i+1 The key frame state position; The visual special effect signal output when the rule is triggered includes the target object of the special effect trigger, the business attribute vector and the timestamp.

[0031] The data flow synchronization mechanism of this part in this embodiment is: the CPU writes timing data and rule parameters to the GPU, the GPU calculates the dynamic interpolation position corresponding to the interpolation attribute in the vertex shader for the rendered frame, and passes it to the fragment shader, the fragment shader obtains the dynamic attributes in the current fragment, and calls the GPU executable instructions based on the current time key frame to perform business rule judgment, and decides whether to trigger special effects based on the truth or falseness of the judgment result.

[0032] S5. Generate a differential update package according to the rule trigger signal, and return the differential update package to the time series data layer to update the time series slot key frame.

[0033] The differential update package in S5 includes the visual special effect signal output when the rule is triggered, the interval between the timestamp in the visual special effect signal and the timestamp corresponding to any element in the corresponding timestamp sequence in the extended timing slot, and the vector difference between the business attribute vector in the visual special effect signal and the business attribute vector corresponding to any element in the corresponding attribute key frame sequence in the extended timing slot; Based on the obtained inserted update package, the update demand evaluation coefficient of the current time key frame is calculated. The calculation formula involved is as follows:

[0034] Among them, PX1 represents the update demand evaluation coefficient of the current time key frame; BC i Indicates BD and B i The modulus length corresponding to the vector difference between them; BC i+1 Indicates BD and B i+1 The modulus length corresponding to the vector difference between them; Compare PX with the first preset evaluation coefficient Y1 respectively, When PX1<Y1, calculate B i The previous key frame of the corresponding key frame and B i+1 Attribute mutation coefficient BS between corresponding key frames （i-1，i+1） , further BS （i-1，i+1） Compared with the preset mutation coefficient, If BS （i-1，i+1） If it is greater than or equal to the preset mutation coefficient, the current time key frame is inserted into B i With B i+1 Between the corresponding key frames, the updated time slot key frame is obtained; if BS （i-1，i+1） If it is less than the preset mutation coefficient, the current time key frame will be overwritten by B i The corresponding key frame obtains the updated timing slot key frame; When Y1≤PX1, insert the current time key frame into B i With B i+1 Between the corresponding key frames, the updated time slot key frames are obtained; The calculation formula for calculating the attribute mutation coefficient between any two key frames is as follows:

[0035] Among them, BS represents the attribute mutation coefficient between the corresponding two key frames; SPQ represents the quotient of the average value of the absolute value of the difference between the attribute value of each business attribute type corresponding to the business attribute vector of the previous key frame in the corresponding two key frames and the attribute value of the same business attribute type in the business attribute vector of the current key frame, divided by the difference between the timestamp of the corresponding key frame and the current time; SPH represents the quotient of the average value of the absolute value of the difference between the attribute value of each business attribute type corresponding to the business attribute vector of the latter key frame in the corresponding two key frames and the attribute value of the same business attribute type in the business attribute vector of the current key frame, divided by the difference between the timestamp of the corresponding key frame and the current time; min{} represents the minimum value function; max{} represents the maximum value function.

[0036] It should be noted that, in this document, relational terms such as first and second, etc., are used only to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any actual relationship or order between these entities or operations. Moreover, the terms "comprises," "comprising," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that includes a list of elements includes not only those elements but also other elements not explicitly listed, or elements inherent to such process, method, article, or apparatus.

[0037] Finally, it should be noted that the above descriptions are merely preferred embodiments of the present invention and are not intended to limit the present invention. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art will be able to modify the technical solutions described in the aforementioned embodiments or substitute equivalents for some of the technical features. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of the present invention shall be included within the scope of protection of the present invention.

Claims

1. A digital twin multidimensional data visualization method based on the OGC standard, characterized by: The method comprises: S1. Extend the time slots in the batch attribute table of OGC 3D Tiles to store the key frame states of objects within a time window of preset length, and build a dynamic attribute stream in the time-enhanced 3D Tiles data layer; S2. Based on the dynamic attribute flow in the timing-enhanced 3D Tiles data layer, linear interpolation is performed on the key frame state at the current time in the GPU shader to extract the state attributes of the key frame at the current time; S3. Obtain RDF / SPARQL business rules, convert RDF triples or SPARQL query conditions into a logical expression tree, and extract the results based on the state attributes of the current time key frame to obtain GPU executable instructions based on the current time key frame; S4. In the WebGPU rendering pipeline, the dynamic interpolation position corresponding to the state attribute of the current time keyframe is calculated, the business rule determination is performed based on the GPU executable instructions of the current time keyframe, and a visual special effect signal is output when the business rule is triggered; S5. Generate a differential update package according to the rule trigger signal, and return the differential update package to the time series data layer to update the time series slot key frame.

2. The digital twin multidimensional data visualization method based on the OGC standard according to claim 1 is characterized in that: The key frame state of the object stored in S1 within a time window of a preset length includes a timestamp sequence, a position key frame sequence, and an attribute key frame sequence corresponding to the key frame in the extended time slot; The number of elements in the timestamp sequence, the position key frame sequence, and the attribute key frame sequence is the same, and each element corresponds to a key frame; the elements in the attribute key frame sequence are the service attribute vectors of the corresponding key frame, and the service attribute vector is a matrix composed of attribute values ​​of multiple different service attribute types, and the number of service attribute types is preset; The attribute keyframe sequence in the keyframe state of the stored object within a preset time window is used as a dynamic attribute stream in a timing-enhanced 3D Tiles data layer.

3. The digital twin multidimensional data visualization method based on the OGC standard according to claim 2 is characterized in that: The calculation formula involved in extracting the state attributes of the current time key frame in S2 is as follows: Among them, BD represents the state attribute of the key frame at the current time; ξ represents the time progress coefficient corresponding to the current time; TD represents the current time; T i Indicates the timestamp in the timestamp sequence that is earlier than the current time and has the smallest time interval with the current time; T i+1 Indicates the timestamp in the timestamp sequence that is later than the current time and has the smallest time interval with the current time; B i Indicates that the corresponding timestamp in the attribute keyframe sequence is T i Business attribute vector of B i+1 Indicates that the corresponding timestamp in the attribute keyframe sequence is T i+1 Business attribute vector.

4. The digital twin multidimensional data visualization method based on the OGC standard according to claim 1 is characterized in that: Said S3 includes: S31, parsing the input RDF triple or SPARQL query condition into a logical expression tree; S32. Partially evaluate the logical expression tree based on the state attributes of the current time key frame; S33, compile the partially evaluated logical expression tree into a WGSL code snippet executable by the GPU shader; In the process of partial evaluation of the logical expression tree by S32, when the tree node is an attribute type, the attribute of the corresponding tree node is replaced with a preset constant value corresponding to the corresponding attribute type; when all child nodes of the tree node are constant values, the value of the node is calculated and replaced with a constant node; the logical expression tree after partial evaluation is an expression tree that is minimized and includes the attribute type of the tree node and the various attribute types involved in the state attributes of the previous time key frame; if the entire expression tree is a constant after partial evaluation, a WGSL code fragment that returns the constant value is generated; each tree node of the logical expression tree includes 0 or more child nodes of the corresponding tree node, and each child node is a tree node.

5. The digital twin multidimensional data visualization method based on the OGC standard according to claim 3 is characterized in that: The calculation formula involved in calculating the dynamic interpolation position corresponding to the current time key frame state attribute in S4 is as follows: Among them, PD represents the dynamic interpolation position corresponding to BD; B i Indicates that the corresponding timestamp in the position keyframe sequence is T i The key frame state position of B i+1 Indicates that the corresponding timestamp in the position keyframe sequence is T i+1 The key frame state position; The visual special effect signal output when the rule is triggered includes the target object of the special effect trigger, the business attribute vector and the timestamp.

6. The digital twin multidimensional data visualization method based on the OGC standard according to claim 5 is characterized in that: The differential update package in S5 includes the visual special effect signal output when the rule is triggered, the interval between the timestamp in the visual special effect signal and the timestamp corresponding to any element in the corresponding timestamp sequence in the extended timing slot, and the vector difference between the business attribute vector in the visual special effect signal and the business attribute vector corresponding to any element in the corresponding attribute key frame sequence in the extended timing slot; Based on the obtained inserted update package, the update demand evaluation coefficient of the current time key frame is calculated. The calculation formula involved is as follows: Among them, PX1 represents the update demand evaluation coefficient of the current time key frame; BC i Indicates BD and B i The modulus length corresponding to the vector difference between them; BC i+1 Indicates BD and B i+1 The modulus length corresponding to the vector difference between them; Compare PX with the first preset evaluation coefficient Y1 respectively, When PX1<Y1, calculate B i The previous key frame of the corresponding key frame and B i+1 Attribute mutation coefficient BS between corresponding key frames （i-1，i+1） , further BS （i-1，i+1） Compared with the preset mutation coefficient, If BS （i-1，i+1） If it is greater than or equal to the preset mutation coefficient, the current time key frame is inserted into B i With B i+1 Between the corresponding key frames, the updated time slot key frame is obtained; if BS （i-1，i+1） If it is less than the preset mutation coefficient, the current time key frame will be overwritten by B i The corresponding key frame obtains the updated timing slot key frame; When Y1≤PX1, insert the current time key frame into B i With B i+1 Between the corresponding key frames, the updated time slot key frames are obtained; The calculation formula for calculating the attribute mutation coefficient between any two key frames is as follows: Among them, BS represents the attribute mutation coefficient between the corresponding two key frames; SPQ represents the quotient of the average value of the absolute value of the difference between the attribute value of each business attribute type corresponding to the business attribute vector of the previous key frame in the corresponding two key frames and the attribute value of the same business attribute type in the business attribute vector of the current key frame, divided by the difference between the timestamp of the corresponding key frame and the current time; SPH represents the quotient of the average value of the absolute value of the difference between the attribute value of each business attribute type corresponding to the business attribute vector of the latter key frame in the corresponding two key frames and the attribute value of the same business attribute type in the business attribute vector of the current key frame, divided by the difference between the timestamp of the corresponding key frame and the current time; min{} represents the minimum value function; max{} represents the maximum value function.

7. A digital twin multidimensional data visualization system based on the OGC standard, applying the digital twin multidimensional data visualization method based on the OGC standard according to any one of claims 1 to 6, characterized in that: The system comprises: A dynamic attribute stream construction module is used to extend the time slots in the batch attribute table of OGC 3D Tiles, store the keyframe states of objects within a time window of preset length, and build a dynamic attribute stream in the time-enhanced 3D Tiles data layer; The state attribute extraction module, based on the dynamic attribute flow in the timing-enhanced 3D Tiles data layer, linearly interpolates the key frame state at the current time in the GPU shader to extract the state attributes of the key frame at the current time; The GPU execution acquisition module is used to obtain RDF / SPARQL business rules, convert RDF triples or SPARQL query conditions into logical expression trees, and extract results based on the state attributes of the current time key frame to obtain GPU executable instructions based on the current time key frame; The visual effects signal analysis module is used to calculate the dynamic interpolation position corresponding to the current time keyframe state attribute in the WebGPU rendering pipeline, perform business rule determination based on the GPU executable instructions of the current time keyframe, and output visual effects signals when the business rules are triggered; The timing slot key frame update module is used to generate a differential update package according to the rule trigger signal, and return the differential update package to the timing data layer to update the timing slot key frame.

8. The digital twin multidimensional data visualization system based on the OGC standard according to claim 7, characterized in that: The GPU execution acquisition module includes a logic expression tree acquisition unit and an execution instruction analysis unit. The logical expression tree acquisition unit is used to acquire RDF / SPARQL business rules and convert RDF triples or SPARQL query conditions into a logical expression tree; The execution instruction analysis unit obtains a GPU executable instruction based on the current time key frame in combination with the state attribute extraction result of the current time key frame.

9. The digital twin multidimensional data visualization system based on the OGC standard according to claim 7, characterized in that: The visual special effect signal analysis module includes an interpolation position acquisition unit and a special effect signal output unit. The interpolation position acquisition unit is used to calculate the dynamic interpolation position corresponding to the current time key frame state attribute in the WebGPU rendering pipeline; The special effect signal output unit performs business rule determination based on the GPU executable instructions of the current time key frame, and outputs a visual special effect signal when the business rule is triggered.

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