Parametric model visualization method and device, computer equipment and storage medium

Abstract

The invention discloses a parameterized model visualization method and device, computer equipment and a storage medium, relates to the technical field of vehicle engineering, and is used for solving the problem that the visualization state of a parameterized model of an automobile body structure cannot be dynamically adjusted in related technologies. The method comprises the following steps: in response to a received display rule of a target parameterized model, setting node visible attributes in a target scene graph corresponding to the target parameterized model based on the display rule to obtain a target visible node list; and calculating a world transformation matrix corresponding to the target visible node list, and rendering the target visible node list to the first interface based on the world transformation matrix.

Description

Technical Field

[0001] This invention relates to the field of vehicle engineering technology, and in particular to a parametric model visualization method, apparatus, computer equipment, and storage medium. Background Technology

[0002] In the design and optimization of automotive body structures, the construction and management of parametric models are crucial, especially in the conceptual design phase, where engineers need to quickly adjust model parameters and evaluate the performance of different structural schemes. Related technologies primarily use engineering software to create, simulate, and store parametric models for automotive body structures. However, this storage method employs a static storage model, which prevents dynamic adjustments to the visualization of the parametric model. Summary of the Invention

[0003] Based on this, a method, apparatus, computer device, and storage medium for visualizing parametric models are provided to solve the problem in related technologies that the visualization state of parametric models of automobile body structures cannot be dynamically adjusted.

[0004] In a first aspect, the present invention provides a method for visualizing a parametric model, the method comprising: In response to receiving the display rules of the target parameterized model, the visibility attributes of the nodes in the target scene graph corresponding to the target parameterized model are set based on the display rules to obtain a list of target visible nodes; Calculate the world transformation matrix corresponding to the target visible node list, and render the target visible node list to the first interface based on the world transformation matrix.

[0005] In one embodiment, the step of setting the node visibility attributes in the target scene graph corresponding to the target parameterized model based on the display rules to obtain a list of target visible nodes includes: The display rules are parsed to obtain the parameters to be displayed, and the target nodes corresponding to the parameters to be displayed in the target scene graph are determined. Set the visibility attribute of the target node to visible, and set the visibility attribute of all other nodes in the target scene graph except the target node to invisible, to obtain the updated target scene graph; Traverse the visibility attributes of all nodes in the updated target scene graph to obtain an initial list of visible nodes, and then perform boundary removal on the initial list of visible nodes to obtain the target list of visible nodes.

[0006] In one embodiment, before setting the node visibility attributes in the target scene graph corresponding to the target parameterized model based on the display rules, the method further includes: Analyze the target hierarchy structure of the target parameterization model; The target scene diagram is generated based on the target hierarchy structure.

[0007] In one embodiment, calculating the world transformation matrix corresponding to the target visible node list includes: Determine the first local transformation matrix of the target parent node in the target visible node list, and the second local transformation matrix of the target child node corresponding to the target parent node; Calculate the first world transformation matrix of the target parent node based on the first local transformation matrix; Based on the first world transformation matrix and the second local transformation matrix, calculate the second world transformation matrix of the target child node.

[0008] In one embodiment, the response prior to receiving the display rules for the target parameterized model further includes: In response to importing the target parameterized model, if an abnormal operation event of the target object is detected, the input data is marked to obtain the marked input data, wherein the marked content includes at least the target object, the abnormal operation time, and the abnormal operation event; The entered data is stored after the tag.

[0009] In one embodiment, the response after importing the target parameterized model further includes: In response to the completion of the import of the target parameterized model and the display of the target parameterized model on the first interface, if an input device event of the target parameterized model is detected, the input device event is parsed to obtain the target transformation parameters; A target transformation matrix is ​​generated based on the target transformation parameters, and the model matrix of the target parameterized model is updated based on the target transformation matrix. Based on the updated model matrix, the target parameterized model is re-rendered to the first interface.

[0010] In one embodiment, the response after importing the target parameterized model further includes: In response to the completion of the import of the target parameterized model and the receipt of a chart comparison request between the target parameterized model and the comparison parameterized model, the obtained target parameterized model and comparison parameterized model are aligned and arranged to obtain the updated target parameterized model and the updated comparison parameterized model. Each parameter is assigned a corresponding visual identifier, and based on the visual identifier corresponding to each parameter, the updated target parameterized model and the updated comparison parameterized model are rendered to the second interface in a preset format.

[0011] Secondly, the present invention provides a parametric model visualization device, the device comprising: The setting module is used to respond to the received display rules of the target parameterized model, set the node visibility attributes in the target scene graph corresponding to the target parameterized model based on the display rules, and obtain a list of target visible nodes; The visualization module is used to calculate the world transformation matrix corresponding to the target visible node list, and render the target visible node list to the first interface based on the world transformation matrix.

[0012] Thirdly, the present invention provides a computer device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the parametric model visualization method of the first aspect described above.

[0013] Fourthly, the present invention provides a computer-readable storage medium having a computer program stored thereon, wherein the computer program, when executed by a processor, implements the parametric model visualization method of the first aspect described above.

[0014] The aforementioned parametric model visualization method, device, computer equipment, and storage medium dynamically set the visibility attributes of the corresponding parametric nodes in the target scene graph according to the display rules of the target parametric model, generate a list of target visible nodes, calculate its world transformation matrix, and render the list of target visible nodes based on the world transformation matrix, thereby realizing the dynamic adjustment of the visualization state of the parametric model during the vehicle body structure design process. Attached Figure Description

[0015] Figure 1 This is a diagram illustrating the application environment of a parametric model visualization method in one embodiment. Figure 2 This is a flowchart illustrating a parametric model visualization method in one embodiment; Figure 3 This is a schematic diagram of a data interface in one embodiment; Figure 4 This is a structural block diagram of a parametric model visualization device in one embodiment; Figure 5 This is an internal structural diagram of a computer device in one embodiment. Detailed Implementation

[0016] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to the accompanying drawings. The specific operational methods in the method embodiments can also be applied to the device embodiments or system embodiments. It should be noted that in the description of this invention, "multiple" is understood as "at least two". "And / or" describes the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A existing alone, A and B existing together, or B existing alone. A connected to B can represent: A and B directly connected, or A and B connected through C. Furthermore, in the description of this invention, terms such as "first" and "second" are used only for descriptive purposes and should not be construed as indicating or implying relative importance or order.

[0017] To facilitate understanding by those skilled in the art, the technical terms involved in this invention will first be explained.

[0018] (1) A quaternion is a hypercomplex number used to describe rotations in three-dimensional space. A quaternion q consists of two parts: a real part (scalar) s and an imaginary part (vector) v. Its standard form is: q = s + v, where v = v x i+v y j+v z k, s, v x v y v z All are real numbers, i, j, and k are imaginary units, and i 2 =j 2 =k 2 =ijk=-1. Geometrically, when rotation is represented by quaternions: i rotation represents the rotation from the positive X-axis to the positive Y-axis in the plane where the X-axis and Y-axis intersect; j rotation represents the rotation from the positive Z-axis to the positive X-axis in the plane where the Z-axis and X-axis intersect; and k rotation represents the rotation from the positive Y-axis to the positive Z-axis in the plane where the Y-axis and Z-axis intersect.

[0019] (2) Spherical linear interpolation is a linear interpolation operation of quaternions, mainly used to smooth the difference between two quaternions that represent rotation.

[0020] (3) ECharts is a data visualization chart library based on the JavaScript programming language, which provides intuitive, vivid, interactive and customizable data visualization charts.

[0021] In this invention, the acquisition, transmission, storage, and use of data all comply with the requirements of relevant national laws and regulations.

[0022] Before introducing the parametric model visualization method provided by this invention, the technical background of this invention will be described in detail below for ease of understanding.

[0023] In the design and optimization of automotive body structures, the construction and management of parametric models are crucial, especially in the conceptual design phase, where engineers need to quickly adjust model parameters and evaluate the performance of different structural schemes. Related technologies primarily utilize engineering software to create, simulate, and store parametric models for automotive body structures. This storage method employs a static storage model, saving parametric model data in a predefined, fixed format (such as tables, database fields, or file structures). For example, parameters like the thickness and length of body beams are stored in a traditional database row-column format. However, the column names and numbers are pre-set and not deeply integrated with the parametric modeling logic, resulting in an inability to dynamically adjust the visualization state of the parametric model.

[0024] In view of this, the present invention provides a parametric model visualization method, apparatus, computer equipment and storage medium to solve the problem in the related art that the parametric model of automobile body structure is stored in a static storage mode, which is not deeply bound to the parametric modeling logic, resulting in the inability to dynamically adjust the visualization state of the parametric model.

[0025] The following is a brief introduction to the application scenarios to which the technical solution of the present invention is applicable. It should be noted that the application scenarios described below are for illustrative purposes only and are not intended to limit the scope of the invention. In specific implementations, the technical solution provided by the present invention can be flexibly applied according to actual needs.

[0026] The parametric model visualization method provided by this invention can be applied to, for example... Figure 1 The application environment shown mainly includes terminal 102 and server 104. Terminal 102 and server 104 can exchange information through a communication network, which can use wireless communication or wired communication methods.

[0027] For example, terminal 102 can access the network and communicate with server 104 through cellular mobile communication technology, which may include 5th generation mobile network (5G) technology.

[0028] For example, terminal 102 can access the network and communicate with server 104 via short-range wireless communication, which may include Wireless Fidelity (Wi-Fi) technology.

[0029] This invention does not impose any limitation on the number of the aforementioned devices, such as Figure 1As shown, only terminal 102 and server 104 are described as examples. The following is a brief introduction to each of the above devices and their respective functions.

[0030] Terminal 102 is a device that can provide voice and / or data connectivity to a target object, including: handheld terminal devices with wireless connectivity, vehicle-mounted terminal devices, etc.

[0031] For example, terminal 102 includes, but is not limited to: mobile phones, tablets, laptops, handheld computers, mobile internet devices (MID), wearable devices, virtual reality (VR) devices, augmented reality (AR) devices, wireless terminal devices in industrial control, wireless terminal devices in autonomous driving, wireless terminal devices in smart grids, wireless terminal devices in transportation safety, wireless terminal devices in smart cities, or wireless terminal devices in smart homes, etc.

[0032] Furthermore, a parametric model management platform can be installed on terminal 102. This management platform can be software (e.g., an application, a browser, etc.), or a webpage, a mini-program, etc. In this invention, the target object can log in to the parametric model management platform on terminal 102 and interact with the server 104 to query data, and then receive corresponding results back to the target object.

[0033] For example, server 104 can host backend microservices corresponding to the aforementioned management platform and store various parameterized models. Server 104 can be implemented using a standalone server or a server cluster consisting of multiple servers.

[0034] The target object initiates a Hypertext Transfer Protocol (HTTP) request, such as a add request or view request, through the parameterized model management platform on terminal 102, and sends it directly to the backend Application Programming Interface (API) gateway via network services. The backend API gateway routes the request to the appropriate backend microservice based on the Uniform Resource Locator (URL) and HTTP method. Upon receiving the HTTP request, the backend microservice parses and processes the request, constructs an HTTP response, and returns it to terminal 102. Upon receiving the HTTP response, terminal 102 parses and processes it, and then displays it to the parameterized model management platform.

[0035] Optionally, when the backend microservice receives an HTTP request, it can also perform permission verification on the HTTP request, including but not limited to: verifying the target object's role (e.g., only allowing administrators or data analysts to access sensitive parameterized models, depending on the situation, not limited here), and the permission list (e.g., querying whether the target object is in the authorization list of the parameterized model, depending on the situation, not limited here).

[0036] Optionally, when the backend microservice receives an HTTP request, it can also perform parameter validation on the HTTP request, including but not limited to: validating the HTTP request, such as whether the time range is reasonable, whether the parameterized model exists, etc., depending on the situation, and is not limited here.

[0037] The technical solution provided by the present invention will be described in detail below with reference to the accompanying drawings and specific embodiments.

[0038] Figure 2 This is a flowchart illustrating a parametric model visualization method in one embodiment. This process can be executed by a parametric model visualization device, which can be implemented in software, hardware, or a combination of both. Figure 2 As shown, the process includes the following steps: S201, in response to receiving the display rules of the target parameterized model, set the node visibility attributes in the target scene graph corresponding to the target parameterized model based on the display rules, and obtain the target visible node list; S202, calculate the world transformation matrix corresponding to the target visible node list, and render the target visible node list to the first interface based on the world transformation matrix.

[0039] In this invention, the target object can access the main management interface through the parameterized model management platform on the login terminal 102. The main management interface includes a data directory and a pre-selected model directory.

[0040] In response to a click on the target object's data catalog, a data interface is displayed. The target object can import a parametric model into the data interface. The parametric model includes at least one of body-in-white data, module data, and cross-sectional data.

[0041] Body-in-white refers to the bare body frame structure without paint, interior and exterior trim, and electronic systems. It is the core carrier of body rigidity and safety. Body-in-white data includes at least the whole vehicle parameters (such as wheelbase, length, width, height, torsional stiffness, etc.), geometric topological relationships (such as the layout and connection relationships of beams, columns, joints, etc.), primary dimensional parameters (such as sheet thickness, beam cross-sectional dimensions, hole coordinates, etc.), and material properties (material type, such as steel, aluminum alloy, etc., key physical characteristic parameters of the material under stress or deformation, such as rigidity parameters, strength parameters, etc.).

[0042] Module data refers to the subsystems and functional modules of the vehicle body, including at least module classification (such as door modules, front compartment modules, battery pack housings, etc.), module boundary conditions (such as physical boundaries: the envelope size of the module, performance boundaries: load requirements, sealing standards, etc.), interface definitions between modules (such as mechanical interfaces: mounting point coordinates, fastener specifications, etc., electrical or fluid interfaces: wiring harness connector models, cooling pipe diameters, etc., process constraints: assembly sequence, welding or adhesive bonding process requirements, etc.), and local features of the module (such as the position of door hinges, parameterized definitions of battery pack mounting points, etc.).

[0043] Cross-sectional data refers to the cross-sectional shape of structural components such as body beams and columns, including at least the cross-sectional type (such as closed box shape, C-shape, multi-cavity, etc.), secondary dimensional parameters (such as wall thickness, flange width, stiffener layout, etc.) and performance parameters (such as cross-sectional moment of inertia, bending stiffness, and other derived attributes).

[0044] Figure 3 This is a schematic diagram of a data interface in one embodiment, including imported parameterized model identifiers (parameterized model a, parameterized model b, parameterized model c), options to view chart comparisons, options to view model comparisons, and an add option. The target object can initiate a add request by clicking the add option, or initiate a view request by clicking the parameterized model identifier, the options to view chart comparisons, or the options to view model comparisons.

[0045] Based on the above method, in response to the target object clicking the target parameterized model identifier and the view model comparison option on the data interface, the first interface is displayed, wherein the first interface is used to display the target parameterized model.

[0046] In the above-mentioned parametric model visualization method, the visibility attributes of the corresponding parametric nodes in the target scene graph are dynamically set according to the display rules of the target parametric model. After generating the target visible node list, its world transformation matrix is ​​calculated, and the target visible node list is rendered based on the world transformation matrix, thereby realizing the dynamic adjustment of the visualization state of the parametric model during the vehicle body structure design process.

[0047] In one embodiment, exemplarily described, before setting the node visibility attributes in the target scene graph corresponding to the target parameterized model based on the display rules in S201, the method further includes: The target hierarchy structure of the target parameterization model is analyzed, and the target scene graph corresponding to the target parameterization model is generated based on the target hierarchy structure.

[0048] For example, if the target parameterized model is body-in-white data, the target hierarchical structure can include: the first level is the whole vehicle parameters, which are used to define global constraints and affect all substructures; the second level is the geometric topology, which are used to describe the body structure layout; the third level is the first dimension parameters; and the fourth level is the material properties, which depend on the situation and are not limited here.

[0049] If the target parameterized model is module data, the target hierarchical structure can include: the first level is module classification; the second level is module boundary conditions and inter-module interface definitions; the third level is module local features, which depends on the situation and is not limited here.

[0050] If the target parameterized model is cross-sectional data, the target hierarchical structure may include: the first level is the cross-sectional type; the second level is the second dimension parameter; and the third level is the performance parameter, depending on the situation, which is not limited here.

[0051] A tree structure is generated based on the target hierarchical structure (that is, each parameter is converted into a tree node, while preserving the hierarchical relationship), and the tree structure is mapped to the target scene graph, that is, each tree node is mapped to a scene graph node, while preserving the parent-child relationship as scene graph edges.

[0052] Using the above method, the target hierarchical structure of the target parameterized model is analyzed, the relationship between each level is clarified, and the target scene graph is automatically generated based on the target hierarchical structure, thus realizing the presentation of complex parameter relationships in a visual topological form.

[0053] In one embodiment, exemplarily described, in S201, the visibility attributes of nodes in the target scene graph corresponding to the target parameterized model are set based on the display rules to obtain a list of target visible nodes, including but not limited to: The display rules are parsed to obtain the parameters to be displayed, and the target nodes corresponding to the parameters to be displayed in the target scene graph are determined.

[0054] Specifically, if the node corresponding to the parameter to be displayed in the target scene graph is a child node, then the target node includes the child node and the parent node corresponding to the child node; if the node corresponding to the parameter to be displayed in the target scene graph is a parent node, then the target node is the parent node.

[0055] Set the visibility attribute of the target node to visible, and set the visibility attribute of all other nodes in the target scene graph except the target node to invisible, to obtain the updated target scene graph.

[0056] Optionally, the target scene graph may also contain some nodes whose visibility attribute is set to visible by default. Therefore, when setting the visibility attribute of nodes in the target scene graph based on display rules, the visibility attribute of the target node can be set to visible, and the visibility attributes of other nodes in the target scene graph, excluding the target node and nodes whose visibility attribute is set to visible by default, can be set to invisible, resulting in an updated target scene graph.

[0057] Then, the visibility attributes of all nodes in the updated target scene graph are traversed to obtain an initial list of visible nodes. Boundary culling is then performed on this initial list to obtain the target list of visible nodes. The initial list of visible nodes includes parent-child relationships. Boundary culling is also known as view frustum culling. The view frustum is the camera's view space, including the near clipping plane (the view plane closest to the camera), the far clipping plane (the view plane farthest from the camera), and the four sides that make up the frustum.

[0058] For example, the visibility attribute of all nodes in the updated target scene graph is traversed, skipping nodes with an invisible visibility attribute during traversal and automatically interrupting the animation and physics calculations of nodes with an invisible visibility attribute, to obtain an initial list of visible nodes. Then, by culling nodes that are completely outside the view frustum from the initial list of visible nodes, the target list of visible nodes is obtained. If a parent node in the initial list of visible nodes is not culled by boundary, its corresponding child nodes are also culled by default; if a parent node in the initial list of visible nodes is culled by boundary, its corresponding child nodes are also culled by default.

[0059] By using the above method, the visibility attributes of nodes in the target scene graph are dynamically set based on the display rules, only the target nodes are activated, while irrelevant nodes are hidden. Then, the list of visible nodes is further optimized by boundary culling, which achieves efficient focusing of the target parametric model, reduces the load on the graphics processor, and significantly improves the interactive performance and rendering efficiency of the parametric model.

[0060] In one embodiment, exemplarily illustrated, the world transformation matrix corresponding to the target visible node list is calculated in S202, including but not limited to: Since nodes in the target visible node list may have parent-child hierarchical relationships, and the transformation of child nodes depends on the transformation of parent nodes, the calculation process needs to be recursive or processed in hierarchical order.

[0061] For example, the first local transformation matrix of the target parent node in the target visible node list and the second local transformation matrix of the target child node corresponding to the target parent node are determined.

[0062] For example, the transformation of each node typically includes translation (T): the position offset of the node; rotation (R): the rotation angle of the node (Euler angles or quaternions); and scaling (S): the scaling ratio of the node along each axis. These transformations can be combined into a local transformation matrix M. local =T×R×S.

[0063] The first world transformation matrix of the target parent node is calculated based on the first local transformation matrix, and the second world transformation matrix of the target child node is calculated based on the first world transformation matrix and the second local transformation matrix.

[0064] For example, the world transformation matrix M world The calculation method can be: M world =M parent_world ×M local , of which M local M is the local transformation matrix. parent_world M is the world transformation matrix of the parent node of the compute node. If the compute node is the root node, then M... parent_world Let be the identity matrix. When calculating the first-world transformation matrix, the calculation node is the target parent node; when calculating the second-world transformation matrix, the calculation node is the target child node.

[0065] Optionally, when the visibility attribute of any node is reset to visible, the third-world transformation matrix of that node is incrementally updated to achieve efficient and accurate local matrix updates.

[0066] The above method first calculates the first-world transformation matrix of the target parent node, and then calculates the second-world transformation matrix of the corresponding target child node based on the first-world transformation matrix. This allows for precise control of the position, rotation, and scaling of the node in global space, ensuring the correct transmission of the spatial transformation relationship between parent and child nodes in complex hierarchical structures and providing accurate coordinate references for subsequent rendering.

[0067] In one embodiment, exemplarily illustrated, S201 further includes, prior to receiving the display rules for the target parameterized model: When the target object is in, for example Figure 3 When you click the "Add" option in the data interface shown, the "Add" interface will be displayed, which shows the input boxes for each parameter to be entered.

[0068] For example, when importing body-in-white data, the input parameters include, but are not limited to: name, category (classified according to purpose, size, and styling, such as sedan, SUV, sports car, etc.), power type (referring to the vehicle's energy and power system form, such as fuel, pure electric, range-extended, etc.), body type (referring to the material combination of the main body structure, such as steel, aluminum, steel-aluminum hybrid, etc.), and overall vehicle parameters. The new interface also includes a reset option (the target object can clear all data in the input boxes by clicking the reset option) and a submit option (the target object can generate a new request by clicking the submit option).

[0069] In response to the import of the target parameterized model, if an abnormal operation event of the target object is detected, the input data (i.e., the partially input target parameterized model) is marked, resulting in the marked input data. Abnormal operation events include, but are not limited to: the target object exiting the new user interface without clicking the submit option, a detected network connection interruption, or no operation event of the target object on the new user interface being detected within a preset time period (e.g., 30 minutes, the specific time depending on the situation, not limited here). The marking content must include at least the target object, the time of the abnormal operation, and the abnormal operation event.

[0070] Then, the marked input data is stored (e.g., the marked input data is stored in a preset database or preset cache space). Additionally, for submission options that fail due to network interruption, an automatic submission attempt can be made after the network is restored; if no operation event of the target object is detected in the new user interface within a preset time, a prompt message can be displayed in the new user interface, prompting the target object to continue the operation or confirm and abandon.

[0071] In addition, the marked input data can be displayed in the pre-selected model directory of the main management interface in a preset manner. For example, the marked input data can be displayed in the pre-selected model directory in the form of a table for easy viewing and processing at any time.

[0072] Using the above method, abnormal operation events during the import process of the target parameterized model are monitored in real time. The input data before the abnormal operation event is automatically marked and stored to avoid data loss and to achieve traceability of abnormal operation events.

[0073] In one embodiment, exemplarily illustrated, in response to importing the target parameterized model, the method further includes: Upon completion of the import of the target parametric model and its display on the first screen, if an input device event for the target parametric model is detected, the input device event is parsed to obtain the target transformation parameters. Then, a target transformation matrix is ​​generated based on the target transformation parameters, and the model matrix of the target parametric model (i.e., the world transformation matrix of the target parametric model) is updated based on the target transformation matrix. Finally, based on the updated model matrix, the target parametric model is re-rendered to the first screen.

[0074] For example, if a displacement command for the target parameterized model is detected, the displacement command is parsed to obtain the target displacement vector, and a target translation transformation matrix is ​​generated based on the displacement vector. Then, the model matrix of the target parameterized model is updated based on the translation transformation matrix, resulting in an updated model matrix = model matrix × target translation transformation matrix. Finally, based on the updated model matrix, the target parameterized model is re-rendered to the first interface.

[0075] The rendering method could be as follows: Instantiated rendering is used to reduce GPU calls. The GPU stores the model matrices of all parametric models. The updated model matrices are bound to the matrix partition corresponding to the target parametric model, avoiding full data transfer and significantly reducing bandwidth usage. The updated model matrices are then read through the vertex shader, and the target parametric model is re-rendered to the first interface through matrix cascading calculations.

[0076] If a rotation command for the target parametric model is detected, the rotation command is parsed to obtain the target rotation parameters (such as the rotation angle and rotation axis), and a target rotation matrix is ​​generated based on these parameters. Then, the model matrix of the target parametric model is updated based on the target rotation matrix, resulting in an updated model matrix = model matrix × target rotation matrix. Finally, based on the updated model matrix, the target parametric model is re-rendered to the first interface (the rendering method is the same as described above and will not be repeated here).

[0077] The rotation matrix can be generated by: calculating the target quaternion based on the rotation parameters, obtaining the initial quaternion based on the model matrix of the target parameterized model, and calculating the duration based on the initial and target quaternions. Then, the target quaternion, initial quaternion, and duration are passed from the main thread to the browser's Web Worker thread. The Web Worker thread performs spherical linear interpolation using a pre-compiled quaternion operation module based on the received initial, target, and duration quaternions, converts the interpolation result into a rotation matrix, and returns it to the main thread. This ensures smooth rotation animation and avoids blocking the main thread.

[0078] Optionally, the Web Worker thread can also write the rotation matrix to shared memory, and the main thread can obtain it directly from the shared memory without copying the data, achieving zero transmission overhead.

[0079] By using the above method, input device events are parsed in real time and a target transformation matrix is ​​generated. The model matrix is ​​then updated based on the target transformation matrix, and the model is redrawn, ensuring seamless synchronization between target object operations and model rendering. This ensures smooth interface performance while accurately reflecting the interaction intent.

[0080] In one embodiment, exemplarily illustrated, in response to importing the target parameterized model, the method further includes: In response to the completion of the import of the target parameterized model and the receipt of a chart comparison request between the target parameterized model and the comparison parameterized model (the target object initiates the chart comparison request by clicking the target parameterized model icon, the comparison parameterized model icon, and the view chart comparison option in the data interface), the obtained target parameterized model and comparison parameterized model are aligned and arranged to obtain the updated target parameterized model and the updated comparison parameterized model.

[0081] For example, the target parameterized model and the comparison parameterized model are body-in-white data. The target parameterized model includes first weight m1, first length l1, first width w1, first height h1, first wheelbase a1, first front overhang b1, and first rear overhang c1. The comparison parameterized model includes second weight m2, second width w2, second wheelbase a2, second length l2, second height h2, second front overhang b2, and second rear overhang c2. Then, the target parameterized model and the comparison parameterized model are aligned and arranged to obtain the updated target parameterized model including m1, l1, w1, h1, a1, b1, and c1, and the updated comparison parameterized model including m2, l2, w2, h2, a2, b2, and c2.

[0082] Assign a corresponding visual identifier (such as a color identifier, depending on the situation, not limited here) to each parameter, and based on the visual identifier corresponding to each parameter, render the updated target parameterized model and the updated comparison parameterized model to the second interface in a preset format.

[0083] For example, the updated target parameterized model includes m1, l1, and w1, and the updated contrast parameterized model includes m2, l2=0, and w2. Then, a first color identifier (red) is assigned to m1 and m2, a second color identifier (green) is assigned to l1 and l2, and a third color identifier (purple) is assigned to w1 and w2. This can be customized or a preset assignment scheme can be used, depending on the specific situation; no limitation is made here.

[0084] Based on the color identifier corresponding to each parameter, ECharts is used to render the updated target parameterized model into a first visualization chart and the updated comparison parameterized model into a second visualization chart. The first and second visualization charts are then displayed on the second interface. The visualization charts can be bar charts or radar charts, depending on the situation, and are not limited here.

[0085] Optionally, the parameter difference between the updated target parameterized model and the updated comparison parameterized model can be calculated, and during rendering, parameters with a parameter difference greater than a preset threshold (the specific value depends on the situation and is not limited here) can be highlighted, such as by making them bold or blinking, so that the target object can quickly focus on the difference.

[0086] Optionally, input events (such as hover, click, etc.) can be bound to the first visualization chart and the second visualization chart. In response to the detection of an input event of any parameter in the first visualization chart or any parameter in the second visualization chart, the specific value of any parameter can be dynamically displayed, thereby achieving fast data acquisition and reducing interface jumps.

[0087] Using the above method, the parameter arrangement of the target parameterized model and the comparison parameterized model is automatically aligned, and a visual label is assigned to each parameter. Finally, the updated target parameterized model and the updated comparison parameterized model are rendered in a preset format, enabling the target object to intuitively identify parameter differences and improving the efficiency and accuracy of model comparison analysis.

[0088] It should be understood that, although Figure 2 The steps in the flowchart are shown sequentially as indicated by the arrows, but these steps are not necessarily executed in the order indicated by the arrows. Unless otherwise specified herein, there is no strict order in which these steps are executed, and they can be performed in other orders. Figure 2 At least some of the steps in the process may include multiple sub-steps or multiple stages. These sub-steps or stages are not necessarily completed at the same time, but can be executed at different times. The execution order of these sub-steps or stages is not necessarily sequential, but can be executed in turn or alternately with other steps or at least some of the sub-steps or stages of other steps.

[0089] In one embodiment, such as Figure 4 As shown, a parametric model visualization device is provided, including: a setting module 401 and a visualization module 402, wherein: Setting module 401 is used to respond to the received display rules of the target parameterized model, set the node visibility attributes in the target scene graph corresponding to the target parameterized model based on the display rules, and obtain a list of target visible nodes; The visualization module 402 is used to calculate the world transformation matrix corresponding to the target visible node list, and render the target visible node list to the first interface based on the world transformation matrix.

[0090] In one embodiment, the setting module 401 is used for: Parse the display rules to obtain the parameters to be displayed, and determine the target nodes corresponding to the parameters to be displayed in the target scene graph; Set the visibility attribute of the target node to visible, and set the visibility attribute of all other nodes in the target scene graph except the target node to invisible, to obtain the updated target scene graph; Traverse the visibility attributes of all nodes in the updated target scene graph to obtain an initial list of visible nodes, and then perform boundary culling on the initial list of visible nodes to obtain the target list of visible nodes.

[0091] In one embodiment, the setting module 401 is further configured to: Analyze the target hierarchy structure of the target parameterization model; Generate a target scene diagram based on the target hierarchy structure.

[0092] In one embodiment, the visualization module 402 is used for: Determine the first local transformation matrix of the target parent node in the target visible node list, and the second local transformation matrix of the target child node corresponding to the target parent node; Calculate the first world transformation matrix of the target parent node based on the first local transformation matrix; Calculate the second world transformation matrix of the target child node based on the first world transformation matrix and the second local transformation matrix.

[0093] In one embodiment, the setting module 401 is further configured to: In response to the import of the target parameterized model, if an abnormal operation event of the target object is detected, the input data is marked to obtain the marked input data. The marked content includes at least the target object, the abnormal operation time and the abnormal operation event. Store the entered data after the tag.

[0094] In one embodiment, the visualization module 402 is further configured to: In response to the completion of the import of the target parameterized model, the target parameterized model is displayed on the first interface. If an input device event of the target parameterized model is detected, the input device event is parsed to obtain the target transformation parameters. Generate a target transformation matrix based on the target transformation parameters, and update the model matrix of the target parameterized model based on the target transformation matrix; Based on the updated model matrix, the target parameterized model is re-rendered to the first interface.

[0095] In one embodiment, the visualization module 402 is further configured to: In response to the completion of the import of the target parameterized model and the receipt of a chart comparison request between the target parameterized model and the comparison parameterized model, the parameters of the obtained target parameterized model and comparison parameterized model are aligned and arranged to obtain the updated target parameterized model and the updated comparison parameterized model. Assign a corresponding visual identifier to each parameter, and based on the visual identifier corresponding to each parameter, render the updated target parameterized model and the updated comparison parameterized model to the second interface in a preset format.

[0096] Specific limitations regarding the parametric model visualization device can be found in the limitations of the parametric model visualization method described above, and will not be repeated here. Each module in the aforementioned parametric model visualization device can be implemented entirely or partially through software, hardware, or a combination thereof. These modules can be embedded in or independent of the processor in a computer device, or stored in the memory of a computer device as software, so that the processor can call and execute the corresponding operations of each module.

[0097] In one embodiment, a computer device is provided, which may be a server, and its internal structure diagram may be as follows: Figure 5 As shown, the computer device includes a processor, memory, network interface, and database connected via a system bus. The processor provides computing and control capabilities. The memory includes non-volatile storage media and internal memory. The non-volatile storage media stores the operating system, computer programs, and database. The internal memory provides an environment for the operation of the operating system and computer programs in the non-volatile storage media. The database stores parametric model visualization data. The network interface communicates with external terminals via a network connection. When the computer program is executed by the processor, it implements a parametric model visualization method. The display screen can be an LCD screen or an e-ink display screen. The input device can be a touch layer covering the display screen, buttons, a trackball, or a touchpad on the computer device casing, or an external keyboard, touchpad, or mouse.

[0098] Those skilled in the art will understand that Figure 5The structure shown is merely a block diagram of a portion of the structure related to the present invention and does not constitute a limitation on the computer device to which the present invention is applied. A specific computer device may include more or fewer components than those shown in the figure, or combine certain components, or have different component arrangements.

[0099] In one embodiment, a computer device is provided, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to perform the following steps: In response to receiving the display rules of the target parameterized model, the visibility attributes of the nodes in the target scene graph corresponding to the target parameterized model are set based on the display rules to obtain a list of visible nodes of the target. Calculate the world transformation matrix corresponding to the list of visible nodes of the target, and render the list of visible nodes of the target to the first screen based on the world transformation matrix.

[0100] In one embodiment, the processor, when executing a computer program, also performs the following steps: Parse the display rules to obtain the parameters to be displayed, and determine the target nodes corresponding to the parameters to be displayed in the target scene graph; Set the visibility attribute of the target node to visible, and set the visibility attribute of all other nodes in the target scene graph except the target node to invisible, to obtain the updated target scene graph; Traverse the visibility attributes of all nodes in the updated target scene graph to obtain an initial list of visible nodes, and then perform boundary culling on the initial list of visible nodes to obtain the target list of visible nodes.

[0101] In one embodiment, the processor, when executing a computer program, also performs the following steps: Analyze the target hierarchy structure of the target parameterization model; Generate a target scene diagram based on the target hierarchy structure.

[0102] In one embodiment, the processor, when executing a computer program, also performs the following steps: Determine the first local transformation matrix of the target parent node in the target visible node list, and the second local transformation matrix of the target child node corresponding to the target parent node; Calculate the first world transformation matrix of the target parent node based on the first local transformation matrix; Calculate the second world transformation matrix of the target child node based on the first world transformation matrix and the second local transformation matrix.

[0103] In one embodiment, the processor, when executing a computer program, also performs the following steps: In response to the import of the target parameterized model, if an abnormal operation event of the target object is detected, the input data is marked to obtain the marked input data. The marked content includes at least the target object, the abnormal operation time and the abnormal operation event. Store the entered data after the tag.

[0104] In one embodiment, the processor, when executing a computer program, also performs the following steps: In response to the completion of the import of the target parameterized model, the target parameterized model is displayed on the first interface. If an input device event of the target parameterized model is detected, the input device event is parsed to obtain the target transformation parameters. Generate a target transformation matrix based on the target transformation parameters, and update the model matrix of the target parameterized model based on the target transformation matrix; Based on the updated model matrix, the target parameterized model is re-rendered to the first interface.

[0105] In one embodiment, the processor, when executing a computer program, also performs the following steps: In response to the completion of the import of the target parameterized model and the receipt of a chart comparison request between the target parameterized model and the comparison parameterized model, the parameters of the obtained target parameterized model and comparison parameterized model are aligned and arranged to obtain the updated target parameterized model and the updated comparison parameterized model. Assign a corresponding visual identifier to each parameter, and based on the visual identifier corresponding to each parameter, render the updated target parameterized model and the updated comparison parameterized model to the second interface in a preset format.

[0106] In one embodiment, a computer-readable storage medium is provided having a computer program stored thereon, the computer program performing the following steps when executed by a processor: In response to receiving the display rules of the target parameterized model, the visibility attributes of the nodes in the target scene graph corresponding to the target parameterized model are set based on the display rules to obtain a list of visible nodes of the target. Calculate the world transformation matrix corresponding to the list of visible nodes of the target, and render the list of visible nodes of the target to the first screen based on the world transformation matrix.

[0107] In one embodiment, when the computer program is executed by a processor, it also performs the following steps: Parse the display rules to obtain the parameters to be displayed, and determine the target nodes corresponding to the parameters to be displayed in the target scene graph; Set the visibility attribute of the target node to visible, and set the visibility attribute of all other nodes in the target scene graph except the target node to invisible, to obtain the updated target scene graph; Traverse the visibility attributes of all nodes in the updated target scene graph to obtain an initial list of visible nodes, and then perform boundary culling on the initial list of visible nodes to obtain the target list of visible nodes.

[0108] In one embodiment, when the computer program is executed by a processor, it also performs the following steps: Analyze the target hierarchy structure of the target parameterization model; Generate a target scene diagram based on the target hierarchy structure.

[0109] In one embodiment, when the computer program is executed by a processor, it also performs the following steps: Determine the first local transformation matrix of the target parent node in the target visible node list, and the second local transformation matrix of the target child node corresponding to the target parent node; Calculate the first world transformation matrix of the target parent node based on the first local transformation matrix; Calculate the second world transformation matrix of the target child node based on the first world transformation matrix and the second local transformation matrix.

[0110] In one embodiment, when the computer program is executed by a processor, it also performs the following steps: In response to the import of the target parameterized model, if an abnormal operation event of the target object is detected, the input data is marked to obtain the marked input data. The marked content includes at least the target object, the abnormal operation time and the abnormal operation event. Store the entered data after the tag.

[0111] In one embodiment, when the computer program is executed by a processor, it also performs the following steps: In response to the completion of the import of the target parameterized model, the target parameterized model is displayed on the first interface. If an input device event of the target parameterized model is detected, the input device event is parsed to obtain the target transformation parameters. Generate a target transformation matrix based on the target transformation parameters, and update the model matrix of the target parameterized model based on the target transformation matrix; Based on the updated model matrix, the target parameterized model is re-rendered to the first interface.

[0112] In one embodiment, when the computer program is executed by a processor, it also performs the following steps: In response to the completion of the import of the target parameterized model and the receipt of a chart comparison request between the target parameterized model and the comparison parameterized model, the parameters of the obtained target parameterized model and comparison parameterized model are aligned and arranged to obtain the updated target parameterized model and the updated comparison parameterized model. Assign a corresponding visual identifier to each parameter, and based on the visual identifier corresponding to each parameter, render the updated target parameterized model and the updated comparison parameterized model to the second interface in a preset format.

[0113] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer-readable storage medium. When executed, the computer program can include the processes of the embodiments of the above methods. Any references to memory, storage, databases, or other media used in the embodiments provided by this invention can include non-volatile and / or volatile memory. Non-volatile memory can include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM), or flash memory. Volatile memory can include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in various forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), dual data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link DRAM (SLDRAM), Rambus direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM), etc.

[0114] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0115] The embodiments described above are merely illustrative of several implementations of the present invention, and while the descriptions are relatively specific and detailed, they should not be construed as limiting the scope of the invention patent. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of the present invention, and these all fall within the protection scope of the present invention. Therefore, the protection scope of this invention patent should be determined by the appended claims.

Claims

1. A method for visualizing parametric models, characterized in that, The method includes: In response to receiving the display rules of the target parameterized model, the visibility attributes of the nodes in the target scene graph corresponding to the target parameterized model are set based on the display rules to obtain a list of target visible nodes; Calculate the world transformation matrix corresponding to the target visible node list, and render the target visible node list to the first interface based on the world transformation matrix.

2. The method according to claim 1, characterized in that, The step of setting the node visibility attributes in the target scene graph corresponding to the target parameterized model based on the display rules yields a list of target visible nodes, including: The display rules are parsed to obtain the parameters to be displayed, and the target nodes corresponding to the parameters to be displayed in the target scene graph are determined. Set the visibility attribute of the target node to visible, and set the visibility attribute of all other nodes in the target scene graph except the target node to invisible, to obtain the updated target scene graph; Traverse the visibility attributes of all nodes in the updated target scene graph to obtain an initial list of visible nodes, and then perform boundary removal on the initial list of visible nodes to obtain the target list of visible nodes.

3. The method according to claim 1, characterized in that, Before setting the node visibility attributes in the target scene graph corresponding to the target parameterized model based on the display rules, the method further includes: Analyze the target hierarchy structure of the target parameterization model; The target scene diagram is generated based on the target hierarchy structure.

4. The method according to claim 1, characterized in that, The calculation of the world transformation matrix corresponding to the target visible node list includes: Determine the first local transformation matrix of the target parent node in the target visible node list, and the second local transformation matrix of the target child node corresponding to the target parent node; Calculate the first world transformation matrix of the target parent node based on the first local transformation matrix; Based on the first world transformation matrix and the second local transformation matrix, calculate the second world transformation matrix of the target child node.

5. The method according to claim 1, characterized in that, The response prior to receiving the display rules for the target parameterized model also includes: In response to importing the target parameterized model, if an abnormal operation event of the target object is detected, the input data is marked to obtain the marked input data, wherein the marked content includes at least the target object, the abnormal operation time, and the abnormal operation event; The entered data is stored after the tag.

6. The method according to claim 5, characterized in that, The response after importing the target parameterized model also includes: In response to the completion of the import of the target parameterized model and the display of the target parameterized model on the first interface, if an input device event of the target parameterized model is detected, the input device event is parsed to obtain the target transformation parameters; A target transformation matrix is ​​generated based on the target transformation parameters, and the model matrix of the target parameterized model is updated based on the target transformation matrix. Based on the updated model matrix, the target parameterized model is re-rendered to the first interface.

7. The method according to claim 5, characterized in that, The response after importing the target parameterized model also includes: In response to the completion of the import of the target parameterized model and the receipt of a chart comparison request between the target parameterized model and the comparison parameterized model, the obtained target parameterized model and comparison parameterized model are aligned and arranged to obtain the updated target parameterized model and the updated comparison parameterized model. Each parameter is assigned a corresponding visual identifier, and based on the visual identifier corresponding to each parameter, the updated target parameterized model and the updated comparison parameterized model are rendered to the second interface in a preset format.

8. A parametric model visualization device, characterized in that, The device includes: The setting module is used to respond to the received display rules of the target parameterized model, set the node visibility attributes in the target scene graph corresponding to the target parameterized model based on the display rules, and obtain a list of target visible nodes; The visualization module is used to calculate the world transformation matrix corresponding to the target visible node list, and render the target visible node list to the first interface based on the world transformation matrix.

9. A computer device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the computer program, it implements the method of any one of claims 1 to 7.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by a processor, it implements the method of any one of claims 1 to 7.

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