BIM (Building Information Modeling)-based automatic circulation method and system for curtain wall metal keel component model data

Abstract

The invention belongs to the technical field of building information model (BIM) and digital manufacturing, and particularly discloses a BIM-based curtain wall metal keel component model data automatic circulation method and system.The method comprises the steps that firstly, a parameterized model of a curtain wall metal keel is established based on BIM software, and geometric dimensions, material attributes and connection node key information are defined; then geometric data and non-geometric data of the curtain wall metal keel are extracted from the parameterized model of the curtain wall metal keel, and the extracted data are converted into a JSON structured format; and finally, based on the kinematic model of the mechanical arm, the extracted geometric data and non-geometric data of the curtain wall metal keel are combined to plan and generate a cutter cutting path for curtain wall metal keel machining and production. According to the scheme provided by the invention, the seamless data link between the BIM model of the curtain wall metal keel and the numerical control machining equipment is established, so that intelligent, high-precision and batch production of the curtain wall metal keel component is realized.

Description

Technical Field

[0001] This invention belongs to the field of Building Information Modeling (BIM) and digital manufacturing technology, specifically involving a BIM-based method and system for the entire process of data transfer from design modeling and robotic arm path planning to automated processing of curtain wall metal keel components, applicable to the intelligent production of aluminum alloy curtain wall components. Background Technology

[0002] Aluminum alloy curtain wall components are high-precision building parts. To ensure processing accuracy, the traditional processing of curtain wall metal keel usually relies on manual conversion of design drawings into processing instructions. This traditional process, which involves manually converting two-dimensional design drawings into processing instructions, suffers from long conversion cycles (especially significant for large projects) and numerous manual checks. The manual conversion process introduces an average 3-5% dimensional error rate, severely impacting component assembly accuracy. The drawing conversion stage reduces overall production efficiency by approximately 30-40%.

[0003] The lack of a standardized data interface between BIM design software (such as Revit / Rhino) and CAM manufacturing software (such as PowerMill) necessitates at least 3-4 intermediate format conversions (such as IGES / STEP conversion), resulting in a 15-20% loss of geometric information. Manufacturing parameters also need to be redefined within the CAM system, increasing repetitive workload by more than 30%.

[0004] Multi-axis robotic arm path planning relies on technician experience for debugging, with single-piece debugging time reaching 2-4 hours. Path planning consistency is poor, batch processing size fluctuations exceed ±1.5mm, and collision risk detection completeness is less than 60% when processing complex curved surfaces.

[0005] Design changes cannot be automatically transmitted to the manufacturing end, version updates are delayed by 8-12 hours, manufacturing feedback data cannot be linked to the BIM model in real time, quality traceability completeness is less than 40%, and data isolation in each link forms "information silos", resulting in a loss of more than 25% in overall production efficiency.

[0006] In addition, the processing procedures and construction process are complex because the metal keel components of the curtain wall involve the processing of different types of holes and different cutting operations on the cutting end faces.

[0007] For the reasons mentioned above, the average processing cycle of curtain wall metal keel components is 45-60% longer than the theoretical value, and the accuracy qualification rate can only be maintained at 82-88%.

[0008] For example, Chinese invention patent CN103774859B discloses a method of converting BIM models into code that can be recognized by CNC program execution devices through a CNC program generation system, and controlling the operation of robotic arms, electronic nozzles, and cement mortar pumps to achieve automated construction processes. However, this solution cannot achieve collaborative operation, which may lead to interference and conflicts between equipment during application; at the same time, it lacks a safety protection mechanism, posing safety hazards.

[0009] Meanwhile, since the automated processing of curtain wall metal keel components involves the identification and handling of different types of holes, as well as the processing of cut end faces, and the above solution does not have specific implementation methods, the above solution is not suitable for the automated processing of curtain wall metal keel components. Summary of the Invention

[0010] To address the problems of existing curtain wall metal keel processing solutions in terms of processing cycle and accuracy pass rate, the present invention aims to provide a BIM-based automated data transfer solution for curtain wall metal keel component models, which are building components with high precision requirements, such as aluminum alloy curtain wall components. This solution establishes a seamless data link between the BIM model and CNC machining equipment (such as a multi-axis robotic arm), enabling intelligent, high-precision, and mass production of aluminum alloy curtain wall components. It can effectively solve problems such as low efficiency of manual conversion, data gap between BIM and CAM, and reliance on experience for robotic arm path planning in traditional processing methods.

[0011] To achieve the above objectives, this invention provides a BIM-based method for automated data transfer of curtain wall metal keel component model data, the method comprising:

[0012] (1) Establish a parametric model of the curtain wall metal keel based on BIM software, and define the geometric dimensions, material properties, and key information of the connection nodes;

[0013] (2) Based on the OpenCASCADE open source package, a feature information extraction algorithm for curtain wall metal keel is constructed to extract the geometric and non-geometric data of curtain wall metal keel from the parametric model of curtain wall metal keel, and convert the extracted data into JSON structured format. During the conversion process, the geometric topology data and processing attributes of the model are preserved.

[0014] (3) Based on the kinematic model of the robotic arm, the extracted geometric and non-geometric data of the curtain wall metal keel are combined to plan and generate the tool cutting path for the processing and production of the curtain wall metal keel.

[0015] Furthermore, in step (1), the method also performs collision detection on the established parametric model of the curtain wall metal keel.

[0016] Furthermore, the method selects a hole surface with precise dimensions in the parametric model of the curtain wall metal keel established in step (1), and adjusts its material color to the corresponding color.

[0017] Furthermore, in step (2), the method removes redundant component values ​​from the parametric model of the curtain wall metal keel constructed in step (1).

[0018] Furthermore, in step (2), the curved surface shape of the hole is divided into three forms: round hole, waist hole, and oblique hole, and the cutting end face is divided into two forms: tangent and oblique cut.

[0019] Furthermore, in step (2), the method extracts information, identifies the surface type by matching the color rendered on the hole surface with the corresponding surface contour, and uses the least squares method to fit the surface boundary to determine the actual position of the surface; then, based on the identified hole surface type, it extracts the geometric data of the hole surface; finally, for the determined hole surface, it further identifies the cutting end face.

[0020] Furthermore, in step (2), the method also checks whether there are missing values ​​in the parametric model of the curtain wall metal keel, such as the size or material properties of the components, and fills in the missing values.

[0021] Furthermore, the step (3) of planning and generating the tool cutting path includes the following sub-steps:

[0022] (31) Initial toolpath generation: The initial toolpath of the robotic arm is generated based on the geometric data of the parametric model of the curtain wall metal keel and the kinematic model of the robotic arm.

[0023] (32) Minimize idle travel time optimization: Minimize the idle travel time T by optimizing the objective function:

[0024]

[0025] Among them, L i : The straight-line distance of the (i)th segment of the path; Δθ i Changes in joint angles between adjacent path segments;

[0026] (33) Applying constraints: Applying collision-free constraints, curvature adaptive constraints, and machining accuracy constraints:

[0027] (331) No collision constraints,

[0028] The distance d between the tool and the workpiece / environment must be greater than the safety threshold d. safe :

[0029] d(Tool,Obstacle)≥d safe ;

[0030] Distances are calculated in real time using geometric data from the BIM model;

[0031] (332) Curvature adaptive constraint

[0032] The tool orientation φ needs to be dynamically adjusted according to the surface curvature κ:

[0033]

[0034] R: Tool radius;

[0035] (333) Machining accuracy constraints.

[0036] The allowable dimensional error ∈ must satisfy:

[0037] ∈≤∈ max (usually ∈ max =0.1mm)

[0038] Dynamic parameter adjustment: Optimization of cutting parameters based on material properties

[0039]

[0040] K: Material cutting coefficient; M: Tool mass.

[0041] To achieve the above objectives, the present invention provides an automated data transfer system for curtain wall metal keel component models based on BIM, the system comprising:

[0042] The component modeling module can create a parametric model of the curtain wall metal keel based on BIM software and define geometric dimensions, material properties, and key information of connection nodes.

[0043] The data conversion and processing module is configured to interact with the component modeling module. It constructs a feature information extraction algorithm for curtain wall metal keel based on the OpenCASCADE open source package, extracts the geometric and non-geometric data of the curtain wall metal keel from the parametric model of the curtain wall metal keel, converts the extracted data into JSON structured format, and retains the geometric topology data and processing attributes of the model during the conversion process.

[0044] The path planning module interacts with the data conversion and processing module, and can plan and generate tool cutting paths for the processing and production of curtain wall metal keels based on the kinematic model of the robotic arm and the extracted geometric and non-geometric data of the curtain wall metal keel.

[0045] Furthermore, when the data conversion and processing module extracts the feature information of the curtain wall metal keel, it identifies the surface type by matching the color rendered on the hole surface with the corresponding surface contour, and uses the least squares method to fit the surface boundary to determine the actual position of the surface; then, based on the identified hole surface type, it extracts the geometric data of the hole surface; finally, for the determined hole surface, it further identifies the cutting end face.

[0046] Furthermore, the path planning module includes an initial toolpath generation submodule, a path optimization submodule, and a constraint condition submodule.

[0047] The initial toolpath generation submodule is configured to generate the initial robotic arm toolpath based on the geometric data of the parametric model of the curtain wall metal keel and the kinematic model of the robotic arm.

[0048] The path optimization submodule is configured to interact with the initial toolpath generation submodule, enabling it to optimize the generated initial robotic arm toolpath by minimizing idle travel time.

[0049] The constraint condition submodule interacts with the path optimization submodule, enabling the embedding of collision-free constraints, curvature adaptive constraints, and machining accuracy constraints in the optimized robotic arm tool path.

[0050] The solution provided by this invention achieves intelligent, high-precision, and mass production of curtain wall metal keel components by establishing a seamless data link between the BIM model of the curtain wall metal keel and CNC machining equipment (such as a multi-axis robotic arm).

[0051] The solution provided by this invention can reduce the number of tool changes, optimize the feed path, and improve machining efficiency in practical applications. At the same time, in actual machining tests, the surface roughness Ra≤1.6μm is ensured through curvature adaptive constraints and machining accuracy constraints. Attached Figure Description

[0052] The present invention will be further described below with reference to the accompanying drawings and specific embodiments.

[0053] Figure 1 This is a flowchart illustrating the automated data transfer and processing of curtain wall metal keel component model data in this invention;

[0054] Figure 2 This is an example diagram of the hole surface color differentiation model in Rhino software in this invention;

[0055] Figure 3 This is an example diagram illustrating the OpenCASCADE file parsing process and the extraction of geometric data for hole surfaces in this invention;

[0056] Figure 4This is an example diagram of the core optimization comparison of adaptive path planning in this invention;

[0057] Figure 5 This is a schematic diagram illustrating the conversion from the Rhino model to PowerMill path planning in an example of the present invention. Detailed Implementation

[0058] To make the technical means, creative features, objectives and effects of this invention easier to understand, the invention will be further described below with reference to specific illustrations.

[0059] This invention, after thorough research into the structural characteristics of curtain wall metal keel and the problems encountered in its processing, presents a BIM-based automated data transfer and processing solution for curtain wall metal keel component models. This innovative solution utilizes BIM software such as Rhino to establish a parametric model of the curtain wall metal keel, defining key information such as geometric dimensions, material properties, and connection nodes, ensuring that design data can be directly used for processing. Based on this, an efficient data conversion and processing module is constructed to achieve efficient data conversion between the curtain wall metal keel BIM model (Rhino) and CAM software (PowerMill), avoiding the accuracy loss caused by traditional manual import / export. Furthermore, based on the kinematic model of the robotic arm involved in the processing of curtain wall metal keel components, the toolpath is automatically optimized in conjunction with the component curvature characteristics to reduce idle travel and prevent collisions. Finally, cutting parameters are automatically matched according to material properties (such as aluminum alloy 6061) to generate high-precision, low-vibration G-code, improving processing quality and efficiency.

[0060] Combination Figure 1 As shown, the BIM-based automated data transfer and processing scheme for curtain wall metal keel component models provided by this invention is mainly achieved through the following steps:

[0061] (1) Establish a parametric model of the curtain wall metal keel based on BIM software, and define the geometric dimensions, material properties, and key information of the connection nodes;

[0062] (2) Based on the OpenCASCADE open source package, a feature information extraction algorithm for curtain wall metal keel is constructed to extract the geometric and non-geometric data of curtain wall metal keel from the parametric model of curtain wall metal keel, and convert the extracted data into JSON structured format. During the conversion process, the geometric topology data and processing attributes of the model are preserved.

[0063] (3) Based on the kinematic model of the robotic arm, the extracted geometric and non-geometric data of the curtain wall metal keel are combined to plan and generate the tool cutting path for the processing and production of the curtain wall metal keel.

[0064] (4) Generate the corresponding final machining code for the generated tool cutting path.

[0065] The following section explains the specific implementation of each step in the above scheme and the components that may be involved.

[0066] In step (1) of this invention, when establishing the parametric model of the curtain wall metal keel, a parametric modeling method is adopted. Preferably, a 1:1 parametric model of the curtain wall metal keel to be processed is created in Rhino software, and on this basis, the geometric shape, size, material (aluminum alloy 6061), opening of the connection node, cutting port and other attributes are specifically defined to achieve a model accuracy of Lod400.

[0067] Based on this, collision detection is performed on the established parametric model of the curtain wall metal keel to detect collision interference between the model and the building structure, ensuring that the design model does not conflict with the actual situation.

[0068] As a further step, in this step, for the established parametric model of the curtain wall metal keel, the surface of the hole with precise dimensions is selected in the model, and its material color is adjusted to the specified color that meets the requirements of the specification. The BIM model containing complete processing information (such as NURBS surface data) is output to provide a basis for subsequent processing. Based on this, the PowerMill software can directly identify and extract the shape, size and dimensions of the hole by color.

[0069] See Figure 2 The image shown is an example of a color differentiation model for hole surfaces in Rhino software.

[0070] Based on the illustration, in the parametric model of the curtain wall metal keel established in this example, the oblique holes and the oblique surfaces that serve as clamps for avoidance are rendered in black, the groove surfaces and notch surfaces on the front are colored in red, the groove surfaces and notch surfaces on the front side are colored in green, and the groove surfaces and notch surfaces on the rear side are colored in blue.

[0071] In step (2) of this invention, when performing data conversion processing, the redundant values ​​of the components are removed first for the constructed parametric model of the curtain wall metal keel. That is, decorative or non-structural components that are not related to processing are removed, and redundant information in the BIM model, such as duplicate components and useless annotations, are removed, thereby reducing the amount of data processing calculation and improving calculation efficiency.

[0072] Specifically, by introducing the Grasshope plugin into the RHino software for visual operation, the function of directly exporting the required components from the RHino software can be realized, thereby removing redundant values ​​from the components.

[0073] After removing redundant values ​​from the parametric model of the curtain wall metal keel, data format conversion is then performed.

[0074] Further, see Figure 3 To ensure the reliability and accuracy of data format conversion, this paper constructs a feature information extraction algorithm for metal keel based on the OpenCASCADE open source package, and extracts the geometric and non-geometric data of the curtain wall metal keel from the parametric model of the curtain wall metal keel, thereby ensuring lossless data transfer.

[0075] The geometric data extracted here for the curtain wall metal keel includes component length, position, hole surface shape and size, and hole location; the non-geometric data extracted here includes tolerances, material properties (surface color), and thickness.

[0076] As a further explanation, the present invention further defines the curved surface shape of the hole into three forms: round hole, waist hole, and oblique hole, and the cutting end face is divided into two forms: normal cutting and oblique cutting; at the same time, the present invention provides corresponding information extraction methods for these three different curved surface types to ensure the efficiency and accuracy of information extraction.

[0077] Based on this, in order to effectively and accurately extract information about different holes, the present invention first automatically identifies the surface by color representation and / or geometric features. Then, the least squares method is used to fit the surface contour for different surface types to ensure accuracy, thereby reducing manual intervention, enabling multi-section processing, and adapting to different design requirements.

[0078] Specifically, the following method is used to extract information about different types of hole surfaces:

[0079] (1) Based on the color rendered for the hole surface during modeling, the surface type is identified in conjunction with the corresponding surface contour, and the surface boundary is fitted using the least squares method to determine the actual position of the surface, such as the center point position, radius, major axis, minor axis, axis direction, etc.

[0080] (2) Based on the hole surface type identified in step (1), extract the geometric data of the hole surface:

[0081] The geometric data extracted for the circular hole includes the center coordinates (x, y, z), radius r, and hole depth;

[0082] The geometric data extracted for the waist hole includes the center point coordinates (x, y, z), the major axis a and the minor axis b, and the depth of the hole;

[0083] The geometric data extracted for the oblique hole includes the center point coordinates (x, y, z), the axis direction vector (dx, dy, dz), the radius r or the major axis a and minor axis b, and the depth of the hole.

[0084] (3) For the identified hole surface, further identify the cutting end face:

[0085] For the curved surface of a circular hole, based on the extracted geometric data, the distribution state between the end face and the hole axis is determined by calculating the angle between the end face normal vector and the hole axis, and this is used to identify the cutting end face: if the end face is perpendicular to the hole axis, the cutting end face is determined to be tangent; if the end face is at a certain angle to the hole axis, the cutting end face is determined to be oblique.

[0086] For the curved surface of the waist hole, based on the extracted geometric data, the distribution state between the end face and the waist hole axis is determined by calculating the angle between the end face normal vector and the waist hole axis, and the cutting end face is identified accordingly: if the end face is perpendicular to the waist hole axis, the cutting end face is determined to be tangent; if the end face is at a certain angle to the waist hole axis, the cutting end face is determined to be oblique.

[0087] For the inclined hole surface, based on the extracted geometric data, the distribution state between the end face and the inclined hole axis is determined by calculating the angle between the end face normal vector and the inclined hole axis, and the cutting end face is identified accordingly: if the end face is perpendicular to the inclined hole axis, the cutting end face is determined to be tangent; if the end face is at a certain angle to the inclined hole axis, the cutting end face is determined to be oblique.

[0088] Here, we will take a circular hole surface as an example to illustrate the implementation scheme of the present invention for extracting circular hole information.

[0089] In this invention, for cylindrical surface features, a fitting and intersection line calculation algorithm is constructed. Based on a multimodal optimized cylindrical surface feature extraction and intersection line calculation algorithm, a geometric algorithm (such as the least squares method) is used to fit the cylindrical surface and extract the center point, radius, and depth. Furthermore, if the cutting end face is tangent, the intersection line (circle) between the cutting surface and the cylindrical surface is calculated; if the cutting end face is oblique, the intersection line (ellipse) between the cutting surface and the cylindrical surface is calculated.

[0090] This approach employs geometric algorithms such as the least squares method to ensure high-precision fitting of the cylindrical surface, exhibiting strong robustness against noise and incomplete data. Geometric constraints are used to improve fitting accuracy, enabling the processing of large amounts of point cloud data. Furthermore, it can accurately calculate intersection lines (circular or elliptical) based on different cut end face shapes. Geometric transformations and matrix operations are utilized to enhance the efficiency of intersection line calculation.

[0091] Furthermore, for hole identification, the hole surface is identified based on color markings, and its geometric data—vertex coordinates, normal vector, and surface equation—is extracted. Based on this, a geometric algorithm is used to fit a cylindrical surface to the identified hole surface, extracting the center point position, radius, and depth.

[0092] The equation of the cylindrical surface is:

[0093] (χ-χ0) 2 +(y-y0) 2 =r 2 ;

[0094] Use the least squares method to fit the cylindrical surface and solve for the center point position and radius:

[0095]

[0096] Based on the z-coordinate range of the hole surface, extract the depth information:

[0097] z min =min(z) i ),z max =max(z) i ).

[0098] Where (x,y) are the coordinates of any point on the cylindrical surface, r is the radius of the cylindrical surface, N is the number of data points, (x0,y0) are the coordinates of the center point of the fitted cylindrical surface, and Z is the hole depth.

[0099] Furthermore, this step converts the extracted geometric and non-geometric data of the curtain wall metal keel into a JSON structured format. During the conversion process, geometric topological data such as bolt hole positions and tolerances, as well as manufacturing attributes, are preserved to ensure lossless data transfer.

[0100] Furthermore, during the data format conversion process, this step automatically verifies the integrity and consistency of the data to ensure that geometric information and processing parameters are accurately transmitted to subsequent path planning steps.

[0101] Furthermore, before data conversion, this step involves handling missing component values ​​in the constructed parametric model of the curtain wall metal keel. This means checking for missing values ​​such as component dimensions or material properties in the parametric model and supplementing them according to design specifications or default values. If missing values ​​cannot be supplemented, the corresponding components are marked. Marked components can be manually corrected, avoiding the accuracy loss caused by traditional manual conversion.

[0102] In step (3) of this invention, when planning and generating the tool cutting path for the processing and production of curtain wall metal keel, it is preferable to plan and generate the tool cutting path for the processing and production of curtain wall metal keel based on the kinematic model of the robotic arm combined with the curvature features of the extracted curtain wall metal keel BIM model components. The planned and generated tool cutting path for the processing and production of curtain wall metal keel can effectively reduce idle stroke and can also dynamically adjust the tool posture.

[0103] Specifically, the process of planning and generating the tool cutting path in this step is mainly accomplished through the cooperation of the following sub-steps:

[0104] (31) Initial tool path generation: The initial tool path of the robotic arm is generated based on the geometric data of the parametric model of the curtain wall metal keel and the kinematic model of the robotic arm.

[0105] This step further introduces multi-objective optimization, adaptive path adjustment, machine learning, and integrated geometric fitting techniques when generating the initial toolpath. This can significantly improve the efficiency and accuracy of path planning, thereby not only improving machining quality but also enhancing the robustness and adaptability of the entire solution.

[0106] (32) Optimize the initial robotic arm toolpath generated in step (31) by minimizing the idle travel time: Minimize the idle travel time T by optimizing the objective function, such as... Figure 4 As shown, this ensures both collision-free operation and machining accuracy:

[0107]

[0108] Among them, L i : The straight-line distance of the (i)th segment of the path; Δθ i Changes in joint angles between adjacent path segments.

[0109] (33) For the tool path optimization operation of the robotic arm in step (32), further constraints are introduced. Specifically, collision-free constraints, curvature adaptive constraints and machining accuracy constraints are introduced to further improve the accuracy of the tool path of the robotic arm.

[0110] Specifically, (331) there are no collision constraints.

[0111] The distance d between the tool and the workpiece / environment must be greater than the safety threshold d. safe :

[0112] d(Tool,Obstacle)≥d safe ;

[0113] Specifically, the distance is calculated in real time using the geometric data of the BIM model.

[0114] (332) Curvature adaptive constraint

[0115] The tool orientation φ needs to be dynamically adjusted according to the surface curvature κ:

[0116]

[0117] Where R: tool radius.

[0118] (333) Machining accuracy constraints.

[0119] Allowable dimensional errors satisfy:

[0120] ∈≤∈ max (usually ∈ max =0.1mm)

[0121] Dynamic parameter adjustment: Optimizing cutting parameters based on material properties.

[0122]

[0123] Where K is the material cutting coefficient and M is the tool mass.

[0124] Based on the application of the above three constraints, the final optimized robotic arm toolpath, when executed, optimizes the straight-line distance L of the path segments. i and joint angle change Δθ i It significantly reduces idle travel time, while dynamically adjusting the tool posture according to the curvature of the surface to improve machining accuracy and surface quality. It also detects the distance between the tool and the workpiece / environment in real time and adjusts the path to greatly reduce the risk of collision.

[0125] To further illustrate, after this step is completed, the present invention also performs simulation verification on the final robotic arm tool path, that is, performs simulation verification on the NC code of the optimized robotic arm tool path generated based on the above constraints to further check whether the path meets the machining requirements.

[0126] In step (4) of this invention, when generating the corresponding final machining code for the generated tool cutting path, the optimized path is converted into machining code that can be executed by the robotic arm, and the machining code file is output.

[0127] Furthermore, this step also utilizes an optimization engine to automatically match cutting parameters based on the material properties of the metal keel used in the curtain wall manufacturing (such as aluminum alloy 6061) to prevent overcutting, vibration, and other issues. At the same time, it optimizes the G-code generation logic to reduce tool changes, optimize feed paths, and improve processing efficiency.

[0128] Specifically, cutting parameter optimization is performed after the initial toolpath is generated, automatically matching appropriate cutting parameters to prevent overcutting and vibration. Meanwhile, G-code generation logic optimization is performed after the cutting parameter optimization, improving machining efficiency by optimizing the toolpath and tool-changing strategy. This optimization process ensures high efficiency, high quality, and stability in subsequent machining processes.

[0129] Furthermore, in this step, the optimized NC code is transmitted to the robotic arm control system for actual machining. Through curvature adaptive constraints and machining accuracy constraints, the surface roughness Ra is ensured to be ≤1.6μm.

[0130] The BIM-based automated data transfer and processing scheme for curtain wall metal keel component models provided in this invention can be implemented as a corresponding software program, forming a system for automated data transfer and processing of curtain wall metal keel component models. When running, this software program executes the aforementioned automated data transfer and processing method for curtain wall metal keel component models and stores the data in a suitable storage medium for retrieval and execution by a processor.

[0131] The resulting automated data transfer and processing system for curtain wall metal keel component models mainly includes: a component modeling module, a data conversion and processing module, a path planning module, and a code conversion module.

[0132] Among them, the component modeling module in this system can create a parametric model of the curtain wall metal keel based on BIM software, and define the geometric dimensions, material properties, and key information of the connection nodes;

[0133] The data conversion and processing module in this system is configured to interact with the component modeling module. Based on the OpenCASCADE open-source package, an algorithm for extracting feature information of curtain wall metal keel is built. The geometric and non-geometric data of the curtain wall metal keel are extracted from the parametric model of the curtain wall metal keel, and the extracted data is converted into JSON structured format. During the conversion process, the geometric topology data and processing attributes of the model are preserved.

[0134] The path planning module and data conversion and processing module in this system interact with each other, and can plan and generate tool cutting paths for the processing and production of curtain wall metal keel based on the kinematic model of the robotic arm and the extracted geometric and non-geometric data of the curtain wall metal keel.

[0135] The code conversion module in this system is configured to interact with the path planning module, and can generate the corresponding final machining code for the generated tool cutting path.

[0136] As further explanation, the component modeling module in this system can be implemented based on the scheme of the aforementioned step (1), that is, the specific scheme for implementing step (1) can be executed.

[0137] As further explanation, the data conversion and processing module in this system is specifically based on the OpenCASCADE open-source package. It constructs a feature information extraction algorithm for the metal keel and uses this algorithm to extract the geometric and non-geometric data of the curtain wall metal keel from the parametric model, thereby ensuring lossless data transfer. The extracted geometric data of the curtain wall metal keel includes component length, position, hole surface shape and size, and hole location; the extracted non-geometric data includes tolerances, material properties (surface color), and thickness.

[0138] As a further explanation, the present invention further defines the curved surface shape of the hole into three forms: round hole, waist hole, and oblique hole, and the cutting end face is divided into two forms: normal cutting and oblique cutting; at the same time, the present invention provides corresponding information extraction methods for these three different curved surface types to ensure the efficiency and accuracy of information extraction.

[0139] Based on this, in order to effectively and accurately extract information about different holes, this system first automatically identifies the surface by color representation and / or geometric features. Then, it uses the least squares method to fit the surface contour for different surface types to ensure accuracy, thereby reducing manual intervention, enabling multi-section processing, and adapting to different design requirements.

[0140] Specifically, this data conversion and processing module extracts information about different types of hole surfaces using the following method:

[0141] (1) Based on the color rendered for the hole surface during modeling, the surface type is identified in conjunction with the corresponding surface contour, and the surface boundary is fitted using the least squares method to determine the actual position of the surface, such as the center point position, radius, major axis, minor axis, axis direction, etc.

[0142] (2) Based on the hole surface type identified in step (1), extract the geometric data of the hole surface:

[0143] The geometric data extracted for the circular hole includes the center coordinates (x, y, z), radius r, and hole depth;

[0144] The geometric data extracted for the waist hole includes the center point coordinates (x, y, z), the major axis a and the minor axis b, and the depth of the hole;

[0145] The geometric data extracted for the oblique hole includes the center point coordinates (x, y, z), the axis direction vector (dx, dy, dz), the radius r or the major axis a and minor axis b, and the depth of the hole.

[0146] (3) For the identified hole surface, further identify the cutting end face:

[0147] For the curved surface of a circular hole, based on the extracted geometric data, the distribution state between the end face and the hole axis is determined by calculating the angle between the end face normal vector and the hole axis, and this is used to identify the cutting end face: if the end face is perpendicular to the hole axis, the cutting end face is determined to be tangent; if the end face is at a certain angle to the hole axis, the cutting end face is determined to be oblique.

[0148] For the curved surface of the waist hole, based on the extracted geometric data, the distribution state between the end face and the waist hole axis is determined by calculating the angle between the end face normal vector and the waist hole axis, and the cutting end face is identified accordingly: if the end face is perpendicular to the waist hole axis, the cutting end face is determined to be tangent; if the end face is at a certain angle to the waist hole axis, the cutting end face is determined to be oblique.

[0149] For the inclined hole surface, based on the extracted geometric data, the distribution state between the end face and the inclined hole axis is determined by calculating the angle between the end face normal vector and the inclined hole axis, and the cutting end face is identified accordingly: if the end face is perpendicular to the inclined hole axis, the cutting end face is determined to be tangent; if the end face is at a certain angle to the inclined hole axis, the cutting end face is determined to be oblique.

[0150] In practice, this data conversion and processing module can be implemented based on the solution in step (2) above, that is, the specific solution for implementing step (2) can be executed.

[0151] As further explanation, the path planning module in this system is mainly composed of an initial toolpath generation submodule, a path optimization submodule, and a constraint condition submodule working together.

[0152] The initial toolpath generation submodule is configured to generate the initial robotic arm toolpath based on the geometric data of the parametric model of the curtain wall metal keel and the kinematic model of the robotic arm.

[0153] The path optimization submodule is configured to interact with the initial toolpath generation submodule, enabling it to optimize the generated initial robotic arm toolpath by minimizing idle travel time.

[0154] The constraint condition submodule interacts with the path optimization submodule, enabling the embedding of collision-free constraints, curvature adaptive constraints, and machining accuracy constraints in the optimized robotic arm tool path.

[0155] The resulting path planning module is a concrete implementation of step (3).

[0156] The following section further illustrates the implementation process of the BIM-based automated data transfer and processing scheme for curtain wall metal keel components provided in this invention through specific application examples.

[0157] In the implementation of this solution, the first step is to build and deploy an automated data transfer and processing system for curtain wall metal keel component models based on the aforementioned solution.

[0158] Based on this, combined Figure 5 As shown, the system enables intelligent production of aluminum alloy curtain wall components, and the corresponding implementation process is as follows:

[0159] First, a parametric model of the irregular curtain wall keel is created in Rhino software, defining key parameters such as component material, geometry, curvature, hole position, and connection point.

[0160] The model material is set to 6061 aluminum alloy, with a machining tolerance of ±0.5mm. Its modular design allows for rapid adjustment and optimization to adapt to different architectural design needs.

[0161] Based on the data acquisition, the Rhino model is exported as a STEP file using a data conversion module, preserving all geometric and topological information. Specifically, an algorithm for extracting feature information of curtain wall metal keel is built based on the OpenCASCADE open-source package. This algorithm extracts the geometric and non-geometric data of the curtain wall metal keel from the Rhino model and converts the extracted data into a JSON structured format. During the conversion process, the geometric and topological data and processing attributes of the model are preserved.

[0162] See further Figure 3 When extracting the geometric data of the curtain wall metal keel, the STEP file is first read using STEPControl Reader, and any warnings or failures during the reading process are checked. Next, the hole information is extracted. Specifically, TopExp_Explorer is used to traverse all faces in the model, and BRepBndLib:Add is used to calculate the bounding box of each face. The size of the bounding box is used to determine whether it is a hole (assuming the hole size is small). The center point, size, and tolerance of the hole are then extracted. Finally, the results are output, showing detailed information for each hole, including the center point, size, and tolerance.

[0163] Next, the exported STEP file is automatically imported into PowerMill software as the basis for machining path planning. In PowerMill, the system automatically identifies the areas in the model that need to be built, drilled, milled, and cut, and generates the corresponding toolpaths.

[0164] In this example, PowerMill generates a complete flexible machining path based on the parameters of the KUKA KR300 robotic arm. Specifically, it includes:

[0165] (1) Rough machining: Use large-diameter tools to quickly remove excess material and shorten machining time.

[0166] (2) Finishing: Replace with a small diameter tool and perform fine milling on the keel surface to ensure smoothness and precision.

[0167] (3) Drilling: Based on the hole position information in the model, the robotic arm automatically positions and completes drilling, with the accuracy controlled within ±0.5mm.

[0168] (4) Cutting: Use a special cutting tool to precisely cut the keel to ensure that the edges are flat.

[0169] Next, for the generated toolpath, a verified optimization algorithm is selected to optimize the toolpath.

[0170] Next, the selected optimization algorithm is applied to optimize the generated toolpath, aiming to minimize machining time, reduce tool wear, and improve accuracy.

[0171] Next, after path planning is completed, PowerMill generates KRL code to drive the KUKA KR300 robotic arm for simulation verification. In the virtual environment, the robotic arm performs processing operations according to the planned path, and the system detects potential collision risks in real time. Through simulation verification, the robotic arm's motion trajectory is optimized to ensure efficient and safe processing.

[0172] Finally, the KRL code is uploaded to the KUKA KR300 robotic arm controller to initiate actual machining. During machining, the robotic arm automatically switches between different tools to complete operations such as building, drilling, milling, and cutting. Sensors and a monitoring system monitor the machining status in real time to ensure the accuracy and quality of each step. For example, if the drilling depth is insufficient or the cutting edges are uneven, the system automatically adjusts the parameters to ensure the machining results meet the requirements.

[0173] After machining, the keel is dimensionally inspected using a coordinate measuring machine (CMM) to ensure it meets the tolerance requirement of ±0.5mm. Simultaneously, the surface finish and edge quality are checked to ensure there are no burrs, scratches, or other defects. If any problems are found, the system automatically records and optimizes the machining path, providing a reference for the next machining operation.

[0174] In view of the above-mentioned BIM-based automated transfer and processing scheme for curtain wall metal keel component model data, this embodiment of the invention also provides a computer-readable storage medium storing a program thereon, which, when executed by a processor, implements the steps of the above-mentioned automated transfer and processing method for curtain wall metal keel component model data.

[0175] This invention also provides a processor for running a program, wherein the program executes the steps of the above-described method for automated data transfer and processing of curtain wall metal keel component model data.

[0176] This invention also provides a terminal device, which includes a processor, a memory, and a program stored in the memory and executable on the processor. The program code is loaded and executed by the processor to realize the steps of the above-described method for automated transfer and processing of curtain wall metal keel component model data.

[0177] The present invention also provides a computer program product, which, when executed on a data processing device, is suitable for performing the steps of the above-described method for automated data transfer and processing of curtain wall metal keel component model data.

[0178] In the above embodiments, the descriptions of each embodiment have different focuses. For parts not described in detail in a certain embodiment, please refer to the relevant descriptions in other embodiments.

[0179] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the specific working processes of the systems, devices, and modules described above can be referred to the corresponding processes in the foregoing method embodiments, and will not be repeated here.

[0180] Those skilled in the art will understand that embodiments of the present invention can be provided as methods, systems, or computer program products. Therefore, the present invention can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention can take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0181] This invention is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart illustrations and / or block diagrams. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0182] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0183] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0184] In a typical configuration, a computing device includes one or more processors (CPU), input / output interfaces, network interfaces, and memory.

[0185] Memory may include non-persistent memory in computer-readable media, such as random access memory (RAM) and / or non-volatile memory, like read-only memory (ROM) or flash RAM. Memory is an example of computer-readable media.

[0186] Computer-readable media, including both permanent and non-permanent, removable and non-removable media, can store information using any method or technology. Information can be computer-readable instructions, data structures, program modules, or other data. Examples of computer storage media include, but are not limited to, phase-change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technologies, CD-ROM, digital versatile optical disc (DVD) or other optical storage, magnetic tape, magnetic disk storage or other magnetic storage devices, or any other non-transfer medium that can be used to store information accessible by a computing device.

[0187] It should also be noted that the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such process, method, article, or apparatus. Unless otherwise specified, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes that element.

[0188] Those skilled in the art will understand that embodiments of the present invention can be provided as methods, systems, or computer program products. Therefore, the present invention can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention can take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0189] The method, specific system unit, or part thereof of the present invention described above is a pure software architecture. It can be deployed via program code on physical media, such as hard disks, optical discs, or any electronic device (such as smartphones or computer-readable storage media). When a machine loads and executes the program code (e.g., a smartphone loads and executes it), the machine becomes an apparatus for implementing the present invention. The method and apparatus of the present invention can also be transmitted in program code form via transmission media, such as cables, optical fibers, or any transmission method. When the program code is received, loaded, and executed by a machine (e.g., a smartphone), the machine becomes an apparatus for implementing the present invention.

[0190] The foregoing has shown and described the basic principles, main features, and advantages of the present invention. Those skilled in the art should understand that the present invention is not limited to the above embodiments. The embodiments and descriptions in the specification are merely illustrative of the principles of the invention. Various changes and modifications can be made to the invention without departing from its spirit and scope, and all such changes and modifications fall within the scope of the present invention as claimed. The scope of protection of this invention is defined by the appended claims and their equivalents.

Claims

1. A method for automated data transfer of BIM-based curtain wall metal keel component model, characterized in that, The method includes: (1) Establish a parametric model of the curtain wall metal keel based on BIM software, and define the geometric dimensions, material properties, and key information of the connection nodes; (2) Based on the OpenCASCADE open source package, a feature information extraction algorithm for curtain wall metal keel is constructed to extract the geometric and non-geometric data of curtain wall metal keel from the parametric model of curtain wall metal keel, and convert the extracted data into JSON structured format. During the conversion process, the geometric topology data and processing attributes of the model are preserved. (3) Based on the kinematic model of the robotic arm, the extracted geometric and non-geometric data of the curtain wall metal keel are combined to plan and generate the tool cutting path for the processing and production of the curtain wall metal keel.

2. The method for automated data transfer of BIM-based curtain wall metal keel component model as described in claim 1, characterized in that, In step (1), the method also performs collision detection on the established parametric model of the curtain wall metal keel.

3. The method for automated data transfer of BIM-based curtain wall metal keel component model as described in claim 1, characterized in that, The method selects a hole surface with precise dimensions in the parametric model of the curtain wall metal keel established in step (1), and adjusts its material color to the corresponding color.

4. The method for automated data transfer of BIM-based curtain wall metal keel component model as described in claim 1, characterized in that, In step (2) of the method, the curved surface shape of the hole is divided into three forms: round hole, waist hole and oblique hole, and the cutting end face is divided into two forms: normal cutting and oblique cutting.

5. The method for automated data transfer of BIM-based curtain wall metal keel component model as described in claim 4, characterized in that, The method extracts information in step (2), identifies the surface type by matching the color rendered on the hole surface with the corresponding surface contour, and uses the least squares method to fit the surface boundary to determine the actual position of the surface; then, based on the identified hole surface type, it extracts the geometric data of the hole surface; finally, for the determined hole surface, it further identifies the cutting end face.

6. The method for automated data transfer of BIM-based curtain wall metal keel component model as described in claim 1, characterized in that, In step (2), the method further checks the parametric model of the curtain wall metal keel to see if there are any missing values ​​in the model, such as the size or material properties of the components, and fills in the missing values.

7. The method for automated data transfer of BIM-based curtain wall metal keel component model as described in claim 1, characterized in that, The step (3) of planning and generating the tool cutting path includes the following sub-steps: (31) Initial toolpath generation: The initial toolpath of the robotic arm is generated based on the geometric data of the parametric model of the curtain wall metal keel and the kinematic model of the robotic arm. (32) Minimize idle travel time optimization: Minimize the idle travel time T by optimizing the objective function: Among them, L i : The straight-line distance of the (i)th segment of the path; Δθ i Changes in joint angles between adjacent path segments; (33) Applying constraints: Applying collision-free constraints, curvature adaptive constraints, and machining accuracy constraints: (331) No collision constraints, The distance d between the tool and the workpiece / environment must be greater than the safety threshold d. safe : d(Tool,Obstacle)≥d safe ; Distances are calculated in real time using geometric data from the BIM model; (332) Curvature adaptive constraint The tool orientation φ needs to be dynamically adjusted according to the surface curvature κ: R: Tool radius; (333) Machining accuracy constraints. The allowable dimensional error ∈ must satisfy: ∈≤∈ max (usually ∈ max =0.1mm) Dynamic parameter adjustment: Optimization of cutting parameters based on material properties K: Material cutting coefficient; M: Tool mass.

8. A BIM-based automated data transfer system for curtain wall metal keel component models, characterized in that, The system includes: The component modeling module can create a parametric model of the curtain wall metal keel based on BIM software and define geometric dimensions, material properties, and key information of connection nodes. The data conversion and processing module is configured to interact with the component modeling module. It constructs a feature information extraction algorithm for curtain wall metal keel based on the OpenCASCADE open source package, extracts the geometric and non-geometric data of the curtain wall metal keel from the parametric model of the curtain wall metal keel, converts the extracted data into JSON structured format, and retains the geometric topology data and processing attributes of the model during the conversion process. The path planning module interacts with the data conversion and processing module, and can plan and generate tool cutting paths for the processing and production of curtain wall metal keels based on the kinematic model of the robotic arm and the extracted geometric and non-geometric data of the curtain wall metal keel.

9. The BIM-based automated data transfer system for curtain wall metal keel component models according to claim 8, characterized in that, When the data conversion and processing module extracts the feature information of the curtain wall metal keel, it identifies the surface type by matching the color rendered on the hole surface with the corresponding surface contour, and uses the least squares method to fit the surface boundary to determine the actual position of the surface. Then, based on the identified hole surface type, it extracts the geometric data of the hole surface. Finally, for the determined hole surface, it further identifies the cutting end face.

10. The BIM-based automated data transfer system for curtain wall metal keel components according to claim 8, characterized in that, The path planning module includes an initial toolpath generation submodule, a path optimization submodule, and a constraint condition submodule. The initial toolpath generation submodule is configured to generate the initial robotic arm toolpath based on the geometric data of the parametric model of the curtain wall metal keel and the kinematic model of the robotic arm. The path optimization submodule is configured to interact with the initial toolpath generation submodule, enabling it to optimize the generated initial robotic arm toolpath by minimizing idle travel time. The constraint condition submodule interacts with the path optimization submodule, enabling the embedding of collision-free constraints, curvature adaptive constraints, and machining accuracy constraints in the optimized robotic arm tool path.

Images