A method and system for controlling the corner accuracy of a modular steel structure of an aerial building machine

Abstract

The application discloses an air building machine modular steel structure corner precision control method and system, relates to the technical field of high-altitude construction equipment, and comprises the following steps: presetting a geometric tolerance adjustment domain at the splicing interface of a non-standard corner column head and a steel truss, generating a measured digital twin model containing manufacturing errors through entity pre-assembly and three-dimensional laser scanning, calculating a target installation compensation value and attaching the target installation compensation value to the non-standard corner column head in the form of coding, taking the measured spatial coordinates of adjacent installed standard modules as a registration reference after hoisting to a high-altitude working position, performing spatial registration and attitude adjustment on the non-standard corner column head by using the geometric tolerance adjustment domain, determining corner attitude adjustment parameters, and finally realizing assembly alignment control of the air building machine. The application solves the technical problem that the traditional method is difficult to realize accurate docking of components in the high-altitude modular assembly scene, achieves accurate docking of the air building machine modular steel structure corner, and guarantees the technical effects of the safety of the overall structure and the construction quality.

Description

Technical Field

[0001] This invention relates to the field of high-altitude construction equipment technology, and in particular to a method and system for controlling the corner accuracy of a modular steel structure for an aerial building machine. Background Technology

[0002] In building construction, the corner accuracy of the modular steel structure of the aerial building machine directly affects the overall stability and safety of the building, making it a core control point. Current technologies for controlling this corner accuracy largely rely on theoretical model deduction, manual experience adjustments, or forced assembly, which have played a certain role in conventional steel structure assembly. However, as building construction demands increasing precision in modular construction, these traditional methods reveal significant limitations when applied to the high-altitude operation scenarios of aerial building machines: influenced by manufacturing errors, installation deviations, and interference from the high-altitude environment, traditional methods cannot accurately capture actual assembly deviations, resulting in inaccurate adjustment data, low efficiency, and an inability to meet the precise corner alignment requirements of modular steel structures in building construction, thus affecting overall construction quality and structural safety. Summary of the Invention

[0003] This application provides a method and system for controlling the corner accuracy of modular steel structures in aerial building construction machines, which solves the technical problem that traditional methods are difficult to use to achieve precise component docking in high-altitude modular assembly scenarios.

[0004] The first aspect of this application provides a method for controlling the corner accuracy of a modular steel structure for a building-in-the-sky machine. The method includes: pre-setting a geometric tolerance adjustment domain at the splicing interface between a non-standard corner column head and the horizontal and vertical steel trusses; the geometric tolerance adjustment domain being used to provide a mechanical adjustment margin for the non-standard corner column head relative to the standard module; performing physical pre-assembly of the non-standard corner column head and the standard module; acquiring spatial pose data of the actual assembly state through three-dimensional laser scanning; and generating a measured digital twin model containing manufacturing error information. The measured digital twin model calculates the target installation compensation value of the non-standard corner column head and attaches the compensation value to the non-standard corner column head in the form of a code. The non-standard corner column head carrying the code is hoisted to the high-altitude operation position. Based on the installation compensation value in the code, and using the measured spatial coordinates of the connection port of the adjacent installed standard module as the registration reference, the non-standard corner column head is spatially registered and its attitude is adjusted using the geometric tolerance adjustment domain to determine the corner attitude adjustment parameters. The assembly alignment control of the aerial building machine is performed according to the corner attitude adjustment parameters.

[0005] A second aspect of this application provides a modular steel structure corner precision control system for an aerial building machine. The system includes: a geometric tolerance adjustment domain setting module, used to preset a geometric tolerance adjustment domain at the splicing interface between the non-standard corner column head and the horizontal and vertical steel trusses, the geometric tolerance adjustment domain being used to provide mechanical adjustment margin for the non-standard corner column head relative to the standard module; a measured digital twin model construction module, used to perform physical pre-assembly of the non-standard corner column head and the standard module, acquire spatial pose data of the actual assembly state through three-dimensional laser scanning, and generate a measured digital twin model containing manufacturing error information; and a target installation compensation value acquisition module. The module calculates the target installation compensation value of the non-standard corner column head based on the measured digital twin model, and attaches the compensation value to the non-standard corner column head in the form of a code; the corner attitude adjustment parameter acquisition module is used to hoist the non-standard corner column head carrying the code to the high-altitude operation position, and based on the installation compensation value in the code, use the measured spatial coordinates of the connection port of the adjacent installed standard module as the registration reference, and use the geometric tolerance adjustment domain to perform spatial registration and attitude adjustment on the non-standard corner column head to determine the corner attitude adjustment parameters; the assembly alignment control execution module is used to perform assembly alignment control of the aerial building machine according to the corner attitude adjustment parameters.

[0006] One or more technical solutions provided in this application have at least the following technical effects or advantages: This application pre-assembles non-standard components and standard modules by pre-setting the adjustment margin area for component splicing and collecting spatial pose data. Compensation parameters are obtained and encoded by digital twin modeling and error analysis. During high-altitude operations, based on the encoded parameters and the measured benchmarks of adjacent installed modules, the application achieves precise docking of the modular steel structure corners of the aerial building machine through layered registration adjustment, dynamic physical field data correction, and cumulative error prediction, thus ensuring the technical effect of overall structural safety and construction quality. Attached Figure Description

[0007] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0008] Figure 1 This is a flowchart illustrating a method for controlling the corner accuracy of a modular steel structure for an aerial building machine, as provided in an embodiment of this application.

[0009] Figure 2 This is a schematic diagram of the structural control system for the cornering accuracy of a modular steel structure for an aerial building machine, provided in an embodiment of this application.

[0010] Figure labeling: 1. Geometric tolerance adjustment domain setting module; 2. Measured digital twin model construction module; 3. Target installation compensation value acquisition module; 4. Angle attitude adjustment parameter acquisition module; 5. Assembly alignment control execution module. Detailed Implementation

[0011] This application provides a method and system for controlling the corner accuracy of modular steel structures in aerial building construction machines, which solves the technical problem that traditional methods are difficult to use to achieve precise component docking in high-altitude modular assembly scenarios.

[0012] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of this application, and not all of them. All other embodiments obtained by those skilled in the art based on the embodiments of this application without creative effort are within the scope of protection of this application.

[0013] It should be noted that the terms "first," "second," etc., in the specification and accompanying drawings of this application are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of this application described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion; for example, a process, method, system, product, or server that includes a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or modules not explicitly listed or inherent to such processes, methods, products, or devices.

[0014] Example 1, as Figure 1 As shown, a method for controlling the corner accuracy of a modular steel structure for an aerial building machine, wherein the method includes: At the interface between the non-standard corner column head and the horizontal and vertical steel trusses, a geometric tolerance adjustment range is preset. The geometric tolerance adjustment range is used to provide the mechanical adjustment margin of the non-standard corner column head relative to the standard module.

[0015] In this embodiment, the non-standard corner column head is a non-standard steel structure connection component customized according to the specific dimensional requirements of the target building's corner. It is mainly used to achieve the connection and force transfer between the horizontal and vertical steel trusses in the corner area. The horizontal and vertical steel trusses are the standardized load-bearing structural frames of the aerial building machine. The horizontal steel truss bears the lateral load and forms the basic support for the working platform, while the vertical steel truss bears the vertical load and realizes the transfer of load to the core tube structure.

[0016] Specifically, based on the BIM model of the target building structure, a digital assembly of the "sky-building machine" is first constructed. The assembly process of non-standard corner column heads and standard modules is simulated within the BIM model, with virtual collision checks and gap analysis conducted simultaneously to obtain simulation results. Based on these simulation results, the assembly gaps are fitted with angular rotation. Under the premise of meeting the construction and assembly constraints of the target building structure, the optimal dimensional parameters of the geometric tolerance adjustment domain are determined. Finally, based on these optimal dimensional parameters, while ensuring that the load-bearing capacity requirements of the connecting components are met, the preset geometric tolerance adjustment domain is completed. This step will be explained in detail later.

[0017] The non-standard corner column head and standard module are pre-assembled in physical form. Spatial pose data of the actual assembly state are obtained by three-dimensional laser scanning, and a measured digital twin model containing manufacturing error information is generated.

[0018] In this embodiment, the standard module is a standardized steel truss unit designed with a fixed modulus and equipped with standardized connection interfaces (such as pin holes), which is used for rapid assembly and to form the core load-bearing and support structure of the building machine.

[0019] Optionally, firstly, the non-standard corner column head is naturally fitted and trial-assembled with the corresponding numbered standard horizontal and vertical steel trusses according to the design theoretical angle, without applying any forced assembly force. Then, a 3D laser scanner is used to measure the gap distribution and relative pose between the non-standard corner column head and the standard module. Finally, based on the measured gap distribution and relative pose data, spatial positional relationship projection is performed to obtain the required spatial pose data.

[0020] Next, based on the actual assembly status data obtained from 3D laser scanning, a measured digital twin model is constructed through mirror projection of the modular steel structure of the aerial building machine. Simultaneously, an embedded calibration module is established based on the BIM model of the target building structure. This calibration module is spatially registered with the measured digital twin model to identify spatial manufacturing error information between the actual assembly status data and the BIM model. These two steps will be explained in detail later.

[0021] The target installation compensation value of the non-standard corner column head is calculated based on the measured digital twin model, and the compensation value is attached to the non-standard corner column head in the form of a code.

[0022] In one embodiment of this application, based on the measured digital twin model, the theoretical error of the model is identified by spatially aligning the actual assembly state data with the target data of the BIM model; then, combined with the acquired spatial pose data, spatial error decoupling is carried out based on the theoretical error of the model, and finally the target installation compensation values ​​of the non-standard corner column head in the horizontal X direction, horizontal Y direction and rotation direction around the Z axis are determined and attached to the non-standard corner column head in the form of a code. This step will be described in detail in the following content.

[0023] The non-standard corner column head carrying the code is hoisted to the high-altitude work position. Based on the installation compensation value in the code, the measured spatial coordinates of the connection port of the adjacent installed standard module are used as the registration reference. The non-standard corner column head is spatially registered and its attitude is adjusted using the geometric tolerance adjustment domain to determine the corner attitude adjustment parameters.

[0024] Specifically, using the measured spatial coordinates of the connection ports of adjacent installed standard modules as the registration reference, the target installation compensation amount in the code is first decomposed into translational compensation components and rotational compensation components. Then, self-guiding coarse positioning is achieved through the vertical tolerance adjustment domain to eliminate the initial deviation. Subsequently, an external fine-tuning force is applied in the horizontal tolerance adjustment domain to achieve fine alignment (the gap distribution is measured in real time during fine-tuning). The combination of shim thickness and bolt tightening sequence are calculated. Finally, these two items and the final target pose data are recorded as the rotation attitude adjustment parameters. This step will be explained in detail in the following content.

[0025] The assembly and alignment control of the aerial building machine is performed based on the aforementioned angle attitude adjustment parameters.

[0026] In this embodiment, the aerial building machine is a liftable intelligent construction platform that integrates functions such as construction elevator, material platform, formwork system, safety protection, and intelligent control for the construction of the core tube of super high-rise buildings.

[0027] Specifically, first, verify the angle and attitude adjustment parameters to confirm the accuracy of the shim thickness combination, bolt tightening sequence, and final target position data. Select standard metal shims and suitable high-strength bolts of the corresponding specifications according to the parameters to ensure that the material specifications match the design requirements of the connectors. Precisely place the shims at the corresponding measuring points on the splicing interface according to the preset thickness combination, ensuring that the shims are flat, fit, and without deviation. Then, insert the bolts into the connecting holes for pre-installation according to the bolt tightening sequence, tightening them until they just contact the shims, without applying full tightening torque.

[0028] Next, a total station was used to monitor the actual position and orientation of the non-standard corner column head in real time. Using the final target position and orientation as a reference, and combining the gap distribution data measured with a feeler gauge, the shim thickness or bolt preload was fine-tuned until the deviation between the measured and target positions was ≤ ±3mm, and the gap distribution was uniform. A torque wrench was then used for final bolt tightening, strictly following the preset tightening sequence. Each bolt was tightened gradually with a uniform torque gradient. The tightening torque value was set according to the structural load-bearing capacity requirements of the connecting parts, ensuring consistent tightening force on each bolt and avoiding component orientation deviation due to excessive local stress. During the tightening process, the total station was continuously used to monitor position and orientation changes. If a slight deviation occurred, tightening was immediately paused, fine-tuned, and then continued until all bolts reached the specified tightening torque and the component orientation remained stable.

[0029] After assembly and alignment are completed, a total station is used again to comprehensively measure the final actual position of the non-standard corner column head, and the deviation between the measured data and the final target position data is recorded to confirm that the deviation is within the allowable range. At the same time, feeler gauges are used to check the gap distribution at the splicing interface to ensure that there are no abnormal gaps. The parameter usage, measured deviation data, and tightening torque records during this assembly process are compiled and archived to form a complete assembly and alignment construction record, providing a basis for subsequent floor assembly and quality traceability.

[0030] Furthermore, the method provided in this application embodiment includes: Based on the long connecting bolt holes set at the horizontal connection end face of the non-standard corner column head and the horizontal steel truss, with the long axis of the long connecting bolt holes arranged along the axis of the horizontal truss, the mechanical connection allowance of the sliding groove of the long connecting bolt holes and the connecting slider of the horizontal steel truss is analyzed to obtain the horizontal tolerance adjustment range; based on the automatic guidance and angle adjustment allowance of the vertical connection end face of the non-standard corner column head and the vertical steel truss, the vertical tolerance adjustment range is obtained; based on the horizontal tolerance adjustment range and the vertical tolerance adjustment range, the preset geometric tolerance adjustment range is determined.

[0031] In this embodiment, the long connecting bolt hole is a hole structure machined on the horizontal connecting end face of the non-standard corner column head and the horizontal steel truss, with the long axis arranged along the axis of the horizontal truss and having a sliding groove. It is used to adapt to the connecting slider of the horizontal steel truss and provide a horizontal mechanical adjustment margin.

[0032] Specifically, at the horizontal connection end face where the non-standard corner column head connects to the horizontal steel truss, long connecting bolt holes are machined using machining methods. During machining, the long axis of the long connecting bolt holes is strictly aligned with the axis of the horizontal steel truss to ensure that the long axis is consistent with the force transmission direction of the horizontal steel truss, avoiding any adverse effects on the structural load-bearing performance during adjustment. Subsequently, calipers and other common measuring tools are used to measure the effective length of the sliding groove inside the long connecting bolt hole and the actual mating length of the connecting slider at the end of the horizontal steel truss. By calculating the difference between the effective length of the sliding groove in the long connecting bolt hole and the mating length of the connecting slider, the range of relative sliding distances when they are mated is obtained. This range of distances is the allowable mechanical adjustment margin in the horizontal direction, thereby determining the horizontal tolerance adjustment range.

[0033] For the vertical connection end face of the non-standard corner column head connecting to the vertical steel truss, a gradually changing slope is machined on the vertical connection end face of the non-standard corner column head as an automatic guiding structure, while a matching fitting slope is machined on the corresponding connection end face of the vertical steel truss. This slope guiding structure can achieve initial alignment using the weight of the components themselves. Simultaneously, when machining the vertical connection end face, a certain fitting clearance is reserved according to design requirements as an angle adjustment allowance. By using an angle gauge to measure the maximum deflectable angle corresponding to the reserved clearance, the angle adjustment range achievable by this clearance is determined, thereby obtaining the vertical tolerance adjustment range.

[0034] After obtaining the horizontal and vertical tolerance adjustment domains, their adjustment ranges are clarified and defined. The horizontal tolerance adjustment domain is responsible for horizontal translation adjustment, while the vertical tolerance adjustment domain is responsible for vertical alignment and angle adjustment, ensuring clear functional boundaries and no interference between the two domains. By combining the sliding adjustment range of the horizontal tolerance adjustment domain with the guiding and angle adjustment range of the vertical tolerance adjustment domain, a complete geometric tolerance adjustment domain is formed. This domain covers all the mechanical adjustment space required when connecting non-standard corner column heads to horizontal and vertical steel trusses.

[0035] By employing methods such as machining, dimensional measurement, clearance allowance, and adjustment range integration, tolerance adjustment ranges in the horizontal and vertical directions were constructed, providing operable mechanical adjustment margins for the precise docking of non-standard corner column heads with standard modules.

[0036] Furthermore, the method provided in this application embodiment includes: A digital assembly of a building-in-the-sky machine is established based on the BIM model of the target building structure. The assembly process of the non-standard corner column head and standard modules is simulated in the BIM model, and virtual collision checks and gap analyses are performed to obtain simulation results. Based on the simulation results, the angle of the assembly gap is fitted by rotation. Under the construction assembly constraints of the target building structure, the optimal size parameters of the geometric tolerance adjustment domain are determined. Based on the optimal size parameters, the geometric tolerance adjustment domain is preset under the constraint of the load-bearing capacity requirements of the connecting structure.

[0037] Optionally, firstly, using BIM modeling software familiar to those skilled in the art, the existing BIM model data of the target building structure is imported. This data includes key information such as the dimensions and spatial layout of the building's core tube. Then, based on the design drawings of the aerial construction machine, three-dimensional solid models of standard horizontal steel trusses, standard vertical steel trusses, and non-standard corner column heads are built in the BIM modeling software. The materials, dimensions, and connection interfaces of these models are consistent with the actual components produced and processed. The completed steel truss modules and non-standard corner column head models are then integrated into the BIM model of the target building structure according to the actual assembly layout of the aerial construction machine, forming a complete digital assembly of the aerial construction machine. This ensures that the assembly accurately reflects the relative positional relationships of the components during actual construction.

[0038] Next, using the clash detection function built into the BIM modeling software, the assembly process of non-standard corner column heads with standard horizontal and vertical steel trusses was simulated according to the theoretical process of modular assembly in aerial building construction. During the simulation, the software automatically identified whether there were spatial conflicts between components and recorded information such as the specific location and degree of conflict. At the same time, the distance measurement tool of the BIM modeling software was used to measure the gap dimensions at the interface between the non-standard corner column head and the standard module, and the distribution range, maximum gap value, minimum gap value, and areas of uneven gap were statistically analyzed. The clash detection results and gap measurement data were summarized and compiled to form a complete simulation result.

[0039] Then, the least squares method was used as the geometric fitting algorithm. First, the central axis of the interface between the non-standard corner column head and the steel truss was used as a fixed rotation reference. Gap data from each measuring point on the interface was extracted from the simulation results, and a coordinate dataset was established. Then, a rotation angle step of 1° was set, and the attitude of the non-standard corner column head was adjusted one by one around the central axis. After each rotation adjustment, the gap data of each measuring point under the current attitude was substituted into the least squares formula for fitting calculation. The standard deviation of the gap distribution was calculated to quantify the gap uniformity. The smaller the standard deviation, the more uniform the gap distribution. Simultaneously, it was verified whether the adjustment domain size parameters corresponding to the current attitude met the allowable error range of modular splicing, the design angle standard of the corner structure, and other construction and assembly constraints. If the calculated gap uniformity does not meet the assembly requirements or the dimensional parameters violate the constraints, the rotation angle is adjusted according to the set step size. The above data fitting, uniformity calculation and constraint verification steps are repeated. Through multiple iterations, the optimal parameter range is gradually narrowed down. Finally, the target posture with the smallest gap standard deviation and that fully meets the constraint requirements is selected. Then, the optimal dimensional parameters such as the sliding stroke length of the horizontal tolerance adjustment domain and the automatic guide slope angle and angle adjustment reserved gap of the vertical tolerance adjustment domain are determined based on the target posture.

[0040] Finally, structural mechanics analysis tools such as ANSYS are used to verify the load-bearing capacity of the connectors corresponding to the determined optimal dimensional parameters. Based on the loads that the aerial construction machine may bear during construction, including the self-weight of the components, the weight of construction personnel and equipment, and wind loads, these are input into the structural mechanics analysis tool to calculate the stress and strain of connectors such as long connecting bolt holes, connecting sliders, and pins. If the verification results show that the load-bearing capacity of the connectors does not meet the requirements, the optimal dimensional parameters are adjusted appropriately, such as increasing the contact area of ​​the connectors or increasing the wall thickness of the bolt holes, until the load-bearing capacity of the connectors meets the design standards. After the final confirmation of the parameters, corresponding structural processing is performed at the splicing interface between the non-standard corner column head and the horizontal and vertical steel trusses according to these optimal dimensional parameters, completing the preset geometric tolerance adjustment range.

[0041] Through the above-mentioned sequential steps, the optimal size parameters of the geometric tolerance adjustment range are accurately determined and safely preset, ensuring that the adjustment margin of the adjustment range meets the error compensation requirements and that the structural load-bearing capacity of the connector meets the construction safety requirements.

[0042] Furthermore, the method provided in this application embodiment includes: The non-standard corner column head is naturally fitted and trial-assembled with the corresponding numbered standard horizontal steel truss and standard vertical steel truss according to the design theoretical angle; a three-dimensional laser scanner is used to measure the gap distribution and relative pose between the non-standard corner column head and the standard module without applying forced assembly force; based on the gap distribution and relative pose between the non-standard corner column head and the standard module, spatial position relationship is projected to obtain the spatial pose data.

[0043] Specifically, the non-standard corner column head is first placed on a flat pre-assembly platform along with the corresponding numbered standard horizontal and vertical steel trusses. Following the theoretical angles specified in the target building structure design drawings, the connection surfaces of the three components are naturally brought into contact and fitted for trial assembly. No forced assembly force is applied during the assembly process; the natural fit is achieved solely by the weight of the components themselves. This ensures that the assembly state accurately reflects the actual fit of the components after manufacturing, avoiding assembly deviations caused by external forces from affecting subsequent data measurement results.

[0044] Then, a 3D laser scanner was used for data acquisition. Before acquisition, the 3D laser scanner was calibrated for accuracy, and the scanning resolution parameters were set according to the dimensions of the pre-assembled components. Subsequently, scanning was performed around the pre-assembled component assembly from multiple evenly distributed angles to ensure that the scanning range completely covered all splicing interfaces between the non-standard corner column head and the standard horizontal and vertical steel trusses. The 3D laser scanner captured 3D coordinate point cloud data of the component surface, and the gap information at the splicing interface was extracted from the point cloud data to determine the specific location of the gap, the gap width at each point, and the distribution pattern. Simultaneously, based on the spatial coordinate relationship of point cloud data, common feature points of the splicing interface between the standard module and the non-standard corner column are selected, such as the center of the bolt hole and the center of the end face. The three-dimensional coordinates of each common feature point are extracted from the point cloud data of both parties. By calculating the average value of the coordinate difference of the corresponding common feature points, the relative translation of the non-standard corner column relative to the standard module in the horizontal X, Y and vertical Z directions is obtained. Then, using the spatial vector formed by the common feature points as the reference, the angle between the two vectors is solved by the vector angle calculation formula to obtain the relative rotation angle of the non-standard corner column around the horizontal axis and the vertical axis, thus completing the measurement of the relative pose.

[0045] Subsequently, a reference coordinate system was established based on the design reference axes of the standard horizontal and vertical steel trusses. The relative pose data and gap distribution data acquired through scanning were imported into the 3D modeling software. First, the absolute coordinates of the standard module in this reference coordinate system were determined. These coordinates were based on the design drawings and were known data. Then, using a coordinate transformation algorithm, the relative translation and relative rotation angles of the non-standard corner column head were converted into absolute position parameters in the reference coordinate system, using the absolute coordinates of the standard module as a reference. Key feature points such as the center point of the connection end face of the non-standard corner column head and the center of the long connecting bolt hole were selected. The coordinates of each key feature point were corrected in conjunction with the gap distribution data to eliminate the influence of gap width on position judgment. By integrating the absolute coordinates and attitude parameters of all key feature points, the complete spatial pose data of the non-standard corner column head in the actual assembly state was finally obtained, including three-dimensional spatial coordinates and attitude angle information.

[0046] Furthermore, the method provided in this application embodiment includes: Based on the actual assembly status data obtained by 3D laser scanning, the modular steel structure of the aerial building machine is mirrored and projected to construct a measured digital twin model of the aerial building machine. Based on the BIM model of the target building structure, an embedded calibration module is established to perform spatial registration with the digital twin model and identify the spatial manufacturing error information between the actual assembly status data and the BIM model.

[0047] In this embodiment, the actual assembly state data is a massive set of discrete three-dimensional coordinate points directly obtained by scanning the non-standard corner column head and the standard module pre-assembled assembly by a three-dimensional laser scanner. It covers all geometric information of the component surface, including the component outline, the three-dimensional position of the splicing interface gap, the coordinates of the connection interface feature points, etc.

[0048] Specifically, the actual assembly state data acquired by 3D laser scanning is first preprocessed. A statistical filtering algorithm is used to remove isolated noise points from the point cloud data by setting a distance threshold, retaining only valid point clouds that reflect the true surface of the component. Three or more pre-defined non-collinear target markers on the component surface are selected as stitching references. An iterative nearest-point algorithm is used to stitch the point cloud data acquired from multi-view scanning, ensuring that the stitching error is controlled within ±0.1mm. The stitched point cloud data is then converted to STL format to meet the import requirements of subsequent 3D modeling software, completing data preprocessing to ensure the accuracy of the modeling data.

[0049] Then, Revit, a well-known 3D modeling software in this field, was selected. A global reference coordinate system was established with the design axis of the standard horizontal steel truss as the X-axis, the design axis of the standard vertical steel truss as the Z-axis, and the center point of the splicing interface as the origin. The preprocessed point cloud data was imported into the modeling software, and the modular steel structure of the aerial building machine was mirrored and projected based on the point cloud data. First, the geometry of the standard horizontal and vertical steel trusses was restored, including the truss length, cross-sectional dimensions, pin hole positions and dimensions, etc. Then, the shape structure of the non-standard corner column head, the position and size of the long connection bolt holes, the guide slope shape of the vertical connection end face and other key features were accurately mapped. Finally, according to the actual assembly state, the connection relationship of the three was restored in the model to ensure that the relative position of the components in the model and the fit of the connection interface are consistent with the physical entity, and the deviation between the geometric dimensions of the model and the actual measured dimensions of the entity does not exceed ±0.2mm, thus completing the basic geometric construction of the measured digital twin model.

[0050] Based on the BIM model of the target building structure, target data such as design geometric dimensions, theoretical spatial coordinates, design gap requirements for splicing interfaces, and design angles of corner structures are extracted for standard modules and non-standard corner column heads. After integrating these target data, an embedded verification module is established in the measured digital twin model. This module includes a data storage unit and a comparison unit. The data storage unit is used to store the target data extracted from the BIM model, and the comparison unit is used for subsequent difference analysis with the measured data, making the embedded verification module the benchmark for error identification.

[0051] Spatial registration was then performed using an iterative nearest-point algorithm. Three or more common feature points, such as the center of the bolt hole and the center of the component end face, were selected from the point cloud data of the measured digital twin model. Simultaneously, the theoretical coordinates of the corresponding common feature points were extracted from the BIM target data stored in the embedded calibration module. Using the theoretical coordinates of the common feature points in the BIM target data as a reference, the coordinates of the corresponding common feature points in the measured digital twin model were used as the initial input. The pose of the measured digital twin model was continuously adjusted through iterative calculations to minimize the sum of squared spatial distances between the two sets of feature points until the registration error was less than ±0.2 mm, thus completing the spatial registration between the measured digital twin model and the embedded calibration module.

[0052] After spatial registration, error identification is performed using the comparison unit of the embedded calibration module. The actual 3D coordinates of each component in the measured digital twin model are compared with the theoretical coordinates in the BIM model. The Euclidean distance formula is used to calculate the coordinate deviation value, determining the translation errors in the horizontal X, Y, and vertical Z directions. The actual axis angles of the components in the model are compared with the theoretical axis angles in the BIM model. The vector angle calculation formula is used to solve for the angle deviation value, determining the rotation error around each coordinate axis. Simultaneously, the differences between the actual gap dimensions at the splicing interface and the design gap requirements are analyzed to clarify the distribution of gap deviations. Areas where coordinate deviations, angle deviations, and gap deviations exceed the design allowable thresholds are marked as error areas. The specific location, error value, and error type of each error area are recorded, completing the identification of actual assembly state data and spatial manufacturing error information in the BIM model.

[0053] Through point cloud data preprocessing, 3D mirror projection modeling, BIM data extraction and verification module construction, spatial registration and deviation comparison, the construction of a measured digital twin model containing manufacturing error information and the identification of manufacturing errors were realized, providing accurate digital basis for the subsequent calculation of target installation compensation values.

[0054] Furthermore, the method provided in this application embodiment includes: Using the measured digital twin model, spatial alignment is performed between the actual assembly status data and the target data of the BIM model to identify theoretical errors in the model; based on the spatial pose data, spatial error decoupling is performed based on the theoretical errors in the model to determine the target installation compensation values ​​of the non-standard corner column head in the horizontal X-axis, Y-axis and rotational direction around the Z-axis.

[0055] Specifically, firstly, the actual data of key feature points of the non-standard corner column head are extracted from the measured digital twin model, including the three-dimensional spatial coordinates of feature points such as the center point of the connecting end face, the center of the long connecting bolt hole, and the vertex of the guide slope of the vertical connecting end face, as well as the actual attitude angle data of the non-standard corner column head. Simultaneously, the theoretical three-dimensional coordinates and theoretical attitude angle data of the corresponding key feature points are extracted from the target data of the BIM model, ensuring a one-to-one correspondence between the feature points of the two sets of data and a consistent coordinate system. Then, spatial alignment is performed using the least squares method. The measured feature point data and the theoretical feature point data are substituted into the least squares formula, and the pose of the measured digital twin model is adjusted through iterative calculation to minimize the sum of squared spatial distances between all corresponding feature points, thus completing the spatial alignment between the actual assembly state data and the target data of the BIM model. After alignment, the coordinate deviations of each key feature point in the horizontal X, Y and vertical Z directions are calculated using the Euclidean distance formula. The deviation between the actual attitude angle and the theoretical attitude angle is calculated using the vector angle formula. The coordinate deviations and attitude deviations of all feature points are statistically summarized. After removing abnormal deviation values, the average value is taken to identify the theoretical model error that reflects the overall deviation, including translation error and rotation error.

[0056] Next, spatial error decoupling is carried out. Specifically, a fixed coordinate system is established with the design axis of the standard horizontal steel truss as the X-axis, the design axis of the standard vertical steel truss as the Z-axis, and the center point of the splicing interface as the origin. The horizontal X and Y directions are defined as the two vertical translation directions in the plane, and the rotation direction around the Z-axis is defined as the rotation direction in the plane. The actual three-dimensional coordinates and actual rotation angle of the non-standard corner column head are extracted from the acquired spatial pose data. Combined with the identified model theoretical errors, the complex spatial comprehensive error is decomposed into three independent error components. For the horizontal X-axis error component, the difference between the actual X-coordinates of key feature points in the measured digital twin model and the theoretical X-coordinates of the corresponding feature points in the BIM model is calculated, and the average of these differences across all feature points is taken as the independent error in the horizontal X-axis. For the horizontal Y-axis error component, the average difference between the actual Y-coordinates and the theoretical Y-coordinates is calculated using the same method, and this is taken as the independent error in the horizontal Y-axis. For the rotational error component around the Z-axis, the Z-axis of the fixed coordinate system is used as the rotation reference, and the difference between the actual rotation angle and the theoretical rotation angle of the non-standard corner column head is calculated. This difference is the independent error of rotation around the Z-axis, thus decoupling the spatial errors and ensuring that the error components do not interfere with each other.

[0057] Then, based on the three decoupled independent error components, the corresponding target installation compensation values ​​are determined. The horizontal X-axis target installation compensation value is the inverse of the horizontal X-axis independent error, that is, the compensation amount that is equal in magnitude but opposite in direction to the target error component. The horizontal Y-axis target installation compensation value is the inverse of the horizontal Y-axis independent error. The rotational target installation compensation value around the Z-axis is the inverse of the rotational independent error around the Z-axis, ensuring that the compensation values ​​can accurately offset the corresponding errors. Finally, an encoding tool is used to convert the horizontal X-axis, Y-axis, and rotational target installation compensation values ​​around the Z-axis into standardized digital codes. The encoding format adopts the commonly used QR code or barcode in this field, ensuring that it can be quickly read by scanning equipment during high-altitude operations. The generated codes are printed on wear-resistant and waterproof labels and attached to a prominent position on the side of the non-standard corner column head. The labels are firmly attached without obscuring the installation area of ​​the connectors, facilitating quick identification and reading after hoisting to the high-altitude working position.

[0058] By employing spatial alignment and deviation calculation, step-by-step spatial error decoupling, and compensation value encoding and attachment methods, the target installation compensation value for non-standard corner column heads was accurately determined and conveniently transmitted, providing accurate and directly applicable data for spatial registration and attitude adjustment during high-altitude operations.

[0059] Furthermore, the method provided in this application embodiment includes: The target installation compensation amount in the code is decomposed into components, including translation compensation components and rotation compensation components. The translation compensation component includes offsets in the horizontal X, horizontal Y, and vertical Z directions; the rotation compensation component includes tilt corrections around the horizontal axis and horizontal rotation corrections around the vertical axis. Based on the translation compensation components and the vertical tolerance adjustment domain, self-guiding coarse positioning is performed, causing the non-standard corner column head to automatically slide to a coarse alignment state close to the target pose under gravity, eliminating initial horizontal and vertical deviations. Based on the rotation compensation components and translation compensation components... Within the mechanical degrees of freedom of the horizontal tolerance adjustment domain, with the goal of eliminating residual deviations, an external fine-tuning force is applied to cause the non-standard corner head to make slight translation and rotation relative to the adjacent installed standard module, achieving a precise alignment state. During the precise alignment process, the gap distribution between the non-standard corner head and the adjacent installed standard module is measured in real time. The required shim thickness combination and bolt tightening sequence are calculated based on the gap distribution. The shim thickness combination, bolt tightening sequence, and final target pose data are recorded as the corner attitude adjustment parameters.

[0060] In one embodiment, a tower crane is first used to smoothly hoist the non-standard corner column head, carrying a code, to a high-altitude work position, avoiding collisions with the already installed standard modules during the hoisting process. Before hoisting to the desired position, a total station is used to measure the connection ports of adjacent installed standard modules. Using the design axis of the standard horizontal steel truss as the X-axis, the design axis of the standard vertical steel truss as the Z-axis, and the center point of the splicing interface as the reference, the three-dimensional measured spatial coordinates of the connection ports are obtained, serving as the benchmark for subsequent spatial registration. When the non-standard corner column head is hoisted close to the work position, a handheld barcode scanner is used to read the code attached to the side of the component to quickly obtain the target installation compensation value, ensuring the accuracy of the compensation data.

[0061] Then, the read target installation compensation values ​​are decomposed into translational compensation components and rotational compensation components. Specifically: First, the horizontal X-axis, Y-axis, and rotational Z-axis target installation compensation values ​​determined in the previous steps are identified. These three sets of values ​​are the basic data for component decomposition. The vertical Z-axis translational compensation component is obtained based on the deviation calculation results between the actual Z-coordinates of key feature points in the measured digital twin model and the theoretical Z-coordinates of the corresponding feature points in the BIM model. The inverse phase of this deviation is taken as the vertical Z-axis translational compensation component. The tilt angle correction around the horizontal axis is based on the axis parallel to the horizontal X-axis. The deviation between the actual tilt angle of the non-standard corner column head in the spatial pose data and the theoretical tilt angle of the BIM model is extracted. The inverse phase of this deviation is taken as the tilt angle correction value around the horizontal axis. The horizontal rotation angle correction value around the vertical axis (coinciding with the Z-axis) is directly adopted from the determined target installation compensation value around the Z-axis. During the decomposition process, an Excel software was used to create a data classification table. The horizontal X-axis, Y-axis, and vertical Z-axis translational deviations were uniformly classified into the translational compensation component column, and the tilt correction values ​​around the horizontal axis and the horizontal rotation correction values ​​around the vertical axis were uniformly classified into the rotational compensation component column. The entire process followed the coordinate system consistent with the previous modeling and error calculation. The component decomposition could be completed simply by classifying the corresponding values ​​and organizing the tables.

[0062] Next, coarse positioning is performed using the automatic guide structure of the vertical tolerance adjustment domain. The vertical connection end face of the non-standard corner column head is equipped with a gradually changing guide slope, which cooperates with the corresponding fitting slope of the standard vertical steel truss. Under the action of gravity, the non-standard corner column head slides naturally along the guide slope. During the slope contact process, it automatically corrects large deviations in the vertical and horizontal directions until the component connection end faces are initially fitted. This process does not require the application of additional external force, but only relies on the self-positioning of the component's own weight and the cooperation of the guide slope to achieve self-positioning. Finally, the non-standard corner column head slides to a coarse alignment state close to the target pose, effectively eliminating the initial horizontal and vertical deviations and ensuring that the subsequent fine adjustment range is within the allowable range of the geometric tolerance adjustment domain.

[0063] During the fine alignment stage, jacks and crowbars, commonly used on-site in engineering projects, are employed as external fine-tuning tools, operating within the mechanical degrees of freedom of the horizontal tolerance adjustment domain. Based on the residual values ​​of the decomposed rotational and translational compensation components—specifically, the residual values ​​of the translational compensation components representing the uncompensated horizontal X, Y, and vertical Z-axis translational deviations after initial deviation elimination via self-guided coarse positioning in the vertical tolerance adjustment domain—a small jacking force is applied, or a small prying motion is performed with a crowbar. This allows the non-standard corner column head to undergo slight horizontal X and Y-axis translations and slight rotations around the vertical axis relative to adjacent installed standard modules. During fine-tuning, feeler gauges and laser rangefinders are used to measure the gap distribution at the splicing interface in real time. At least six measuring points are evenly selected along the interface, and the gap width data is recorded point by point to ensure real-time monitoring of deviation changes until the residual deviations are gradually eliminated, achieving a fine alignment state.

[0064] Next, based on the real-time measured gap distribution data, the required combination of gasket thicknesses is calculated. Existing standard engineering specifications of metal gaskets are selected, with thicknesses covering common sizes such as 0.1mm, 0.2mm, 0.5mm, and 1mm. For each measuring point's gap width, gaskets of corresponding thicknesses are selected and combined to ensure that the combined gasket thickness matches the gap width, enabling a tight fit between the non-standard corner column head and the standard module's connection surface. The bolt tightening sequence adopts the conventional symmetrical tightening method in steel structure assembly. Using the center of the splicing interface as a reference, the tightening sequence is determined according to the principle of diagonal tightening followed by peripheral tightening, and center tightening followed by side tightening, to avoid excessive single tightening force causing component displacement. The bolt tightening sequence number is clearly defined before tightening to ensure that those skilled in the art perform the tightening in the correct order.

[0065] Finally, the angle attitude adjustment parameters are recorded using paper records or electronic documents. The selected shim thickness combinations are recorded in detail, including the specific thickness and quantity of shims at each position, and the order of bolt tightening. At the same time, the final actual position data of the non-standard angle column head is measured again using a total station, including three-dimensional spatial coordinates and attitude angles. After verifying that the data is consistent with the target position data, it is recorded as the final target position data to form a complete angle attitude adjustment parameter file.

[0066] Through engineering steps including hoisting and positioning, data decomposition, self-guiding coarse adjustment, mechanical fine adjustment, gap measurement and shim matching, and parameter recording, the precise spatial registration and attitude adjustment of non-standard corner column heads were achieved, providing clear and executable operational guidelines and parameter support for the efficient and precise assembly of modular steel structures for aerial building machines.

[0067] Furthermore, the method provided in this application embodiment includes: Real-time physical field characteristic data, including real-time temperature, stress, and vibration modes, are collected by distributed sensing nodes. The physical field characteristic data is input into the measured digital twin model, and real-time simulation is performed based on the physical field-geometric deviation mapping relationship to generate the predicted geometric pose of the physical field. The predicted geometric pose of the physical field is compared with the measured geometric pose, and the difference is calculated as a dynamic correction amount. The target installation compensation value is updated in real time based on the dynamic correction amount.

[0068] Optionally, temperature sensors, strain gauge stress sensors, and accelerometers are selected as distributed sensing nodes. The sensor accuracies must meet the following requirements: temperature measurement error ≤ ±0.5℃, stress measurement error ≤ ±1MPa, and vibration measurement frequency range 5-1000Hz. Based on the stress characteristics and temperature distribution patterns of the modular steel structure of the aerial building machine, sensing nodes are arranged at key locations such as the interface between non-standard corner column heads and standard modules, steel truss nodes, and around long connecting bolt holes. At least three sensors are arranged in each key area to ensure data reliability. The sensors are connected to the data acquisition terminal via a wireless transmission module. Before data acquisition, the sensors are calibrated and adjusted, and the acquisition frequency is set to once per minute. Real-time temperature, stress, and vibration modal data are collected from the site, and the collected data is automatically stored in the terminal database to ensure continuous and complete data.

[0069] The collected physical field feature data is then preprocessed using a moving average filtering algorithm with a sliding window size of 5-10 acquisition cycles. Temperature and stress time-series data are smoothed to remove transient noise. For vibration modal data, a fast Fourier transform is used to convert the time-domain signal to the frequency-domain signal, extracting key feature parameters such as vibration frequency and amplitude. The preprocessed physical field feature data is then converted to CSV format to ensure compatibility with the import format of the measured digital twin model. After the basic geometric construction of the measured digital twin model is completed through point cloud modeling and BIM registration, further supplementation is needed to build the built-in physical field-geometric deviation mapping relationship. The specific steps are as follows: Step a: Taking Q355B steel, a commonly used grade of steel in modular steel structures for aerial building machines, as an example, retrieve the basic parameters of this steel that are well-known in the field of building steel structures, among which the coefficient of thermal expansion and contraction is... The elastic modulus is 206 GPa. Data was obtained through indoor simulation experiments. The specific parameter ranges for the experiment were set as follows: temperature gradient from -10℃ to 50℃, divided into 7 gradients in every 10℃ increments; stress load from 0MPa to 300MPa, divided into 7 levels in every 50MPa increments; vibration frequency from 5Hz to 500Hz, selected at 10 frequency points in every 50Hz intervals, forming 3×7×10=210 complete sets of experimental parameter combinations.

[0070] Step b: Select Q355B steel of the same material as the non-standard corner column head to make a standard specimen. The specimen size is consistent with the cross-sectional size of the key stress parts of the actual component. Use a laser displacement meter with an accuracy of ≤±0.01mm to measure the horizontal X-axis, Y-axis and vertical Z-axis geometric displacement of the specimen under various experimental conditions. The measurement points are selected from two key feature points: the center point of the specimen end face and the center of the simulated bolt hole. Use an electronic inclinometer with an accuracy of ≤±0.001° to measure the tilt angle deviation around the horizontal X-axis and the horizontal rotation angle deviation around the vertical Z-axis. Repeat the measurement 3 times under each parameter combination and take the average value as the valid data.

[0071] Step c: Import all valid experimental data into the data fitting software Origin. The selection criterion for the fitting method is: if the physical field parameters and geometric deviations are linearly distributed, that is, the correlation coefficient is determined through correlation analysis. Using linear regression, the goodness of fit is required. If the distribution is nonlinear, a second-order polynomial fitting is used, requiring the sum of squared residuals. Empirical formulas are established for the relationship between temperature change and X / Y / Z displacement, rotation angle deviation around the X / Z axis, stress value and the above-mentioned geometric deviations, and vibration amplitude and the above-mentioned geometric deviations. All empirical formulas are then integrated to form a complete physical field-geometric deviation mapping relationship.

[0072] Step d: The physical field-geometric deviation mapping relationship is embedded into the data analysis module of the measured digital twin model in a standardized mathematical expression format. This is achieved through the model's built-in data interface. The comprehensive influence of multiple physical field parameters on geometric deviation is calculated using a weighted superposition logic. The weight coefficients are determined based on the deviation contribution ratio when each physical field acts alone, specifically derived from statistical analysis of experimental data. This clarifies the quantitative correspondence between each physical field parameter and the geometric deviation, ensuring that the model can accurately deduce the geometric pose changes of non-standard corner column heads based on the input physical field data.

[0073] The converted physical field feature data is then imported into the measured digital twin model. The model automatically reads parameters such as temperature, stress, and vibration, and uses the built-in physical field-geometric deviation mapping relationship for real-time simulation. Based on the input temperature data, the expansion and contraction of the component due to temperature changes and the rotational deviation are calculated using the thermal expansion and contraction formula. Based on the stress data, the micro-deformation of the structure caused by stress is calculated using the material's elastic modulus. Based on the vibration modal parameters, the influence of vibration on the spatial position of the component is analyzed. The geometric deviations corresponding to temperature, stress, and vibration are superimposed and integrated to generate the predicted geometric pose of the non-standard corner column head under the action of the physical field, including three-dimensional spatial coordinates and attitude angle information.

[0074] Subsequently, a total station was used to measure the actual spatial pose of the non-standard corner column head in real time, with the measurement accuracy controlled within ±0.1mm. Measured geometric pose data, including measured 3D coordinates and measured attitude angles, were obtained. The predicted geometric pose generated by the simulation was compared with the measured geometric pose. The Euclidean distance formula was used to calculate the coordinate differences in the horizontal X, Y, and vertical Z directions, and the attitude angle difference was calculated using the vector angle formula. The set of these coordinate and angle differences constitutes the dynamic correction value. The dynamic correction value was superimposed on the original target installation compensation value. If the original compensation value was a fixed value, it was directly updated by algebraic addition. If the compensation value was already encoded and attached to the component, the updated compensation value was re-encoded via a data acquisition terminal or stored in a readable and writable electronic tag, achieving real-time updates of the target installation compensation value and ensuring that the compensation value could dynamically adapt to geometric deviations caused by changes in the on-site physical field.

[0075] Through the above steps, the target installation compensation value is updated in real time, effectively offsetting the impact of changes in the on-site physical field on the corner accuracy of the steel structure, and improving the dynamic precision control capability of the modular assembly of the aerial building machine.

[0076] Furthermore, the method provided in this application embodiment includes: An error propagation prediction model is trained based on historical corner deviation data of the constructed floors to predict the cumulative error trend during the lifting process from the current floor to the future M floors, where M is a positive integer greater than 2. Based on the cumulative error trend, the inverse phase of the cumulative error trend is superimposed on the current compensation value to perform predicted corner accuracy control, so that the non-standard corner column head can offset the predicted cumulative deviation during installation.

[0077] In one embodiment, the historical corner deviation data for constructed floors refers to the cumulative deviation between the actual installation posture and the design target posture of the non-standard corner column head in each floor where assembly has been completed. Its core includes the cumulative deviation data in the horizontal X-axis, Y-axis, and rotational direction around the Z-axis. This data is obtained as follows: Within 24 hours after the alignment control of the non-standard corner column head assembly on each constructed floor is completed, a total station with an accuracy ≤ ±0.1mm is used, with the measured coordinates of the connection ports of adjacent standard modules installed on that floor as a reference, to measure the three-dimensional actual coordinates and attitude angles of the key feature points (end face center point, simulated bolt hole center) of the non-standard corner column head. Simultaneously, the construction records for that floor are retrieved to obtain the corresponding target posture data (including design coordinates and attitude angles), actual installation compensation values, jacking operation time, and the average ambient temperature during construction collected by distributed sensor nodes. By calculating the difference between the measured coordinates and the target coordinates in the horizontal X and Y directions, and the difference between the measured attitude angle and the target attitude angle, the difference in each direction is accumulated with the deviation of the corresponding direction of all previous floors to obtain the cumulative angle deviation value of the floor. After being associated with the above construction-related data, it is stored sequentially according to the floor number to form a complete historical angle deviation dataset.

[0078] Next, the historical corner deviation dataset was preprocessed. First, the 3σ principle was used to remove outliers: the mean and standard deviation of each feature data were calculated, and data exceeding ±3 times the standard deviation were identified as outliers and deleted to avoid data distortion caused by accidental factors such as hoisting errors or extreme weather. Then, data standardization was performed: floor numbers were encoded as consecutive integers from 1, 2, 3 to N, where N is the total number of floors constructed; the mean ambient temperature was retained to one decimal place; the jacking operation time was converted to minutes; and installation compensation and cumulative deviation values ​​were retained to two decimal places, ensuring a consistent data format. Finally, the dataset was divided into training and validation sets in a 7:3 ratio. The training set was used for model parameter learning, and the validation set was used for model accuracy verification. Random sampling was used during the partitioning process to ensure consistent data distribution.

[0079] Next, the error propagation prediction model is constructed using the Gradient Boosting Tree (XGBoost) model. The core of the model comprises three modules: a data input layer, a gradient boosting decision tree layer, and an output layer. The data input layer receives standardized feature data. The gradient boosting decision tree layer consists of 100 base decision trees, each with a depth of 3 to avoid overfitting. The output layer is a continuous value prediction module used to output the cumulative error trend. Model training is implemented using the Python XGBoost open-source library. The core hyperparameters are set as follows: a learning rate of 0.1 to control the contribution weight of each decision tree; a subsample ratio of 0.8, meaning that 80% of the training set data is randomly selected during training of each decision tree to improve the model's generalization ability; a regularization parameter λ of 1.0 to suppress model complexity; and a mean squared error (MSE) objective function to minimize the deviation between the predicted and true values.

[0080] The training steps are as follows: First, import the preprocessed training set data. The input features are defined as floor number, installation compensation value, jacking operation duration, and average ambient temperature. The output label is set as the cumulative deviation value of the corner, including the cumulative deviations in the horizontal X-axis, Y-axis, and rotational direction around the Z-axis. Then, initialize the model, call the XGBRegressor class to load the aforementioned hyperparameters, input the training set data into the model for iterative training, and calculate the mean squared error using the validation set every 20 iterations. When the mean squared error of the validation set does not decrease after three consecutive iterations, stop training and save the trained model file.

[0081] After model training, cumulative error trend prediction is performed. First, the current floor number and current installation compensation value are obtained. Combined with the average lifting operation time of already constructed floors, the expected lifting time for the next M floors is determined. The predicted environmental temperature for the next M floors is determined by referring to historical ambient temperature data for the same period, where M is a positive integer greater than 2. After the above data is formatted according to preprocessing standards, it is input into the trained gradient boosting tree model. The model receives feature data through the data input layer, performs calculations through the gradient boosting decision tree layer, and then outputs the cumulative error prediction values ​​for each floor of the next M floors in the horizontal X-axis, Y-axis, and rotational direction around the Z-axis, forming a complete cumulative error trend.

[0082] Finally, based on the predicted cumulative error trend, the inverse phase of the cumulative error in each direction is calculated, i.e., keeping the numerical values ​​consistent but the directions opposite. This inverse phase is then superimposed on the current installation compensation value to obtain the predicted installation compensation value for each floor of the future M-layer. During the installation of non-standard corner column heads on each floor in the future, spatial registration and attitude adjustment are performed based on the updated predicted installation compensation value. By offsetting the predicted cumulative deviation in advance, predictive control of corner accuracy is achieved.

[0083] By standardizing historical data collection and preprocessing, constructing and training a gradient boosting tree model with clear parameters, and accurately predicting error trends and optimizing compensation values, the cumulative corner error of the modular steel structure of the aerial building machine was controlled in advance, effectively improving the corner accuracy and stability of multi-story continuous construction.

[0084] In summary, the method for controlling the corner accuracy of a modular steel structure for an aerial building machine provided in this application has the following technical effects: This application constructs a measured digital twin model containing manufacturing errors through pre-setting a geometric tolerance adjustment domain, physical pre-assembly, and 3D laser scanning. It calculates the target installation compensation value and attaches a code. Using the measured coordinates of adjacent standard modules as a reference, it completes spatial registration and attitude adjustment. Based on the angle attitude adjustment parameters, it controls the assembly and precisely ensures the angle assembly accuracy of the modular steel structure of the aerial building machine. This achieves the technical effect of precise docking of the angle of the modular steel structure of the aerial building machine, ensuring the overall structural safety and construction quality.

[0085] Example 2, as Figure 2 As shown, based on the same inventive concept as in Embodiment 1, this application provides a modular steel structure cornering accuracy control system for an aerial building machine, the system comprising: The geometric tolerance adjustment domain setting module 1 is used to preset a geometric tolerance adjustment domain at the splicing interface between the non-standard corner column head and the horizontal steel truss and the vertical steel truss. The geometric tolerance adjustment domain is used to provide the mechanical adjustment margin of the non-standard corner column head relative to the standard module.

[0086] The measured digital twin model construction module 2 is used to pre-assemble the non-standard corner column head and the standard module, obtain the spatial pose data of the actual assembly state through three-dimensional laser scanning, and generate a measured digital twin model containing manufacturing error information.

[0087] The target installation compensation value acquisition module 3 calculates the target installation compensation value of the non-standard corner column head based on the measured digital twin model, and attaches the compensation value to the non-standard corner column head in the form of a code.

[0088] The corner attitude adjustment parameter acquisition module 4 is used to hoist the non-standard corner column head carrying the code to the high-altitude operation position, and based on the installation compensation value in the code, use the measured spatial coordinates of the connection port of the adjacent installed standard module as the registration reference, and use the geometric tolerance adjustment domain to perform spatial registration and attitude adjustment on the non-standard corner column head to determine the corner attitude adjustment parameters.

[0089] Assembly alignment control execution module 5 is used to perform assembly alignment control of the aerial building machine according to the angle attitude adjustment parameters.

[0090] Furthermore, the geometric tolerance adjustment domain setting module 1 is used to perform the following steps: Based on the long connecting bolt holes set at the horizontal connection end face of the non-standard corner column head and the horizontal steel truss, with the long axis of the long connecting bolt holes arranged along the axis of the horizontal truss, the mechanical connection allowance of the sliding groove of the long connecting bolt holes and the connecting slider of the horizontal steel truss is analyzed to obtain the horizontal tolerance adjustment range; based on the automatic guidance and angle adjustment allowance of the vertical connection end face of the non-standard corner column head and the vertical steel truss, the vertical tolerance adjustment range is obtained; based on the horizontal tolerance adjustment range and the vertical tolerance adjustment range, the preset geometric tolerance adjustment range is determined.

[0091] Furthermore, the geometric tolerance adjustment domain setting module 1 is used to perform the following steps: A digital assembly of a building-in-the-sky machine is established based on the BIM model of the target building structure. The assembly process of the non-standard corner column head and standard modules is simulated in the BIM model, and virtual collision checks and gap analyses are performed to obtain simulation results. Based on the simulation results, the angle of the assembly gap is fitted by rotation. Under the construction assembly constraints of the target building structure, the optimal size parameters of the geometric tolerance adjustment domain are determined. Based on the optimal size parameters, the geometric tolerance adjustment domain is preset under the constraint of the load-bearing capacity requirements of the connecting structure.

[0092] Furthermore, the measured digital twin model construction module 2 is used to perform the following steps: The non-standard corner column head is naturally fitted and trial-assembled with the corresponding numbered standard horizontal steel truss and standard vertical steel truss according to the design theoretical angle; a three-dimensional laser scanner is used to measure the gap distribution and relative pose between the non-standard corner column head and the standard module without applying forced assembly force; based on the gap distribution and relative pose between the non-standard corner column head and the standard module, spatial position relationship is projected to obtain the spatial pose data.

[0093] Furthermore, the measured digital twin model construction module 2 is used to perform the following steps: Based on the actual assembly status data obtained by 3D laser scanning, the modular steel structure of the aerial building machine is mirrored and projected to construct a measured digital twin model of the aerial building machine. Based on the BIM model of the target building structure, an embedded calibration module is established to perform spatial registration with the digital twin model and identify the spatial manufacturing error information between the actual assembly status data and the BIM model.

[0094] Furthermore, the target installation compensation value acquisition module 3 is used to perform the following steps: Using the measured digital twin model, spatial alignment is performed between the actual assembly status data and the target data of the BIM model to identify theoretical errors in the model; based on the spatial pose data, spatial error decoupling is performed based on the theoretical errors in the model to determine the target installation compensation values ​​of the non-standard corner column head in the horizontal X-axis, Y-axis and rotational direction around the Z-axis.

[0095] Furthermore, the angle attitude adjustment parameter acquisition module 4 is used to perform the following steps: The target installation compensation amount in the code is decomposed into components, including translation compensation components and rotation compensation components. The translation compensation component includes offsets in the horizontal X, horizontal Y, and vertical Z directions; the rotation compensation component includes tilt corrections around the horizontal axis and horizontal rotation corrections around the vertical axis. Based on the translation compensation components and the vertical tolerance adjustment domain, self-guiding coarse positioning is performed, causing the non-standard corner column head to automatically slide to a coarse alignment state close to the target pose under gravity, eliminating initial horizontal and vertical deviations. Based on the rotation compensation components and translation compensation components... Within the mechanical degrees of freedom of the horizontal tolerance adjustment domain, with the goal of eliminating residual deviations, an external fine-tuning force is applied to cause the non-standard corner head to make slight translation and rotation relative to the adjacent installed standard module, achieving a precise alignment state. During the precise alignment process, the gap distribution between the non-standard corner head and the adjacent installed standard module is measured in real time. The required shim thickness combination and bolt tightening sequence are calculated based on the gap distribution. The shim thickness combination, bolt tightening sequence, and final target pose data are recorded as the corner attitude adjustment parameters.

[0096] Furthermore, the measured digital twin model construction module 2 is used to perform the following steps: Real-time physical field characteristic data, including real-time temperature, stress, and vibration modes, are collected by distributed sensing nodes. The physical field characteristic data is input into the measured digital twin model, and real-time simulation is performed based on the physical field-geometric deviation mapping relationship to generate the predicted geometric pose of the physical field. The predicted geometric pose of the physical field is compared with the measured geometric pose, and the difference is calculated as a dynamic correction amount. The target installation compensation value is updated in real time based on the dynamic correction amount.

[0097] Furthermore, the assembly alignment control execution module 5 is used to perform the following steps: An error propagation prediction model is trained based on historical corner deviation data of the constructed floors to predict the cumulative error trend during the lifting process from the current floor to the future M floors, where M is a positive integer greater than 2. Based on the cumulative error trend, the inverse phase of the cumulative error trend is superimposed on the current compensation value to perform predicted corner accuracy control, so that the non-standard corner column head can offset the predicted cumulative deviation during installation.

[0098] The modular steel structure cornering accuracy control system for aerial building construction machines provided in this embodiment of the invention can execute the modular steel structure cornering accuracy control method for aerial building construction machines provided in any embodiment of the invention, and has the corresponding functional modules and beneficial effects of the execution method.

[0099] Although this application makes various references to certain modules in the system according to the embodiments of this application, any number of different modules can be used and run on user terminals and / or servers. The various units and modules included are only divided according to functional logic, but are not limited to the above division, as long as the corresponding functions can be achieved; in addition, the specific names of each functional unit are only for easy distinction between each other and are not used to limit the scope of protection of this invention.

[0100] The specific embodiments described above do not constitute a limitation on the scope of protection of this application. Those skilled in the art should understand that various modifications, combinations, and substitutions can be made according to design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of this application should be included within the scope of protection of this application. In some cases, the actions or steps described in this application can be performed in a different order than that shown in the embodiments and still achieve the desired results. Furthermore, the processes depicted in the accompanying drawings do not necessarily require a specific or sequential order to achieve the desired results. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

Claims

1. A method for controlling the corner accuracy of a modular steel structure for an aerial building machine, characterized in that, include: At the splicing interface between the non-standard corner column head and the horizontal and vertical steel trusses, a geometric tolerance adjustment range is preset. The geometric tolerance adjustment range is used to provide the mechanical adjustment margin of the non-standard corner column head relative to the standard module. The non-standard corner column head and standard module are pre-assembled in a physical manner. Spatial pose data of the actual assembly state are obtained by three-dimensional laser scanning to generate a measured digital twin model containing manufacturing error information. The target installation compensation value of the non-standard corner column head is calculated based on the measured digital twin model, and the compensation value is attached to the non-standard corner column head in the form of a code; The non-standard corner column head carrying the code is hoisted to the high-altitude work position. Based on the installation compensation value in the code, the measured spatial coordinates of the connection port of the adjacent installed standard module are used as the registration reference. The non-standard corner column head is spatially registered and its attitude is adjusted using the geometric tolerance adjustment domain to determine the corner attitude adjustment parameters. The assembly and alignment control of the aerial building machine is performed based on the aforementioned angle attitude adjustment parameters; The preset geometric tolerance adjustment range includes: Based on the long connecting bolt holes set at the horizontal connection end face of the non-standard corner column head and the horizontal steel truss, the long axis of the long connecting bolt holes is arranged along the axis of the horizontal truss. The mechanical connection allowance of the sliding groove of the long connecting bolt holes and the connecting slider of the horizontal steel truss is analyzed to obtain the horizontal tolerance adjustment range. Based on the automatic guidance and angle adjustment margin of the non-standard corner column head and the vertical connection end face of the vertical steel truss, the vertical tolerance adjustment range is obtained. Based on the horizontal tolerance adjustment domain and the vertical tolerance adjustment domain, a preset geometric tolerance adjustment domain is determined.

2. The method for controlling the corner accuracy of modular steel structures in aerial building construction machines according to claim 1, characterized in that, At the interface between the non-standard corner column head and the horizontal and vertical steel trusses, a preset geometric tolerance adjustment range is included, which also includes: A digital assembly of the aerial building machine is established based on the BIM model of the target building structure; The assembly process of the non-standard corner column head and the standard module is simulated in the BIM model, and virtual collision checks and gap analysis are performed to obtain simulation results. Based on the simulation results, the angle rotation fitting of the assembly gap is performed, and the optimal size parameters of the geometric tolerance adjustment domain are determined under the construction assembly constraints of the target building structure. Based on the optimal size parameters, a preset geometric tolerance adjustment range is established while meeting the load-bearing capacity requirements of the connector structure.

3. The method for controlling the corner accuracy of modular steel structures in aerial building construction machines according to claim 1, characterized in that, Acquire spatial pose data in the actual assembly state, including: The non-standard corner column head is naturally fitted and trial-assembled with the corresponding numbered standard horizontal steel truss and standard vertical steel truss according to the design theoretical angle. A 3D laser scanner was used to measure the gap distribution and relative pose between the non-standard corner column head and the standard module without applying forced assembly force. Based on the gap distribution and relative pose between the non-standard corner column and the standard module, spatial position relationship projection is performed to obtain the spatial pose data.

4. The method for controlling the corner accuracy of modular steel structures in aerial building construction machines according to claim 2, characterized in that, Generate a measured digital twin model containing manufacturing error information, including: Based on the actual assembly status data obtained by 3D laser scanning, the modular steel structure of the aerial building machine is mirrored and projected to construct a measured digital twin model of the aerial building machine. Based on the BIM model of the target building structure, an embedded calibration module is established to perform spatial registration with the digital twin model and identify the spatial manufacturing error information between the actual assembly status data and the BIM model.

5. The method for controlling the corner accuracy of the modular steel structure of the aerial building machine according to claim 4, characterized in that, The target installation compensation value of the non-standard corner column head is calculated based on the measured digital twin model, including: By using the measured digital twin model, spatial alignment is performed between the actual assembly status data and the target data of the BIM model to identify theoretical errors in the model. Based on the spatial pose data, spatial error decoupling is performed based on the theoretical error of the model to determine the target installation compensation values ​​of the non-standard corner column in the horizontal X-axis, Y-axis and rotational direction around the Z-axis.

6. The method for controlling the corner accuracy of modular steel structures in aerial building construction machines according to claim 1, characterized in that, Using the measured spatial coordinates of the connection ports of adjacent installed standard modules as the registration reference, the non-standard corner head is spatially registered and its attitude adjusted using the geometric tolerance adjustment domain, including: The target installation compensation amount in the code is decomposed into components, including translation compensation components and rotation compensation components. The translation compensation components include the offsets in the horizontal X direction, horizontal Y direction, and vertical Z direction; the rotation compensation components include the tilt angle correction around the horizontal axis and the horizontal rotation angle correction around the vertical axis. Based on the translation compensation component, self-guided coarse positioning is performed based on the vertical tolerance adjustment domain, so that the non-standard corner column head automatically slides to a coarse alignment state close to the target pose under the action of gravity, eliminating the initial horizontal and vertical deviations. Based on the residual values ​​of the rotation compensation component and the translation compensation component, within the mechanical degrees of freedom in the horizontal tolerance adjustment domain, with the goal of eliminating residual deviation, an external fine-tuning force is applied to make the non-standard corner column head perform a slight translation and rotation relative to the adjacent installed standard module to achieve a precise alignment state. During the precision alignment process, the gap distribution between the non-standard corner column and the adjacent installed standard module is measured in real time. The required gasket thickness combination and bolt tightening sequence are calculated based on the gap distribution. The combination of shim thickness, bolt tightening sequence, and final target pose data are recorded as the angle attitude adjustment parameters.

7. The method for controlling the corner accuracy of modular steel structures in aerial building construction machines according to claim 4, characterized in that, Also includes: Real-time data collection of on-site physical field characteristics, including real-time temperature, stress, and vibration modes, is achieved through distributed sensing nodes. The physical field feature data is input into the measured digital twin model, and real-time simulation is performed based on the physical field-geometric deviation mapping relationship to generate the physical field predicted geometric pose. The predicted geometric pose of the physical field is compared with the measured geometric pose, and the difference is calculated as a dynamic correction value. The target installation compensation value is updated in real time based on the dynamic correction value.

8. The method for controlling the corner accuracy of modular steel structures in aerial building construction machines according to claim 1, characterized in that, Also includes: An error propagation prediction model is trained based on historical corner deviation data of existing floors to predict the cumulative error trend during the lifting process from the current floor to the future M floors, where M is a positive integer greater than 2. Based on the cumulative error trend, the inverse of the cumulative error trend is superimposed on the current compensation value to perform predictive corner accuracy control, so that the non-standard corner head can offset the predicted cumulative deviation during installation.

9. A modular steel structure cornering accuracy control system for an aerial building machine, characterized in that, A method for controlling the corner accuracy of a modular steel structure for an aerial building machine as described in any one of claims 1-8, the system comprising: The geometric tolerance adjustment range setting module is used to preset the geometric tolerance adjustment range at the splicing interface between the non-standard corner column head and the horizontal steel truss and the vertical steel truss. The geometric tolerance adjustment range is used to provide the mechanical adjustment margin of the non-standard corner column head relative to the standard module. The measured digital twin model construction module is used to pre-assemble the non-standard corner column head and the standard module in a physical manner, obtain the spatial pose data of the actual assembly state through three-dimensional laser scanning, and generate a measured digital twin model containing manufacturing error information. The target installation compensation value acquisition module calculates the target installation compensation value of the non-standard corner column head based on the measured digital twin model, and attaches the compensation value to the non-standard corner column head in the form of a code; The corner attitude adjustment parameter acquisition module is used to hoist the non-standard corner column head carrying the code to the high-altitude operation position. Based on the installation compensation value in the code, the measured spatial coordinates of the connection port of the adjacent installed standard module are used as the registration reference. The geometric tolerance adjustment domain is used to perform spatial registration and attitude adjustment on the non-standard corner column head to determine the corner attitude adjustment parameters. The assembly alignment control execution module is used to perform assembly alignment control of the aerial building machine according to the angle attitude adjustment parameters. The geometric tolerance adjustment domain setting module is used to: obtain a horizontal tolerance adjustment domain by analyzing the mechanical connection allowance between the sliding groove of the long connecting bolt hole and the connecting slider of the horizontal steel truss, based on the long connecting bolt hole provided at the horizontal connection end face of the non-standard corner column head and the horizontal steel truss, wherein the long axis of the long connecting bolt hole is arranged along the axis of the horizontal truss; obtain a vertical tolerance adjustment domain based on the automatic guidance and angle adjustment allowance of the vertical connection end face of the non-standard corner column head and the vertical steel truss; and determine a preset geometric tolerance adjustment domain based on the horizontal tolerance adjustment domain and the vertical tolerance adjustment domain.

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