Building construction scheme dynamic collaborative design system and method based on real-time surveying and mapping

Abstract

The invention provides a building construction scheme dynamic collaborative design system and method based on real-time surveying and mapping, and belongs to the technical field of building construction management and intelligent construction, and the system comprises a data collection module which is used for collecting surveying and mapping data of a construction site through a multi-source sensor, and generating real-time surveying and mapping data; the data analysis module is used for comparing the real-time surveying and mapping data with a preset BIM model so as to identify a construction deviation area and obtain key deviation parameters; the deviation acquisition module is used for determining a dynamic deviation coefficient based on the key deviation parameter and the construction deviation area; the strategy generation module is used for dividing deviation grades according to the numerical range of the dynamic deviation coefficient and generating a corresponding construction response strategy; and the deviation correction module executes the construction response strategy, verifies a deviation correction result based on the executed surveying and mapping data, and updates the dynamic deviation coefficient until the deviation correction result meets a preset requirement. And the accuracy and efficiency of the construction process are improved.

Description

Technical Field

[0001] The present invention relates to the technical field of construction management and intelligent construction, and particularly to a dynamic collaborative design system and method for construction plans based on real-time surveying and mapping. Background Art

[0002] With the development of the construction industry, deviation control during the construction process has become an important factor in ensuring construction quality and progress. Traditional construction deviation monitoring relies on manual inspections and static data, making it difficult to detect and correct problems during the construction process in a timely manner, resulting in delays in construction progress and increased costs. In recent years, the combination of BIM (Building Information Modeling) and real-time surveying and mapping technologies has become a key means to improve construction accuracy and efficiency.

[0003] Currently, many construction management systems use a combination of BIM models and sensor data for deviation detection, but these solutions usually have problems such as poor real-time performance and lagging deviation correction. For example, some systems can only perform static comparisons of deviations and cannot achieve dynamic adjustment and real-time feedback. Existing technologies mostly rely on manual intervention. After construction deviations are discovered, manual judgment and manual adjustment of the construction plan are required, resulting in low efficiency in correcting construction deviations. The main defects of existing technical solutions are that deviation monitoring and correction cannot be coordinated in real time, lack a dynamic deviation correction mechanism, and the system has a slow response speed to deviations. In addition, existing technologies mostly rely on static analysis, making it difficult to achieve continuous optimization and automated adjustment of construction plans, and unable to make full use of real-time surveying and mapping data to work in collaboration with BIM models, resulting in inaccurate and inefficient construction deviation correction.

[0004] Therefore, the present invention provides a dynamic collaborative design system and method for construction plans based on real-time surveying and mapping. Summary of the Invention

[0005] The present invention provides a dynamic collaborative design system and method for construction plans based on real-time surveying and mapping, which realizes real-time monitoring and automatic correction of construction deviations through the dynamic collaboration of real-time surveying and mapping data and BIM models. Compared with existing technologies, it can obtain real-time surveying and mapping data of the construction site, and optimize the deviation correction strategy through spatio-temporal registration algorithms and dynamic deviation coefficients, avoiding the problems of lagging deviation correction and relying on manual adjustment in traditional solutions, improving the accuracy and efficiency of the construction process, and ensuring the precise control of construction quality and progress.

[0006] According to the dynamic collaborative design system for construction plans based on real-time surveying and mapping provided by the present invention, it includes:

[0007] A data acquisition module: used to collect surveying and mapping data of the construction site through multi-source sensors, and use spatio-temporal registration algorithms to unify surveying and mapping data from several sources under the global construction coordinate system to generate real-time surveying and mapping data;

[0008] Data analysis module: used to compare real-time surveying and mapping data with a preset BIM model, thereby identifying construction deviation areas, and obtaining key deviation parameters in combination with real-time surveying and mapping data;

[0009] Deviation acquisition module: determine the dynamic deviation coefficient based on the key deviation parameters and the construction deviation area;

[0010] Strategy generation module: divide the deviation level according to the numerical range of the dynamic deviation coefficient, and generate corresponding construction response strategies;

[0011] Deviation correction module: execute the construction response strategy and obtain the surveying and mapping data after execution, verify the deviation correction result based on the surveying and mapping data after execution, update the dynamic deviation coefficient based on the deviation correction result until the deviation correction result meets the preset requirements.

[0012] Preferably, the data acquisition module includes:

[0013] Multi-source data acquisition unit: obtain the overall three-dimensional point cloud data of the construction area through a ground-fixed laser scanner, obtain local fine surveying and mapping data through a mobile measurement device, and obtain the real-time pose data of the mechanical working surface through a positioning sensor carried by the construction machinery;

[0014] Spatio-temporal registration unit: perform time synchronization processing on the data collected by multi-source sensors, establish the conversion relationship between the coordinate systems corresponding to all acquisition devices, and unify the surveying and mapping data from all sources into the construction global coordinate system through the spatio-temporal registration algorithm;

[0015] Data fusion unit: perform fusion processing on all surveying and mapping data to generate real-time surveying and mapping data.

[0016] Preferably, the data analysis module includes:

[0017] Data extraction unit: extract the significant feature point set in the real-time surveying and mapping data, and at the same time, identify the corresponding theoretical feature point set in the preset BIM model;

[0018] Initial registration unit: perform initial registration on the significant feature point set and the theoretical feature point set through a feature matching algorithm, and determine the preliminary registration error, and determine the registration quality based on the preliminary registration error;

[0019] Grid construction unit: if the registration quality meets the preset requirements, construct a three-dimensional space grid based on the initial registration;

[0020] Region candidate unit: perform local geometric feature comparison within the three-dimensional space grid to obtain the geometric difference degree of each grid unit, and use the grid units with geometric difference degrees exceeding the preset difference degree threshold as candidate deviation regions;

[0021] Region determination unit: Merge spatially adjacent candidate deviation regions to generate deviation regions with continuous boundaries, and determine the deviation regions with continuous boundaries as construction deviation regions;

[0022] Parameter extraction unit: Determine the volume characteristics, spatial distribution characteristics, and time duration characteristics of the construction deviation region based on real-time surveying and mapping data as key deviation parameters.

[0023] Preferably, the parameter extraction unit includes:

[0024] Volume characteristic extraction subunit: Use the voxel grid division method to determine the volume percentage of the construction deviation region in the corresponding region of the preset BIM model;

[0025] Spatial distribution characteristic extraction subunit: Perform spatial distribution analysis on the real-time surveying and mapping data to determine the main direction of the spatial distribution of the deviation region, and determine the deviation angle between the main direction of the spatial distribution and the preset reference axis;

[0026] Time duration characteristic extraction subunit: Based on the first occurrence time of the deviation, the current construction progress, and the criticality of the current process, further determine the deviation duration impact coefficient:

[0027]

[0028] Among them, I is the deviation duration impact coefficient, record the first detection time of the deviation as t0, t c is the time corresponding to the current construction progress, t p is the pre-designed planned completion time of the current construction process, γ1 is the attenuation coefficient, and the value is based on the criticality of the process.

[0029] Preferably, the deviation acquisition module includes:

[0030] Weight determination unit: Determine the dynamic weight based on the construction deviation region:

[0031]

[0032] Among them, w v is the dynamic weight of the volume characteristic, w θ is the dynamic weight of the spatial distribution characteristic structure, w t is the dynamic weight of the time duration characteristic, α is the reference weight coefficient of the volume characteristic, β is the reference weight coefficient of the spatial distribution characteristic, γ is the reference weight coefficient of the time duration characteristic, η1 is the increase coefficient of the weight of the volume characteristic by the load-bearing structure, and η1 ∈ [0, 1], η2 is the increase coefficient of the weight of the time duration characteristic for the non-load-bearing structure, and η2 ∈ [0, 1], δ is the increase coefficient of the spatial range weight, and δ ∈ [0, 1], A is the actual area of the deviation region, A thrThe preset threshold of the deviation area, ReLU(A - A thr ) is the rectified linear unit function, and its function is: It is used to determine whether the deviation area exceeds the threshold A thr , if it exceeds, it participates in the weight adjustment. ξ1 is the amplification coefficient of the weight of the spatial distribution characteristics in the structural construction stage, and ξ1 ∈ [0, 1]. ξ2 is the amplification coefficient of the weight of the volume characteristics in the decoration construction stage, and ξ2 ∈ [0, 1]. d is the distance from the deviation area to the key structure, and d thr is the preset threshold of the critical distance;

[0033] Coefficient determination unit: Determine the dynamic deviation coefficient based on the dynamic weight and the key deviation parameters:

[0034]

[0035] Among them, DDC is the dynamic deviation coefficient.

[0036] Preferably, the strategy generation module includes:

[0037] Level division unit: Divide the construction deviation into several deviation levels according to the numerical range of the dynamic deviation coefficient;

[0038] Strategy matching unit: Match the corresponding strategy for each deviation level in the preset response strategy library, and generate a construction response strategy including specific operation instructions.

[0039] Preferably, the deviation correction module includes:

[0040] Instruction issuing unit: Convert the construction response strategy into an executable instruction and send it to the corresponding construction terminal device;

[0041] Effect verification unit: Obtain the surveyed and mapped data after execution, and verify the execution effect of the deviation correction measures;

[0042] Iterative optimization unit: Adjust the dynamic weight corresponding to the dynamic deviation coefficient according to the verification result until the deviation correction result meets the preset requirements.

[0043] According to the dynamic collaborative design method of building construction plan based on real-time surveying and mapping provided by the present invention, it includes:

[0044] Step 1: It is used to collect the surveyed and mapped data of the construction site through multi-source sensors, and use the spatio-temporal registration algorithm to unify the surveyed and mapped data from several sources into the construction global coordinate system to generate real-time surveyed and mapped data;

[0045] Step 2: It is used to compare the real-time surveyed and mapped data with the preset BIM model, and then identify the construction deviation area, and obtain the key deviation parameters in combination with the real-time surveyed and mapped data;

[0046] Step 3: Determine the dynamic deviation coefficient based on the key deviation parameters and the construction deviation area;

[0047] Step 4: Divide the deviation levels according to the value range of the dynamic deviation coefficient and generate corresponding construction response strategies;

[0048] Step 5: Execute the construction response strategy and obtain the surveying and mapping data after execution. Verify the deviation correction result based on the surveying and mapping data after execution, and update the dynamic deviation coefficient based on the deviation correction result until the deviation correction result meets the preset requirements.

[0049] Compared with the prior art, the beneficial effects of the present application are as follows:

[0050] Through the dynamic collaboration between real-time surveying and mapping data and the BIM model, the real-time monitoring and automatic correction of construction deviations are realized. Compared with the prior art, it is possible to obtain the surveying and mapping data of the construction site in real time, and optimize the deviation correction strategy through the spatio-temporal registration algorithm and the dynamic deviation coefficient, avoiding the problems of lagging deviation correction and relying on manual adjustment in the traditional scheme, improving the accuracy and efficiency of the construction process, and ensuring the precise control of construction quality and progress. Description of the Drawings

[0051] In order to more clearly illustrate the technical solutions in the present invention or the prior art, the following will briefly introduce the drawings required for the description of the embodiments or the prior art. Obviously, the drawings in the following description are some embodiments of the present invention. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative efforts.

[0052] Figure 1 is a schematic structural diagram of a dynamic collaborative design system for building construction plans based on real-time surveying and mapping provided by an embodiment of the present invention.

[0053] Figure 2 is a schematic flowchart of a dynamic collaborative design method for building construction plans based on real-time surveying and mapping provided by an embodiment of the present invention. Detailed Embodiments

[0054] To make the objectives, technical solutions, and advantages of the present invention clearer, the following will clearly and completely describe the technical solutions in the present invention with reference to the drawings in the present invention. Obviously, the described embodiments are some, but not all, of the embodiments of the present invention. All other embodiments obtained by those of ordinary skill in the art without creative efforts based on the embodiments in the present invention belong to the scope of protection of the present invention.

[0055] Example 1:

[0056] The embodiment of the present invention provides a dynamic collaborative design system for building construction plans based on real-time surveying and mapping, as Figure 1 shown, including:

[0057] Data acquisition module: used to collect surveying and mapping data of the construction site through multi-source sensors, and adopt a spatio-temporal registration algorithm to unify surveying and mapping data from several sources under the global construction coordinate system to generate real-time surveying and mapping data;

[0058] Data analysis module: used to compare real-time surveying and mapping data with a preset BIM model, and then identify the construction deviation area, and obtain key deviation parameters in combination with real-time surveying and mapping data;

[0059] Deviation acquisition module: determine the dynamic deviation coefficient based on the key deviation parameters and the construction deviation area;

[0060] Strategy generation module: divide the deviation level according to the numerical range of the dynamic deviation coefficient, and generate corresponding construction response strategies;

[0061] Deviation correction module: execute the construction response strategy and obtain the surveying and mapping data after execution, verify the deviation correction result based on the surveying and mapping data after execution, update the dynamic deviation coefficient based on the deviation correction result until the deviation correction result meets the preset requirements.

[0062] In this embodiment, the global construction coordinate system refers to a unified coordinate system used to provide a consistent reference framework for various data and models during the building construction process. This coordinate system is usually based on the geographical location of the construction site, the specific requirements of the building structure, and the standards of surveying and mapping tools to ensure that data from different sensors or measurement sources can be seamlessly integrated. Through the spatio-temporal registration algorithm, data from different sensors are unified under this global coordinate system to ensure that the position of each data point in space can correctly correspond to the actual position of the construction site. Suppose GPS sensors and laser scanners are used to measure building components at different positions during building construction. In order to effectively compare and synthesize these two measurement results, they need to be unified into a common coordinate system so as to ensure that all data represents the same position of the construction site.

[0063] In this embodiment, the construction deviation area refers to the area where there is a difference between the measured data and the preset design (such as the BIM model) during the actual construction process. Construction deviations can be caused by factors such as construction errors, material problems, or equipment accuracy. When comparing the real-time surveying and mapping data with the BIM model, deviation areas will be identified. These areas may have differences in size, position, or shape, and need to be further corrected or adjusted. For example: when constructing a wall, the length of the wall is scheduled to be 10 meters on the design drawing, but through real-time surveying and mapping, it is found that the actual length of the wall is only 9.8 meters. This 0.2-meter difference is the construction deviation, and the area involved constitutes the "construction deviation area."

[0064] The beneficial effects of the above technical solution are: through the dynamic coordination of real-time surveying and mapping data and BIM models, real-time monitoring and automatic correction of construction deviations are achieved. Compared with the existing technology, it can obtain the surveying and mapping data of the construction site in real time, and optimize the deviation correction strategy through the spatiotemporal registration algorithm and dynamic deviation coefficient, avoiding the problems of deviation correction lag and reliance on manual adjustment in traditional solutions, improving the accuracy and efficiency of the construction process, and ensuring the precise control of construction quality and progress.

[0065] Embodiment 2:

[0066] The embodiment of the present invention provides a dynamic collaborative design system for building construction schemes based on real-time surveying and mapping, and a data acquisition module, including:

[0067] Multi-source data acquisition unit: obtain the overall 3D point cloud data of the construction area through a ground-mounted laser scanner, obtain local fine mapping data through mobile measurement equipment, and obtain the real-time posture data of the mechanical working surface through the positioning sensor carried by the construction machinery;

[0068] Spatiotemporal registration unit: performs time synchronization processing on the data collected by multi-source sensors, establishes the conversion relationship between the coordinate systems corresponding to all acquisition devices, and unifies the surveying and mapping data from all sources into the global construction coordinate system through the spatiotemporal registration algorithm;

[0069] Data fusion unit: fuses all surveying and mapping data to generate real-time surveying and mapping data.

[0070] In this embodiment, the transformation relationship refers to the mathematical relationship between different coordinate systems, which is used to transform data from one coordinate system to another. During the multi-source sensor data acquisition process, each sensor may have its own independent coordinate system. The transformation relationship is to determine how to transform the data points in one coordinate system to other coordinate systems, and finally unify all the data under a global coordinate system. This is the key to ensuring that data from different sources can work in harmony. Suppose the coordinate system of the three-dimensional point cloud data measured by a terrestrial laser scanner is different from the coordinate system of the positioning sensor on a construction machine. The transformation relationship is used to transform the coordinates of the laser scanner data to the same coordinate system as the machine coordinate system, ensuring that the measurement results of both can be compared and analyzed under the same reference framework.

[0071] In this embodiment, the spatio-temporal registration algorithm is an algorithm for aligning multi-source data in time and space. It not only takes into account the time differences when different data are acquired, but also deals with the spatial differences between different devices. Through this algorithm, it can be ensured that the surveying and mapping data from different sensors can be accurately merged and synchronized to the same unified global coordinate system. Suppose the terrestrial laser scanner and the positioning sensor mounted on a construction machine obtain data at different time points, and their coordinate systems are different. The spatio-temporal registration algorithm can accurately align the measurement results of these two data sources to the same time point and unified coordinate system according to the time stamps and spatial positions, making the data fusion and analysis more accurate.

[0072] In this embodiment, the fusion processing refers to integrating and processing data from different sensors or data sources, so that the final data set can provide more comprehensive and accurate information about the construction site. The fusion processing not only has to solve the differences in time and space, but also has to synthesize the data characteristics from different sources, remove redundant information, fill in data gaps, and ensure the consistency and efficiency of the data. For example, during the building construction process, a terrestrial laser scanner obtains the overall three-dimensional point cloud data, a mobile measurement device obtains the fine surveying and mapping data of a local area, and the construction machine provides the real-time operation pose data. The fusion processing process will unify and integrate the data from these different devices to generate a complete and seamless real-time surveying and mapping data set for subsequent analysis and decision-making.

[0073] The beneficial effects of the above technical solution are: Through the spatio-temporal registration and fusion processing of multi-source sensor data, the efficient integration of real-time surveying and mapping data from different devices can be achieved. This method ensures the accurate synchronization and unification of various types of data, provides a reliable basis for deviation monitoring and correction during the construction process, avoids data inconsistencies and manual interventions in traditional technologies, improves construction accuracy and efficiency, and optimizes construction management.

[0074] Embodiment 3:

[0075] An embodiment of the present invention provides a dynamic collaborative design system for building construction plans based on real-time surveying and mapping. The data analysis module includes:

[0076] A data extraction unit: extracts a set of significant feature points from the real-time surveying and mapping data. At the same time, it identifies the corresponding theoretical feature point set in the preset BIM model;

[0077] An initial registration unit: performs initial registration on the set of significant feature points and the theoretical feature point set through a feature matching algorithm, and determines the preliminary registration error. Based on the preliminary registration error, it determines the registration quality;

[0078] A grid construction unit: if the registration quality meets the preset requirements, a three-dimensional space grid is constructed based on the initial registration;

[0079] A region candidate unit: performs local geometric feature comparison within the three-dimensional space grid to obtain the geometric difference degree of each grid unit. The grid units with a geometric difference degree exceeding the preset difference degree threshold are candidate deviation regions;

[0080] A region determination unit: merges spatially adjacent candidate deviation regions to generate a deviation region with a continuous boundary, and determines the deviation region with a continuous boundary as the construction deviation region;

[0081] A parameter extraction unit: determines the volume feature, spatial distribution feature, and time duration feature of the construction deviation region based on the real-time surveying and mapping data as the key deviation parameters.

[0082] In this embodiment, the set of significant feature points: refers to the representative and easily identifiable points extracted from the real-time surveying and mapping data. These points are usually spatial positions with geometric features and easy to distinguish, such as corner points, edges, or intersection points, etc. They can effectively describe the shape and structure of the construction site. For example, in building construction, the four corner points of a wall can be used as significant feature points, and these points are easy to identify and locate in three-dimensional space;

[0083] In this embodiment, the set of theoretical feature points: refers to the corresponding feature points defined based on the design model in the preset BIM (Building Information Model). Theoretical feature points are usually model features determined according to architectural design drawings, such as the center of a column, the intersection point of a wall, etc. For example, in the BIM model, the center position of a building column and the intersection point of a wall corner can be used as theoretical feature points.

[0084] In this embodiment, initial registration refers to the process of initially aligning and matching the significant feature points in the real-time surveying data with the theoretical feature points in the BIM model. The goal of this step is to determine the relationship between the two through feature matching algorithms and find the initial geometric alignment. For example, at a construction site, there may be a positional deviation between the 3D point cloud data collected by a laser scanner and the design data in the BIM model. Through initial registration, the system will align the feature points of the two (such as the corner of a wall, the center point of a column, etc.) to find their relative positions.

[0085] In this embodiment, the initial registration error refers to the geometric differences or positional deviations between the matched feature points during the initial registration process. These errors reflect the alignment accuracy between the surveying data and the BIM model. A large initial registration error may indicate problems with data matching or the need for further adjustment. For example, after initial registration, there is a 1 cm deviation between a certain theoretical feature point in the BIM model and a significant feature point in the surveying data. This 1 cm is the initial registration error and may require further optimization of the registration method.

[0086] In this embodiment, the preset requirement refers to the standards or conditions predefined in the system for measuring whether the data registration meets the expected accuracy or quality. Only when the registration error meets the preset requirements can subsequent mesh construction or other processing steps be carried out. For example, the preset requirement of the system may be that the registration error is less than 5 mm, which means that if the initial registration error is greater than 5 mm, the system will consider the registration quality unqualified and further adjustment is needed.

[0087] In this embodiment, the geometric difference degree refers to the degree of difference between the measured geometric features when comparing different spatial regions (such as mesh cells). The geometric difference degree is usually used to evaluate the gap between the shape, size, etc. of a certain region and the theoretical design. For example, within a mesh cell, there is a difference between the measured wall thickness and the wall thickness in the BIM model. This difference constitutes the geometric difference degree. If the difference is too large, it means that there may be a deviation in this region;

[0088] In this embodiment, the preset difference degree threshold refers to the difference degree standard predefined in the system. Only when the geometric difference degree of a certain region exceeds this threshold will it be considered a deviation region. This threshold is used to determine which regions need further processing or correction. When the difference degree exceeds 2 cm, this unit will be marked as a candidate deviation region and enter the subsequent correction process.

[0089] Advantages of the above technical solution: Through multi-step processing such as data extraction, registration, grid construction, and area recognition, the construction deviation area can be accurately identified and key deviation parameters can be extracted. Compared with the prior art, through the dynamic comparison of real-time surveying data and the BIM model, not only the accuracy of deviation recognition is improved, but also the volume, spatial distribution, and duration characteristics of the deviation can be analyzed in real time, ensuring the fine management and timely correction of the construction process, improving the construction accuracy and efficiency, and reducing the risk of human error and delay.

[0090] Embodiment 4:

[0091] The embodiment of the present invention provides a dynamic collaborative design system for building construction plans based on real-time surveying, and a parameter extraction unit, including:

[0092] Volume feature extraction sub-unit: Using the voxel grid division method, determine the volume percentage of the construction deviation area in the corresponding area of the preset BIM model;

[0093] Spatial distribution feature extraction sub-unit: Perform spatial distribution analysis on the real-time surveying data, determine the main direction of the spatial distribution of the deviation area, and determine the deviation angle between the main direction of the spatial distribution and the preset reference axis;

[0094] Time duration feature extraction sub-unit: Based on the first occurrence time of the deviation, the current construction progress, and the key degree of the current construction process, further determine the deviation duration influence coefficient:

[0095]

[0096] Wherein, I is the deviation duration influence coefficient, record the first detection time of the deviation as t0, t c is the time corresponding to the current construction progress, t p is the pre-designed planned completion time of the current construction process, and γ1 is the attenuation coefficient, which is valued according to the key degree of the process.

[0097] In this embodiment, the spatial distribution analysis includes: spatial distribution feature analysis, determining the covariance matrix of the point cloud of the deviation area, performing eigenvalue decomposition on the covariance matrix, extracting the eigenvectors to form a local coordinate system, determining the direction of the eigenvector corresponding to the largest eigenvalue, main direction determination, taking the largest eigenvector direction as the preliminary main direction, optimizing the main direction estimation through the RANSAC algorithm, verifying the spatial consistency of the main direction, and determining the final main direction of the spatial distribution.

[0098] In this embodiment, the criticality of processes is based on the construction schedule plan (PERT / CPM network) to extract process relationships, determine the total float of each process, identify the set of core processes on the critical path, and the criticality assessment dimensions are as follows: Path criticality: the location characteristics of the process in the project network, Resource exclusivity: the availability of special resources required for the process, Quality sensitivity: the impact of the process quality on the overall project, Safety risk: the safety risk level of the process implementation; The grading standard is determined as follows: k = 3 (critical path process): processes with zero total float, processes directly affecting the total project duration, processes requiring special equipment or technologies; k = 2 (generally critical processes): non-critical path processes with total float less than the threshold (e.g., 3 days), processes with quality acceptance criteria as critical control points, processes involving high-risk operations, k = 1 (non-critical processes): ordinary processes with total float greater than the threshold, processes with high resource substitutability, processes with less impact on the overall quality.

[0099] In this embodiment, according to the criticality value of the process: when k = 1, γ1 = 1.0 (non-critical process), when k = 2, γ1 = 1.5 (generally critical process), when k = 3, γ1 = 2.0 (critical path process).

[0100] The beneficial effects of the above technical solutions are as follows: Through the extraction of multi-dimensional deviation characteristics such as volume, spatial distribution, and time duration, it is possible to comprehensively and accurately analyze construction deviations and provide dynamic collaborative design support based on real-time surveying and mapping. Compared with the prior art, it can not only monitor construction deviations in real time, but also analyze the impact of deviations on the construction schedule, and dynamically adjust construction strategies by calculating the deviation duration impact coefficient, thereby optimizing construction management, improving construction accuracy, reducing costs, and timely adjusting the construction plan to ensure project quality and schedule control.

[0101] Embodiment 5:

[0102] The embodiment of the present invention provides a dynamic collaborative design system for building construction plans based on real-time surveying and mapping, and a deviation acquisition module, including:

[0103] Weight determination unit: Determine the dynamic weight based on the construction deviation area:

[0104]

[0105] Among them, w v is the dynamic weight of the volume feature, w θ is the dynamic weight of the spatial distribution feature, w tis the dynamic weight for the time duration feature, α is the baseline weight coefficient for the volume feature, β is the baseline weight coefficient for the spatial distribution feature, γ is the baseline weight coefficient for the time duration feature, η1 is the increase coefficient for the weight of the volume feature by the load-bearing structure, and η1 ∈ [0, 1], η2 is the increase coefficient for the weight of the time duration feature for the non-load-bearing structure, and η2 ∈ [0, 1], δ is the increase coefficient for the spatial range weight, and δ ∈ [0, 1], A is the actual area of the deviation region, A thr is the preset threshold of the deviation region area, ReLU(A - A thr ) is the rectified linear unit function, and its function is: used to determine whether the deviation area exceeds the threshold A thr , if it exceeds, it participates in the weight adjustment. ξ1 is the increase coefficient for the weight of the spatial distribution feature in the structural construction stage, and ξ1 ∈ [0, 1], ξ2 is the increase coefficient for the weight of the volume feature in the decoration construction stage, and ξ2 ∈ [0, 1], d is the distance from the deviation region to the key structure, d thr is the preset threshold of the critical distance;

[0106] Coefficient determination unit: Determine the dynamic deviation coefficient based on the dynamic weight and the key deviation parameters:

[0107]

[0108] where DDC is the dynamic deviation coefficient.

[0109] In this embodiment, determining the dynamic weight based on the construction deviation region is determined based on the following logic: When the range of the deviation region exceeds the preset threshold area, increase the weight coefficient of the spatial distribution feature; According to the distance relationship between the deviation region and the key structural part, dynamically adjust the weight value of the volume feature; Structural importance weight adjustment: Identify the type of structural part where the deviation region is located; For the deviation of the load-bearing structural part, increase the weight coefficient of the volume feature; For the deviation of the non-load-bearing part, increase the weight coefficient of the time duration feature; Construction stage weight adjustment: Obtain the current construction progress stage information; In the structural construction stage, increase the weight of the spatial distribution feature; In the decoration construction stage, increase the weight of the volume feature.

[0110] In this embodiment, the baseline weight coefficient of the volume feature represents the proportion of the basic weight of the volume feature before adjustment;

[0111] In this embodiment, the increase coefficient for the weight of the volume feature by the load-bearing structure, when the deviation is in the load-bearing structure, increases the weight of the volume feature, and the increase coefficient reflects the specific increase ratio;

[0112] In this embodiment, the increase coefficient for the weight of the time duration feature for the non-load-bearing structure is used to increase the proportion of the weight of the time duration feature when the deviation region is in the non-load-bearing structure;

[0113] In this embodiment, the spatial range weight increase coefficient is used to increase the weight of the spatial distribution characteristics when the area of the deviation region exceeds the threshold, representing the specific increase ratio.

[0114] In this embodiment, the preset threshold of the area of the deviation region is the critical area that triggers the adjustment of the spatial range weight.

[0115] In this embodiment, the distance from the deviation region to the key structure is the spatial straight-line distance from the geometric center of the construction deviation region to the nearest key structural member (such as load-bearing wall, core tube, etc.). This distance is obtained by calculating three-dimensional spatial coordinates, using the structural positioning data in the BIM model as the benchmark. The distance value reflects the degree of influence of the deviation on the safety of the main structure. The closer the distance, the higher the structural risk. When calculating, the thickness of the structural protective layer in actual construction is considered, and non-permanent structures such as temporary supports are automatically excluded. This parameter is used to dynamically adjust the weight distribution to ensure higher attention is given to the deviations in key areas.

[0116] In this embodiment, the preset threshold of the critical distance refers to the minimum safety distance value preset to determine whether the deviation region affects the key structure. This threshold is determined based on structural design specifications, material properties, and engineering experience. When the actual distance between the deviation region and the key structure is less than this threshold, the system will automatically increase the risk level. For example, for a reinforced concrete frame structure: the critical threshold for the main beam area can be set to 500 mm, the core tube area to 300 mm, and the ordinary floor area to 800 mm. Different thresholds are set for different structural parts to ensure safety and avoid over-warning. The threshold data is stored in the BIM model attributes and can be dynamically adjusted with the progress of construction.

[0117] In this embodiment, the value range of α is [0.4, 0.7]. The lower limit of 0.4 ensures that the volume characteristics still have a basic influence in non-critical parts (such as the decorative layer), and the upper limit of 0.7 strengthens the sensitivity to large volume deviations in load-bearing structures (such as concrete defects at beam-column joints). The value range of the spatial distribution characteristic β is [0.2, 0.5]. The lower limit of 0.2 ensures the basic monitoring of minor spatial deviations (such as curtain wall installation errors), and the upper limit of 0.5 focuses on the axis deviation on the critical path (such as the deviation of the core tube verticality). The value range of γ is [0.1, 0.4]. The lower limit of 0.1 maintains the baseline tracking of long-term untreated deviations (such as masonry misalignment lasting for a week), and the upper limit of 0.4 highlights the time pressure of urgent process delays (such as the lag in steel bar acceptance before the initial setting of concrete).

[0118] The beneficial effects of the above technical solution are: by introducing dynamic weight calculation, the impact of construction deviation on different construction stages and structural types can be accurately evaluated. Compared with the existing technology, it not only considers the volume, spatial distribution and time duration characteristics, but also combines the load-bearing structure, construction stage, deviation area and key structure distance to adjust the weight, realize the intelligent quantification of the deviation impact, improve the accuracy of deviation identification, provide a scientific basis for construction adjustment, optimize construction quality management, reduce rework costs, and improve the overall efficiency and safety of the project.

[0119] Embodiment 6:

[0120] The embodiment of the present invention provides a dynamic collaborative design system for building construction schemes based on real-time surveying and mapping, and a strategy generation module, including:

[0121] Grade division unit: According to the numerical range of the dynamic deviation coefficient, the construction deviation is divided into several deviation grades;

[0122] Strategy matching unit: matches the corresponding strategy in the preset response strategy library for each deviation level, and generates a construction response strategy containing specific operation instructions.

[0123] In this embodiment, according to the numerical range of the dynamic deviation coefficient, the construction deviation is divided into several deviation levels, including: establishing an adaptive threshold model based on historical data, when DDC∈[0,μ-σ], it is divided into a first-level deviation (slight), when DDC∈(μ-σ,μ+σ], it is divided into a second-level deviation (moderate), and when DDC>μ+σ, it is divided into a third-level deviation (severe), where μ and σ are the mean and standard deviation dynamically calculated during the operation of the system, respectively.

[0124] In this embodiment, the construction response strategy: the first-level deviation strategy includes: AR visual annotation specifications, manual correction operation instructions, and a list of local reinforcement materials; the second-level deviation strategy includes: mechanical path replanning algorithm, resource scheduling optimization plan, and process connection adjustment suggestions; the third-level deviation strategy includes: structural safety verification process, design change impact assessment, and emergency resource allocation plan.

[0125] The beneficial effects of the above technical solution are: through the classification and strategy matching of the dynamic deviation coefficient, the corresponding construction response strategy can be accurately generated for different deviation levels. Compared with the existing technology, it can automatically generate a construction response strategy with specific operation instructions based on real-time surveying and mapping data and deviation levels, which improves the real-time and accuracy of construction adjustments, not only improves the adaptability during the construction process, but also optimizes resource allocation, reduces unnecessary waste caused by deviations, and ensures that the project proceeds smoothly as planned.

[0126] Embodiment 7:

[0127] The embodiment of the present invention provides a dynamic collaborative design system for building construction plans based on real-time surveying and mapping. The deviation correction module includes:

[0128] Instruction issuing unit: Convert the construction response strategy into an executable instruction and send it to the corresponding construction terminal device;

[0129] Effect verification unit: Obtain the surveyed data after execution and verify the execution effect of the deviation correction measure;

[0130] Iterative optimization unit: Adjust the dynamic weight corresponding to the dynamic deviation coefficient according to the verification result until the deviation correction result meets the preset requirements.

[0131] In this embodiment, to verify the execution effect of the deviation correction measure is to determine the deviation improvement rate of the deviation area and determine the effect based on the preset improvement rate threshold.

[0132] Beneficial effects of the above technical solution: Through the closed-loop control of instruction issuing, effect verification, and iterative optimization, the construction deviation can be adjusted in real time and the correction effect can be ensured. Compared with the prior art, it not only automatically converts the construction response strategy into an execution instruction, but also continuously optimizes the deviation correction strategy by verifying the execution result, improves the correction accuracy and construction efficiency, can effectively reduce human intervention, improve the construction accuracy, ensure that the construction quality meets the preset requirements, and adjusts and optimizes according to the real-time feedback to enhance the flexibility and accuracy of the construction process.

[0133] Embodiment 8:

[0134] The embodiment of the present invention provides a dynamic collaborative design method for building construction plans based on real-time surveying and mapping, as Figure 2 shown, including:

[0135] Step 1: Used to collect the surveyed data of the construction site through multi-source sensors and use the spatio-temporal registration algorithm to unify the surveyed data from several sources into the construction global coordinate system to generate real-time surveyed data;

[0136] Step 2: Used to compare the real-time surveyed data with the preset BIM model, then identify the construction deviation area, and obtain the key deviation parameters in combination with the real-time surveyed data;

[0137] Step 3: Determine the dynamic deviation coefficient based on the key deviation parameters and the construction deviation area;

[0138] Step 4: Divide the deviation level according to the numerical range of the dynamic deviation coefficient and generate the corresponding construction response strategy;

[0139] Step 5: Execute the construction response strategy and obtain the surveyed data after execution, verify the deviation correction result based on the surveyed data after execution, update the dynamic deviation coefficient based on the deviation correction result until the deviation correction result meets the preset requirements.

[0140] Beneficial effects of the above technical solution: Through the dynamic collaboration between real-time surveying and mapping data and the BIM model, real-time monitoring and automatic correction of construction deviations are achieved. Compared with the prior art, it is possible to obtain real-time surveying and mapping data of the construction site, and optimize the deviation correction strategy through spatio-temporal registration algorithms and dynamic deviation coefficients, avoiding the problems of lagging deviation correction and relying on manual adjustment in the traditional solution, improving the accuracy and efficiency of the construction process, and ensuring the precise control of construction quality and progress.

[0141] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that they can still modify the technical solutions recorded in the foregoing embodiments, or perform equivalent replacements for some of the technical features; and these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A dynamic collaborative design system for building construction plans based on real-time surveying and mapping, characterized in that Including: Data acquisition module: used to collect surveying and mapping data of the construction site through multi-source sensors, and use a spatio-temporal registration algorithm to unify surveying and mapping data from several sources into the construction global coordinate system to generate real-time surveying and mapping data; Data analysis module: used to compare real-time surveying and mapping data with a preset BIM model, thereby identifying construction deviation areas, and obtaining key deviation parameters in combination with real-time surveying and mapping data; Deviation acquisition module: determining a dynamic deviation coefficient based on key deviation parameters and construction deviation areas; Strategy generation module: dividing deviation levels according to the numerical range of the dynamic deviation coefficient and generating corresponding construction response strategies; Deviation correction module: executing the construction response strategy and obtaining the surveying and mapping data after execution, verifying the deviation correction result based on the surveying and mapping data after execution, and updating the dynamic deviation coefficient based on the deviation correction result until the deviation correction result meets the preset requirements.

2. The dynamic collaborative design system for building construction plans based on real-time mapping according to claim 1, characterized in that The data acquisition module includes: Multi-source data acquisition unit: obtaining the overall three-dimensional point cloud data of the construction area through a ground-fixed laser scanner, obtaining local fine surveying and mapping data through a mobile measurement device, and obtaining the real-time pose data of the mechanical working surface through a positioning sensor carried by construction machinery; Spatio-temporal registration unit: performing time synchronization processing on the data collected by multi-source sensors, establishing the conversion relationship between the coordinate systems corresponding to all acquisition devices, and unifying surveying and mapping data from all sources into the construction global coordinate system through a spatio-temporal registration algorithm; Data fusion unit: performing fusion processing on all surveying and mapping data to generate real-time surveying and mapping data.

3. The dynamic collaborative design system for building construction plans based on real-time surveying and mapping according to claim 1, characterized in that, The data analysis module includes: Data extraction unit: extracting the significant feature point set in the real-time surveying and mapping data, and at the same time, identifying the corresponding theoretical feature point set in the preset BIM model; Initial registration unit: initially registering the significant feature point set and the theoretical feature point set through a feature matching algorithm, determining the preliminary registration error, and determining the registration quality based on the preliminary registration error; Grid construction unit: constructing a three-dimensional space grid on the basis of initial registration if the registration quality meets the preset requirements; Region candidate unit: performing local geometric feature comparison within the three-dimensional space grid to obtain the geometric difference degree within each grid unit, and taking the grid unit with the geometric difference degree exceeding the preset difference degree threshold as the candidate deviation area; Region determination unit: merging spatially adjacent candidate deviation areas to generate a deviation area with a continuous boundary, and determining the deviation area with a continuous boundary as the construction deviation area; Parameter extraction unit: determining the volume feature, spatial distribution feature, and time duration feature of the construction deviation area based on the real-time surveying and mapping data as the key deviation parameters.

4. The dynamic collaborative design system for building construction plans based on real-time surveying and mapping according to claim 3, characterized in that, The parameter extraction unit includes: Volume feature extraction sub-unit: using a voxel grid division method to determine the volume percentage of the construction deviation area in the corresponding area of the preset BIM model; Spatial distribution feature extraction sub-unit: performing spatial distribution analysis on the real-time surveying and mapping data, determining the main direction of the spatial distribution of the deviation area, and determining the deviation angle between the main direction of the spatial distribution and the preset reference axis; Time duration feature extraction sub-unit: determining the deviation duration influence coefficient based on the first occurrence time of the deviation, the current construction progress, and the key degree of the current process: Where I is the influence coefficient of the deviation duration, the first detection time of the deviation is recorded as t0, t c is the time corresponding to the current construction progress, t p The planned completion time is preset for the current construction process, and γ1 is the attenuation coefficient, which is determined according to the criticality of the process.

5. The dynamic collaborative design system for building construction plans based on real-time surveying and mapping according to claim 1, wherein Deviation acquisition module, including: Weight determination unit: determining dynamic weights based on the construction deviation area: Among them, w v is the dynamic weight of the volume feature, w θ is the dynamic weight of the spatial distribution feature structure, w t is the dynamic weight of the time duration feature, α is the reference weight coefficient of the volume feature, β is the reference weight coefficient of the spatial distribution feature, γ is the reference weight coefficient of the time duration feature, η1 is the increase coefficient of the weight of the volume feature by the load-bearing structure, and η1 ∈ [0, 1], η2 is the increase coefficient of the weight of the time duration feature for the non-load-bearing structure, and η2 ∈ [0, 1], δ is the increase coefficient of the spatial range weight, and δ ∈ [0, 1], A is the actual area of the deviation region, A thr is the preset threshold of the area of the deviation region, ReLU(A - A thr ) is the rectified linear unit function, and its function is: used to judge whether the deviation area exceeds the threshold A thr , if it exceeds, it participates in the weight adjustment, ξ1 is the increase coefficient of the weight of the spatial distribution feature in the structural construction stage, and ξ1 ∈ [0, 1], ξ2 is the increase coefficient of the weight of the volume feature in the decoration construction stage, and ξ2 ∈ [0, 1], d is the distance from the deviation region to the key structure, d thr is the preset threshold of the critical distance; Coefficient determination unit: determining dynamic deviation coefficients based on the dynamic weights and key deviation parameters: Wherein, DDC is the dynamic deviation coefficient.

6. The dynamic collaborative design system for building construction plans based on real-time surveying and mapping according to claim 1, characterized in that, Strategy generation module, including: Level division unit: dividing the construction deviation into several deviation levels according to the numerical range of the dynamic deviation coefficient; Strategy matching unit: matching corresponding strategies for each deviation level in the preset response strategy library to generate a construction response strategy including specific operation instructions.

7. The dynamic collaborative design system for building construction plans based on real-time surveying and mapping according to claim 1, wherein Deviation correction module, including: Instruction issuance unit: converting the construction response strategy into executable instructions and sending them to the corresponding construction terminal device; Effect verification unit: obtaining the surveyed and mapped data after execution and verifying the execution effect of the deviation correction measures; Iterative optimization unit: adjusting the dynamic weights corresponding to the dynamic deviation coefficients according to the verification results until the deviation correction results meet the preset requirements.

8. A dynamic collaborative design method for building construction plans based on real-time surveying and mapping, characterized in that, Including: Step 1: used to collect the surveyed and mapped data of the construction site through multi-source sensors and use the spatio-temporal registration algorithm to unify the surveyed and mapped data from several sources under the construction global coordinate system to generate real-time surveyed and mapped data; Step 2: used to compare the real-time surveyed and mapped data with the preset BIM model, and then identify the construction deviation area, and obtain key deviation parameters in combination with the real-time surveyed and mapped data; Step 3: determining the dynamic deviation coefficient based on the key deviation parameters and the construction deviation area; Step 4: dividing the deviation levels according to the numerical range of the dynamic deviation coefficient and generating corresponding construction response strategies; Step 5: executing the construction response strategy and obtaining the surveyed and mapped data after execution, verifying the deviation correction results based on the surveyed and mapped data after execution, and updating the dynamic deviation coefficient based on the deviation correction results until the deviation correction results meet the preset requirements.

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