Construction process simulation system for pc sandwich wall and composite floor connection based on digital twinning

Abstract

The application discloses a PC sandwich wall and composite floor connection construction process simulation system based on digital twinning, relates to the technical field of process simulation, and comprises a data acquisition module, which is used for collecting three-dimensional point cloud data and design drawing data of all connection nodes in a target construction area; an analysis and processing module, which is used for comparing the three-dimensional point cloud data with the design drawing data, generating a steel bar position deviation value and a component installation seam width value of each connection node, and dividing the nodes into different construction process control difficulty levels according to the steel bar position deviation value; and the application realizes the early identification of the steel bar position deviation and the component installation seam width through the accurate comparison of the three-dimensional point cloud data and the design drawing and the application of an ICP iterative closest point algorithm, effectively reduces the rectification frequency in the construction process, and reduces the rework cost and the risk of construction period delay.

Description

Technical Field

[0001] This invention belongs to the field of process simulation technology, specifically a simulation system for the construction process of connecting PC sandwich walls and composite floor slabs based on digital twins. Background Technology

[0002] The connection points between precast concrete sandwich walls and composite floor slabs are core load-bearing components of prefabricated buildings, and their construction accuracy directly determines the building's stability and seismic performance. Currently, the construction of these connection points largely relies on manual operation based on drawings, which has the following limitations:

[0003] Before construction, there was a lack of precise comparison between the working conditions and the drawings, making it impossible to identify problems such as rebar deviations and excessive joint widths in advance, which easily led to repeated rectifications. After construction, there was no real-time feedback of verification data, and the lack of intuitive path comparison made it difficult to judge the rationality of the optimization sequence.

[0004] The construction sequence was arranged solely based on spatial location, without considering the construction difficulty or tower crane characteristics, resulting in fixed constraint parameters. Operational instructions were not differentiated and could not be dynamically reprogrammed, leading to significant equipment rotation and operational delays.

[0005] The alternating construction of nodes with varying levels of difficulty can lead to confusion in the transition process. When switching from high-difficulty nodes to lower-difficulty nodes after continuous construction, sudden changes in the process can easily cause errors. Traditional methods lack dynamic simulation visualization and progress linkage, making it difficult for on-site personnel to grasp the key points of process adjustments. Furthermore, the lack of clear rules for technical measures to switch between different difficulty levels can easily exacerbate quality risks due to inappropriate measures. Summary of the Invention

[0006] The purpose of this invention is to provide a simulation system for the construction process of connecting PC sandwich walls and composite floor slabs based on digital twins, so as to solve the problems mentioned in the background art.

[0007] A simulation system for the construction process of connecting PC sandwich walls and composite floor slabs based on digital twins includes:

[0008] The data acquisition module is used to collect 3D point cloud data and design drawing data of all connected nodes within the target construction area;

[0009] The analysis and processing module is used to compare the 3D point cloud data with the design drawing data, generate the rebar position deviation value and component installation joint width value for each connection node, and classify the nodes into different construction process control difficulty levels based on the rebar position deviation value.

[0010] The sequence optimization module receives the construction process control difficulty level information of all nodes, and takes maximizing the length of the segment of consecutive nodes with the same control difficulty level in the sequence as the first objective and minimizing the standard deviation of the change of the slewing angle of the tower crane boom between adjacent nodes as the second objective to generate a physical construction sequence that is different from the original spatial position sequence, as the optimized construction sequence.

[0011] The simulation execution and output module is used to drive the 3D model to perform dynamic simulation of the construction process in sequence according to the node order of the optimized construction sequence, and generate the corresponding construction equipment operation instructions for each step.

[0012] The innovation of this invention lies in generating an optimized construction sequence that differs from the original spatial sequence by combining the difficulty level of node control with the movement characteristics of the tower crane. This improves process continuity, reduces sudden changes in tower crane rotation, and enhances construction efficiency and safety.

[0013] In some possible implementations, the analysis and processing module also performs the following steps:

[0014] Establish a mapping relationship between the difficulty level of construction process control and the necessary technical measures;

[0015] Among them, the high level of control difficulty is mapped to at least one of the following essential technical measures: using high-precision laser positioning fixtures, using low-flow grouting material and combining it with vibration densification, and adding temporary adjustable supports on both sides of the node;

[0016] The difficulty level of medium control is mapped to at least one of the following essential technical measures: using standard mechanical positioning fixtures, or using standard flowability grouting material;

[0017] The low level of control difficulty is mapped to the standard construction process, requiring no special technical measures.

[0018] The present invention employs the above-mentioned necessary technical measures mapping relationship to establish standardized nodes with different control difficulty levels, thereby improving the stability and consistency of node construction quality.

[0019] In some possible implementations, when the control difficulty levels of two adjacent nodes in the sequence are different, switching from construction at a low-difficulty node to construction at a high-difficulty node requires the mandatory execution of the necessary technical measures mapped by the high-difficulty level in the construction instructions.

[0020] When switching from high-difficulty construction nodes to low-difficulty construction nodes, it is necessary to explicitly cancel the special technical measures that are no longer needed in the construction instructions.

[0021] This approach clarifies the rules for the mandatory enforcement and cancellation of technical measures when the difficulty level of adjacent nodes changes, avoiding omissions or inappropriate switching of measures and ensuring the standardization and safety of the construction process.

[0022] In some possible implementations, the sequence optimization module generates the optimized construction sequence by including a reverse buffer segment insertion step:

[0023] The original construction sequence is segmented based on the control difficulty level of nodes, and segments with the same continuous control difficulty level are identified as process stability segments.

[0024] Identify all process stability sections consisting of consecutive nodes with high control difficulty levels, and denot them as high-load sections;

[0025] For each high-load segment, if this high-load segment is immediately followed by another process stabilization segment with a different control difficulty level in the initial sequence, then a buffer analysis is performed between the two segments:

[0026] Select a node with a low control difficulty level from the global node pool and insert it as a candidate buffer node between the two segments;

[0027] The judgment criterion is: after inserting this candidate buffer node, whether the overall process switching complexity and motion change rate from the end node of the previous high-load segment to the buffer node and then to the start node of the next segment are lower than the values ​​when the two high-load segments are directly connected.

[0028] If the judgment criteria are met, insertion is performed, generating a sequence to be optimized that contains a reverse buffer segment.

[0029] This invention inserts low-difficulty buffer nodes between high-load sections and sections of varying difficulty, reducing the complexity of process switching and the abrupt changes in tower crane movement, smoothing the construction transition, and reducing operational errors.

[0030] In some possible implementations, after completing the reverse buffer insertion, the sequence optimization module performs a multi-objective optimization sorting step:

[0031] Based on the sequence to be optimized, which includes buffer segments, while keeping the order of nodes within each process stable segment unchanged, we attempt to swap the positions of different process stable segments in the overall sequence to form multiple candidate sequences.

[0032] Calculate the process continuity score and tower crane motion smoothness score for each candidate sequence;

[0033] The process continuity score is based on the length of the longest stable process segment in the sequence;

[0034] The smoothness of tower crane movement is scored based on the standard deviation of the change in tower crane rotation angle between all adjacent nodes in the sequence; the smaller the standard deviation, the higher the score.

[0035] From all candidate sequences, first select the set of candidate sequences with the highest process continuity score, and then select the sequence with the highest tower crane motion smoothness score from this set as the final output.

[0036] By adopting the above steps and optimizing the sequence through multi-objective optimization, the construction sequence is comprehensively optimized while maintaining the internal order of the stable process section and taking into account both process continuity and tower crane movement smoothness.

[0037] In some possible implementations, the sequence optimization module is also connected to the real-time signal interface of the tower crane hoisting control system;

[0038] When generating an optimized construction sequence, a dynamic constraint is added: the spatial position of the current node to be constructed in the sequence must be within a fan-shaped coverage area centered on the expected stopping position when the previous node above the tower crane boom is completed, with a preset length as the radius.

[0039] Specifically, by introducing the real-time movement status of the tower crane as a dynamic constraint, the construction node is ensured to be within the fan-shaped coverage area of ​​the tower crane's expected stopping position, thereby reducing large-scale equipment rotation and unnecessary waiting.

[0040] In some possible implementations, the radius of the preset length is not a fixed value, but is dynamically calculated by the sequence optimization module based on the control difficulty level of the current node to be constructed;

[0041] The calculation method is as follows: compare the time required to rotate the tower crane boom from the previous node position to the theoretical position of the current node to be constructed at a constant speed with the standard preparation time for the necessary technical measures to be completed for the current node to be constructed.

[0042] If the slewing time is greater than the standard preparation time, the maximum working radius of the tower crane shall be used as the sector radius.

[0043] If the slewing time is less than or equal to the standard preparation time, a calculation radius is used to ensure that the tower crane's slewing time is equal to the standard preparation time, so that the construction preparation is just completed when the tower crane is in place.

[0044] Specifically, the construction radius is dynamically calculated based on the difficulty level of node control, so that the tower crane slewing time matches the construction preparation time, realizing the synchronous operation of tower crane arrival and preparation completion, and improving the coordination of construction rhythm.

[0045] In some possible implementations, the simulation execution and output module generates construction equipment operation instructions in the following ways:

[0046] For the first node in the optimized construction sequence, a complete instruction package is generated, which includes the initial pressure setting value of the grouting machine, the selection of the vibrator model, and the installation coordinates of the positioning fixture.

[0047] For each node after the first node in the sequence, the complete instruction package of the current node is compared item by item with the instruction package of the previous node, and only instruction items with different content are generated. The instruction clearly explains the basis for the change in control difficulty level corresponding to each change.

[0048] In some possible implementations, the system also includes a field data receiving module, which:

[0049] Connect to the measuring instruments at the construction site to receive the final positioning data of the reinforcing bars at the completed construction nodes;

[0050] The final positioning data of the reinforcing bars is compared with the position deviation value of the reinforcing bars at the node in the simulation system. When the difference between the two exceeds the allowable error range, the control difficulty level of the node is automatically reassessed.

[0051] Send instructions to the sequence optimization module to perform local replanning of subsequent unconstructed nodes based on the current sequence of constructed nodes, and seamlessly embed the newly planned local sequence into the original optimized construction sequence.

[0052] In some possible implementations, the simulation execution and output module includes a comparison display unit, which:

[0053] In the 3D simulation view, each node is connected sequentially according to the original drawing order using the first color line to form the first construction path, and the control difficulty level of the node is marked on the node with different color blocks.

[0054] Using lines of the second color, connect each node sequentially according to the optimized construction sequence to form a second construction path;

[0055] On the second construction path, a dynamic arrow indicates the current simulation progress. When the arrow moves to a node where the control difficulty level changes, a pop-up window automatically displays a list of necessary technical measures changes triggered by the level change.

[0056] This invention uses dual-path comparison and dynamic visualization to intuitively present the rationality of the optimized sequence and process switching nodes, thereby improving the understanding and execution effect of construction personnel on process adjustments.

[0057] In this application, unless otherwise stated, the following terms have the following meanings:

[0058] Stable process segment: refers to a segment in the construction sequence consisting of at least two nodes with the same level of control difficulty.

[0059] High-load section: refers to the process stability section consisting of continuous nodes with high control difficulty.

[0060] Process switching complexity: refers to the number of technical changes required to switch from the construction process of the previous node to the construction process of the next node. The activation, cancellation or parameter adjustment of each technical measure is counted as 1 complexity item.

[0061] Motion abrupt change: refers to the absolute value of the angle change of the tower crane boom between two adjacent nodes (unit: degrees).

[0062] The combined process changeover complexity and motion abruptness is a weighted sum, calculated as: Combined value = α × Process changeover complexity + β × Motion abruptness, where α and β are weighting coefficients, both defaulting to 0.5, but can be adjusted according to actual engineering conditions.

[0063] The technical solutions provided by the embodiments of this disclosure have at least the following beneficial effects:

[0064] This invention achieves early identification of rebar position deviation and component installation joint width by accurately comparing three-dimensional point cloud data with design drawings and applying the ICP iterative nearest point algorithm, effectively reducing the frequency of rectification during construction and lowering rework costs and the risk of construction delays.

[0065] Based on a three-level control difficulty grading mechanism for rebar deviation values, combined with precise mapping of corresponding technical measures, the adaptability of construction technology under different working conditions is ensured, the stability of construction quality at connection nodes is improved, and the construction quality meets the requirements of current technical specifications and engineering design for prefabricated concrete structures. Attached Figure Description

[0066] Figure 1 This is a schematic diagram of the system framework structure of the present invention. Detailed Implementation

[0067] The technical solution of the present invention will be clearly and completely described below with reference to the embodiments. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative effort are within the scope of protection of the present invention.

[0068] Please see Figure 1 This application provides a construction system for connecting PC sandwich walls and composite floor slabs based on digital twins, including a data acquisition module, an analysis and processing module, a sequence optimization module, a simulation execution and output module, and a field data receiving module. These modules work together to achieve intelligent optimization and dynamic simulation of the construction process. The specific implementation process is as follows:

[0069] The data acquisition module is used to collect 3D point cloud data and design drawing data of all connected nodes within the target construction area;

[0070] It should be noted that the data acquisition module consists of a 3D laser scanning device, a drawing digitization terminal, a data transmission unit, and a data storage unit, ensuring data integrity and format consistency.

[0071] In this step, the 3D laser scanning equipment uses a pulsed laser scanner, adapted to the scanning distance requirements, and the point cloud accuracy meets the needs for identifying the position of reinforcing bars and the installation dimensions of components. The drawing digitization terminal supports importing and parsing formats such as DWG, DXF, and BIM, and can extract core parameters such as reinforcing bar coordinates, installation dimensions, and node positions.

[0072] Furthermore, the data transmission unit employs a 5G industrial-grade communication module to transmit data to the storage unit in real time. The data storage unit adopts a distributed cloud storage architecture, supporting categorized storage and fast read / write operations, and features backup functionality to prevent data loss.

[0073] It should be understood that before data collection, the laser scanning equipment needs to be calibrated, duplicate and invalid information on the drawings needs to be removed, and the coordinate system needs to be unified as the building construction coordinate system to eliminate the influence of deviations.

[0074] The analysis and processing module is used to compare the 3D point cloud data with the design drawing data, generate the rebar position deviation value and component installation joint width value for each connection node, and classify the nodes into different construction process control difficulty levels based on the rebar position deviation value.

[0075] It should be noted that the core of the analysis and processing module is a multi-dimensional comparison algorithm and a difficulty classification model. The ICP iterative nearest point algorithm is used to complete the registration of point cloud and design model. The registration error is ≤2mm, which meets the requirements for deviation calculation.

[0076] Furthermore, after registration, the actual and design coordinates of the reinforcing bars are extracted, and then calculated using the formula... Calculate the deviation value. Extract the actual and designed joint widths of the component, and take the average of no less than 3 sampling points as the actual joint width. The joint width value is the absolute difference between the two.

[0077] It should be understood that the difficulty level is classified according to the steel reinforcement deviation value, based on the Technical Specification for Precast Concrete Structures GB / T51231-2016:

[0078] Δd≤5mm indicates a low level of control difficulty and requires no rectification.

[0079] 5mm < Δd ≤ 15mm represents a medium control difficulty level, with slight adjustments to the reinforcing bars to ensure a deviation of ≤ 5mm.

[0080] Δd>15mm indicates a high level of control difficulty, requiring specific rectification and re-inspection.

[0081] The analysis and processing module also performs the following steps: establishing a mapping relationship between the difficulty level of construction process control and the necessary technical measures. Specifically, a high control difficulty level is mapped to at least one of the following necessary technical measures:

[0082] High-precision laser positioning fixtures are used, low-flow grouting material is employed and vibration is used to reinforce the joint, and temporary adjustable supports are added on both sides of the node.

[0083] The difficulty level of medium control is mapped to at least one of the following essential technical measures: using standard mechanical positioning fixtures and employing standard flowability grouting materials;

[0084] The low level of control difficulty is mapped to the standard construction process, requiring no special technical measures.

[0085] Simultaneously, a preparation time is allocated for the configuration standards at each level. This time is set based on the prefabricated building construction process specifications and the measured data of on-site workers' operational efficiency. The mapping relationship is stored synchronously in the local database, including the allowable error of ±3mm for rebar positioning. It is set according to the GB50204-2015 Code for Acceptance of Construction Quality of Concrete Structures. The database supports classified retrieval and modification, and the matching logic is one-to-one level matching.

[0086] Construction personnel must select at least one measure from the corresponding set of measures based on the joint width, rebar deviation direction, and site space conditions. The results must be entered into the system for traceability. Among these measures, the high-precision laser positioning fixture must be aligned with a unified coordinate system and verified after correction.

[0087] Low-flowability grout is injected using a special grouting gun, with a vibration point spacing of ≤200mm.

[0088] The temporary adjustable support is fixed to the main structure, and verticality is monitored during adjustment. Standard mechanical positioning clamps are used for calibration and then secured. Standard flowable grout is mixed and poured according to the specified proportions.

[0089] When two adjacent nodes in a sequence have different control difficulty levels, switching from construction at a low-difficulty node to a high-difficulty node requires the mandatory execution of the necessary technical measures mapped to the high-difficulty level in the construction instructions. Conversely, switching from construction at a high-difficulty node to a low-difficulty node requires the explicit removal of any no longer needed special technical measures in the construction instructions.

[0090] When transitioning from low to high altitudes, preparatory work should be carried out simultaneously with the tower crane's rotation, and construction instructions should be issued after acceptance. When transitioning from high to low altitudes, the requirements for equipment removal or repositioning, material discontinuation, parameter restoration, and the switching and recording of data should be clearly defined and matched with the tower crane's operational rhythm.

[0091] On-site data receiving module: Connects to surveying instruments at the construction site to receive the final positioning data of the reinforcing bars at completed construction nodes. It compares the final positioning data with the node reinforcing bar position deviation values ​​in the simulation system. When the difference exceeds the allowable error range, it automatically reassesses the control difficulty level of this node. Based on the current sequence of completed nodes, it performs local replanning for subsequent unconstructed nodes and seamlessly embeds the newly planned local sequence into the original optimized construction sequence.

[0092] The on-site data receiving module connects to high-precision measuring equipment such as total stations and 3D laser positioning instruments to receive the final positioning data of the reinforcing bars at constructed nodes in real time, including node number, 3D coordinates, construction time, instrument accuracy parameters, and data accuracy down to the millimeter level.

[0093] Through two-way communication between the 5G industrial-grade communication module and the measuring instrument, the on-site rebar positioning data is compared point by point with the preset deviation value of the simulation system, according to the formula. Calculate the coordinate difference. If Δs exceeds the allowable error of ±3mm, call the difficulty classification model in the analysis and processing module, re-evaluate the actual control difficulty level of the node according to the original standard, upgrade the level if the deviation increases, and downgrade the level if the deviation decreases and meets the lower level requirement, update the system database and mark it.

[0094] The specific implementation method of local replanning is as follows: a combination method of inserting reverse buffer segments and multi-objective optimization sorting is adopted. The maximum number of local replanning nodes is 20. Starting from the last node of the completed nodes, the order and instructions of the completed nodes are kept unchanged, and replanning is only performed on the subsequent uncompleted nodes.

[0095] The reverse buffer segment insertion step is as follows: Based on the node control difficulty level, unconstructed nodes are segmented. Consecutive stable process segments of the same level and consecutive high-load segments with high control difficulty levels are identified. If a high-load segment is subsequently connected to a segment of a different level, a candidate buffer node is selected from the low-control-difficulty nodes and inserted between the two segments. The criterion is whether, after inserting this candidate buffer node, the overall process switching complexity and motion abruptness from the end node of the previous high-load segment to the buffer node, and then to the beginning node of the next segment, are lower than the values ​​when the two high-load segments are directly connected. This overall value is calculated using the formula: Overall Value = α × Process Switching Complexity + β × Motion Abruptness, where α and β are weighting coefficients (both default to 0.5). Process switching complexity refers to the number of technical changes, and motion abruptness refers to the absolute value of the tower crane's slewing angle change. If the overall value is lower after insertion, the insertion is performed.

[0096] The multi-objective optimization sorting steps are as follows: keep the order of nodes within each stable segment of the process unchanged, exchange the positions of different stable segments to form candidate sequences, calculate the process continuity score, and based on the length of the longest stable segment and the smoothness score of the tower crane movement, and based on the standard deviation of the rotation angle change, prioritize the sequence with the best smoothness score in the set with the highest process continuity score as the subsequence after local reprogramming, and seamlessly embed it into the original optimized construction sequence.

[0097] The comparison display unit is a core component of the simulation execution and output module, and its functions are as follows:

[0098] In the 3D simulation view, the nodes are connected in the order of the original drawings using lines of the first color to form the first construction path, and the nodes are marked with different colored blocks to control the difficulty level.

[0099] A second construction path is formed by connecting each node with a second-colored line according to the optimized construction sequence. On the second construction path, the simulation progress is marked with dynamic color blocks. When the dynamic color block moves to a node where the difficulty level changes, a pop-up window automatically displays a list of technical measure changes.

[0100] In this unit, the first color uses a 2mm solid blue line, and the second color uses a 3mm solid red line. Red has a higher visual priority, achieving a side-by-side contrast.

[0101] The nodes are marked with spherical semi-transparent blocks according to difficulty levels: light green for low difficulty, yellow for medium difficulty, and orange-red for high difficulty. The diameter is 1.2 times the maximum size of the node, and they fit the model without obstruction.

[0102] The dynamic color block has a red gradient pattern and a length of 1 / 5 of a single path segment. It moves dynamically according to the sum of the node construction time and the tower crane rotation time.

[0103] The pop-up window is changed to an 800×600 pixel floating draggable window. It displays the removal, addition, and adjustment measures in categories, and marks the operation requirements, parameter standards and level switching basis. It automatically collapses when it reaches the next node and supports locking and retention.

[0104] The sequence optimization module receives the construction process control difficulty level information of all nodes, and takes maximizing the length of the node segment with the same control difficulty level in the sequence as the first objective and minimizing the standard deviation of the change in the slewing angle of the tower crane boom between adjacent nodes as the second objective to generate a physical construction sequence that is different from the original spatial position sequence, i.e., optimize the construction sequence.

[0105] The sequence optimization module receives the node difficulty level and standard preparation time, and also connects to the real-time signal interface of the tower crane hoisting control system to obtain the boom slewing angle, luffing length, and uniform slewing speed of 0.5° / s-1.5° / s. Based on the tower crane equipment technical manual and on-site measured data, it sets the operating speed, expected stopping position, and other data, adds dynamic constraints to generate an optimized construction sequence, and receives replanning instructions to complete local sequence adjustments and embedding.

[0106] When generating an optimized construction sequence, a dynamic constraint is added: the spatial position of the current node to be constructed in the sequence must be within a fan-shaped area with a preset length as the center and the expected stopping position when the previous node above the tower crane boom is completed. The fan angle is 60°-120°, set according to the measured data of the tower crane boom's rotation flexibility and the distribution of obstacles on the construction site, to avoid large-scale equipment rotation and match the construction preparation rhythm.

[0107] The radius of the preset length is not a fixed value, but is dynamically calculated by the sequence optimization module based on the control difficulty level of the current node to be constructed: the time t1 required to rotate the tower crane boom from the previous node position to the theoretical position of the current node at a constant speed is compared with the standard preparation time t2 of the technical measures required for the current node.

[0108] If t1>t2, the maximum working radius of the tower crane is 30-50m, which is set according to the technical parameters of the tower crane equipment.

[0109] If t1≤t2, use the calculated radius to ensure t1=t2, so that construction preparation is just completed when the tower crane is in place.

[0110] The dynamic calculation of the sector radius is as follows: the rotation time is calculated according to the formula t1=L / v, where L is the straight-line distance in space, v is the uniform rotation speed, and the standard preparation time t2 of the node is retrieved.

[0111] If t1 > t2, the maximum working radius shall be used;

[0112] If t1≤t2, calculate the radius using the formula R=v×t2×π / 180.

[0113] The sequence optimization module generates optimized construction sequences by including a reverse buffer segment insertion step: the original construction sequence is segmented based on the node control difficulty level, and consecutive segments of the same level are identified as process stability segments.

[0114] Identify a process stability segment composed of consecutive high-difficulty nodes, denoted as a high-load segment. If a high-load segment is subsequently connected to process stability segments of different levels, select a candidate buffer node from the global low-difficulty node pool and insert it between the two segments. The criterion is that after insertion, the combined process switching complexity and motion abruptness from the end node of the preceding high-load segment to the buffer node to the beginning node of the following segment are lower than the values ​​when the two segments are directly connected. If the condition is met, insert the node and generate an optimization sequence containing a reverse buffer segment.

[0115] In the reverse buffer segment insertion process, candidate buffer nodes are preferentially selected based on the minimum sum of spatial distances to the high-load segment termination node and the subsequent segment start node, while also meeting the constraints. If no candidate node is found, the node at the end of the low-difficulty stable segment is referenced. The comprehensive value is calculated using the formula: Comprehensive Value = α × Process Switching Complexity + β × Motion Abruptness, where α and β are both taken as 0.5 and can be adjusted according to actual engineering conditions. If the comprehensive value is smaller after insertion and meets the constraints, insertion is performed; otherwise, insertion is not performed.

[0116] After completing the reverse buffer segment insertion, the sequence optimization module performs a multi-objective optimization sorting step: based on the sequence to be optimized containing the buffer segment, the order of nodes within each process stable segment remains unchanged, and the positions of different stable segments are exchanged to form multiple candidate sequences.

[0117] The process continuity score for each candidate sequence is calculated separately, based on the length of the longest stable process segment using the formula S1 = K1 × Lmax, where K1 is 1-2. The crane motion smoothness score is calculated based on the standard deviation of the rotation angle change using the formula S2 = K2 - K3 × σ, where K2 is 10-20 and K3 is 0.5-1. The set of candidate sequences with the highest process continuity scores is prioritized, and then the sequence with the highest crane motion smoothness score is selected as the final output. Here, K1, K2, and K3 are scoring coefficients used to map the length and standard deviation to a comparable score range. In this embodiment, K1 is 1.5, K2 is 15, and K3 is 0.5. These coefficients can be adjusted according to the importance placed on process continuity and equipment motion smoothness in actual engineering practice.

[0118] When generating the optimized sequence, a multi-objective optimization algorithm framework is adopted, with a population size of 50-100, a crossover probability of 0.7-0.9, a mutation probability of 0.01-0.05, and ≥50 iterations. The parameters are set based on experimental data and algorithm convergence requirements. During local reprogramming, the number of optimized nodes is ≤20, the algorithm parameters remain unchanged, only the range of optimized nodes is adjusted, and a unified sorting rule is followed.

[0119] The multi-objective optimization ranking process involves treating buffer segments as independent stable segments, exchanging the positions of different stable segments to form candidate sequences, and eliminating invalid sequences based on the order of processes. After calculating two scores, the optimal sequence is selected based on process priority and equipment compatibility.

[0120] The simulation execution and output module drives the 3D model to perform dynamic simulation of the construction process according to the node order of the optimized construction sequence, and generates corresponding construction equipment operation instructions for each step. Instructions are regenerated synchronously after the sequence is updated, and the comparison display unit synchronously updates the path and dynamic color block trajectory.

[0121] It should be noted that the full-element 3D simulation model is built based on digital twin technology, with a geometric accuracy error of ≤1mm, material and mechanical properties that closely match reality, a simulation frame rate of ≥30fps, and an integrated tower crane operation simulation module to restore the operation actions and construction preparation process. It supports full process restoration and synchronous adaptation after sequence updates.

[0122] Furthermore, the simulation incorporates process parameters such as rebar adjustment, hoisting, and grouting, conforming to the current prefabricated concrete structure construction code GB51231-2016. It integrates deviation values, technical measures, standard preparation times, follows grade switching rules, buffer connection requirements, and optimizes sequences and dynamic constraints to achieve a simulation that integrates working conditions, measures, sequences, and tower crane operation rhythm. The comparison display unit is always active, visually presenting operation nodes, parameters, acceptance standards, etc., to verify the compliance and synchronization of tower crane operations.

[0123] The simulation execution and output module generates construction equipment operation instructions in the following way: it optimizes the first node in the construction sequence and generates a complete instruction package that includes the initial pressure setting value of the grouting machine, the selection of the vibrator model, and the installation coordinates of the positioning fixture.

[0124] For each node after the first node, the complete instruction package of the current node is compared item by item with the instruction package of the previous node, and only instruction items with different content are generated. The instruction clearly explains the basis for the change in control difficulty level corresponding to each change.

[0125] In the instruction generation logic, the grouting machine pressure is set according to difficulty level: low difficulty 0.3-0.5MPa, medium difficulty 0.5-0.8MPa, high difficulty 0.8-1.2MPa, based on the characteristics of the grouting material and the compaction requirements of the joint construction.

[0126] Vibrator model selection based on difficulty level:

[0127] Low difficulty: φ30; Medium difficulty: φ50; High difficulty: φ70, depending on the node size and grout density requirements. Positioning fixture installation coordinate accuracy is down to the millimeter level. Differentiated instructions focus on parameter adjustments, model changes, and other core modifications, clearly defining the basis for grade changes.

[0128] It should be understood that the instructions target core equipment such as tower cranes and grouting machines, and include quantitative information such as work coordinates, steps, parameters, duration, acceptance criteria, and preparation time. Tower crane instructions specify constraints such as slewing angle and luffing length to guide simultaneous construction preparation. Instructions for other equipment are matched with the tower crane's slewing time. The instructions use MODBUS or Profinet format and can directly interface with the equipment control system.

[0129] Among them, the buffer node instructions clearly define the connection process and constraint parameters with the preceding and following sections. The high-precision laser positioning fixture instructions clearly define the positioning benchmark, fixed position, etc. The low-flowability grouting material instructions clearly define the pressure, speed, vibration parameters, etc. The temporary adjustable support instructions clearly define the installation position, adjustment step size, etc. The technical measure switching instructions clearly define the equipment, materials, acceptance requirements, and time nodes.

[0130] The simulation design process error monitoring stage covers the entire process, including rebar adjustment, installation, and grouting, and adds monitoring indicators for tower crane constraint compliance and construction preparation synchronization. Anomaly handling is prioritized based on the following: over-sectoral areas at nodes, delayed construction preparation, process issues, and improper measure switching, with rectification suggestions output. The specific process is as follows: The criteria for determining delayed construction preparation are: when the tower crane arrives at the node, the completion rate of the necessary technical measures corresponding to that node is less than 90%; improper measure switching includes failing to explicitly cancel high-difficulty measures in the instructions or failing to activate necessary measures when transitioning from low to high altitudes.

[0131] If a node exceeds the fan-shaped area, an early warning will be triggered immediately, prompting an adjustment to the tower crane's slewing path. If construction preparation is delayed, a reminder will be issued, suggesting optimization of the construction preparation process. If a process problem or improper switching of measures occurs, the system will pause the simulation, locate the problematic process and operation node, output specific rectification steps, including parameter adjustment ranges, equipment operation correction methods, and technical measure adaptation suggestions. Dynamic color blocks will be paused synchronously. The simulation can resume after rectification is completed. The monitoring mechanism and anomaly handling process remain unchanged after the sequence is updated.

[0132] After simulation, a construction process simulation report and equipment operation instruction set are generated. The reports are numbered according to an optimized sequence, with the first node labeled with a complete instruction package, and subsequent nodes labeled with differentiated instructions and the basis for level changes. Technical measures, switching requirements, and buffer transition processes are also included. The report and instruction set support both paper and digital output, with electronic versions synchronized to mobile devices. Only partial content is added after sequence updates, and path comparisons and progress records are saved synchronously.

[0133] The target construction area contains 20 connecting nodes. The average length of consecutive nodes with the same control difficulty level in the original sequence is 2.1, and the standard deviation of the tower crane slewing angle variation is 28°. The sequence optimization module obtains the tower crane's uniform slewing speed of 1° / s, the maximum working radius of 40m, the set sector angle of 90°, and the standard preparation time for each node: J1 (low difficulty) 6min, J5 (medium difficulty) 12min, J9 (high difficulty) 25min, and the allowable error for rebar positioning is ±3mm.

[0134] After the reverse buffer section is inserted, an optimization sequence is formed, which includes process stability section A (low difficulty J1-J2), section B (high difficulty J9-J10-J8), section C (low difficulty J3 buffer section), and section D (medium difficulty J5-J6-J7). The dynamic calculation radius of J3 is 6.28m, located within the fan-shaped coverage area, and the rotation time is the same as the preparation time.

[0135] Taking the high-load section B (J9-J10-J8) and the medium-difficulty section D (J5-J6-J7) as examples, if they are directly connected, the process switching complexity is 3 items (such as canceling the laser positioning fixture, changing the grouting material type, and adjusting the vibration parameters), and the motion mutation degree is 25°. After inserting the low-difficulty buffer node J3, the complexity from B to J3 is 2 items, and the complexity from J3 to D is 2 items, with motion mutation degrees of 10° and 12° respectively. The overall value is reduced, which meets the insertion conditions.

[0136] Fifty candidate sequences were generated, 15 of which were eliminated due to non-compliance with constraints, and 35 were evaluated. Eight of these had the highest scores for process continuity. Section A had four nodes, and scored 6 points when K1=1.5. From these, the sequence with the best tower crane motion smoothness score was selected, with a score of 9.9 points when σ=10.2°, K2=15, and K3=0.5. The final optimized sequences were A, B, C, and D. The remaining nodes were arranged according to difficulty and tower crane characteristics.

[0137] During simulation, the original path is drawn with a blue solid line, and the optimized path is drawn with a red solid line. When the dynamic color block moves from J2 (low difficulty) to J9 (high difficulty), a pop-up window displays measures such as the addition of a high-precision laser positioning fixture and the basis for switching.

[0138] During construction, the site received the positioning data for the J2 rebar. The Δs=5mm exceeded the allowable error, so J2 was re-evaluated as medium difficulty, triggering sequence replanning. The subsequent 15 nodes were adjusted to J2, J4, B, C, and D. The comparison display unit synchronously updated the path and dynamic color block trajectory. The simulation execution module regenerated the differentiated instructions for J4 and subsequent nodes. When the dynamic color block moved from the medium difficulty of J2 to the low difficulty of J4, a pop-up window displayed measures such as removing the standard mechanical positioning fixture.

[0139] In the J2-J4 connection process, the dynamic slewing radius of J4 is 6.28m, the dynamic color block movement speed is matched with a 6-minute slewing time, and the construction preparation is completed when the tower crane is in place. After the monitoring standard deviation is adjusted, it is 9.8°, thus optimizing efficiency.

[0140] This invention achieves early identification of rebar position deviation and component installation joint width by accurately comparing three-dimensional point cloud data with design drawings and applying the ICP iterative nearest point algorithm, effectively reducing the frequency of rectification during construction and lowering rework costs and the risk of construction delays.

[0141] Based on a three-level control difficulty grading mechanism for rebar deviation values, combined with precise mapping of corresponding technical measures, the adaptability of construction technology under different working conditions is ensured, the stability of construction quality at connection nodes is improved, and the construction quality meets the requirements of current technical specifications and engineering design for prefabricated concrete structures.

[0142] Furthermore, relying on dynamic constraints and real-time calculation of the sector radius, the construction sequence can fully adapt to the characteristics of tower crane operations and the difficulty of node construction, reducing redundant operations such as large-scale tower crane rotation and unnecessary waiting, reducing equipment energy consumption and construction noise, and optimizing the hoisting operation process. The combination of reverse buffer segment insertion and multi-objective optimization sequencing alleviates the problem of sudden process changes in alternating construction of nodes with different difficulty levels, avoids operational errors caused by sudden changes in process complexity, and ensures the continuity and safety of the construction process.

[0143] The above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

Claims

1. A simulation system for the construction process of PC sandwich walls and composite floor slabs based on digital twins, characterized in that, include: The data acquisition module is used to collect 3D point cloud data and design drawing data of all connected nodes within the target construction area; The analysis and processing module is used to compare the 3D point cloud data with the design drawing data, generate the rebar position deviation value and component installation joint width value for each connection node, and classify the nodes into different construction process control difficulty levels based on the rebar position deviation value. The sequence optimization module receives the construction process control difficulty level information of all nodes, and takes maximizing the length of the segment of consecutive nodes with the same control difficulty level in the sequence as the first objective and minimizing the standard deviation of the change of the slewing angle of the tower crane boom between adjacent nodes as the second objective to generate a physical construction sequence that is different from the original spatial position sequence, as the optimized construction sequence. The simulation execution and output module is used to drive the 3D model to perform dynamic simulation of the construction process in sequence according to the node order of the optimized construction sequence, and generate the corresponding construction equipment operation instructions for each step.

2. The simulation system for construction process of PC sandwich wall and composite floor slab connection based on digital twin as described in claim 1, characterized in that, The analysis and processing module also performs the following steps: Establish a mapping relationship between the difficulty level of construction process control and the necessary technical measures; Among them, the high level of control difficulty is mapped to at least one of the following essential technical measures: using high-precision laser positioning fixtures, using low-flow grouting material and combining it with vibration densification, and adding temporary adjustable supports on both sides of the node; The difficulty level of medium control is mapped to at least one of the following essential technical measures: using standard mechanical positioning fixtures, or using standard flowability grouting material; The low level of control difficulty is mapped to the standard construction process, requiring no special technical measures.

3. The simulation system for construction process of PC sandwich wall and composite floor slab connection based on digital twin as described in claim 2, characterized in that, When the control difficulty levels of two adjacent nodes in the sequence are different, when switching from construction at a low-difficulty node to construction at a high-difficulty node, the necessary technical measures mapped by the high-difficulty level must be enforced in the construction instructions. When switching from high-difficulty construction nodes to low-difficulty construction nodes, it is necessary to explicitly cancel the special technical measures that are no longer needed in the construction instructions.

4. The simulation system for construction process of PC sandwich wall and composite floor slab connection based on digital twin as described in claim 1, characterized in that, The sequence optimization module generates optimized construction sequences by including a reverse buffer segment insertion step: The original construction sequence is segmented based on the control difficulty level of nodes, and segments with the same continuous control difficulty level are identified as process stability segments. Identify all process stability sections consisting of consecutive nodes with high control difficulty levels, and denot them as high-load sections; For each high-load segment, if this high-load segment is immediately followed by another process stabilization segment with a different control difficulty level in the preliminary sequence, then a buffer analysis is performed between the two segments. Select a node with a low control difficulty level from the global node pool and insert it as a candidate buffer node between the two segments; The judgment criterion is: after inserting this candidate buffer node, whether the overall process switching complexity and motion change rate from the end node of the previous high-load segment to the buffer node and then to the start node of the next segment are lower than the values ​​when the two high-load segments are directly connected. If the judgment criteria are met, insertion is performed, generating a sequence to be optimized that contains a reverse buffer segment.

5. The simulation system for construction process of PC sandwich wall and composite floor slab connection based on digital twin as described in claim 4, characterized in that, After completing the reverse buffer segment insertion, the sequence optimization module performs a multi-objective optimization sorting step: Based on the sequence to be optimized, which includes buffer segments, while keeping the order of nodes within each process stable segment unchanged, we attempt to swap the positions of different process stable segments in the overall sequence to form multiple candidate sequences. Calculate the process continuity score and tower crane motion smoothness score for each candidate sequence; The process continuity score is based on the length of the longest stable process segment in the sequence; The smoothness of tower crane movement is scored based on the standard deviation of the change in tower crane rotation angle between all adjacent nodes in the sequence; the smaller the standard deviation, the higher the score. From all candidate sequences, first select the set of candidate sequences with the highest process continuity score, and then select the sequence with the highest tower crane motion smoothness score from this set as the final output.

6. The simulation system for construction process of PC sandwich wall and composite floor slab connection based on digital twin as described in claim 1, characterized in that, The sequence optimization module is also connected to the real-time signal interface of the tower crane hoisting control system; When generating an optimized construction sequence, a dynamic constraint is added: the spatial position of the current node to be constructed in the sequence must be within a fan-shaped coverage area with the expected stopping position when the previous node above the tower crane boom is completed as the center and the preset length as the radius.

7. The simulation system for construction process of PC sandwich wall and composite floor slab connection based on digital twin as described in claim 6, characterized in that, The length of the preset radius is not a fixed value, but is dynamically calculated by the sequence optimization module based on the control difficulty level of the current node to be constructed; The calculation method is as follows: compare the time required to rotate the tower crane boom from the previous node position to the theoretical position of the current node to be constructed at a constant speed with the standard preparation time for the necessary technical measures to be completed for the current node to be constructed. If the slewing time is greater than the standard preparation time, the maximum working radius of the tower crane shall be used as the sector radius. If the slewing time is less than or equal to the standard preparation time, a calculation radius is used to ensure that the tower crane's slewing time is equal to the standard preparation time, so that the construction preparation is just completed when the tower crane is in place.

8. The simulation system for construction process of PC sandwich wall and composite floor slab connection based on digital twin as described in claim 1, characterized in that, The simulation execution and output module generates construction equipment operation instructions in the following way: For the first node in the optimized construction sequence, a complete instruction package is generated, which includes the initial pressure setting value of the grouting machine, the selection of the vibrator model, and the installation coordinates of the positioning fixture. For each node after the first node in the sequence, the complete instruction package of the current node is compared item by item with the instruction package of the previous node, and only instruction items with different content are generated. The instruction clearly explains the basis for the change in control difficulty level corresponding to each change.

9. The simulation system for construction process of PC sandwich wall and composite floor slab connection based on digital twin as described in claim 1, characterized in that, The system also includes a field data receiving module, which includes: Connect to the measuring instruments at the construction site to receive the final positioning data of the reinforcing bars at the completed construction nodes; The final positioning data of the reinforcing bars is compared with the position deviation value of the reinforcing bars at the node in the simulation system. When the difference between the two exceeds the allowable error range, the control difficulty level of the node is automatically reassessed. Send instructions to the sequence optimization module to perform local replanning of subsequent unconstructed nodes based on the current sequence of constructed nodes, and seamlessly embed the newly planned local sequence into the original optimized construction sequence.

10. The simulation system for construction process of PC sandwich wall and composite floor slab connection based on digital twin as described in claim 1, characterized in that, The simulation execution and output module includes a comparison display unit. The comparison display unit: In the 3D simulation view, each node is connected sequentially according to the original drawing order using the first color line to form the first construction path, and the control difficulty level of the node is marked on the node with different color blocks. Using lines of the second color, connect each node sequentially according to the optimized construction sequence to form a second construction path; On the second construction path, a dynamic arrow indicates the current simulation progress. When the arrow moves to a node where the control difficulty level changes, a pop-up window automatically displays a list of necessary technical measures changes triggered by the level change.

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