Civil construction progress intelligent management method and system

Abstract

This application relates to the field of engineering construction technology, specifically to an intelligent management method and system for civil engineering construction progress. The method includes: determining the total number of people affected and the weighted average service time based on single take-off and landing baseline time parameters and dynamic parameters of the construction area. The dynamic parameters characterize the spatiotemporal distribution of personnel. Based on the total number of people affected, the weighted average service time, and operational fluctuation parameters, the method determines the labor idle cost and, based on the labor idle cost, determines a target scheduling calendar from multiple progress simulation schemes. Based on the target scheduling calendar, the method generates access control instructions and sends them to the access control system. The access control instructions include the work type's access time period and the corresponding work type dependency, enabling the access control system to either deny or allow entry requests outside of the access time period based on the work type dependency. This application provides a method for improving the accuracy and efficiency of construction progress management.

Description

Technical Field

[0001] This application relates to the field of engineering construction technology, specifically to an intelligent management method and system for civil engineering construction progress. Background Technology

[0002] In the construction of large-scale building projects, schedule management is a crucial aspect of ensuring on-time project delivery. As construction projects become increasingly large-scale and time constraints more stringent, the complexity of construction organization and resource scheduling has significantly increased. Construction sites typically involve the parallel progress of multiple work areas (i.e., work grids), which are spatially independent yet interconnected through vertical transportation equipment such as tower cranes. Tower cranes, as indispensable heavy-duty material lifting equipment on civil construction sites, directly impact the progress of each work area. However, due to unforeseen factors such as changes in pre-construction drawings and extreme weather, actual project progress often deviates from the planned schedule, forcing management to implement measures such as compressing subsequent work processes to expedite the process.

[0003] In common rush-work scenarios, managers often force multiple work grids that were originally staggered in time to work concurrently within the same time window. A large number of workers of different trades arrive on site simultaneously, distributed across different work grids, and frequently request material lifting from a limited number of tower cranes. Existing project schedule management tools, such as the critical path method or Gantt chart scheduling software, typically set the duration of each work process based on static execution data from a quota manual and treat equipment capacity as a fixed throughput threshold.

[0004] Therefore, in actual implementation, directly inputting static execution data into the construction site can easily lead to serious backlogs in the tower crane operation queue due to unforeseen fluctuations in equipment service time and a large number of concurrent requests. This can result in a large number of laborers being stranded in the construction area, which not only fails to complete the work on schedule but also causes a significant waste of labor costs, resulting in low efficiency of the overall construction progress. Summary of the Invention

[0005] To address the technical problem of low overall construction progress efficiency, the purpose of this application is to provide an intelligent management method and system for civil engineering construction progress. The specific technical solution adopted is as follows: Firstly, a method for intelligent management of civil engineering construction progress is provided, comprising: constructing a spatial topology weighted graph based on the inter-grid rotation time in the static parameters of the construction area; determining operational fluctuation parameters based on the eigenvalues ​​of the Laplace matrix of the spatial topology weighted graph; the operational fluctuation parameters characterizing the degree of fluctuation caused by spatial discreteness to tower crane service time; the static parameters also include a single lifting and lowering baseline time parameter and work type dependency; determining the total number of obstructed personnel and the weighted average service time based on the single lifting and lowering baseline time parameter and the dynamic parameters of the construction area; the dynamic parameters characterizing the spatiotemporal distribution of personnel; determining the labor idle cost based on the total number of obstructed personnel, the weighted average service time, and the operational fluctuation parameters; and determining a target scheduling calendar from multiple progress simulation schemes based on the labor idle cost; generating access control instructions based on the target scheduling calendar and issuing them to the access control system; the access control instructions including the work type access time period and the corresponding work type dependency, so that the access control system can perform operations of denying or allowing entry requests outside the access time period based on the work type dependency.

[0006] As one possible approach, the process of determining operational fluctuation parameters includes: treating each participating concurrent job grid as a node, determining the edge weights based on the inter-grid rotation time between any two job grids, and constructing an undirected weighted graph. A preset global baseline connectivity value is added to all elements in the edge weight matrix corresponding to the undirected weighted graph. A degree matrix and a Laplacian matrix are generated based on the edge weight matrix after adding the global baseline connectivity value, and the smallest non-zero eigenvalue in the Laplacian matrix is ​​extracted as the grid spatial distribution dispersion characteristic value. Operational fluctuation parameters are determined based on the negative exponential calculation result of the grid spatial distribution dispersion characteristic value and the square of the weighted average service time.

[0007] One possible approach to generating the degree matrix and Laplacian matrix involves: obtaining the weights of all nodes in the undirected weighted graph for their corresponding edges, forming an initial edge weight matrix; superimposing each element of the initial edge weight matrix with a preset global baseline connectivity value to obtain a modified edge weight matrix; aggregating the elements of each row of the modified edge weight matrix to obtain the degree value of the corresponding node, and placing the degree values ​​of each node on the diagonal to generate the degree matrix; and finally, generating the Laplacian matrix based on the degree matrix and the modified edge weight matrix.

[0008] One possible approach is to determine the total number of people blocked and the weighted average service time based on the single take-off and landing baseline time parameter and the dynamic parameters of the construction area. This includes: for any concurrent work grid participating in a single calculation time window, determining the number of people blocked in that grid based on the number of personnel of each type of work assigned to that grid and the corresponding work type dependency, and determining the total number of people blocked based on the number of people blocked in all concurrent grids. Determining the grid call frequency based on the number of personnel of each type of work assigned to that grid and the number of lifts per worker per unit time for that corresponding work type. Determining the request weight based on the proportion of the grid call frequency to the total call frequencies of all concurrent grids, and determining the weighted average service time based on the request weight of each work grid and the corresponding single take-off and landing baseline time parameter.

[0009] One possible approach is to determine the cost of idle labor based on the total number of people affected, the weighted average service time, and operational fluctuation parameters. This includes: determining the total tower crane request frequency based on the grid call frequency of all concurrent work grids, and determining the load factor based on the total tower crane request frequency and the weighted average service time. When the load factor is less than the congestion control threshold, a queuing time evaluation value is determined based on the total tower crane request frequency, the square of the weighted average service time, operational fluctuation parameters, and the load factor. When the load factor is greater than or equal to the congestion control threshold, a queuing time evaluation value is determined based on the degree to which the load factor exceeds the congestion control threshold and the preset daily limit duration. Finally, the cost of idle labor is determined based on the queuing time evaluation value and the total number of people affected.

[0010] One possible approach is to determine the target scheduling calendar from multiple project schedule simulation scenarios based on labor idle costs. This includes: determining a cost tolerance threshold based on the ratio of the project's total labor budget to historical idle costs; aggregating the labor idle costs of a project schedule simulation across all its included time windows to obtain the cumulative idle cost on a calendar; determining the monetized idle cost based on the cumulative idle cost on a calendar and a preset average unit labor hour rate; and identifying project schedule simulation scenarios with monetized idle costs less than or equal to the cost tolerance threshold as compliant candidate scenarios; and finally, extracting the project schedule simulation scenario with the shortest total project completion time from all compliant candidate scenarios as the target scheduling calendar.

[0011] One possible approach involves generating access control commands based on the target scheduling calendar and sending them to the access control system. This allows the system to respond to entry requests outside of permitted hours by either denying or allowing access based on job dependency. This includes: parsing the target scheduling calendar to obtain the permitted hours and job codes for each work grid, and establishing a mapping table between the grid-assigned job codes, permitted hours, and corresponding job dependencies. This mapping table is then sent as access control commands to the facial recognition access controller. Upon receiving an entry request, the facial recognition access controller identifies the person's job category and obtains the current time. If the current time is not within the permitted hours for the job category, it retrieves the job dependency for that category. If the job dependency exceeds a preset parallel work allowable threshold, access is denied. If the job dependency is less than or equal to the parallel work allowable threshold, access is granted.

[0012] As one possible approach, the inter-grid rotation time and the reference time for a single lift-and-lowering operation are determined as follows: the tower crane's rotation center coordinates and the center coordinates of each work grid are extracted from the building information model of the construction area. Based on the tower crane's rated rotation speed and rated lifting speed, the reference time for a single lift-and-lowering operation and the inter-grid rotation time between any two work grids are determined.

[0013] As one possible approach, job dependence and the number of hoisting operations per worker per unit time are determined as follows: Access a pre-set quota database to query the total labor hours and associated machinery hours required for each type of work to complete a standard unit of work. Based on the associated machinery hours and total labor hours, determine the number of hoisting operations per worker per unit time for each type of work. Normalize the ratio of associated machinery hours to total labor hours for all types of work to obtain the job dependence for each type of work.

[0014] Secondly, a civil engineering construction progress intelligent management system is provided, the system comprising: The spatial fluctuation quantification unit is used to construct a spatial topology weighted graph based on the inter-grid rotation time in the static parameters of the construction area. Operational fluctuation parameters are determined based on the eigenvalues ​​of the Laplace matrix of the spatial topology weighted graph. These parameters characterize the degree of fluctuation caused by spatial discretization to the tower crane's service time. Static parameters also include the baseline time for a single lift and lowering operation and the job type dependence.

[0015] The load calculation unit is used to determine the total number of people affected and the weighted average service time based on the baseline time parameters for a single takeoff and landing and the dynamic parameters of the construction area. The dynamic parameters are used to characterize the spatiotemporal distribution of personnel.

[0016] The cost estimation unit is used to determine the cost of idle labor based on the total number of people affected, the weighted average service time, and operational fluctuation parameters.

[0017] The scheduling optimization unit is used to determine the target scheduling calendar from multiple progress simulation schemes based on the cost of idle labor.

[0018] The access control unit is used to generate access control instructions based on the target scheduling calendar and send them to the access control system. The access control instructions include the access time period for each job and the corresponding job dependency, so that the access control system can perform the operation of denying or allowing entry requests outside the access time period according to the job dependency.

[0019] This application has the following beneficial effects: By constructing a spatial topology weighted graph based on the rotation time between grids and extracting the Laplace matrix eigenvalues, the spatial distribution dispersion of the work grid is transformed into a quantifiable operational fluctuation parameter, enabling the scheduling scheme to pre-calculate the additional time fluctuations caused by the tower crane boom serving the dispersed work grids; furthermore, by combining the total number of obstructed personnel with the weighted average service time, the cost of idle labor is determined, and the target scheduling calendar is selected from multiple pre-simulation schemes, thereby avoiding the risks of equipment request backlog and labor idleness at the source; finally, through differentiated access control based on job dependence, the scheduling scheme is ensured to be physically executed, realizing consistent management of construction progress scheduling and on-site labor access, significantly improving the accuracy of construction progress and execution efficiency, thereby reducing the risk of project delays and wasted labor costs. Attached Figure Description

[0020] To more clearly illustrate the technical solutions and advantages in the embodiments of this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0021] Figure 1 This is a flowchart illustrating an intelligent management method for civil engineering construction progress provided in one embodiment of this application. Detailed Implementation

[0022] To further illustrate the technical means and effects adopted by this application to achieve the intended purpose of the invention, the following, in conjunction with the accompanying drawings and preferred embodiments, details the specific implementation, structure, features, and effects of an intelligent management method for civil engineering construction progress proposed in this application. In the following description, different "one embodiment" or "another embodiment" do not necessarily refer to the same embodiment. Furthermore, specific features, structures, or characteristics in one or more embodiments can be combined in any suitable form.

[0023] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application pertains.

[0024] The following description, in conjunction with the accompanying drawings, details a specific scheme for an intelligent management method for civil engineering construction progress provided in this application.

[0025] Please see Figure 1 It illustrates a flowchart of an intelligent management method for civil construction progress according to an embodiment of this application, such as... Figure 1 As shown, the method includes the following steps: S101-S104.

[0026] S101. Construct a spatial topology weighted graph based on the rotation time between grids in the static parameters of the construction area, and determine the operation fluctuation parameters based on the eigenvalues ​​of the Laplace matrix of the spatial topology weighted graph.

[0027] Among them, the operational fluctuation parameter is used to characterize the degree of fluctuation caused by spatial dispersion to the tower crane service time; the static parameters also include the single lifting and lowering benchmark time parameter and the job type dependence.

[0028] In this embodiment, a global spatiotemporal reference is set before constructing the spatial topology weighted map. Since civil construction involves both long-term unchanging drawing space and daily changing labor schedules, the global spatiotemporal reference is set before data acquisition to ensure consistency between the time scale and the spatial reference. All extracted time-consuming variables and rate indicators are uniformly converted into floating-point values ​​with hours as the smallest unit of calculation. The tower crane slewing center coordinates in the Building Information Model (BIM) are anchored as the absolute origin of the global coordinate system. BIM is a digital model based on three-dimensional digital technology, integrating engineering physical and functional characteristic information. In this embodiment, it is used to extract the spatial coordinate data of the tower crane and the work grid, sequentially performing the initial extraction of static reference parameters. Inherent constants are extracted from static architectural drawings and quota standards, including: single lifting and lowering reference time parameters. Time consumed during inter-grid rotation Number of hoisting operations per worker per unit time and job dependence .

[0029] Specifically, in this embodiment, static parameters need to be determined in advance. Static parameters may include the inter-mesh rotation time. Reference time parameters for a single takeoff and landing Job type dependence and the number of times a single worker can lift objects per unit of time. The determination process of the above static parameters will be explained in detail below.

[0030] Time consumed for inter-grid rotation and single takeoff and landing reference time parameters The following methods can be used to determine the following: Extract the tower crane's slewing center coordinates and the center coordinates of each work grid from the building information model of the construction area. Based on the tower crane's rated slewing speed and rated lifting speed, determine the baseline time parameters for a single lifting and lowering operation, as well as the inter-grid slewing time between any two work grids. Identify the total number of independent construction work grids within the target construction area. and define grid index labels. as well as Read the building information model and obtain the set coordinates of the tower crane's slewing center. For the first... For each work grid, obtain the 3D center coordinates of that grid. After obtaining the 3D center coordinates of the grid, use the Euclidean distance formula to calculate the distance from the origin of the tower crane coordinates to that grid. The vertical lifting distance and the arc length of the horizontal rotation angle between the three-dimensional centers of each work grid are calculated. The rated lifting speed specified on the nameplate of the tower crane on site is extracted. (e.g., 4800 m / h) and rated rotation speed (For example, 240 rad / h). Divide the vertical lifting distance by the rated lifting speed to calculate the time for a single lifting operation. Divide the arc length of the horizontal slewing angle by the rated slewing speed to calculate the time for a single slewing operation. Add the time for a single lifting operation to the time for a single slewing operation, and output the result. The baseline time for a single takeoff and landing corresponding to each work grid ,Right now: in, Indicates the first The reference time for a single lift-and-lower operation (also known as the reference time for a single lift-and-lower operation of a tower crane) is the unit of hours for each work grid. Indicates the coordinate origin of the tower crane to the first... The vertical lifting distance of the three-dimensional center of each work grid is expressed in meters. This indicates the rated lifting speed specified on the tower crane's nameplate, in m / h. Indicates the coordinate origin of the tower crane to the first... The horizontal rotation angle arc length of the three-dimensional center of each work grid, in radians; This indicates the rated slewing speed specified on the tower crane's nameplate, in radians per hour (rad / h). This is the baseline time parameter for a single lift-and-lower operation. This reflects that the tower crane is the first The absolute basic time required for each grid to independently complete a round of material hoisting. The larger this value is, the farther away the grid is from the tower crane or the higher it is, and the longer the rigid time of a single service.

[0031] Obtain the baseline time parameters for a single takeoff and landing Then, for any two different grids within the boom slewing working surface on site (the first grid... The grid and the first (Multiple grids), calculate the horizontal spatial angle between the center points of the two points relative to the origin of the tower crane coordinate system. Divide this horizontal spatial angle by the rated slewing speed. Output the time taken for inter-mesh rotation between these two meshes. ,Right now: in, Indicates the first The first task grid and the first Inter-grid rotation time between individual task grids, in hours; Indicates the first The center point of the first task grid and the first The horizontal spatial angle between the center point of each work grid and the origin of the tower crane coordinate system is expressed in radians. This indicates the rated slewing speed specified on the tower crane's nameplate, in radians per hour. The time taken for slewing between the grid sections... The higher the value, the higher the time cost of the tower crane boom moving laterally between the two grids.

[0032] Job Dependency Number of hoisting operations per worker per unit time The following methods can be used to determine the required labor hours and supporting machinery hours for each type of work to complete a standard unit of work: Access a pre-set quota database to query the total labor hours and supporting machinery hours required for each type of work to complete a standard unit of work. Based on the supporting machinery hours and total labor hours, determine the number of hoisting operations per worker per unit time for each type of work. Normalize the ratio of supporting machinery hours to total labor hours for all types of work to obtain the work dependency for each type of work. The pre-set quota database contains official data sets of standards for labor, materials, and machinery hours required for various construction engineering procedures. In this embodiment, it is used to obtain the labor hours and tower crane hours required for each type of work to complete a unit of work.

[0033] Specifically, identify the total number of labor types involved at the construction site. Define job index numbers Access the pre-set quota database, targeting the first... This query shows the total man-hours required to complete a standard unit of work for each type of job. Simultaneously query the corresponding machine shift consumption of the standard unit project quantity. .

[0034] The ratio coefficient is used to calculate the proportion of machine shifts required per unit of human labor hours. / This ratio coefficient is a dimensionless proportionality coefficient, representing the first... The degree to which certain types of work rely on tower cranes. This includes the standard number of lifting operations per shift. The time can be determined based on the average value of the single takeoff and landing baseline time parameter corresponding to each work grid, and the calculation formula is as follows: .in, This is the standard daily working time constant (e.g., 8 hours) specified for a standard shift. This is the arithmetic mean of the baseline takeoff and landing time parameters for all job grids. The unit is times per hour, representing the standard number of lifts that a tower crane can complete continuously at full load in a standard shift. Multiplying the proportionality coefficient by the standard number of lifts per shift outputs the number of lifts. Number of hoisting operations per worker per unit time for each type of work ,Right now: in, Indicates the first The number of times a single worker can lift objects per unit of time for each type of work, measured in times per hour; Indicates the first The number of machine shifts required for a type of work to complete a standard unit of work, in machine shifts; Indicates the first The total man-hours required for a given type of work to complete a standard unit of work, expressed in man-hours. A higher value for this parameter indicates a higher level of labor intensity. The more times a worker in a certain type of job makes a work call to the tower crane within an hour, the better.

[0035] Output the number of times a single worker lifts a crane per unit of time. Then, extract all The percentage of machine hours consumed by a type of work as a percentage of the total man-hours consumed by the corresponding workers. .

[0036] Extract the numerical proportions of all job types Subsequently, to assess the relative dependence of different work types on tower crane equipment, a maximum-minimum normalization method with zero-reduction protection was adopted to uniformly map these numerical proportions to a range greater than 0 and less than or equal to 1. The mapping calculation was performed using the following formula: in, Indicates the first Job dependency degree corresponding to a type of job; Indicates the first The ratio of machine shifts to manual labor hours for each type of work. Indicates all of the construction site The maximum value of the numerical proportion in a given job category; Indicates all of the construction site The minimum numerical proportion among different job categories; combination items This represents the extreme range of dependence on the tower crane by all types of workers on site. This represents the first preset constant, which is set to 0.001 in this embodiment. This constant is used to prevent calculation errors caused by a zero denominator, ensuring the stability of the mapping calculation. The resulting calculation error is within the allowable range.

[0037] Calculate and output the first value using the mapping formula described above. Job Dependency of Job Type The closer this parameter value is to 1, the more dependent the job is on the tower crane; if the tower crane is unavailable, work will stop. The closer this parameter value is to 0, the lower the probability that the job will be forced to stop work due to the absence of the tower crane, and the stronger its ability to carry out independent parallel ground operations.

[0038] This step involves constructing a spatial topology weighted graph based on the inter-grid rotation time from the static parameters of the construction area, and determining the operational fluctuation parameters based on the eigenvalues ​​of the Laplace matrix of the spatial topology weighted graph. These operational fluctuation parameters characterize the degree of fluctuation in tower crane service time caused by spatial discretization, and can be the variance of the tower crane's cross-regional operational time. Static parameters also include the baseline time parameter for a single lift and lowering operation and the job type dependency.

[0039] Optionally, the process of determining the above-mentioned operational fluctuation parameters includes: S1011 to S1014.

[0040] S1011. Treat each job grid participating in the concurrency as a node, determine the weight of the edge based on the rotation time between any two job grids, and construct an undirected weighted graph.

[0041] Determine the current time window Total number of concurrent grids When the total number of concurrent grids When the value equals 1, it is determined that there is no equipment transfer across regions without load, and the operating fluctuation parameter is directly set. The value is assigned to 0.

[0042] When the total number of concurrent grids When the value is greater than 1, each job grid participating in the concurrency is treated as a node. The weight of the edge is determined based on the inter-grid rotation time between any two job grids, and an undirected weighted graph representing the topological characteristics of the concurrent jobs is constructed. Specifically, obtain any two grids (grids...) With grid Inter-mesh rotation time between ) To prevent two grids at the same rotation angle from causing... If it is 0, then With the second preset constant (In this embodiment, the value is 0.01 hours, representing the physical and mechanical delay of boom start-up and shutdown.) Add them together, and calculate the reciprocal of the sum, that is: in, Represents the connection nodes in an undirected weighted graph. With nodes Edge weights; Indicates the first The first task grid and the first Inter-grid rotation time between individual task grids, in hours; To preset a minimum value, this embodiment uses 0.01 hours to prevent calculation errors caused by a denominator of zero. The resulting computational error is within acceptable limits. The larger the edge weight value, the shorter the time it takes for the upper arm to switch between these two grids, and the tighter the spatial connection.

[0043] After determining the edge weights of all node pairs, the generated size is... edge weight matrix .

[0044] S1012. Add a preset global basic connectivity value to all elements in the edge weight matrix corresponding to the undirected weighted graph.

[0045] Specifically, to prevent the graph from breaking into a disconnected graph due to individual grids being completely isolated in space (with infinitely long idle time), which would cause the Laplacian eigenvalues ​​to degenerate to 0, the edge weight matrix... All elements are appended with a preset global base connectivity value. (In this embodiment, the value is 0.001). Through additional operations, an approximately fully connected topology is constructed.

[0046] S1013. Generate a degree matrix and a Laplacian matrix based on the edge weight matrix after adding global basic connectivity values, and extract the smallest non-zero eigenvalue in the Laplacian matrix as the eigenvalue of the grid spatial distribution dispersion.

[0047] Optionally, the above process of generating the degree matrix and the Laplacian matrix includes: S11 to S14.

[0048] S11. Obtain the weights of all nodes in the undirected weighted graph for their corresponding edges, and form an initial edge weight matrix.

[0049] S12. Add each element of the initial edge weight matrix to the preset global basic connectivity value to obtain the modified edge weight matrix. ,Right now: in, Represents the modified edge weight matrix The Middle Line 1 Column elements; Represents the initial edge weight matrix The Middle Line 1 Column elements; This represents the preset global basic connectivity value, which can be 0.001 in this embodiment.

[0050] S13. Based on the corrected edge weight matrix, aggregate the elements of each row to obtain the degree value of the corresponding node, and place the degree values ​​of each node on the diagonal to generate the degree matrix. Specifically, for each row of the corrected edge weight matrix, the values ​​of all corrected edge weights in that row are summed, and the sum is placed on the diagonal of the corresponding row. Elements in the off-diagonal positions are padded with 0. That is: in, Degree matrix The Middle Line 1 The diagonal elements of the column; Represents the modified edge weight matrix The Middle Line 1 Column elements; This represents the total number of concurrent job grids. Degree matrix. All elements except those on the diagonal are 0.

[0051] S14. Generate the Laplacian matrix based on the degree matrix and the modified edge weight matrix. Specifically, the degree matrix Subtract the corrected edge weight matrix The Laplacian matrix representing the current concurrent network structure is generated through the subtraction operation. .

[0052] Generate Laplacian matrix Then, this Laplace matrix Perform eigenvalue decomposition to obtain the complete set of eigenvalues ​​for the matrix. Extract the smallest non-zero eigenvalue (i.e., algebraic connectivity) from the eigenvalue set, and define this smallest non-zero eigenvalue as the grid spatial distribution dispersion eigenvalue. The spatial distribution dispersion characteristic value of this grid. The smaller the value, the more scattered the distribution of the current concurrent job grid on site.

[0053] S1014. Determine the operation fluctuation parameters based on the negative exponential calculation result of the grid spatial distribution dispersion characteristic value and the square value of the weighted average service time.

[0054] Extracting the spatial distribution dispersion feature value of the grid Then, the operational fluctuation formula is used for conversion calculation to determine the operational fluctuation parameters. For example, the operational fluctuation formula can be: in, This represents the operational fluctuation parameter, expressed in the square of hours. This represents the characteristic value of the spatial distribution dispersion of the grid. This represents an exponential function with the natural constant as its base, since The smaller the value, the more dispersed the result. Taking a negative exponent will cause the value of the result to increase exponentially with the degree of dispersion. This represents the weighted average service time (i.e., the weighted average base time), in hours. This indicates that the weighted average service time is squared to provide the basic order of magnitude for the square of the time dimension; This is a preset normalization constant. In this embodiment, the value of c can be determined by averaging the weights of all off-diagonal elements in the undirected weighted graph. This value reflects the average ease of switching between work grids for the tower crane in the current construction layout. Thus, by combining the grid spatial distribution dispersion characteristic value with this normalization constant... The ratio is used as the input for the negative exponent operation, which not only ensures the harmony of dimensions and the numerical stability of the calculation, but also effectively quantifies the relative dispersion of the current grid space distribution based on the average connectivity level of the system itself.

[0055] It should be noted that here The resulting weighted average service time includes the expected inter-grid transfer time. Its squared term... It reflects the square of the baseline magnitude of the complete service duration.

[0056] S102. Based on the baseline time parameters for a single takeoff and landing and the dynamic parameters of the construction area, determine the total number of people affected and the weighted average service time. The dynamic parameters characterize the spatiotemporal distribution of the personnel.

[0057] Optionally, the total number of people affected and the weighted average service time can be determined based on the baseline time parameters for a single take-off and landing and the dynamic parameters of the construction area, including: S1021 to S1023.

[0058] S1021. For any concurrent work grid within a single calculation time window, determine the number of grid-blocked personnel in that grid based on the number of personnel of each type of work assigned to that grid and the job dependency of the corresponding type of work, and determine the total number of blocked personnel based on the number of grid-blocked personnel in all concurrent grids.

[0059] Specifically, the current calculation time window in the extraction progress simulation plan. Total number of independent work grids participating in concurrent construction operations For any job grid participating in concurrency within a single computation time window, iterate through the jobs assigned to that grid. Different types of jobs.

[0060] Get the first assigned grid cell Planned number of workers for each type of job Retrieving the statically stored... Job Dependency of Job Type The planned number of people to be allocated Multiply by job type dependence The result is the first [unit] in the grid. The base number of workers in a single trade whose work will inevitably be disrupted due to the lack of tower cranes, i.e.: in, Indicates the first Within the first task grid The base number of people whose individual jobs are disrupted within a certain category of work; Indicates time window Internal allocation to the first The first task grid The planned number of workers allocated to each type of job, in units of individuals; Indicates the first The job dependency ratio corresponding to each type of work is a dimensionless parameter. This baseline excludes redundant personnel capable of performing parallel construction operations, reflecting the true scale of rigid work stoppages.

[0061] Based on the same traversal logic, proceed sequentially from category 1 to category 2. Perform multiplication calculations on the same type of work, and include all within that grid. The base number of people obstructed in each type of work category is added together to obtain the number of obstructed workers. The number of people blocked in each work grid, i.e.: in, Indicates the first Each task grid within the time window The number of people blocked within the grid; This indicates the total number of labor types involved in the construction site.

[0062] Perform the same nested calculations as described above on all the remaining job grids in sequence, and then... The number of people blocked in each work grid is accumulated, and the total number of people blocked is determined by the accumulation operation. in, Indicates the current time window The total number of people whose work was disrupted due to the absence of an inner tower crane, expressed in individuals; Indicates the current time window The total number of independent work grids participating in concurrent construction operations.

[0063] S1022. Determine the grid call frequency based on the number of personnel of each type of work assigned to the grid and the number of times a single worker of the corresponding type of work can lift objects per unit time.

[0064] Specifically, retrieve the number assigned to this grid. Planned number of workers for each type of job Retrieving the statically stored... Number of hoisting operations per worker per unit time for each type of work The planned number of people to be allocated Multiply by the number of times a single worker lifts a crane per unit of time. The result is the first [unit] in the grid. The frequency of individual work requests initiated by a group of workers to the tower crane. A higher individual work request frequency indicates that the group of workers requests the crane hook more frequently.

[0065] Following the same traversal logic, proceed sequentially from category 1 to category 2. Perform multiplication calculations on the same type of work, and include all within that grid. The request frequencies of individual job types within the same job category are summed to obtain the first... The grid call frequency of each job grid, i.e.: in, Indicates the first Each task grid within the time window The grid call frequency within the grid is measured in times per hour.

[0066] All The grid call frequencies of each task grid are accumulated, and the current time window is output through the accumulation operation. Total request frequency of tower cranes within ,Right now: in, Indicates the current time window Total tower crane request frequency within the area, in hours. -1 .

[0067] S1023. Determine the request weight based on the proportion of the grid call frequency in all concurrent grid call frequencies, and determine the weighted average service time based on the request weight of each job grid and the corresponding single take-off and landing baseline time parameter.

[0068] The first Grid call frequency per task grid Divide by the total frequency of tower crane requests This yields the request weight of the hoisting request initiated by this grid relative to the global demand, namely: in, Indicates the first Each task grid within the time window The request weight within is a dimensionless parameter.

[0069] The request weight Multiply by the corresponding statically stored single takeoff and landing baseline time parameter The purpose of this multiplication operation is to assign a higher baseline time weight to grids that call frequently.

[0070] All The summation of the product results of each grid cell yields the baseline weighted average takeoff and landing time. .

[0071] in, Indicates the first The baseline time for a single takeoff and landing corresponds to each work grid.

[0072] Further factoring in the expected inter-grid transfer time generated when the tower crane continuously serves different grids is considered. Based on the probability distribution of grid request weights, the expected transfer time is... for: Indicates the first Each task grid within the time window Request weight within.

[0073] The weighted average service time is determined by the sum of the baseline weighted average takeoff and landing time and the expected transfer time. .

[0074] S103. Based on the total number of people affected, the weighted average service time, and operational fluctuation parameters, determine the labor idle cost, and determine the target scheduling calendar from multiple progress simulation schemes based on the labor idle cost.

[0075] Optionally, the cost of idle labor can be determined based on the total number of people affected, the weighted average service time, and operational fluctuation parameters, including: S1031 to S1034.

[0076] S1031. Determine the total request frequency of tower cranes based on the grid call frequency of all concurrent operation grids, and determine the load factor based on the total request frequency of tower cranes and the weighted average service time.

[0077] The load factor, also known as the service intensity in queuing theory, represents the expected proportion of tower cranes in operation per unit time.

[0078] Specifically, the total tower crane request frequency is determined based on the grid call frequency of all concurrent job grids. In terms of the total request frequency of tower cranes. After that, a judgment was made. Is it greater than 0? If so, determine. If the value is 0 (meaning there are no jobs requiring a tower crane call within the current time window), the queuing time evaluation value for a single task will be directly set. and the cost of idle labor The value is forcibly assigned to 0, skipping the queuing model calculation in the current time window and directly advancing to the next time window to prevent subsequent division calculations from crashing.

[0079] If the judgment Greater than 0, the total request frequency of tower cranes Multiply by weighted average service time The current time window is calculated through multiplication. Load rate of internal tower crane equipment ,Right now: in, Indicates the current time window The load factor of the internal tower crane equipment is a dimensionless parameter; This represents the weighted average service time, in hours. This load factor... The value represents the expected proportion of tower cranes in operation per unit time (i.e., the busyness of the equipment). When the value is closer to 1, it indicates that the equipment is operating at full capacity and the queue backlog will worsen sharply.

[0080] S1032. When the load rate is less than the congestion control threshold, the queuing time evaluation value is determined based on the total request frequency of tower cranes, the square of the weighted average service time, the operation fluctuation parameters, and the load rate.

[0081] Specifically, when the load factor Less than the congestion control threshold (Congestion control threshold in this embodiment) A setting of 0.95 (this value accommodates necessary maintenance downtime and operator shift changes) indicates that the tower crane is in an unsaturated queue state. The waiting time is calculated using the Pollacek-Khinchin formula (PK formula) corresponding to the general service time queue model (M / G / 1). The following formula is used for the solution: in, This represents the queue waiting time evaluation value, in hours. This indicates the total request frequency of the tower crane, measured in times per hour (times / h). It can be understood as the number of request events arriving per unit of time, and is equivalent to the reciprocal of time in terms of dimensions. This represents the weighted average service time, in hours. This represents the operational fluctuation parameter, expressed in the square of hours. Indicates the load factor (i.e.) ), which is a dimensionless parameter; combined terms This represents the second-order moment component of service time, which is the sum of the square of the average reference time and the variance parameter representing spatial dispersion, reflecting the overall second-order dispersion of service time under non-ideal conditions; (Combined term) As a numerator term in the formula, its value increases linearly with the increase of the request frequency or spatial variance, representing the incremental source of queue backlog; the combination term... As a term in the denominator of the formula, its value varies with the load factor. Approaching 1 and rapidly approaching 0, the denominator becomes smaller as the load rate increases, resulting in an exponential amplification of the final calculation result.

[0082] Understandably, this step only applies to load factor. The congestion control is executed when the threshold value is less than 0.95, therefore the denominator term... It is always greater than zero and will not cause a division-by-zero anomaly.

[0083] The above division operation outputs a queueing time evaluation value that conforms to the fluctuations in on-site spatial consumption. The waiting time Objectively, this includes the operational wear and tear caused by the frequent switching of equipment across spaces.

[0084] S1033. When the load rate is greater than or equal to the congestion control threshold, the queuing waiting time evaluation value is determined based on the degree to which the load rate exceeds the congestion control threshold and the preset daily limit duration.

[0085] Specifically, when the load factor Greater than or equal to the congestion control threshold When the value reaches 0.95, the tower crane overload condition is determined. At this point, the conventional queuing formula is stopped, and instead, the overload delay evaluation function with a continuous gradient is called to avoid the inability to distinguish the severity of the poor solution due to fixed assignment (such as directly assigning 8 hours).

[0086] Specifically, calculate the overload amount Multiply this overload amount by the daily limit duration constant. (In this embodiment, according to relevant labor laws, the standard daily shift work time is taken as 8 hours). The product result is then multiplied by the daily limit work time constant. The addition operation yields a queue waiting time evaluation value with gradient continuity. ,Right now: At this point, the queue waiting time evaluation value for the current time window is taken as the overload penalty.

[0087] The overload penalty is used to impose a penalty evaluation value of at least one full workday on overload schemes that exceed the congestion control threshold, and it increases linearly with the degree of overload, with the unit being hours (h). This represents the load factor, which is a dimensionless parameter. This represents the congestion control threshold, which is set to 0.95 in this embodiment. This represents the daily maximum duration constant, which is 8 hours in this embodiment.

[0088] S1034. Determine the cost of idle labor based on the evaluation value of queuing time and the total number of people blocked.

[0089] Specifically, the queuing time evaluation value for the current time window is calculated from the PK formula under unsaturated operating conditions and from the overload penalty function under overload operating conditions. The queuing time evaluation value is output. Then, extract a specific time window. The queue waiting time rating within Rate the queue waiting time. Multiply by the total number of people whose work was disrupted due to the absence of the corresponding tower crane. The current progress simulation plan is output through multiplication within this time window. The cost of idle labor arising from this (a specific expression of the cost of idle labor within a single time window). ,Right now: in, This indicates the current progress simulation plan within the time window. The cost of idle labor caused by this is calculated in units of hours. This indicates the total number of people affected by the work stoppage due to the absence of tower cranes, expressed in units. The cost of this idle labor is calculated. The larger the value, the more severe the loss of wages and construction stoppage caused by the current concurrent scheduling.

[0090] For each time window within the lifecycle of a single pre-project schedule. The aforementioned steps S102 to S103 are executed repeatedly. After the loop is completed, the labor idleness cost, including all time windows, is calculated. These cost sets are output to subsequent scheduling optimization steps. These cost sets will serve as penalty indicators, driving the scheduling optimization engine to individually eliminate poor scheduling simulation schemes that cause large-scale queuing congestion.

[0091] Optionally, a target scheduling calendar can be determined from multiple progress simulation scenarios based on the cost of idle labor, including S1035 to S1037.

[0092] S1035. Determine the allowable cost threshold based on the ratio of the total project labor budget to historical idle labor costs.

[0093] Specifically, before implementing the scheduling optimization, it is necessary to set an objective elimination benchmark, namely, a cost tolerance threshold. (This represents the maximum amount of idle labor costs the project can afford). Read the total planned labor budget prepared in advance by the project management department. After retrieving the budgeted costs, the system accesses the historical project database and extracts the average percentage of force majeure-related downtime costs to total labor budget costs from similar historical projects. Extract the average percentage. Then, the total planned labor budget will be calculated. Multiply by that average percentage The objective cost tolerance threshold is obtained through multiplication calculation. ,Right now: in, This represents the acceptable cost threshold, expressed in yuan. This represents the total planned labor budget cost prepared in advance by the project management department, in yuan. This represents the average percentage of force majeure-related downtime costs in the total labor budget, based on statistics from similar historical projects. It is a dimensionless parameter. Determining the allowable cost threshold in this way can eliminate the arbitrariness of subjective human setting.

[0094] In addition, to support comparisons with the same units, we accessed the historical project database and extracted the average unit labor hour rate from similar historical projects, in yuan / person·hour.

[0095] S1036. Aggregate the labor idle costs of a progress simulation plan within all time windows it contains to obtain the cumulative calendar idle cost. Based on the cumulative calendar idle cost and the preset average unit labor hour rate, determine the monetized idle cost, and identify the progress simulation plan with a monetized idle cost less than or equal to the cost allowable threshold as a compliant candidate plan.

[0096] Specifically, the acceptable cost threshold is derived. Then, conventional scheduling optimization engines such as multi-objective genetic algorithms are activated. In each progress simulation calculation, a single complete progress simulation schedule is generated. For this single progress simulation schedule, the total project completion time is extracted.

[0097] After extracting the total project completion time, perform a preliminary schedule simulation covering all time windows from the first day of work to the last day. Labor idleness conversion cost The total downtime cost caused by this single progress simulation schedule is calculated cumulatively and output as the cumulative calendar idle cost (a cumulative expression of labor idle cost at the overall schedule level). ,Right now: in, This indicates the cumulative cost of calendar inactivity, expressed in hours. Indicates time window The cost of idle labor within the area; This indicates the total number of time windows included in the progress rehearsal schedule.

[0098] Calculate the cumulative idle cost of the calendar Next, the product of the cumulative calendar idle cost and the average unit labor hour rate is calculated as the corresponding monetized idle cost. This monetized idle cost is then compared with the cost tolerance threshold calculated above.

[0099] When the cost of monetizing idle resources exceeds the allowable cost threshold, the schedule simulation plan is marked as invalid. This means that although the plan may forcibly compress the paper schedule, it will lead to extreme queuing of tower cranes and severe idle labor. The invalid schedule is removed from the feasible solution set, and the scheduling engine is driven to readjust the process start time to generate a new round of schedule simulation.

[0100] When the cost of monetizing idle resources is determined to be less than or equal to the allowable cost threshold, the progress rehearsal scheduling scheme is marked as a compliant candidate scheme, and all schemes marked as compliant candidate schemes are collected and formed into a candidate set.

[0101] S1037. From all compliant candidate solutions, extract the progress simulation solution with the shortest total project completion time and use it as the target scheduling calendar.

[0102] Specifically, for this candidate set, the total completion time of the projects included in the plan is used as the sole benchmark for comparison, and the plan is sorted in ascending order. After sorting in ascending order, the compliant candidate plan that is at the top of the sequence (i.e., the shortest total completion time) is extracted. The extracted scheduling plan is then officially output as the final target scheduling calendar (also known as the optimal off-peak construction scheduling calendar). This calendar achieves the shortest construction cycle while meeting the upper limit of equipment load.

[0103] S104. Generate access control instructions based on the target scheduling calendar and send them to the access control system. The access control instructions include the job type access time period and the corresponding job type dependency, so that the access control system can perform the operation of denying or allowing entry requests outside the access time period according to the job type dependency.

[0104] Even if the computer calculates a staggered construction calendar to avoid congestion, in actual civil construction management, some workers from certain work teams may still enter the construction area and seize work surfaces during unscheduled periods. To prevent disorderly increases in labor from exceeding the calculated tower crane load-bearing limit, hardware verification methods are used in the access control system to forcibly intervene in entry requests. Simultaneously, to avoid blindly blocking workers capable of parallel work from entering, a differentiated release logic based on job type dependence is introduced.

[0105] Optionally, an access control instruction is generated based on the target scheduling calendar and sent to the access control system so that the access control system can perform operations such as denying or allowing entry requests during non-access periods according to job type dependency, including: S1041 to S1045.

[0106] S1041. Parse the target scheduling calendar, obtain the job access time period and job code assigned to each job grid, and establish an association mapping table of job code assigned to grid, job access time period and corresponding job dependency.

[0107] Specifically, the optimal off-peak construction scheduling calendar output above is parsed. For any future construction date, all construction operation grids involved in the calendar are parsed. For each construction operation grid, the specific job category allowed to enter the grid to carry out work (defined as the grid-assigned job code) and the specific start and end times of the time period allowed for that job (defined as the job access period) are extracted.

[0108] Synchronously retrieve the job dependency (also known as the proportion of job downtime affected by tower crane) corresponding to the job code assigned to this grid from static storage. The grid will assign job codes, job entry periods, and corresponding job dependencies. Establish an association mapping table.

[0109] S1042. Send the association mapping table as an access control command to the face recognition access controller of the access control system.

[0110] Specifically, the aforementioned association mapping table is encapsulated into a structured access verification data packet. This access verification data packet is then sent to the memory of the facial recognition access control controller at the perimeter of the construction site via an IoT communication interface.

[0111] S1043. When the facial recognition access control controller receives a request for personnel to enter the premises, it identifies the personnel's job category and obtains the current time.

[0112] Specifically, when a person requests passage by scanning their face, the facial recognition access controller reads the person's identity and corresponding job category identified by the front-end camera, and simultaneously reads the current hardware clock time.

[0113] S1044. When the current time is not within the job access period corresponding to the job category, retrieve the job dependency corresponding to the job category.

[0114] Specifically, when the current time is not within the permitted entry time period for the job category (i.e., the current clock is not within the permitted entry time period for the job corresponding to the facial recognition worker, constituting unauthorized entry), in order to prevent mistakenly blocking parallel workers who do not rely on the tower crane, the facial recognition access control controller further retrieves the job dependency information of the corresponding job from the access verification data packet. .

[0115] S1045. When the job dependency is greater than the preset parallel operation allowable threshold, execute the rejection release operation; when the job dependency is less than or equal to the parallel operation allowable threshold, execute the release operation.

[0116] Specifically, the facial recognition access control controller reads the job category and compares it with the current clock time in the locally stored access verification data packet using Boolean logic. When the time comparison result is true (i.e., the current clock time is within the access time period for the corresponding job, and the person is in compliance with the scheduled entry), the facial recognition access control controller drives the internal relay to open the gate and allow entry.

[0117] When the time comparison result is false, the facial recognition access control system retrieves the job dependency information for that person's corresponding job type. Then, the dependence on this type of work. Parallel operation allowed threshold (In this embodiment, the value can be taken as 0.3 based on engineering experience) for size comparison.

[0118] When the job dependence exceeds the allowable threshold for parallel operations, it indicates that the person is highly dependent on tower crane auxiliary operations (such as carpentry hoisting large formwork). Once they enter the site, they will inevitably call the tower crane, thereby disrupting the original queuing model balance. At this time, the relay is kept in the off state, and the access control gate is executed to refuse passage.

[0119] When the job dependency is less than or equal to the allowable threshold for parallel operations, it indicates that the worker's job has full ground-based parallel operation capabilities (e.g., on-site material cleaning, manual tying of foundation slab reinforcement). The entry of such personnel will not additionally increase the tower crane's queuing load. However, to avoid overloading of the work surface space due to a large influx of parallel workers during unplanned periods, a space capacity check is further performed in this case: Retrieve the target work grid that the person requested to access via facial recognition. In the time window The planned number of people to be assigned to the grid, and the actual number of people currently present in the grid as recorded by the access control system. The product of the space capacity allowance factor (e.g., a value of 1.2, which allows for 20% overcrowding) and the planned number of people to be assigned is used as the upper limit of the space capacity allowance.

[0120] When the actual number of people present in a grid is greater than or equal to the maximum allowable capacity of the space, the grid is determined to be saturated, the relay is kept off, and a denial of passage operation is performed.

[0121] When the number of people actually present in a grid is less than the maximum allowable capacity of the space, it is determined that there is still space available in the grid. The relay is then activated to open the gate and allow passage, and the person is simultaneously added to the current number of people actually present in the grid.

[0122] Through the differentiated hardware interception and release operations based on the dual verification of job dependence and space capacity, the disorderly spread of tower crane-related labor increments to the work face was precisely blocked, and the overloading of the work face space was effectively prevented when releasing parallel operations that are not dependent on tower cranes. In the end, a two-way closed loop of data and physical data was completed for the intelligent management of civil construction progress.

[0123] One embodiment of this application provides an intelligent management system for civil engineering construction progress. This system includes: a spatial fluctuation quantification unit 201, a load calculation unit 202, a cost estimation unit 203, a scheduling optimization unit 204, and an access control unit 205. The units communicate bidirectionally via a communication link, ensuring real-time interaction of collected data and analysis results. The communication link can employ wired or wireless transmission methods to meet the communication needs of different monitoring scenarios.

[0124] The spatial fluctuation quantification unit 201 is used to construct a spatial topology weighted graph based on the inter-grid rotation time in the static parameters of the construction area. Operational fluctuation parameters are determined based on the eigenvalues ​​of the Laplace matrix of the spatial topology weighted graph. These parameters characterize the degree of fluctuation caused by spatial discretization to the tower crane's service time. Static parameters also include the single-lift / lowering baseline time parameter and the work type dependency.

[0125] The load calculation unit 202 is used to determine the total number of people affected and the weighted average service time based on the baseline time parameters for a single take-off and landing and the dynamic parameters of the construction area. The dynamic parameters are used to characterize the spatiotemporal distribution of personnel.

[0126] Cost estimation unit 203 is used to determine the cost of idle labor based on the total number of people affected, the weighted average service time, and operational fluctuation parameters.

[0127] The scheduling optimization unit 204 is used to determine the target scheduling calendar from multiple progress simulation schemes based on the cost of idle labor.

[0128] The access control unit 205 is used to generate access control instructions based on the target scheduling calendar and send them to the access control system. The access control instructions include the job access time period and the corresponding job dependency, so that the access control system can perform the operation of denying or allowing entry requests outside the access time period according to the job dependency.

[0129] It should be noted that the order of the embodiments described above is merely for descriptive purposes and does not represent the superiority or inferiority of the embodiments. The processes depicted in the accompanying drawings do not necessarily require a specific or sequential order to achieve the desired result. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0130] The various embodiments in this specification are described in a progressive manner. The same or similar parts between the various embodiments can be referred to each other. Each embodiment focuses on describing the differences from other embodiments.

Claims

1. A method for intelligent management of civil engineering construction progress, characterized in that, The method includes: A spatial topology weighted graph is constructed based on the inter-grid rotation time in the static parameters of the construction area. The operation fluctuation parameters are determined based on the eigenvalues ​​of the Laplace matrix of the spatial topology weighted graph. The operation fluctuation parameters are used to characterize the degree of fluctuation caused by spatial discretization to the tower crane service time. The static parameters also include the single lifting and lowering baseline time parameter and the job type dependence. Based on the single take-off and landing baseline time parameter and the dynamic parameters of the construction area, the total number of people obstructed and the weighted average service time are determined, and the dynamic parameters are used to characterize the spatiotemporal distribution of the personnel. Based on the total number of people blocked, the weighted average service time, and the operational fluctuation parameters, the labor idle cost is determined, and the target scheduling calendar is determined from multiple progress simulation schemes based on the labor idle cost; Based on the target scheduling calendar, an access control instruction is generated and sent to the access control system. The access control instruction includes the job type access time period and the corresponding job type dependency, so that the access control system can perform the operation of denying or allowing entry requests outside the access time period according to the job type dependency.

2. The intelligent management method for civil construction progress according to claim 1, characterized in that, The process of determining the operational fluctuation parameters includes: Each concurrent job grid is treated as a node, and the weight of the edge is determined based on the inter-grid rotation time between any two job grids, thus constructing an undirected weighted graph. A preset global basic connectivity value is added to all elements of the edge weight matrix corresponding to the undirected weighted graph; Generate a degree matrix and a Laplacian matrix based on the edge weight matrix after adding the global basic connectivity value, and extract the smallest non-zero eigenvalue in the Laplacian matrix as the feature value of the grid spatial distribution dispersion. The operational fluctuation parameters are determined based on the negative exponential calculation result of the grid spatial distribution dispersion characteristic value and the square value of the weighted average service time.

3. The intelligent management method for civil construction progress according to claim 2, characterized in that, The process of generating the degree matrix and the Laplacian matrix includes: Obtain the weights of all nodes in the undirected weighted graph for their corresponding edges, and form an initial edge weight matrix; Each element in the initial edge weight matrix is ​​superimposed with the preset global basic connectivity value to obtain the modified edge weight matrix; Based on the modified edge weight matrix, the elements of each row are aggregated to obtain the degree value of the corresponding node, and the degree values ​​of each node are placed on the diagonal to generate the degree matrix. The Laplacian matrix is ​​generated based on the degree matrix and the modified edge weight matrix.

4. The intelligent management method for civil construction progress according to claim 1, characterized in that, The process of determining the total number of people affected and the weighted average service time based on the single take-off and landing baseline time parameter and the dynamic parameters of the construction area includes: For any concurrent work grid within a single computation time window, the number of grid-blocked personnel in that grid is determined based on the number of personnel of each type of work assigned to that grid and the work dependency of the corresponding type of work, and the total number of blocked personnel is determined based on the number of grid-blocked personnel in all concurrent grids. The grid call frequency is determined based on the number of personnel of each type of work assigned to the grid and the number of times a single worker of the corresponding type of work can lift objects per unit time. The request weight is determined based on the proportion of the grid call frequency to all concurrent grid call frequencies, and the weighted average service time is determined based on the request weight of each job grid and the corresponding single take-off and landing baseline time parameter.

5. The intelligent management method for civil construction progress according to claim 4, characterized in that, The determination of the labor idle cost based on the total number of people blocked, the weighted average service time, and the operational fluctuation parameters includes: Based on the grid call frequency of all concurrent job grids, determine the total tower crane request frequency, and based on the total tower crane request frequency and the weighted average service time, determine the load factor; When the load rate is less than the congestion control threshold, the queuing waiting time evaluation value is determined based on the total request frequency of the tower crane, the square of the weighted average service time, the operation fluctuation parameters, and the load rate. When the load rate is greater than or equal to the congestion control threshold, the queuing waiting time evaluation value is determined based on the degree to which the load rate exceeds the congestion control threshold and the preset daily limit duration. The cost of idle labor is determined based on the queue waiting time evaluation value and the total number of people blocked.

6. The intelligent management method for civil construction progress according to claim 1, characterized in that, The step of determining the target scheduling calendar from multiple progress simulation schemes based on the labor idle cost includes: The acceptable cost threshold is determined based on the ratio of the total project labor budget to historical idle labor costs. Aggregate the idle labor costs of a progress simulation plan across all time windows it contains to obtain the cumulative calendar idle cost. The monetized idle cost is determined based on the cumulative idle cost of the calendar and the preset average unit labor hour rate; The progress simulation schemes in which the cost of monetizing idle resources is less than or equal to the cost tolerance threshold are identified as compliant candidate schemes. From all the compliant candidate solutions, the schedule simulation solution with the shortest total project completion time is extracted and used as the target scheduling calendar.

7. The intelligent management method for civil construction progress according to claim 1, characterized in that, The step of generating access control instructions based on the target scheduling calendar and sending them to the access control system, so that the access control system can perform operations such as denying or allowing entry requests outside the permitted time period according to the job type dependency, includes: The target scheduling calendar is parsed to obtain the job access time period and job code assigned to each job grid, and an association mapping table is established for the job code assigned to the grid, the job access time period and the corresponding job dependency. The associated mapping table is sent as the access control command to the face recognition access controller of the access control system; When the facial recognition access control controller receives a request for entry, it identifies the job category of the person and obtains the current time. When the current time is not within the job access period corresponding to the job category, retrieve the job dependency corresponding to the job category. When the job dependency is greater than the preset parallel operation allowable threshold, the release operation is executed; when the job dependency is less than or equal to the parallel operation allowable threshold, the release operation is executed.

8. The intelligent management method for civil construction progress according to claim 1, characterized in that, The inter-grid rotation time and the single takeoff and landing reference time parameters are determined in the following way: The tower crane's slewing center coordinates and the center coordinates of each work grid are extracted from the building information model of the construction area. Based on the tower crane's rated slewing speed and rated lifting speed, the single lifting and lowering reference time parameters and the inter-grid slewing time between any two work grids are determined.

9. The intelligent management method for civil construction progress according to claim 1, characterized in that, The job type dependence and the number of hoisting operations per worker per unit time are determined in the following ways: Access the pre-set quota database to query the total man-hours and machine-hours of labor required for each type of work to complete a standard unit of work. Based on the consumption of the supporting machinery shifts and the total man-hours of manual labor, determine the number of times a single worker can lift objects per unit time for each type of work. The ratio of the machine hours consumed by each type of work to the total man-hours consumed by the workers is normalized to obtain the work dependency of each type of work.

10. An intelligent management system for civil engineering construction progress, characterized in that, The system includes: The spatial fluctuation quantification unit is used to construct a spatial topology weighted graph based on the inter-grid rotation time in the static parameters of the construction area, and to determine the operation fluctuation parameters based on the eigenvalues ​​of the Laplace matrix of the spatial topology weighted graph. The operation fluctuation parameters are used to characterize the degree of fluctuation caused by spatial discretization to the tower crane service time. The static parameters also include the single lifting and lowering reference time parameter and the work type dependence. The load calculation unit is used to determine the total number of people obstructed and the weighted average service time based on the single take-off and landing baseline time parameter and the dynamic parameters of the construction area; the dynamic parameters are used to characterize the spatiotemporal distribution of the personnel. The cost estimation unit is used to determine the cost of idle labor based on the total number of people blocked, the weighted average service time, and the operational fluctuation parameters. The scheduling optimization unit is used to determine the target scheduling calendar from multiple progress simulation schemes based on the labor idle cost; The access control unit is used to generate access control instructions based on the target scheduling calendar and send them to the access control system. The access control instructions include the job type access time period and the corresponding job type dependency, so that the access control system can perform the operation of denying or allowing entry requests outside the access time period according to the job type dependency.

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