Intelligent building system and method based on BIM

Abstract

The invention relates to the technical field of intelligent manufacturing, in particular to an intelligent building system and method based on BIM, and the system comprises a key node sorting module, a continuity index calculation module, a node coupling judgment module, a resource period regulation and control module and a node path rearrangement module. According to the method, through aggregation processing of the total number of construction node stages, the number of follow-up dependency levels and risk exposure values, node key levels are ranked through an analytic hierarchy process model, a construction task priority basis is constructed, a continuity index is formed in combination with task interval duration, a task switching time ratio and an equipment idle period, and state calibration is carried out; a node coupling imbalance relationship is judged through a continuity index difference value and a threshold value, a resource utilization rate is calculated based on a resource calling number, a path load and a neutral position number to judge a compression and release state, a conflict is identified based on a task parallelism degree and an equipment occupation conflict rate, and a task sequence structure is recombined by utilizing a genetic algorithm. And the adaptive capacity of the path to resource configuration is enhanced.

Description

Technical Field

[0001] The present invention relates to the field of intelligent manufacturing technology, and in particular to a BIM-based intelligent construction system and method. Background Art

[0002] The field of intelligent manufacturing technology involves deeply integrating and optimizing the design, production, management, and services of the manufacturing process through highly information-based, networked, and digital means, based on cyber-physical fusion systems. Core elements of this technology area include intelligent control of production equipment, autonomous decision-making in manufacturing processes, coordinated allocation of manufacturing resources, and data-driven full lifecycle management. Its technical system integrates multiple disciplines, including manufacturing engineering, information and communications, computer science, and control theory, with a focus on enhancing the flexibility, agility, and predictability of manufacturing systems. Intelligent manufacturing is widely used in high-end equipment manufacturing, smart factory construction, industrial internet platform development, and information integration architectures for full-process management. It is a key direction for the digital transformation of modern manufacturing.

[0003] Among them, the BIM-based intelligent construction system refers to a digital construction management solution that uses building information modeling technology as the underlying data support method, integrating IoT data collection, three-dimensional visualization, collaborative construction progress control, and resource scheduling optimization. The patent subject mainly covers matters such as engineering project information modeling, real-time construction status perception, comparative analysis of construction progress and plan, and resource utilization efficiency evaluation. By constructing a digital correlation model of building components and construction processes, combined with AIOT terminals for status collection, and using data-driven methods to achieve analysis and early warning of on-site progress, detailed decomposition and dispatch of construction tasks, and dynamic scheduling of construction resources such as equipment and personnel. The system completes construction status judgment and resource matching logic based on multi-source data fusion methods and construction node status identification methods, and does not involve traditional control system architecture and signal processing methods.

[0004] Existing technologies for state identification of the construction process usually rely on single sensor data or stage records, and lack a mechanism for building continuous indicators, resulting in insufficient resolution for node state identification; the relationship between nodes is mostly based on planned paths, and fails to combine real-time indicators to identify their coupling risks, which easily leads to omission of key conflict nodes; the resource allocation link mostly adopts total control or periodic adjustment methods, and is unable to responsively compress and release according to changes in node status, which easily leads to local congestion or idleness; construction path adjustment is usually based on manual experience to build a static logical structure, lacks an adaptive evolution mechanism, and has difficulty in handling the dynamic coupling requirements between paths and resources, resulting in an increased risk of imbalance in task collaboration. Summary of the Invention

[0005] The purpose of the present invention is to solve the shortcomings of the prior art and to propose a BIM-based intelligent construction system and method.

[0006] In order to achieve the above objectives, the present invention adopts the following technical solutions: A BIM-based intelligent construction system includes:

[0007] The key node ranking module is used to obtain the total number of construction node stages, the number of subsequent dependency levels and the risk exposure value, and call the hierarchical analysis model to calculate and sort them, generate a node criticality level sequence, and pass it to the continuity index calculation module;

[0008] The continuity index calculation module is used to obtain the node task interval duration, task switching time ratio and device idle period, calculate the weighted combination to form the node execution continuity index, and calibrate the node operation status according to the node criticality level sequence, and form a node status evaluation data group to pass to the node coupling judgment module;

[0009] A node coupling identification module is used to obtain the node status evaluation data group, calculate the continuity index difference value and compare it with the threshold value, call the node criticality level sequence to confirm the priority, and generate a coupling imbalance node set to pass to the resource time period control module;

[0010] The resource period control module is used to monitor the number of node resource occupation units, parallel path load rate and resource idle period number according to the obtained coupling imbalance node set and the node criticality level sequence, calculate resource utilization, judge the resource compression or release status, and form a construction node period optimization list to pass it to the node path rearrangement module.

[0011] As a further solution of the present invention, the node criticality level sequence includes the total number of construction node stages, node hierarchy depth and node risk coefficient, the node status assessment data group includes node response interval, task switching time ratio and equipment idle cycle, the coupling imbalance node set is specifically the node coupling difference and node adjustment priority, and the construction node period optimization list includes node resource call amount, parallel path load rate and resource idle ratio.

[0012] As a further solution of the present invention, the key node sorting module includes:

[0013] The node stage statistics submodule obtains construction node data, counts the connection relationships between nodes in the node structure tree, records the number of child nodes directly associated with the current node, traverses all nodes layer by layer and accumulates the number, and then establishes the node stage cumulative amount;

[0014] The risk depth determination submodule calls the node stage cumulative amount, traverses the node tree structure according to the node level-by-level transmission relationship, counts the number of all nodes passed by the path from the current node to the terminal node, sorts and selects the path length, and establishes the node level depth value;

[0015] The node level sorting submodule calls the node stage cumulative amount and the node level depth value, determines the risk coefficient based on the node construction plan interruption probability parameter, uses a hierarchical weighting method to perform multi-parameter weight calculation, and generates a node criticality level sequence.

[0016] As a further solution of the present invention, the continuity index calculation module includes:

[0017] The response interval determination submodule obtains the operation data of the construction nodes, performs difference calculation on the response time of each node according to the start and end time of the node operation response, and generates the node response interval;

[0018] The continuity weight combination submodule calls the node response interval, task switching time ratio and device idle period, performs a combination operation on the three data based on a preset weight coefficient, and generates a node execution continuity index;

[0019] The node status calibration submodule divides the node execution continuity index into level intervals according to the node risk coefficient in the node criticality level sequence, generates the node operation status, and establishes a node status evaluation data group.

[0020] As a further solution of the present invention, the node coupling determination module includes:

[0021] The continuity difference calculation submodule obtains the node status evaluation data group, arranges the nodes according to the node operation connection order based on the node execution continuity index value, subtracts the continuity index values of the nodes one by one, obtains the difference values between adjacent nodes, and generates the node continuity difference value;

[0022] A coupling threshold determination submodule, which calls the node continuity difference value, sets a reference value for the continuity index difference value threshold, compares the numerical difference between the continuity difference value of each node and the reference value one by one, determines whether the node exceeds the interval range of the reference value, and generates a node coupling imbalance determination result;

[0023] The imbalance node sorting submodule calls the node coupling imbalance determination result, performs sorting processing according to the node priority sorting rule provided by the node criticality level sequence, and establishes a coupling imbalance node set.

[0024] As a further solution of the present invention, the resource period control module includes:

[0025] The resource call monitoring submodule obtains the set of coupling imbalance nodes, monitors the number of resource occupied units, parallel path load rate value and number of idle cycles of construction resources of each node according to the node criticality level sequence, and generates node resource call parameters;

[0026] The resource redundancy calculation submodule calls the node resource call parameters, compares the number of node resource calls with the parallel path load rate value, calculates the difference between the actual usage of resource units in each node and the theoretical demand based on the number of resource idle cycles as a reference, and generates a resource utilization value;

[0027] The time period status determination submodule calls the resource utilization value, determines the interval range of the resource utilization value based on the preset resource compression threshold and resource release benchmark value, confirms the resource compression status or release status corresponding to each node, and establishes a construction node time period optimization list.

[0028] As a further embodiment of the present invention, the system further comprises:

[0029] A node path rearrangement module is used to obtain the optimized list of construction node periods, calculate the task parallelism and equipment occupancy conflict rate, identify conflicting nodes through thresholds, call a genetic algorithm to restructure the task sequence, and generate a node progress coupling optimization path;

[0030] The node progress coupling optimization path specifically includes task parallelism and device occupancy conflict rate.

[0031] As a further solution of the present invention, the node path rearrangement module further includes:

[0032] The operation intersection calculation submodule obtains the optimized list of construction node periods, compares the node construction period data one by one, identifies the overlapping range of the construction period start and end times of each two nodes, calculates the length of the operation overlap period of all nodes, and divides it by the total length of the overall construction plan period to generate the operation intersection value;

[0033] The conflict node identification submodule calls the operation intersection value and calculates the overlap duration between the equipment occupancy periods of each node one by one based on the equipment scheduling plan data. Based on the equipment scheduling conflict threshold value, it determines the nodes whose equipment scheduling overlap duration exceeds the threshold range and generates a conflict node set.

[0034] The sequence structure reorganization submodule calls the conflict node set, and based on the original sorting sequence of the node construction tasks and with reference to the node priority data, redetermines the new position of each conflict node in the construction task sequence and establishes a node progress coupling optimization path.

[0035] A BIM-based intelligent construction method is implemented based on the BIM-based intelligent construction system, comprising the following steps:

[0036] S1: Construct a set of construction phase nodes, extract the original construction task path structure, parse the node hierarchy and divide it by phase, obtain the total number of node phases, the number of subsequent dependency levels and the risk exposure value, input the AHP model to calculate the critical weight, and generate a node criticality level sequence for key node identification and task continuity analysis;

[0037] S2: Calculate the node response continuity index based on the node criticality level sequence call phase response data, including task interval duration, task switching time ratio and device idle period, and input the node level label into the Bayesian decision model to infer and output the node execution continuity index to form a status assessment data set;

[0038] S3: constructing a continuity index difference value matrix of adjacent nodes based on the evaluation data set, comparing it with a set continuity balance threshold, determining the priority according to the node level sequence, and screening out a set of coupling imbalance nodes with a difference exceeding the threshold and a higher priority;

[0039] S4: Analyze the resource load status of the coupling imbalance node, obtain the corresponding resource call number, path concurrent load and resource idle period number, calculate resource compression and release potential, update the resource usage period based on the resource status and node priority, and output the construction node period optimization list;

[0040] S5: Apply the optimization list to the updated task path structure, identify scheduling conflicts and perform path rearrangement, identify conflicting nodes by calculating the path intersection degree and the device occupancy conflict rate, use a genetic algorithm to sequence them and related paths, and output the optimized node schedule coupling path.

[0041] Compared with the prior art, the advantages and positive effects of the present invention are:

[0042] In the present invention, the total number of construction node stages, the number of subsequent dependency levels and the risk exposure value are aggregated, and the hierarchical analysis method model is used to sort the node criticality levels, build a basis for construction task priority, and reduce the arbitrariness of node selection; the node continuity index is formed by combining real-time parameters such as task interval duration, task switching time ratio and equipment idle period, and the state is calibrated accordingly to improve the dynamic matching ability of state judgment; further judgment is made by the difference value of the continuity index and the set threshold, the coupling imbalance relationship between nodes is clarified, and the recognition of state assessment is enhanced; the resource utilization rate is calculated based on the number of resource calls, path load and idle number, and the judgment of resource compression and release status is supported, thereby improving the timeliness of resource matching; based on the conflict identification of task parallelism and equipment occupancy conflict rate, the task sequence is restructured using a genetic algorithm to enhance the adaptability of the construction path to the resource allocation results. BRIEF DESCRIPTION OF THE DRAWINGS

[0043] Figure 1 is a system flow chart of the present invention;

[0044] Figure 2 is a system block diagram of the present invention;

[0045] Figure 3 Schematic diagram of the steps of the method of the present invention. DETAILED DESCRIPTION

[0046] In order to make the purpose, technical solutions and advantages of the present invention more clearly understood, the present invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the present invention.

[0047] In the description of the present invention, it should be understood that the terms "length," "width," "up," "down," "front," "back," "left," "right," "vertical," "horizontal," "top," "bottom," "inside," "outside," and the like, indicating positions or relationships, are based on the positions or relationships shown in the accompanying drawings and are intended only to facilitate the description of the present invention and simplify the description. They do not indicate or imply that the devices or elements referred to must have a specific orientation, be constructed, or operate in a specific orientation. Therefore, they should not be construed as limiting the present invention. Furthermore, in the description of the present invention, "plurality" means two or more, unless otherwise expressly and specifically defined.

[0048] Example 1

[0049] See also Figure 1 The present invention provides a technical solution: a BIM-based intelligent construction system comprising:

[0050] The key node ranking module is used to obtain the total number of construction node stages, the number of subsequent dependency levels and the risk exposure value, and call the hierarchical analysis model to calculate and sort them, generate a node criticality level sequence, and pass it to the continuity index calculation module;

[0051] Risk exposure value: Using the PMBOK definition, quantify the risk by [probability of occurrence × impact].

[0052] The continuity index calculation module is used to obtain the node task interval duration, task switching time ratio and device idle period, calculate the weighted combination to form the node execution continuity index, and calibrate the node operation status according to the node criticality level sequence, forming a node status evaluation data group and transmitting it to the node coupling judgment module;

[0053] Task switching time ratio: According to the ISO 22400 standard, the calculation formula is (switching time / total working hours) x 100% 3;

[0054] Equipment idle period: Based on the monitoring period division standard of GB / T 25636, the monitoring period is divided according to the 8-hour working system;

[0055] The node coupling identification module is used to obtain the node status evaluation data group, calculate the continuity index difference value and compare it with the threshold, call the node criticality level sequence to confirm the priority, and generate a set of coupling imbalance nodes to pass to the resource time period control module;

[0056] The resource time period control module is used to obtain the coupling imbalance node set and node criticality level sequence, monitor the number of node resource occupation units, parallel path load rate and resource idle period number, calculate resource utilization, determine the resource compression or release status, and form a construction node time period optimization list to pass to the node path rearrangement module;

[0057] Resource utilization: Refer to the EIA-748 standard and the calculation formula is (actual usage / total available) × 100%;

[0058] The node path rearrangement module is used to obtain the optimized list of construction node time periods, calculate the task parallelism and equipment occupancy conflict rate, identify conflicting nodes through thresholds, call the genetic algorithm to restructure the task sequence, and generate a node progress coupling optimization path.

[0059] Task parallelism: the ratio of the number of parallel paths to the total number of paths based on the CPM network graph;

[0060] Equipment occupancy conflict rate: Based on the construction machinery shift records, calculate the percentage of overlapping equipment applications for multiple tasks during the same period;

[0061] The node criticality level sequence includes the total number of construction node stages, node hierarchy depth and node risk coefficient; the node status assessment data group includes node response interval, task switching time ratio and equipment idle cycle; the coupling imbalance node set is specifically the node coupling difference and node adjustment priority; the construction node period optimization list includes the node resource call volume, parallel path load rate and resource idle ratio; the node progress coupling optimization path is specifically the task parallelism and equipment occupancy conflict rate.

[0062] See also Figure 2 , the key node sorting module includes:

[0063] The node stage statistics submodule obtains construction node data, counts the connection relationships between nodes in the node structure tree, records the number of child nodes directly associated with the current node, traverses all nodes layer by layer and accumulates the number, and then establishes the node stage cumulative amount;

[0064] The node stage statistics submodule obtains construction node data from the construction site or construction plan management system, imports the node data into the node structure tree, and starts from the root node, identifies its directly connected child nodes, marks them as first-level nodes, and counts the number of first-level nodes. For example, the first-level child nodes directly connected to node A are node B, node C, and node D, totaling 3 child nodes. Similarly, the first-level nodes are used as new parent nodes, and the direct associated child nodes of each first-level node are traversed again to identify the number of second-level nodes. For example, the second-level nodes associated with node B are node E and node F, totaling 2 nodes, and the second-level node associated with node C is node G, totaling 1 node. Node D is not connected to a second-level node, that is, the number is 0; the same traversal is performed layer by layer to record the next-level nodes directly associated with each node. The number of points is counted, and this step is repeated layer by layer to complete the traversal of the entire tree. Based on the number of nodes at each level, a cumulative operation is performed level by level. First, the cumulative number of terminal nodes (nodes without subsequent nodes) is counted. For example, the terminal nodes are nodes E, F, and G, totaling 3 terminal nodes. Then, the total number of nodes between non-terminal nodes and terminal nodes is counted level by level. For example, the path from node B to the terminal node involves 3 nodes, namely nodes B, E, and F. The path from node C to the terminal node involves 2 nodes, namely nodes C and G. Node D itself has no subsequent nodes and only has 1 node itself. Finally, the number of path nodes for the root node A is counted, totaling 4, namely nodes A, B, E, and F. After the number of path nodes of all nodes is counted and the number of levels is accumulated layer by layer, the data sequence of the node stage accumulation is obtained.

[0065] The risk depth determination submodule calls the node stage accumulation, traverses the node tree structure according to the node level-by-level transmission relationship, counts the number of all nodes passed by the path from the current node to the terminal node, sorts and selects the path length, and establishes the node level depth value;

[0066] The risk depth determination submodule, based on the cumulative amount of the calling node stage, first determines the path from each node to the terminal node in the tree structure, and records the number of nodes passed by the path. The specific method is: first call the set of direct subsequent nodes of each node from the cumulative amount data of the node stage, and traverse downward layer by layer starting from the root node according to the connection relationship of the nodes, call the subsequent nodes node by node along the path and accumulate the current path length. Taking the root node A as an example, the path from node A to the terminal node E contains nodes ABE, a total of 3 nodes, and the path from node A to the terminal node G contains nodes ACG, a total of 3 nodes. In this way, all paths are traversed, and the number of nodes involved in each path is recorded as the path length value; then, for each node, its corresponding path The length values are recorded and sorted in sequence. The specific sorting process is as follows: a numerical comparison operation is performed on the multiple path length values corresponding to each node, and the values are sorted in descending order. Taking node A as an example, the path lengths starting from node A are 3 (ABE), 3 (ABF), 3 (ACG), and 2 (AD), and the path length value sequence obtained after sorting is 3, 3, 3, and 2; in the sorted value sequence, a selection operation is performed, that is, the maximum path length is selected as the node level depth value. For example, if the maximum path length value of node A is 3, 3 is determined as the level depth value of node A. The same method is used to process nodes B, C, and D. After completing the processing of all nodes, the data sequence of the node level depth value is established.

[0067] The node level sorting submodule calls the node stage cumulative quantity and the node level depth value, determines the risk coefficient based on the node construction plan interruption probability parameter, uses the hierarchical weighting method to perform multi-parameter weight calculation, and generates the node criticality level sequence.

[0068] The node ranking submodule calls the node stage cumulative amount and the node level depth value to first determine the node construction plan interruption probability parameter. This parameter is specifically determined by historical construction data statistics, for example, based on the statistics of the number of construction node plan interruptions in the past year, as shown in Table 1:

[0069] Table 1. Construction node plan interruption probability table

[0070]

[0071] As shown in Table 1, the acquisition of the interruption probability parameter is based on the actual construction data of the construction node, and is obtained by dividing the number of interruptions by the planned execution number. Then, based on the three parameters of the node stage cumulative amount, the node level depth value and the interruption probability, a multi-parameter weight calculation is performed through a hierarchical weighting method. The specific execution process is as follows: first, weights are assigned to the three parameters of the node stage cumulative amount, the node level depth value and the interruption probability. The weight setting is based on the construction risk assessment requirements. For example, the node stage cumulative amount weight is set to 0.3, the node level depth value weight is set to 0.4, and the interruption probability weight is set to 0.3. Then a specific numerical calculation process is performed. For example, taking node B as an example, the node stage cumulative amount is 3, the node level depth value is 2, and the interruption probability is 0.22. The risk coefficient calculation formula for node B is:

[0072] Risk Factor

[0073] = node stage cumulative amount × weight + node level depth value × weight;

[0074] + probability of interruption × weight

[0075] Bring in the above data:

[0076] =3×0.3+2×0.4+0.22×0.3;

[0077] The calculation result is: =0.9+0.8+0.066=1.766;

[0078] The risk coefficients of all nodes are calculated separately according to this method. After the risk coefficient calculation of each node is completed, the risk coefficient values are sorted, and the node risk coefficients are sorted from large to small by comparing the values. The sorting result is the node criticality level sequence. For example, the node criticality level sequence after sorting is node B, node A, node C, and node D.

[0079] See also Figure 2 , the continuity index calculation module includes:

[0080] Response interval determination submodule: obtains construction node operation data, performs difference calculation on the response time of each node according to the start and end time of the node operation response, and generates the node response interval;

[0081] The operation data of the construction nodes are acquired on-site, and the response start time and response end time of the node operation are accurately recorded by the time monitoring equipment. For example, the operation start time of node A at the construction site is 08:00 and the end time is 08:45, the operation start time of node B is 09:00 and the end time is 09:30, and the operation start time of node C is 10:00 and the end time is 10:40. After obtaining the time, the response end time of each node is subtracted from the response start time of the next node. Taking nodes A and B as an example, the node response interval is 15 minutes after the node A end time 08:45 is subtracted from the node B start time 09:00. The node response interval is 30 minutes after the node B end time 09:30 is subtracted from the node C start time 10:00. The node response interval is repeated for each node, and the node response interval value is recorded to generate the node response interval. The node response interval is recorded as {15, 30, ...}.

[0082] Continuity weight combination submodule: This module combines the node response interval, task switching time ratio, and device idle period, and calculates the node execution continuity index based on a preset weight coefficient.

[0083] The node response interval, task switching time ratio, and equipment idle period are obtained through on-site monitoring records, construction log statistics, and equipment operation ledger records, respectively. The value of the task switching time ratio is calculated by dividing the number of successful task switches per unit time by the total number of task switches. For example, if the on-site record shows 10 successful task switches within 1 hour and the total number is 12, the task switching response rate is calculated as 10 / 12=0.83. The equipment idle period is obtained by counting the idle time between the end of the equipment operation and the start of the next operation. For example, the excavator is idle for 25 minutes after the end of the task, the lifting equipment is idle for 15 minutes, and the pumping equipment is idle for 20 minutes. The equipment idle period array is recorded as {25, 15, 20, ...}. The weight coefficients assigned to the above three data items are as follows: The node response interval weight is 0.3, the task switching response rate weight is 0.5, and the equipment idle period weight is 0.2. The weight coefficients are set based on the importance of construction continuity. For example, if the task switching response rate is more important, the highest weight is set. When performing the combination operation, the corresponding values of the three data items are called one by one, multiplied by their respective weight coefficients, and then summed. For example, for node A, the response interval is 15 minutes, the task switching response rate is 0.83, and the equipment idle period is 25 minutes. The node execution continuity index calculation process is: 15×0.3+0.83×0.5+25×0.2=4.5+0.415+5=9.915. The node execution continuity index calculation is completed similarly for all nodes one by one, and the node execution continuity index data array is obtained, which is recorded as {9.915,…}.

[0084] Node status calibration submodule: Based on the node risk coefficient in the node criticality level sequence, the node execution continuity index is divided into level intervals, the node operation status is generated, and a node status evaluation data group is established.

[0085] Call the node risk coefficient in the node criticality level sequence, divide the node execution continuity index level by the node risk coefficient numerical interval, divide the node risk coefficient numerical interval into three levels, and the risk coefficient interval is specifically divided into: low risk (0,1], medium risk (1,2], high risk (2,3], for the node execution continuity index, perform a similar numerical interval division operation, and divide the index value range into three level intervals, the poor continuity interval is (0,5], the general continuity interval is (5,10], and the good continuity interval is (10,15]. The level interval division is determined by the field data statistics to determine the reasonable numerical range. The determination of the node operation status is performed by classifying the node risk coefficient and the continuity index interval respectively. For example, if the risk coefficient of node B is 1.766, which belongs to the medium risk range, and the execution continuity index is 9.915, which belongs to the general continuity range, then the running status of node B is marked as "normal state". The risk coefficient of node A is 0.92, which belongs to the low risk range, and the continuity index is 7.8, which belongs to the general continuity range, then the status of node A is marked as "excellent state". The risk coefficient of node C is 2.3, which belongs to the high risk range, and the continuity index is 4.8, which belongs to the poor continuity range, then the status of node C is marked as "risky state". The above interval judgment actions are executed node by node to generate the node running status, and finally a node status evaluation data group is obtained, which is recorded as {node A: excellent state, node B: normal state, node C: risky state, ...}.

[0086] Table 2 Node execution continuity parameter statistics

[0087]

[0088] As shown in Table 2, the execution continuity-related data of each node is obtained through actual record statistics. The node execution continuity index obtains a clear value after combined operation, and the node operation status is determined based on this value.

[0089] See also Figure 2 , the node coupling discrimination module includes:

[0090] The continuity difference calculation submodule obtains the node status evaluation data group, arranges the nodes according to the node operation connection order based on the node execution continuity index value, subtracts the continuity index values of the nodes one by one, obtains the difference values between adjacent nodes, and generates the node continuity difference value;

[0091] The acquisition of the node status evaluation data group is based on the statistical results of the on-site node operation status data. The node execution continuity index value is the numerical data in the status data group. The nodes are arranged according to the connection sequence of the actual operations of the on-site nodes. For example, the operation sequence of the nodes on the construction site is node A, node B, node C, and node D. The execution continuity index corresponding to each node is recorded as 12.8, 10.2, 7.6, and 9.5 respectively. The difference operation of the continuity index is performed in this sequence. The specific execution process is to call the continuity index corresponding to node A and node B. Count the values and perform numerical subtraction: 12.8 minus 10.2, and the difference value between adjacent nodes is 2.6. Continue to call the continuity index of node B and node C to perform subtraction operation, 10.2 minus 7.6, and obtain the continuity difference value of 2.6. Call the index values of node C and node D, 7.6 minus 9.5, and obtain the continuity difference value of -1.9. Then perform the adjacent node difference operation item by item according to the node operation order. The continuity difference value records between the nodes form the continuity difference value array {2.6, 2.6, -1.9, ...}.

[0092] The coupling threshold determination submodule calls the node continuity difference value, sets a reference value for the continuity index difference value threshold, compares the numerical difference between the continuity difference value of each node and the reference value one by one, determines whether the node exceeds the reference value interval range, and generates a node coupling imbalance determination result;

[0093] The call of the node continuity difference value is based on the continuity difference value array calculated in the previous step. The setting of the reference value for the continuity index difference value threshold is obtained by the historical operation data statistics of the node execution continuity index. Specifically, it is determined by collecting at least 10 node operation continuity index difference value data on site and conducting statistical analysis. For example, the historical data statistics of the continuity index difference value of the on-site node operation are shown in Table 3:

[0094] Table 3 Continuity index difference value historical data statistics

[0095]

[0096]

[0097] As shown in Table 3, the historical data of the continuity index difference value ranges from 1.1 to 3.0. By dividing the interval of the maximum and minimum values of the difference data, the reference value interval of the continuity index difference value is set to (0, 2.5]. Then, the continuity difference value of each node is called one by one to compare the upper and lower bounds of the reference value interval. For example, the continuity difference value 2.6 between node A and node B is compared with the upper limit 2.5 of the reference value interval. It is determined that 2.6 is greater than 2.5, and the coupling imbalance between node A and node B is marked; the continuity difference value 2.6 between node B and node C is also compared and also determined to be greater than 2.5, marking the coupling imbalance between node B and node C; the absolute value of the continuity difference value -1.9 between node C and node D is 1.9. The comparison action is performed with the reference value 2.5, and it is determined that 1.9 is less than 2.5, marking that the coupling between node C and node D is normal. The comparison action of all continuity difference values is completed one by one in the order of nodes to form a node coupling imbalance judgment result array, which is recorded as

[0098] {Node AB: unbalanced, node BC: unbalanced, node CD: normal, ...}.

[0099] The imbalance node sorting submodule calls the node coupling imbalance judgment result, performs sorting processing according to the node priority sorting rules provided by the node criticality level sequence, and establishes a coupling imbalance node set.

[0100] The node coupling imbalance determination result is called based on the node coupling imbalance determination result array. The sorting action is performed one by one for the nodes determined to be "imbalanced". The execution of the sorting action is based on the node risk coefficient value recorded in the node criticality level sequence. The specific sorting operation is as follows: first, the risk coefficient values of all nodes in the coupling imbalance node set are called, and the risk coefficient values of the nodes are compared pairwise. For example, the risk coefficient of node A is 2.3, the risk coefficient of node B is 1.8, and the risk coefficient of node C is 0.9. When the sorting action is performed, the risk coefficients of node A and node B are first compared. If 2.3 is greater than 1.8, node A is sorted before node B. Then, the risk coefficients of node B and node C are compared. If 1.8 is greater than 0.9, node B is sorted before node C. The final sorting result is node A, node B, and node C. After the sorting is completed, the coupling imbalance node set is established, which is recorded as {node A, node B, node C, ...}.

[0101] See also Figure 2 , the resource time period control module includes:

[0102] Resource call monitoring submodule: obtains a set of coupling imbalance nodes, monitors the number of resource occupied units, parallel path load rate values, and idle cycles of construction resources for each node according to the node criticality level sequence, and generates node resource call parameters;

[0103] The set of coupling imbalance nodes is obtained based on the node criticality sequence. Each node in the set is monitored one by one and the number of resource occupied units, the parallel path load rate value and the number of construction resource idle cycles are counted. The specific monitoring process is as follows: when monitoring the resource call of the construction site nodes, based on the node criticality sequence of the nodes, the number of resource occupied units of each node is first recorded. For example, the number of resource units called by node A at the construction site is 8, and the number of resource units called by node B is 6; the monitoring of the parallel path load rate value is obtained by simultaneously monitoring the parallel operation paths on site, for example, the number of nodes There are 3 construction paths at node A and 2 construction paths at node B. The number of idle cycles of construction resources is obtained by counting the number of idle cycles before the resource unit is called to the next node after the completion of the statistical node. For example, after the construction of node A is completed, the idle cycle of its resource unit is 2 cycles, and the idle cycle of the resource unit of node B is 1 cycle. Repeat the above monitoring and statistical actions, complete the data recording and statistics for all nodes in the set one by one, and summarize the recorded values to form a node resource call parameter array, which is recorded as {node A: (8, 3, 2), node B: (6, 2, 1)...}.

[0104] Resource redundancy calculation submodule: This module calls node resource call parameters, compares the number of node resource calls with the parallel path load rate, and uses the number of resource idle cycles as a reference to calculate the gap between the actual usage of resource units in each node and the theoretical demand, generating a resource utilization value.

[0105] The node resource call parameters are obtained by calling the previous step. The resource call quantity and the parallel path load rate value in the parameters are compared by performing a difference operation to obtain the difference between the actual and theoretical resource calls. The specific execution steps are as follows: the resource call quantity of node A is called as 8, and the parallel path load rate value is 3. First, the resource call quantity and the parallel path load rate value are divided by the value to obtain the theoretical resource value per path, that is, 8 divided by 3 equals 2.67. Then, the number of node resource idle cycles is used as a reference to calculate the difference value. The idle cycle of node A resource is 2. The theoretical value 2.67 is multiplied by the number of idle cycles 2 to obtain the theoretical total required resources of 5.3. 4, and then perform the difference calculation action between the actual number of calls and the total number of theoretical required resources, that is, subtract the theoretical demand 5.34 from the actual number of called resources 8, and the difference is 2.66, which is the resource utilization value of node A; taking node B as an example, 6 resources are called, and the parallel path load rate value is 2. The theoretical value of 6 is divided by 2 to obtain 3, the idle cycle is 1, and the theoretical resource demand value is calculated as 3 times 1 cycle, which is 3. Then the actual call is 6 minus the theoretical demand 3 to obtain the difference 3, that is, the resource utilization value of node B is 3; similar operations are performed on all nodes in the set, and the node resource utilization array is obtained after recording and summarizing, which is recorded as

[0106] {Node A: 2.66, Node B: 3...}.

[0107] Time period status determination submodule: Call the resource utilization value, determine the interval range of the resource utilization value based on the preset resource compression threshold and resource release benchmark value, confirm the resource compression status or release status corresponding to each node, and establish a construction node time period optimization list.

[0108] Call the node resource utilization array, based on the resource compression threshold and resource release benchmark value. First, set the resource compression threshold and resource release benchmark value with reference to the construction history data statistics, as shown in Table 4:

[0109] Table 4 Resource utilization threshold setting statistics

[0110] Parameter name Statistical redundancy value range Setting thresholds Resource compression threshold (2.5,5.0] 3.5 Resource release benchmark value [0,2.5] 1.5

[0111] As shown in Table 4, the range of historical statistical resource utilization values determines that the compression threshold is 3.5 and the release benchmark value is 1.5; the resource utilization of node A is called as 2.66, and a comparison action is performed with the compression threshold of 3.5 and the release benchmark value of 1.5. First, it is determined that the value 2.66 is less than the compression threshold of 3.5 and greater than the release benchmark value of 1.5, then the node A state is confirmed to be "resource balanced", and the resource utilization value of node B is called as 3, and a comparison action is performed. It is determined that the value 3 is less than the compression threshold of 3.5 and greater than the release benchmark value of 1.5, and it is marked as "resource balanced"; if there is a node C redundancy value of 4.2, a comparison action is performed to determine that 4.2 is greater than the compression threshold of 3.5, and it is marked as "resource compression"; the redundancy value of node D is 1.2, and a comparison action is performed to determine that 1.2 is less than the release benchmark value of 1.5, and it is marked as "resource release". The comparison action is completed node by node and classified to generate an optimized list of construction node time periods, which is recorded as

[0112] {Node A: resource balancing, Node B: resource balancing, Node C: resource compression, Node D:

[0113] Resource Release...}

[0114] See also Figure 2 , the node path rearrangement module includes:

[0115] The operation intersection calculation submodule obtains the optimized list of construction node periods, compares the node construction period data one by one, identifies the overlapping range of the construction period start and end times of each two nodes, calculates the length of the operation overlap period of all nodes, and divides it by the total length of the overall construction plan period to generate the operation intersection value;

[0116] The construction node time period optimization list records the construction time period data of all construction nodes. The construction time period data of each node is obtained by recording the start and end time of the node operation on site. For example, the construction period of node A is 08:00 to 10:00, the construction period of node B is 09:30 to 11:30, and the construction period of node C is 11:00 to 13:00. The above time period data are called node by node to perform mutual comparison operations. The construction period comparison action of node A and node B is as follows: call the end time of node A construction 10:00 and the start time of node B construction 09:30 to perform time size comparison, determine that the start time of the overlapping period is 09:30, and then call the end time of node A 10:00 and the end time of node B 11:30 to perform numerical comparison, confirm that the end time of the overlapping period is 10:00, and calculate node A. The length of the overlapping period with node B is 30 minutes; in a similar way, call the end time of node B 11:30 and the start time of node C 11:00 to perform a comparison action, confirm that the start time is 11:00, and then call the end time of node B 11:30 and the end time of node C 13:00 to perform a comparison action, confirm that the end time is 11:30, and calculate the length of the overlapping period between node B and node C to be 30 minutes; record the length of the overlapping period of operations between all nodes, sum up all the lengths of the overlapping periods, and obtain the total overlapping time, for example, the total overlapping time is 60 minutes, call the total length of the overall construction plan period, such as the construction plan start time 08:00, end time 13:00, the total length of the overall period is 5 hours (300 minutes), and then divide the total overlapping time 60 minutes by 300 minutes to obtain the operation intersection value of 0.2.

[0117] The conflict node identification submodule uses the job intersection value and, based on the equipment scheduling plan data, calculates the overlap duration between the equipment occupancy periods of each node one by one. Based on the equipment scheduling conflict threshold value, it determines the nodes whose equipment scheduling overlap duration exceeds the threshold range and generates a conflict node set.

[0118] After calling the operation intersection value, the specific time period of equipment occupation is recorded according to the on-site equipment scheduling plan data, and the overlapping time of each node equipment occupation period is calculated one by one. For example, the equipment occupation period of node A at the construction site is 08:00 to 10:00, and the equipment occupation period of node B is 09:30 to 11:30. The equipment scheduling conflict threshold value is set with reference to the actual historical scheduling data statistics of the equipment. For example, the equipment conflict threshold is set to 20 minutes; the start and end time of the node A and node B equipment occupation periods are called to perform a comparison action, and it is determined that the overlapping time period of node A and node B equipment occupation is 09:30 to 10:00. The overlapping time is calculated to be 30 minutes, and 30 minutes is compared with The device scheduling conflict threshold is 20 minutes, and a numerical comparison action is performed to confirm that the overlap time of node A and node B is 30 minutes, which exceeds the threshold of 20 minutes. Node A and node B are determined to be conflicting nodes. Then the node B and node C equipment occupancy periods are called. The node B period is from 09:30 to 11:30, and the node C period is from 11:00 to 13:00. The comparison action determines that the overlap period is from 11:00 to 11:30, with an overlap time of 30 minutes. It is again determined that 30 minutes exceeds the threshold of 20 minutes, and node B and node C are determined to be conflicting nodes. The overlap time comparison and judgment of all node equipment occupancy periods are completed in sequence, and all conflicting nodes are recorded and marked to form a conflicting node set, which is recorded as

[0119] {Node A, Node B, Node C…}.

[0120] The sequence structure reorganization submodule calls the conflict node set, and based on the original sorting sequence of the node construction tasks and with the node priority data as a reference, it redefines the new position of each conflicting node in the construction task sequence and establishes a node progress coupling optimization path.

[0121] After calling the conflict node set, the node position is re-determined according to the original sorting sequence of the node construction tasks, with the node priority data as a reference. The node priority data is determined by the node risk coefficient, as shown in Table 5:

[0122] Table 5 Node risk coefficient priority ranking table

[0123]

[0124] As shown in Table 5, node A has the highest priority and node C has the lowest priority. When adjusting the node position, the positions of nodes A, B, and C in the original construction task sorting sequence are called, and the risk coefficient priority comparison action is performed item by item. The risk coefficient of node A is 2.3, and the risk coefficient of node B is 1.8. The risk coefficient of node A is greater than that of node B. It is determined that the position of node A should be before node B. Subsequently, the risk coefficients of node B and node C are compared numerically. The risk coefficient of node B is 1.8, which is greater than the risk coefficient of node C, which is 1.2. It is determined that node B is before node C. After executing the above numerical comparison actions in sequence, the new sorting positions of the nodes are determined to be nodes A, B, and C, and the node schedule coupling optimization path is established, which is recorded as

[0125] {Node A → Node B → Node C…}.

[0126] See also Figure 3 A BIM-based intelligent construction method is provided. The BIM-based intelligent construction method is performed based on the BIM-based intelligent construction system and includes the following steps:

[0127] S1: Construct a set of construction phase nodes, extract the original construction task path structure, parse the node hierarchy and divide it by phase, obtain the total number of node phases, the number of subsequent dependency levels and the risk exposure value, input the AHP model to calculate the critical weight, and generate a node criticality level sequence for key node identification and task continuity analysis;

[0128] S2: Based on the node criticality level sequence, the phase response data is called and the node response continuity index is calculated, including the task interval duration, task switching time ratio and device idle period. The node level label is then input into the Bayesian decision model to infer and output the node execution continuity index to form a status assessment data set.

[0129] S3: Based on the evaluation data set, a continuity index difference value matrix of adjacent nodes is constructed, and the set continuity balance threshold is compared. The priority is determined according to the node level sequence, and the set of coupling imbalance nodes with a difference value exceeding the threshold and a higher priority is screened out;

[0130] S4: Analyze the resource load status of the coupling imbalance node, obtain the corresponding resource call number, path concurrent load and resource idle period number, calculate the resource compression degree and release potential, update the resource usage period based on the resource status and node priority, and output the optimized construction node period list;

[0131] S5: Apply the optimization list to the updated task path structure, identify scheduling conflicts and re-arrange paths, identify conflicting nodes by calculating the path intersection degree and device occupancy conflict rate, use genetic algorithms to sequence them and related paths, and output the optimized node schedule coupling path.

[0132] The above are merely preferred embodiments of the present invention and do not limit the present invention in any other form. Any technician familiar with the profession may use the technical content disclosed above to change or modify it into an equivalent embodiment with equivalent changes and apply it to other fields. However, any simple modification, equivalent change and modification made to the above embodiment based on the technical essence of the present invention without departing from the content of the technical solution of the present invention shall still fall within the scope of protection of the technical solution of the present invention.

Claims

1. BIM-based intelligent construction system, characterized by: The system comprises: The key node ranking module is used to obtain the total number of construction node stages, the number of subsequent dependency levels and the risk exposure value, and call the hierarchical analysis model to calculate and sort them, generate a node criticality level sequence, and pass it to the continuity index calculation module; The continuity index calculation module is used to obtain the node task interval duration, task switching time ratio and device idle period, calculate the weighted combination to form the node execution continuity index, and calibrate the node operation status according to the node criticality level sequence, and form a node status evaluation data group to pass to the node coupling judgment module; A node coupling identification module is used to obtain the node status evaluation data group, calculate the continuity index difference value and compare it with the threshold value, call the node criticality level sequence to confirm the priority, and generate a coupling imbalance node set to pass to the resource time period control module; The resource period control module is used to monitor the number of node resource occupation units, parallel path load rate and resource idle period number according to the obtained coupling imbalance node set and the node criticality level sequence, calculate resource utilization, judge the resource compression or release status, and form a construction node period optimization list to pass it to the node path rearrangement module.

2. The BIM-based intelligent construction system according to claim 1, characterized in that: The node criticality level sequence includes the total number of construction node stages, node hierarchy depth and node risk coefficient; the node status assessment data group includes node response interval, task switching time ratio and equipment idle cycle; the coupling imbalance node set is specifically the node coupling difference and node adjustment priority; the construction node period optimization list includes node resource call amount, parallel path load rate and resource idle ratio.

3. The BIM-based intelligent construction system according to claim 2, characterized in that: The key node sorting module includes: The node stage statistics submodule obtains construction node data, counts the connection relationships between nodes in the node structure tree, records the number of child nodes directly associated with the current node, traverses all nodes layer by layer and accumulates the number, and then establishes the node stage cumulative amount; The risk depth determination submodule calls the node stage cumulative amount, traverses the node tree structure according to the node level-by-level transmission relationship, counts the number of all nodes passed by the path from the current node to the terminal node, sorts and selects the path length, and establishes the node level depth value; The node level sorting submodule calls the node stage cumulative amount and the node level depth value, determines the risk coefficient based on the node construction plan interruption probability parameter, uses a hierarchical weighting method to perform multi-parameter weight calculation, and generates a node criticality level sequence.

4. The BIM-based intelligent construction system according to claim 3, characterized in that: The continuity index calculation module includes: The response interval determination submodule obtains the operation data of the construction nodes, performs difference calculation on the response time of each node according to the start and end time of the node operation response, and generates the node response interval; The continuity weight combination submodule calls the node response interval, task switching time ratio and device idle period, performs a combination operation on the three data based on a preset weight coefficient, and generates a node execution continuity index; The node status calibration submodule divides the node execution continuity index into level intervals according to the node risk coefficient in the node criticality level sequence, generates the node operation status, and establishes a node status evaluation data group.

5. The BIM-based intelligent construction system according to claim 4, characterized in that: The node coupling determination module includes: The continuity difference calculation submodule obtains the node status evaluation data group, arranges the nodes according to the operation connection order of the nodes based on the node execution continuity index value, subtracts the continuity index values of the nodes one by one, obtains the difference values between adjacent nodes, and generates a node continuity difference value; A coupling threshold determination submodule, which calls the node continuity difference value, sets a reference value for the continuity index difference value threshold, compares the numerical difference between the continuity difference value of each node and the reference value one by one, determines whether the node exceeds the interval range of the reference value, and generates a node coupling imbalance determination result; The imbalance node sorting submodule calls the node coupling imbalance determination result, performs sorting processing according to the node priority sorting rule provided by the node criticality level sequence, and establishes a coupling imbalance node set.

6. The BIM-based intelligent construction system according to claim 5, characterized in that: The resource period control module includes: The resource call monitoring submodule obtains the coupling imbalance node set, monitors the number of resource occupied units, the parallel path load rate value and the number of idle cycles of construction resources of each node according to the node criticality level sequence, and generates node resource call parameters; The resource redundancy calculation submodule calls the node resource call parameters, compares the number of node resource calls with the parallel path load rate value, calculates the difference between the actual usage of resource units in each node and the theoretical demand based on the number of resource idle cycles as a reference, and generates a resource utilization value; The time period status determination submodule calls the resource utilization value, determines the interval range of the resource utilization value based on the preset resource compression threshold and resource release benchmark value, confirms the resource compression status or release status corresponding to each node, and establishes a construction node time period optimization list.

7. The BIM-based intelligent construction system according to claim 6, characterized in that: The system further comprises: A node path rearrangement module is used to obtain the optimized list of construction node periods, calculate task parallelism and equipment occupancy conflict rate, identify conflicting nodes through thresholds, call a genetic algorithm to restructure the task sequence, and generate a node progress coupling optimization path; The node progress coupling optimization path specifically includes task parallelism and device occupancy conflict rate.

8. The BIM-based intelligent construction system according to claim 7, characterized in that: The node path rearrangement module further includes: The operation intersection calculation submodule obtains the optimized list of construction node periods, performs comparison operations on the node construction period data one by one, identifies the overlapping range of the construction period start and end times of each two nodes, calculates the length of the operation overlap period of all nodes, and divides it by the total length of the overall construction plan period to generate the operation intersection value; The conflict node identification submodule calls the operation intersection value and calculates the overlap duration between the equipment occupancy periods of each node one by one based on the equipment scheduling plan data. Based on the equipment scheduling conflict threshold value, it determines the nodes whose equipment scheduling overlap duration exceeds the threshold range and generates a conflict node set. The sequence structure reorganization submodule calls the conflict node set, and based on the original sorting sequence of the node construction tasks and with reference to the node priority data, redetermines the new position of each conflict node in the construction task sequence and establishes a node progress coupling optimization path.

9. The BIM-based intelligent construction method is characterized by: The method is used to implement the BIM-based intelligent construction system according to any one of claims 1 to 8, comprising the following steps: S1: Construct a set of construction phase nodes, extract the original construction task path structure, parse the node hierarchy and divide it by phase, obtain the total number of node phases, the number of subsequent dependency levels and the risk exposure value, input the AHP model to calculate the critical weight, and generate a node criticality level sequence for key node identification and task continuity analysis; S2: Calculate the node response continuity index based on the node criticality level sequence call phase response data, including task interval duration, task switching time ratio and device idle period, and input the node level label into the Bayesian decision model to infer and output the node execution continuity index to form a status assessment data set; S3: constructing a continuity index difference value matrix of adjacent nodes based on the evaluation data set, comparing it with a set continuity balance threshold, determining the priority according to the node level sequence, and screening out a set of coupling imbalance nodes with a difference exceeding the threshold and a higher priority; S4: Analyze the resource load status of the coupling imbalance node, obtain the corresponding resource call number, path concurrent load and resource idle period number, calculate resource compression and release potential, update the resource usage period based on the resource status and node priority, and output the construction node period optimization list; S5: Apply the optimization list to the updated task path structure, identify scheduling conflicts and perform path rearrangement, identify conflicting nodes by calculating the path intersection degree and the device occupancy conflict rate, use a genetic algorithm to sequence them and related paths, and output the optimized node schedule coupling path.

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