A bim-based project cost dynamic measurement system and method

Abstract

This invention discloses a BIM-based dynamic cost estimation system and method for engineering projects, belonging to the field of engineering cost estimation technology. It aims to solve problems in existing technologies such as lag in estimation, low accuracy, poor component compatibility, and inaccurate deviation analysis. The system includes ten modules, such as a BIM model construction module, a multi-source data acquisition module, and a dynamic estimation core module. Each module achieves bidirectional data interaction through a data bus. The method applying this system includes nine steps: model construction, data acquisition, dynamic estimation, deviation analysis, and data updating. This invention constructs a dedicated component library, employs real-time multi-source data acquisition and deduplication / noise reduction processing, and utilizes multi-factor deviation analysis and hierarchical early warning to achieve real-time, accurate, and dynamic estimation throughout the entire lifecycle of engineering projects. This improves estimation efficiency and accuracy, provides a reliable basis for project decision-making, and possesses good practicality and scalability.

Description

Technical Field

[0001] This invention belongs to the field of engineering cost estimation technology, specifically relating to a BIM-based dynamic engineering cost estimation system and method. Background Technology

[0002] With the digital transformation of the construction industry, BIM (Building Information Modeling) technology has been widely applied in the field of engineering cost estimation. However, existing BIM-based engineering cost estimation systems and methods mostly employ fixed component libraries and static pricing formulas, relying on preset templates and manual intervention, which has several drawbacks: First, existing systems often use general component libraries for their BIM models, failing to dynamically generate custom components based on actual project needs. Modifications to component parameters require manual updates to relationships, resulting in low efficiency. Second, data collection methods are limited, relying mostly on manual entry or single-interface collection. Data updates are untimely, and effective deduplication and noise reduction are lacking, leading to data inefficiency. The problems include: 1) Inaccurate calculation methods; 2) Fixed calculation formulas that cannot dynamically adjust parameters based on project geological conditions, construction techniques, and regional differences, resulting in significant discrepancies between calculation results and actual project conditions; 3) Deviation analysis often uses single-factor analysis, failing to accurately pinpoint the causes of deviations and lacking effective early warning mechanisms to mitigate the risk of widening cost deviations; 4) Poor system interface compatibility, hindering smooth data interaction with multiple external systems and causing severe data fragmentation; and 5) Existing methods are mostly phased calculations, unable to achieve real-time dynamic calculations throughout the entire project lifecycle, lagging behind project construction progress and failing to provide timely and accurate cost basis for project decision-making.

[0003] Furthermore, existing engineering cost calculation formulas often employ fixed pricing logic, failing to consider the dynamic fluctuations of data and the coupling effects of multiple factors, resulting in low calculation accuracy. Simultaneously, existing systems suffer from inadequate access control, insufficient data security, and the inability to fully trace operation records, making them prone to data leaks and misoperations. The utilization efficiency of historical data is low, failing to provide effective references for cost calculations in subsequent similar projects. Therefore, there is an urgent need for a BIM-based dynamic engineering cost calculation system and method that can achieve full lifecycle dynamic adaptation, accurate calculation, multi-source data linkage, precise deviation analysis, and timely and effective early warning. Summary of the Invention

[0004] In view of this, the present invention provides a BIM-based dynamic cost estimation system and method for engineering projects, in order to solve or alleviate one of the technical problems existing in the prior art, and at least provide a beneficial option.

[0005] The technical solution of this invention is implemented as follows: A BIM-based dynamic cost estimation system and method, comprising a BIM model construction module, a multi-source data acquisition module, a dynamic estimation core module, a deviation analysis module, a data update module, a visualization output module, a permission management module, an early warning module, a historical data storage module, and an interface adaptation module. Each module is independent and achieves bidirectional data interaction through a data bus, without relying on the preset templates and static association logic of existing BIM cost estimation systems. The specific functions of each module are as follows: The BIM model building module is used to construct a parametric BIM model containing components from all disciplines based on the design drawings, geological survey reports, and construction organization design documents of the target project. Each component is bound to a unique identification code, which includes component type, specifications, installation location, construction procedures, and material information. Component parameters can be modified independently, and modifications are automatically synchronized to related components. A dedicated component library is dynamically generated according to the actual needs of the project. The component library contains the initial values ​​of cost impact factors for components and supports dynamic factor calibration, rather than using the fixed component library in existing technologies.

[0006] Multi-source data acquisition module: It adopts a multi-interface parallel acquisition method, establishing dedicated data channels with building materials market price platforms, construction management systems, design change systems, and tax systems to collect static and dynamic data throughout the entire life cycle of engineering projects; the acquisition frequency can be customized, and after acquisition, it automatically performs data deduplication and noise reduction processing to avoid data redundancy and errors. The deduplication processing adopts a comparison algorithm based on data feature values, and the noise reduction processing adopts a moving average filtering method, which is different from the single acquisition and simple deduplication methods in existing technologies.

[0007] The core module for dynamic cost estimation, as the system's core, receives component parameter data from the BIM model and multi-source acquired data. Combining this with preset dynamic cost estimation formulas, it completes real-time cost estimation of the project. The core formulas include dynamic unit cost calculation formulas for components and dynamic cost estimation formulas for the total project cost. The formulas incorporate dynamic calibration parameters that can be adjusted according to the actual project situation, avoiding the use of fixed pricing formulas in existing technologies. Simultaneously, it automatically calibrates the component consumption coefficient, schedule fluctuation impact coefficient, and construction quality impact coefficient to ensure accurate calculation results.

[0008] Deviation Analysis Module: Compares real-time cost data with initial estimated cost and planned cost data, calculates cost deviation value and deviation rate, constructs a multi-factor weight analysis model, analyzes the causes of deviation, accurately locates the main deviation factors, and associates them with the corresponding components and construction links in the BIM model, which is different from the single-factor deviation analysis method in existing technologies.

[0009] Data update module: Monitors data changes in real time and adopts an incremental update method, updating only the changed data and automatically synchronizing it to the dynamic calculation core module to recalculate the project cost. At the same time, the updated data is synchronized to the historical data storage module to form a data update log, supporting data backtracking and comparative analysis, and solving the problem of low efficiency of full update in existing technologies.

[0010] Visualization output module: Visualizes BIM models, real-time cost data, deviation analysis results, and data update logs in the form of 3D model linkage and chart display. It supports accurate query of component cost information, and supports custom chart settings and export without relying on third-party visualization tools.

[0011] Access control module: Set operation permissions for different roles, adopt hierarchical encryption, implement dual verification of "account password + dynamic verification code", operation records are traceable throughout the process, support data backup and recovery, and ensure data security and operation standards.

[0012] Early warning module: Based on the deviation rate and preset early warning threshold, it triggers early warning prompts of different levels, generates deviation adjustment suggestions, and predicts deviation trends based on historical data to trigger early warnings in advance, thus preventing the deviation from expanding, which is different from the delayed early warning method in existing technologies.

[0013] Historical data storage module: Adopting a distributed storage method, it stores all relevant data throughout the entire lifecycle of the project, supports data retrieval and query, and can be used as a reference for cost estimation of similar projects in the future, thereby improving the efficiency of historical data utilization.

[0014] Interface adaptation module: Adopting a standardized protocol, this module enables the interface between this system and external systems, supports bidirectional data transmission, and can dynamically adapt to the interface type of external systems without modifying the core system code, thus solving the problem of poor interface adaptability in existing technologies.

[0015] As a preferred method, a BIM-based dynamic cost estimation method is applied to the aforementioned system. This method employs dynamic parameter calibration and real-time multi-source data linkage to achieve accurate and real-time cost estimation. The specific steps are as follows: Step 1: Model building. Through the BIM model building module, obtain relevant project files, adopt a layered modeling approach to build a parametric BIM model, assign a unique identification code to each component, generate a dedicated component library, and calibrate the initial values ​​of cost impact factors. Step 2: Data Acquisition. Static and dynamic data are collected through a multi-source data acquisition module, and deduplication and noise reduction are performed to ensure data accuracy and completeness. Step 3: Dynamic Calculation. Through the core module of dynamic calculation, the dynamic calculation formula is called to calculate the dynamic unit cost of components and the total project cost, and the relevant parameters are automatically calibrated. Step 4: Deviation analysis. Through the deviation analysis module, the deviation rate is calculated, a multi-factor weight analysis model is constructed, and the main causes of deviation are identified. Step 5: Data update. Use incremental update method to update the data and recalculate, then synchronize it to the historical data storage module to form an update log; Step 6: Visual output, outputting relevant data in a visual format, supporting querying and export; Step 7: Access Control and Early Warning. Control operation permissions through the access control module and trigger early warnings and generate adjustment suggestions through the early warning module. Step 8: Data storage and interface integration; store relevant data and integrate with external systems. Step 9: The entire process is dynamically looped, repeating steps 2-8 to achieve dynamic measurement throughout the entire lifecycle.

[0016] The embodiments of the present invention have the following advantages due to the adoption of the above technical solutions: 1. This invention constructs a dedicated component library and adopts parametric hierarchical modeling. After the component parameters are modified, the associated components are automatically synchronized without manual updates, which solves the problems of strong universality, poor adaptability and low update efficiency of component libraries in the prior art. The identification code adopts a custom coding rule to ensure that the component identification is unique, which is different from the coding method in the prior art.

[0017] 2. Employing multi-interface parallel acquisition and a dedicated encrypted data channel, it achieves real-time acquisition of multi-source data. Combined with deduplication and noise reduction processing, it ensures accurate, complete, and timely data acquisition, solving the problems of single data acquisition, delayed updates, and large errors in existing technologies. The acquisition frequency can be customized to adapt to the update needs of different types of data.

[0018] 3. Design a unique dynamic calculation formula and introduce dynamic calibration parameters, which can be adjusted according to project geological conditions, construction technology, regional differences, etc., resulting in high calculation accuracy, which is different from the fixed pricing formula in existing technologies; automatically calibrate the correlation coefficient, reduce manual intervention, and improve calculation efficiency.

[0019] 4. Multi-factor weighting analysis is used for deviation analysis to accurately locate the main causes of deviations and link them to BIM model components and construction processes, solving the problems of inaccurate deviation analysis and inability to locate the root cause of problems in existing technologies; the deviation rate calculation is scientific and provides a reliable basis for deviation analysis.

[0020] 5. Adopting an incremental update method, only updating changed data, greatly improves the efficiency of data updates and cost calculations, and solves the problems of lag and low efficiency in full updates in existing technologies; the data update log is complete, supporting data backtracking and accountability.

[0021] 6. Flexible visualization output, supporting 3D model linkage and customized charts, accurate query of component cost information, convenient export format, no need to rely on third-party tools, improving user experience; 7. Hierarchical encryption access control, dual verification to ensure data security, full traceability of operation records, support for data backup and recovery, solving the problems of insufficient data security and lack of traceability of accidental operations in existing technologies; 8. The combination of tiered early warning and trend prediction triggers early warnings and generates adjustment suggestions in advance, avoiding the expansion of deviations and solving the problems of delayed early warning and lack of adjustment guidance in existing technologies; 9. Distributed storage of historical data, supporting data retrieval and query, which can be used for reference in subsequent similar projects, improving the efficiency of historical data utilization; standardized interface adaptation, enabling smooth connection with external systems and solving the problem of data fragmentation; 10. Real-time dynamic calculation of the entire life cycle of engineering projects, with continuous cyclical updates, ensures that cost calculations are consistent with the actual situation of the project, solves the problem of phased calculations in existing technologies that lag behind the construction progress, provides timely and accurate cost basis for project decision-making, and has good practicality and scalability.

[0022] The above overview is for illustrative purposes only and is not intended to be limiting in any way. In addition to the illustrative aspects, embodiments, and features described above, further aspects, embodiments, and features of the invention will become readily apparent from the accompanying drawings and the following detailed description. Attached Figure Description

[0023] To more clearly illustrate the technical solutions 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.

[0024] Figure 1 This is a flowchart illustrating the architecture of the BIM-based dynamic cost estimation system of the present invention. Figure 2 This is a flowchart illustrating the steps of the BIM-based dynamic cost estimation method for engineering projects according to the present invention. Detailed Implementation

[0025] In the following description, only certain exemplary embodiments are briefly described. As those skilled in the art will recognize, the described embodiments can be modified in various ways without departing from the spirit or scope of the invention. Therefore, the drawings and description are considered to be exemplary in nature and not restrictive.

[0026] The embodiments of the present invention will now be described in detail with reference to the accompanying drawings.

[0027] Example 1: A BIM-based dynamic cost estimation system for engineering projects

[0028] This embodiment provides a BIM-based dynamic cost estimation system for engineering projects, including a BIM model building module, a multi-source data acquisition module, a dynamic estimation core module, a deviation analysis module, a data update module, a visualization output module, a permission management module, an early warning module, a historical data storage module, and an interface adaptation module. Each module achieves bidirectional data interaction through a data bus. Specific implementation details are as follows: The BIM model construction module acquires design drawings, geological survey reports, and construction organization design documents for a residential project. Using a layered modeling approach, it constructs parametric BIM models for the foundation, structural, enclosure, decoration, and MEP layers. Each component is assigned an 18-digit identification code: the first 6 digits are the component type code (e.g., 000001 for concrete components, 000002 for steel reinforcement components), the middle 6 digits are the specification parameter code (e.g., 030000 for C30 concrete, 016000 for Φ16 steel reinforcement), and the last 6 digits are the installation location code (e.g., 010100 for the first floor of Building 1). A dedicated component library is generated, containing concrete components, steel reinforcement components, wall components, etc. Each component has three initial sets of cost influence factors. Based on the project's soft soil geological conditions, the geological condition influence coefficient α is set to 0.05. The construction process adopts a new formwork technology, and the construction process influence coefficient β is set to 0.03. The component consumption coefficient is dynamically calibrated.

[0029] Multi-source data acquisition module: Establishes dedicated encrypted data channels with local building materials market price platforms, project construction management systems, design change systems, and tax systems, using AES encryption algorithm for data transmission; Collects static data: Labor quota standard is 80 yuan / man-day, C30 concrete foundation unit price is 420 yuan / m³, tower crane shift foundation cost is 800 yuan / shift, regulatory fee rate is 3.5%, and VAT rate is 9%; Collects dynamic data: C30 concrete real-time price is collected every 2 hours, labor unit price is collected daily, and design change and on-site visa data are collected in real time; After collection, data feature values ​​are extracted for deduplication, and data with similarity ≥95% are considered duplicates and deleted; Noise reduction is achieved using moving average filtering method, with material price data window size set to 5 and labor and machinery price data window size set to 3 to ensure data accuracy.

[0030] Dynamic calculation core module: Receives parameter data of concrete components from the BIM model ( =0.95, =0.3, =0.15), and dynamic data collected from multiple sources ( =430 yuan / m³, =85 yuan / workday =820 yuan / shift); the planned project duration was 180 days, and the actual duration was 185 days. Calculate the impact coefficient of the project duration fluctuation. =(185-180) / 180×0.04≈0.0011; Quality acceptance passed, construction quality influence coefficient. =0; According to the dynamic unit cost formula for components The dynamic unit cost of the concrete component is calculated to be (0.95×430+0.3×85+0.15×820)×(1+0.0011+0)≈(408.5+25.5+123)×1.0011≈557×1.0011≈557.61 yuan / m³; the quantity of the component... =120m³, the calculated cost of this component is 557.61×120≈66913.2 yuan; summing up the costs of all components, plus regulatory fees F=28000 yuan, taxes G=89000 yuan, and dynamic adjustment costs H=15000 yuan, according to the total cost formula The total project cost is calculated to be 66913.2 + ... + 28000 + 89000 + 15000 ≈ 198913.2 yuan (the calculation process for the remaining components is omitted).

[0031] Deviation Analysis Module: The planned project cost is 190,000 yuan, and the real-time calculated cost is 198,913.2 yuan. According to the deviation rate formula:

[0032] The calculated deviation rate δ = |198913.2 - 190000| / 190000 × 100% ≈ 4.69% was obtained. Using multi-factor weight analysis, the weight of material price fluctuation in residential projects was 0.3, the weight of labor unit price change was 0.2, and the weight of other factors was 0.06 each. The calculation showed that material price fluctuation had the highest contribution to the deviation and was the main cause of the deviation. When linked to concrete components, it was determined that the deviation was caused by the increase in the price of C30 concrete.

[0033] Data update module: The real-time price of C30 concrete was monitored to be updated to 435 yuan / m³. The incremental update method was adopted, which only updated the price data of this material and synchronized it to the dynamic calculation core module to recalculate the cost of concrete components and the total project cost. The updated total cost is 199,563.2 yuan. The updated data, update time, operator and other information are recorded in the update log and synchronized to the historical data storage module.

[0034] Visualization output module: Visualizes and outputs data such as BIM model, real-time total cost of 199,563.2 yuan, deviation rate of 4.69%, and reasons for deviation; Clicking on a concrete component will bring up a detailed information window, displaying the component identification code, specifications, cost composition, real-time material prices, and other information; Generates line charts to show the cost change trend over time, and pie charts to show the cost composition ratios, and supports exporting to PDF and Excel formats.

[0035] Access control module: Sets three roles: administrator, surveyor, and viewer; administrators can set system parameters, manage users, and back up data; surveyors can modify BIM models, set data acquisition parameters, and perform surveying operations; viewers can only view relevant data; when logging in, users enter their account and password and receive a dynamic verification code, and can only log in after successful verification; operation records are fully traceable, and data is automatically backed up at 2:00 AM every day.

[0036] Early warning module: Preset early warning thresholds: Level 1 warning 5%, Level 2 warning 10%, Level 3 warning 15%; The current deviation rate is 4.69%, which has not reached the early warning threshold, so no early warning is triggered; Based on the deviation rate data of the past 30 days, it is predicted that the deviation rate will reach 4.8% in the next 7 days, which still has not reached the early warning threshold, so no early warning is required; If the material price continues to rise and the deviation rate reaches 5%, a Level 1 early warning will be triggered, and the user will be notified via system pop-up and SMS, generating adjustment suggestions (such as changing the concrete supplier).

[0037] Historical data storage module: It adopts a distributed storage method to store all the project's calculation data, BIM model data, collected data, deviation analysis results, update logs and early warning records; it supports data retrieval by time and component type, and can be used as a reference for cost calculation of similar residential projects in the future.

[0038] Interface adaptation module: Adopting standardized protocols, it enables interface with BIM modeling software (Revit), construction management system, and financial management system to achieve bidirectional data transmission; it dynamically adapts interface parameters according to the type of external system interface, without modifying the core system code, ensuring smooth data transmission.

[0039] Example 2: A BIM-based dynamic cost estimation method for engineering projects

[0040] This embodiment provides a BIM-based dynamic cost estimation method for engineering projects, applied to the system described in Embodiment 1. The specific steps are as follows: Step 1: Model Building. Using the BIM model building module, obtain the design drawings, geological survey report, and construction organization design documents for a residential project. Employ a layered modeling approach to build parametric BIM models for the foundation layer, structural layer, enclosure layer, decoration layer, and MEP layer. Assign an 18-digit identification code to each component and bind its relevant information. Based on the actual needs of the project, generate a dedicated component library containing concrete components, steel reinforcement components, etc. Set initial values ​​for component cost influencing factors, and calibrate component consumption coefficients by combining soft soil geology and new construction techniques.

[0041] Step 2: Data Acquisition. Through a multi-source data acquisition module, a dedicated encrypted data channel is established with building materials market price platforms, construction management systems, etc., to collect static data (labor quotas, basic unit prices of materials, etc.) and dynamic data (real-time material prices, design changes, etc.). After collection, a comparison algorithm based on data feature values ​​is used to remove duplicates, and a moving average filtering method is used to reduce noise, ensuring that the data is accurate and complete.

[0042] Step 3: Dynamic Calculation. Through the core module of dynamic calculation, the system receives component parameter data from the BIM model and multi-source acquisition data, calls the dynamic unit cost formula for components and the total project cost formula, calculates the dynamic unit cost and total project cost of each component, and automatically calibrates parameters such as the impact coefficient of construction period fluctuation and the impact coefficient of construction quality to ensure accurate calculation.

[0043] Step 4: Deviation Analysis. Through the deviation analysis module, the real-time cost is compared with the planned cost, the deviation rate is calculated, a multi-factor weight analysis model is constructed, the fluctuation of material prices is identified as the main cause of deviation, and the corresponding concrete components are linked to it.

[0044] Step 5: Data update. Upon detecting an update in material prices, the material price data is updated using an incremental update method. The cost is recalculated and synchronized to the historical data storage module to form an update log.

[0045] Step 6: Visual output, outputting BIM model, real-time cost, deviation analysis results, etc. in 3D linked charts, supporting component cost query and data export.

[0046] Step 7: Access Control and Early Warning. The access control module manages the operation permissions of different roles and records operation logs. The early warning module monitors the deviation rate. If the early warning threshold is not reached, no early warning is triggered, and the deviation trend is predicted.

[0047] Step 8: Data storage and interface integration. The historical data storage module stores all relevant project data and supports data retrieval. The interface adaptation module enables integration with external systems, ensuring smooth two-way data transmission.

[0048] Step 9: The entire process is dynamically cyclical, repeating steps 2-8. Labor and machinery price data are updated daily, material price data is updated every 2 hours, and design changes, on-site approvals, and other data are monitored in real time. Calculation parameters and results are continuously updated to achieve dynamic calculation throughout the entire project lifecycle.

[0049] The above description is merely a specific embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any person skilled in the art can easily conceive of various variations or substitutions within the technical scope disclosed in the present invention, and these should all be included within the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be determined by the scope of the claims.

Claims

1. A BIM-based dynamic cost estimation system and method for engineering projects, characterized in that: It includes a BIM model building module, a multi-source data acquisition module, a dynamic calculation core module, a deviation analysis module, a data update module, a visualization output module, a permission management module, an early warning module, a historical data storage module, and an interface adaptation module. Each module is independent of the others and achieves bidirectional data interaction through a data bus. The entire process does not rely on the preset templates and static association logic of the existing BIM cost estimation system. The specific structure and functions are as follows: The BIM model building module is used to construct a parametric BIM model containing components from all disciplines based on the design drawings, geological survey reports, and construction organization design documents of the target engineering project. Each component in the BIM model is bound to a unique identification code, which includes component type, specifications, installation location, construction procedures, and material information. Component parameters can be modified independently, and modifications are automatically synchronized to related components without the need for manual updates to model relationships. The BIM model does not use the fixed component library of existing technologies, but dynamically generates a dedicated component library according to the actual needs of the project. The component library contains the initial values ​​of cost impact factors for components and supports dynamic calibration of factors. The multi-source data acquisition module is used to collect dynamic and static data throughout the entire lifecycle of the project. Static data includes labor quota standards, basic material unit prices, basic machinery rental costs, regulatory fees rates, and tax rates. Dynamic data includes real-time material prices, fluctuations in labor unit prices, changes in machinery rental prices, adjustments to construction procedures, design changes, on-site approvals, project delays, and quality rectification costs. The acquisition module uses a multi-interface parallel acquisition method, establishing dedicated data channels with the building materials market price platform, construction management system, design change system, and tax system. The acquisition frequency can be customized according to the data type: material price data is collected every 2 hours, labor and machinery price data are collected daily, and design changes and on-site approvals are collected in real time. After acquisition, the module automatically performs deduplication and noise reduction to avoid data redundancy and errors. Deduplication uses a comparison algorithm based on data feature values, and noise reduction uses a moving average filtering method. The dynamic cost calculation core module, as the system's core, receives component parameter data output by the BIM model building module and various static and dynamic data output by the multi-source data acquisition module. Combined with preset dynamic cost calculation formulas, it performs real-time calculations of the project cost. These dynamic cost calculation formulas do not use existing fixed pricing formulas but are constructed based on component cost influencing factors and dynamic data fluctuation coefficients. The core formulas include: Formula for calculating the dynamic unit cost of components: in, The dynamic unit cost (yuan / unit volume / area / length) of the i-th component. , , These are the material consumption coefficient, labor consumption coefficient, and machinery consumption coefficient for the i-th component, respectively (dynamically calibrated based on component specifications and construction procedures). This represents the real-time unit price (in yuan) of the material corresponding to the i-th component. This represents the real-time unit price (yuan / man-day) for the labor corresponding to the i-th component. This represents the real-time unit price (yuan / shift) of the machine corresponding to the i-th component. This is the impact coefficient of the construction period fluctuation (calculated based on the deviation between the actual construction period and the planned construction period). The construction quality impact coefficient is dynamically adjusted based on the quality acceptance results, with 0 for qualified, 0.02 for minor rectification, and 0.08 for major rectification. Formula for dynamic calculation of total project cost: in, Let n be the total cost of the project (in yuan), and n be the total number of components in the BIM model. Let F be the quantity of work for the i-th component (unit volume / area / length), G be the regulatory fee (yuan), G be the tax (yuan), and H be the dynamic adjustment cost (yuan, including design change cost, on-site visa cost, construction period delay loss cost, and quality rectification cost). The deviation analysis module compares the real-time cost data output by the dynamic cost calculation core module with the initial calculated cost data and the planned cost data, calculates the cost deviation value and deviation rate, constructs a deviation analysis model, and analyzes the causes of the deviation. The formula for calculating the deviation rate is as follows: in Cost deviation rate To calculate the construction cost (in yuan) in real time. The planned cost (in yuan) is used; the deviation analysis model does not use the single-factor analysis method in the existing technology, but combines multiple factors such as component parameter changes, dynamic data fluctuations, construction procedure adjustments, and design changes. It achieves accurate positioning of the cause of deviation through weight allocation. The weight of each factor is dynamically adjusted according to the project type, and the deviation analysis results can be linked to the corresponding components and construction links in the BIM model. The data update module receives updated data from the multi-source data acquisition module and modified data from the BIM model in real time. It automatically updates the calculation parameters in the dynamic calculation core module, recalculates the project cost, and ensures the real-time nature of the calculation results. At the same time, it synchronizes the updated calculation data and parameter data to the historical data storage module to form a data update log. The log records the update time, update content, update reason, and operator. It supports data backtracking and comparative analysis. The data update adopts an incremental update method, updating only the changed data to avoid system lag caused by full updates. The visualization output module is used to output BIM models, real-time cost data, deviation analysis results, and data update logs in a visual format. It supports linked display of 3D models. Clicking on any component in the BIM model allows real-time viewing of the component's cost composition, calculation parameters, dynamic data, and deviation status. Simultaneously, it supports chart display of cost data, including line charts (showing cost trends over time), pie charts (showing cost composition ratios), and bar charts (showing cost comparisons of various sub-projects). The visualization charts can be customized with different display dimensions and time ranges, and can be exported to PDF and Excel formats without relying on third-party visualization tools. The access control module is used to set operation permissions for different roles, including administrator permissions, calculation personnel permissions, and viewing personnel permissions. Administrators can set system parameters, enable / disable module functions, manage users, and back up and restore data. Calculation personnel can modify BIM models, set data acquisition parameters, perform dynamic calculations, and conduct deviation analysis. Viewers can only view the visualized cost data and analysis results and cannot modify them. The access control settings use a hierarchical encryption method, with each user having a unique login account and encrypted password. Operation records are fully traceable to prevent data leakage and accidental operations. The early warning module is used to trigger different levels of early warning prompts based on the deviation rate output by the deviation analysis module and the preset early warning thresholds. The early warning thresholds are divided into three levels: Level 1 (deviation rate 5%≤δ<10%), Level 2 (10%≤δ<15%), and Level 3 (δ≥15%). Different levels of early warning correspond to different prompting methods, including system pop-ups, SMS notifications, and email notifications. The early warning information includes the deviation rate, the cause of the deviation, related components, and suggested adjustment schemes. At the same time, the early warning module can predict the cost deviation trend based on historical data and trigger early warnings in advance to prevent the deviation from expanding. The historical data storage module is used to store all calculation data, BIM model data, multi-source acquisition data, deviation analysis results, data update logs and early warning records throughout the entire life cycle of the project. It adopts a distributed storage method to ensure the security and stability of data storage. It supports data retrieval and query by time, project stage and component type. Moreover, the stored data can be used as a reference for cost calculation of similar projects in the future without the need to rebuild the calculation model. The interface adaptation module is used to connect this system with external systems, including BIM modeling software, construction management system, financial management system, building material pricing platform, and tax system. The interface adopts a standardized protocol, supports bidirectional data transmission, and can dynamically adapt to the interface type of the external system without modifying the core system code, thus solving the problems of poor interface compatibility and unsmooth data transmission in existing technologies.

2. The BIM-based dynamic engineering cost measurement system and method of claim 1, wherein: The parametric BIM model in the BIM model building module adopts a layered modeling approach, divided into a foundation layer, a structural layer, an enclosure layer, a decoration layer, and an MEP layer. Each layer contains corresponding professional components, and a linkage relationship is established between the components in each layer. When the parameters of a component in a certain layer are modified, the parameters of the components in the related layers are automatically adjusted adaptively without the need for manual modification. The identification code of the component adopts an 18-bit encoding. The first 6 bits are the component type code, the middle 6 bits are the specification parameter code, and the last 6 bits are the installation location code. The encoding rule is system-defined and does not repeat the encoding rule in the prior art, ensuring the uniqueness of the component identification. In the dedicated component library, each component contains more than three sets of initial values ​​for cost influencing factors. These values ​​are dynamically calibrated based on the project's geological conditions, construction techniques, and regional differences. The calibration coefficients are automatically calculated by the system based on historical data, requiring no manual intervention.

3. The BIM-based dynamic engineering cost measurement system and method of claim 1, wherein: The data deduplication process in the multi-source data acquisition module is as follows: extract the feature values ​​of the acquired data, including data type, data source, data timestamp, and core parameters; compare the extracted feature values ​​with the stored data feature values; if the similarity is ≥95%, it is determined to be duplicate data and the duplicate data is automatically deleted. In data denoising, the window size of the moving average filtering method can be customized according to the data type. The window size for material price data is set to 5, the window size for labor and machinery price data is set to 3, and the window size for design change and on-site visa data is set to 1, ensuring that the denoised data retains the true fluctuations while removing abnormal data. The dedicated data channel uses encrypted transmission and employs the AES encryption algorithm during data transmission to prevent data theft and tampering. Each data channel also has an independent verification mechanism that automatically verifies data integrity upon receiving data. If data is missing or tampered with, an abnormality is immediately reported and data is re-acquired.

4. The BIM-based dynamic cost estimation system and method for engineering projects according to claim 1, characterized in that: In the dynamic calculation core module, the material consumption coefficient of the component Labor consumption coefficient Mechanical consumption coefficient The calibration is performed dynamically based on the component specifications, construction procedures, geological conditions, and construction technology. The calibration formula is as follows: in The calibrated consumption coefficient, This is the initial consumption coefficient. The geological condition influence coefficient is 0.05 for soft soil, -0.02 for hard soil, and 0 for ordinary geology. The coefficient represents the influence of construction technology (0.03 for new technologies and 0 for traditional technologies). Construction period fluctuation impact coefficient The calculation method is as follows: If the actual construction period is less than or equal to the planned construction period ; If the actual construction period is greater than the planned construction period: in The actual construction period (days) is as follows. The planned construction period (days); Work quality influence coefficient The system is dynamically adjusted based on the quality acceptance results, and the quality acceptance data is automatically synchronized to the system without the need for manual input. The dynamic adjustment cost H consists of the sum of design change costs, site visa costs, construction period delay loss costs, and quality rectification costs. Among them, design change costs are calculated based on the cost change of the changed components, site visa costs are calculated based on the labor, material, and machinery costs corresponding to the visa content, construction period delay loss costs are calculated based on the number of delay days and the average daily cost, and quality rectification costs are calculated based on the labor, material, and machinery costs required for rectification.

5. The BIM-based dynamic cost estimation system and method for engineering projects according to claim 1, characterized in that: The deviation analysis module uses a multi-factor weighted analysis method for deviation cause analysis. The specific steps are as follows: First, determine the core factors affecting cost deviation, including material price fluctuations, changes in labor unit price, changes in machinery price, modification of component parameters, design changes, adjustment of construction procedures, delays in construction period, and quality rectification, totaling 8 core factors. Then, the weights of each factor are dynamically allocated according to the project type (residential project, public building project, industrial building project). In residential projects, the weight of material price fluctuation is 0.3, the weight of labor unit price change is 0.2, and the weights of the remaining factors are 0.06 each. In public building projects, the weighting for material price fluctuations is 0.25, the weighting for design changes is 0.2, and the weighting for other factors is 0.068 each. In industrial building projects, the weight of changes in machinery prices is 0.25, the weight of changes in component parameters is 0.2, and the weight of other factors is 0.068 each. Finally, based on the fluctuation range and weight of each factor, the contribution of each factor to the cost deviation is calculated. The factor with the highest contribution is the main cause of the deviation. The results of the deviation cause analysis can be linked to the corresponding components and construction links in the BIM model, which makes it easier for users to accurately locate the problem and make adjustments.

6. The BIM-based dynamic cost estimation system and method for engineering projects according to claim 1, characterized in that: The incremental update method in the data update module is implemented as follows: The data update module monitors the data changes of the multi-source data acquisition module and the BIM model construction module in real time, extracts the changed data segments, records the data change type (addition, modification, deletion), and only transmits the changed data segments to the dynamic calculation core module. The dynamic calculation core module only recalculates the cost of the components corresponding to the changed data segments, without having to perform a full cost calculation for the entire project, which greatly improves the efficiency of data update and cost calculation. Each record in the data update log includes the update time, update content, update reason, operator, and data comparison information before and after. The log data retention period is consistent with the project lifecycle. It supports retrieval by time range, operator, and update type, which facilitates data backtracking and accountability. When synchronizing data to the historical data storage module, a dual backup method is used to ensure that no data is lost.

7. The BIM-based dynamic cost estimation system and method for engineering projects according to claim 1, characterized in that: The visualization output module displays 3D models in a linked manner, supporting multi-angle rotation, scaling, and translation. It can display the model and cost information of a specific layer, a specific profession, or a specific component. After clicking on a component, a detailed information window pops up, which includes the component's identification code, specifications, material information, construction procedures, cost composition (material costs, labor costs, and machinery costs), dynamic data (real-time prices of corresponding materials, labor, and machinery), deviation information (deviation rate and reasons for deviation), and calculation formulas and parameters. The display dimensions of the visualization charts can be customized, and the time range can be selected as day, week, month, quarter, or year. The chart colors and styles can be customized and adjusted. The exported PDF and Excel files contain complete cost data, calculation parameters, deviation analysis results, and visualization charts. The Excel files support data editing and secondary calculations without the need for additional format conversion.

8. The BIM-based dynamic cost estimation system and method for engineering projects according to claim 1, characterized in that: The hierarchical encryption method in the permission management module adopts a dual verification method of "account password + dynamic verification code". When a user logs in, after entering the account password, the system sends a dynamic verification code to the user's bound mobile phone or email. Only after the verification is successful can the user log in. Administrators can flexibly assign operation permissions based on users' job positions and responsibilities, and can refine them to specific operation functions (such as BIM model modification permissions, data collection permissions, calculation permissions, deviation analysis permissions, and visualization export permissions). The operation log is fully traceable, and the recorded content includes the operator, operation time, operation content, and operation result. Administrators can view the operation log at any time, and can immediately lock the relevant user account when abnormal operation is detected to prevent data leakage and misoperation. The system data backup adopts a combination of scheduled backup and manual backup. Scheduled backup is performed automatically at 2:00 AM every day, and the backup data is stored in a distributed storage server. Manual backup can be triggered by the administrator at any time, and the backup data can be restored at any time.

9. The BIM-based dynamic cost estimation system and method for engineering projects according to claim 1, characterized in that: The warning thresholds in the warning module can be customized by the user according to the actual needs of the project. The default thresholds are 5% for Level 1 warning, 10% for Level 2 warning, and 15% for Level 3 warning. Users can choose the warning notification method, either by selecting a single notification method or by combining multiple notification methods. The suggested adjustment schemes in the early warning information are automatically generated by the system based on the cause of the deviation, historical data, and calculation models. For deviations caused by fluctuations in material prices, it is recommended to adjust material suppliers or use alternative materials; for deviations caused by changes in labor unit prices, it is recommended to optimize construction procedures or adjust labor allocation. For deviations caused by design changes, it is recommended to review the design plan again or optimize the changes. The early warning trend prediction uses a linear regression algorithm to predict the deviation trend for the next 7 days based on the deviation rate data of the past 30 days. If the predicted deviation rate reaches the early warning threshold, an early warning will be triggered in advance to allow users time to adjust.

10. A BIM-based dynamic cost estimation system and method for engineering projects according to any one of claims 1-9, characterized in that: The specific steps are as follows: Step 1: Model Building. Using the BIM model building module, obtain the design drawings, geological survey reports, and construction organization design documents of the target project. Using a layered modeling approach, construct a parametric BIM model containing components from all disciplines. Assign a unique identification code to each component and bind the component type, specifications, installation location, construction procedures, and material information. Generate a dedicated component library based on the actual needs of the project, set the initial value of the cost impact factor for the components, and dynamically calibrate it according to geological conditions, construction technology, and regional differences. Step 2: Data Acquisition. Using a multi-source data acquisition module and a multi-interface parallel acquisition method, dedicated encrypted data channels are established with the building materials market price platform, construction management system, design change system, and tax system to collect both static and dynamic data for the project. Static data includes labor quota standards, basic material unit prices, basic machinery shift costs, regulatory fees rates, and tax rates. Dynamic data includes real-time material prices, fluctuations in labor unit prices, changes in machinery rental prices, construction procedure adjustment data, design change data, on-site visa data, construction delay data, and quality rectification cost data. After collection, a comparison algorithm based on data feature values ​​is used for deduplication, and a moving average filtering method is used for noise reduction to ensure data accuracy and completeness. Step 3: Dynamic Calculation. The core module for dynamic calculation receives the BIM model component parameter data output from Step 1 and the deduplicated and noise-reduced static and dynamic data output from Step 2. It then calls a preset dynamic calculation formula to first calculate the dynamic unit cost of each component, and finally summarizes and calculates the total cost of the project. The dynamic unit cost of the components is calculated using the following formula: The total cost of the project is calculated using the following formula: During the calculation process, the consumption coefficient of components, the impact coefficient of construction period fluctuation, and the impact coefficient of construction quality are automatically calibrated to ensure the accuracy of the calculation results; Step 4: Deviation Analysis. Using the deviation analysis module, compare the real-time cost data output in Step 3 with the initial estimated cost data and the planned cost data, using the following formula: Calculate the cost deviation rate, construct a multi-factor weight analysis model, identify the core factors affecting cost deviation, calculate the contribution of each factor to the deviation, locate the main causes of deviation, and link them to the components and construction stages corresponding to the BIM model. Step 5: Data Update. The data update module monitors the modified data of the BIM model in Step 1 and the updated data of the multi-source data in Step 2 in real time. It adopts an incremental update method, only updating the changed data and automatically synchronizing it to the dynamic calculation core module to recalculate the project cost. At the same time, the updated calculation data and parameter data are synchronized to the historical data storage module to form a complete data update log, which supports data backtracking and comparative analysis. Step 6: Visualization Output. Through the visualization output module, the BIM model, the real-time cost data output in Step 3, the deviation analysis results output in Step 4, and the data update log output in Step 5 are visualized and output in the form of 3D model linkage and chart display. It supports accurate query of component cost information and supports custom settings and export of visualization charts. Step 7: Access Control and Early Warning. Through the access control module, set operation permissions for different roles, adopt hierarchical encryption to ensure data security and operational compliance, and record the entire operation log. The early warning module triggers different levels of early warning prompts based on the deviation rate calculated in step 4 and the preset early warning threshold, generates deviation adjustment suggestions, and predicts deviation trends based on historical data to trigger early warnings in advance. Step 8: Data storage and interface integration. Through the historical data storage module, a distributed storage method is adopted to store all calculation data, model data, collected data, deviation analysis results, update logs and early warning records throughout the entire life cycle of the project, supporting data retrieval and query. Through the interface adaptation module, the system achieves standardized integration with external BIM modeling software, construction management system, financial management system, etc., realizing bidirectional data transmission and dynamic adaptation. Step 9: The entire process is dynamically cyclical, repeating steps 2-8 to achieve real-time and dynamic calculation of project cost throughout the entire project lifecycle. The calculation parameters and results are continuously updated based on construction progress, data changes, design adjustments, etc., to ensure that the cost calculation is consistent with the actual situation of the project, thus solving the problems of lagging cost calculation, low accuracy, and inability to dynamically adapt to project changes in existing technologies.

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