A BIM-integrated progress-quality-settlement integrated intelligent management and control method for thermal power infrastructure construction

Abstract

A BIM-integrated intelligent management and control method for the progress, quality, and settlement of thermal power infrastructure projects is proposed. This method uses a coding system as a data bridge, moving the BIM model from the "display layer" to the "data calculation layer," and transforming PDCA from the "management process layer" to the "automatic driving layer." Through an event-driven architecture and state machine, it achieves automatic data flow and state transitions between different stages of quality control, eliminating the need for manual management. This invention offers the following advantages: 1. Comprehensive Data Integration: A unified coding system eliminates data silos. 2. BIM-PDCA Technology Integration: A technical correlation mechanism is established between BIM model component data and data from each stage of the PDCA cycle, achieving a closed-loop technology that automatically drives planning, execution inspection, problem handling, and settlement measurement. 3. Improved Management Efficiency: Based on the integration of BIM-PDCA technology, automatic progress tracking, closed-loop quality rectification, and automatic settlement calculation are achieved, significantly reducing manual intervention and shortening the management cycle.

Description

Technical Field

[0001] This invention relates to the field of information management and control technology for thermal power engineering construction, specifically to an integrated intelligent management and control method and platform for thermal power infrastructure progress, quality, and settlement based on the deep integration of BIM model and PDCA cycle at the technical level. Through real-time interaction and automatic correlation calculation of BIM model component data and PDCA stage data, intelligent technical management and control of the entire life cycle of thermal power engineering EPC general contracting projects is realized. Background Technology

[0002] EPC (Engineering, Procurement, and Construction) for thermal power plant construction refers to a model where the owner entrusts the entire process of a thermal power plant construction—including surveying and design, equipment procurement, construction and installation, and commissioning—to a single general contractor. Thermal power infrastructure projects are characterized by numerous interdisciplinary collaborations, long construction periods, multiple participating units, and complex management dimensions. Current technologies only integrate BIM and the PDCA cycle at the management level, failing to achieve deep data interaction and automatic correlation at the technical level, resulting in the following technical problems: 1. Severe data silos: Business systems such as progress, quality, settlement, materials, and design are independent of each other, with inconsistent coding systems and data that cannot be connected, resulting in low efficiency and large errors in progress tracking, quality traceability, and settlement accounting; 2. Superficial BIM application: BIM models are only used for visualization and are not deeply integrated with the data of each stage of the PDCA cycle at the technical level. There is a lack of automatic data interaction mechanism between BIM model component data and the PDCA planning, execution, inspection and processing stages, and it is impossible to realize automatic correlation calculation and technical control based on model data. 3. Inadequate progress control: Multi-level plan decomposition is not standardized, execution feedback is delayed, critical path monitoring is insufficient, and progress deviations are difficult to be warned and corrected in a timely manner; 4. Insufficient integration of BIM and PDCA technologies: In the current technology, the integration of BIM models and PDCA cycles remains at the management process level. There is a lack of technical means to realize real-time interaction, automatic correlation calculation and closed-loop feedback between BIM model component data and data at each stage of PDCA. Quality inspection data and BIM model components cannot be automatically correlated and located through technical means. 5. Low settlement and accounting efficiency: The measurement of project quantities relies on manual statistics, which is out of sync with the quality inspection and evaluation results, resulting in long settlement cycles, large errors, and easy disputes. 6. Lack of technical linkage mechanism for progress-quality-settlement data: In the existing technology, there is no automatic correlation calculation mechanism based on BIM model components between progress completion data, quality evaluation data and settlement quantity data, resulting in the separation of the three major business data and the inability to realize automatic settlement and accounting based on BIM-PDCA technology integration. Summary of the Invention

[0003] The technical problem to be solved by this invention is to provide an integrated intelligent management and control method and platform for the progress, quality and settlement of thermal power infrastructure that integrates BIM and PDCA cycle at the technical level. By constructing a technical association mechanism between BIM model component data and PDCA stage data, automatic association calculation, closed-loop feedback and intelligent decision-making driven by model data are realized, which solves the technical problem in the prior art that BIM and PDCA are only combined at the management level and lack data interaction and automatic association at the technical level.

[0004] To solve the above problems, the present invention is achieved through the following technical solution: A BIM-integrated intelligent management and control method for the progress, quality, and settlement of thermal power infrastructure projects includes the following steps: Step 1: Construct a multi-dimensional business coding system integrating BIM-PDCA technologies and bind it to the BIM model; Step 2: Multi-level schedule management based on the integration of BIM and PDCA technologies; Step 3: Closed-loop quality management based on the integration of BIM and PDCA technologies; Step 3.1: Digital twin model construction and quality attribute pre-configuration; Step 3.2: Real-time acquisition and digital twin synchronization of on-site quality inspection data: Through the secondary development interface of the BIM platform, the quality attribute model is extended based on the IFC model data model. Calculated attribute fields are added to each component, including: component type code, design geometric parameter vector, design material strength grade, associated acceptance specification number, associated QBS code, quality control point identifier, and allowable deviation threshold vector. These attribute fields are stored in the component attribute table of the BIM model database, serving as the benchmark input for subsequent automatic comparison calculations. The system writes the generated inspection unit code, planned inspection time, and associated WBS code into the inspection plan table of the project database. Simultaneously, a "post-inspection unit code" field is added to the WBS work package record in the schedule database, establishing a foreign key constraint relationship at the database level. When the construction progress reaches this WBS work package, the system automatically checks the status of the associated inspection unit. Only when the inspection unit status is "qualified" is the WBS work package status allowed to be updated to "completed." This constraint is implemented through an automatic verification mechanism at the database transaction level. Step 3.3: Multi-dimensional Automatic Comparison and Judgment Algorithm Based on Digital Twin Model: Deploy a quality judgment algorithm engine on the server side. Using the design parameter vector and acceptance standard threshold stored in the BIM digital twin model as input, and the actual measured data vector as the comparison object, automatically perform multi-dimensional comparison calculations. The quality judgment algorithm engine includes three calculation sub-modules: the geometric dimension calculation sub-module calculates deviation values; if the deviation value is within the allowable deviation threshold range, it is judged as "qualified"; otherwise, it is "unqualified." The material strength calculation sub-module performs statistical judgment, calculating the minimum and average values ​​of the measured strength samples and comparing them with the design requirements. The appearance quality calculation sub-module performs image recognition, receiving component surface photos uploaded by mobile terminals, automatically identifying defect types and defect levels through a pre-trained convolutional neural network model, and then comparing them with the allowable standards in the specifications. The quality assessment algorithm engine executes comprehensive assessment logic: if the assessment results of all sub-modules of the inspection items are "passed", the inspection unit status is "passed"; if there are general non-conformities and the geometric dimensional deviation is within 1.5 times the allowable deviation, the status is "repairable"; if there are serious non-conformities or the material strength does not meet the requirements, the status is "rejected". Step 3.4: Automatic state transition based on judgment results and linkage with downstream business; The quality control process is modeled as a finite state machine, defining four states: P, D, C, and A, and state transition conditions. The state transition rules are as follows: the trigger condition for P→D is "WBS work package start signal"; the trigger condition for D→C is "all measured data have been collected and passed the validity verification"; the trigger condition for C→A is "judgment algorithm outputs the state field"; the trigger condition for A→P is "re-inspection judgment status is qualified". This state machine is automatically executed by the system's event-driven architecture. When the algorithm outputs a status of "Repairable" or "Rejected", the system's event bus automatically publishes a "QualityCheckFailed" event. The rectification workflow engine that subscribes to this event automatically executes the following: reads the QBS code associated with the inspection unit, obtains the responsible WBS work package code and the responsible construction unit code through the WBS-QBS mapping table, automatically generates a Non-Conformance Report (NCR), and automatically associates the BIM model component GUID, measured data vector, judgment result, and specification deviation clause number. The NCR is then pushed to the responsible construction unit's mobile terminal and the supervisor's mobile terminal via a message queue. After receiving the NCR, the construction unit views the BIM 3D positioning, measured deviation value, and specification requirements of the non-conforming component on a mobile terminal, formulates a rectification plan and fills it in. During the rectification construction, the construction unit updates the rectification status in real time through the mobile terminal. The system writes the status back to the "rectification status" attribute field of the BIM model component through API. After the rectification is completed, the construction unit uploads the measured data after rectification through the mobile terminal. The system automatically publishes the "RepairCompleted" event, triggering the re-inspection process, that is, re-executes the judgment algorithm in step 3.3. After the re-inspection is deemed qualified, the system automatically performs cascading update operations: through QBS-WBS mapping, it automatically updates the status field of the work package in the WBS database to "Completed" and releases the progress lock; through QBS-BOQ mapping, it automatically includes the component quantities associated with the inspection unit into the settlement measurement scope and updates the "Measurable Quantities" field in the settlement database; through code association, it automatically updates the quality statistics database. The data of the entire rectification process is automatically written into the quality history table of the project database according to the QBS code, forming a component-level quality life cycle data chain, which supports reverse querying of the complete quality history record of any component in the BIM model. Step 4: Link quality verification and assessment with measurement and settlement based on the integration of BIM-PDCA technology.

[0005] In step 3.2, the system reads the quality attributes of all components in the BIM model database, executes an automatic aggregation algorithm to generate inspection units, and the automatic aggregation algorithm is as follows: traverse all components, group them according to the sub-item code of QBS code, calculate the number of components N of the same type in each group, automatically calculate the sampling quantity according to the acceptance specification, generate the inspection unit code, and write the GUID of the sampled components into the component list field of the inspection unit.

[0006] Step 4 specifically includes: Step 4.1: Settlement Trigger: The measurement and settlement process can only be triggered when the quality inspection unit evaluation data associated with the BIM model component passes the judgment. The quality inspection and evaluation results serve as an auxiliary basis for the engineering measurement and settlement. Step 4.2: Verification and Assisted Measurement: The platform uses the component codes of the BIM model to associate quality verification and evaluation data to perform technical verification and assisted review of the quantities of work submitted by the contractor, and no longer uses the automatically extracted quantities of work from the BIM model as the basis for measurement. Step 4.3: Process Approval: After the contractor submits the work quantity, the supervisor reviews it with the quality inspection results as an auxiliary basis for verification, the follow-up audit reviews it with the quality data as an auxiliary basis for verification, and the owner reviews it in conjunction with the quality inspection technical data for confirmation; Step 4.4: Auxiliary Accounting: Summarize the contractor's reported quantity data after auxiliary verification by the list number, and generate measurement sheets, monthly settlement payments and accounts payable data based on the quality verification results; Step 4.5: Data Linkage: The settlement results are automatically synchronized to the contract, investment, and progress modules through the data interaction interface, forming a closed loop of "quality qualified - progress completed - settlement and pricing".

[0007] Compared with the prior art, the present invention has the following beneficial effects: 1. Data connectivity across the entire domain: A unified coding system eliminates data silos and enables seamless flow of data related to progress, quality, settlement, materials, and design.

[0008] 2. Integration of BIM and PDCA technologies: Establish a technical linkage mechanism between BIM model component data and data at each stage of the PDCA cycle, and realize a technical closed loop in which model data automatically drives planning, execution inspection, problem handling and settlement measurement.

[0009] 3. Improved management and control efficiency: Based on the integration of BIM-PDCA technology, automatic progress tracking, closed-loop quality rectification, and automatic settlement calculation are achieved, significantly reducing manual intervention and shortening the management and control cycle.

[0010] 4. Process traceability: Based on the integration of BIM-PDCA technology, all business data is automatically recorded, model components are accurately positioned, and data at each stage of PDCA can be queried, meeting the requirements for technical compliance and quality improvement.

[0011] 5. Intelligent Decision-Making: Based on the integration of BIM-PDCA technology, it realizes panoramic visualization, multi-dimensional data analysis, and automatic early warning and reminder, and supports technical decision-making through model data correlation calculation. Attached Figure Description

[0012] Figure 1 This is a schematic diagram of the process of linking progress, quality, and settlement operations based on the integration of BIM-PDCA technology in this invention; Figure 2 This is a schematic diagram of the data interaction and correlation computing architecture of the present invention. Detailed Implementation

[0013] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0014] In the description of this invention, it should be understood that the terms "upper", "lower", "front", "rear", "left", "right", "top", "bottom", "inner", "outer", etc., indicate the orientation or positional relationship based on the orientation or positional relationship shown in the accompanying drawings. They are only for the convenience of describing this invention and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation. Therefore, they should not be construed as limitations on this invention.

[0015] like Figures 1-2 As shown, this invention achieves BIM-PDCA technology integration by constructing a technical association mechanism between BIM model component data and data from each stage of the PDCA cycle. It provides an integrated intelligent management and control method for the progress, quality, and settlement of thermal power infrastructure projects, integrating BIM and the PDCA cycle. Using the BIM model as the data carrier, it establishes a technical association mechanism between BIM model components and data from each stage of the PDCA cycle. Through BIM model component data, it automatically drives the planning, execution, inspection, problem handling, and result feedback of each stage of the PDCA cycle, achieving automatic data interaction, correlation calculation, and closed-loop management of BIM-PDCA technology integration. Specifically, it includes the following steps: Step 1: Construct a multi-dimensional business coding system integrating BIM-PDCA technologies and bind it to the BIM model; Step 1.1: Construct a standardized four-dimensional coding system covering the entire lifecycle of thermal power EPC, serving as the data foundation for the integration of BIM-PDCA technologies: (1.1) WBS Coding: The WBS is established in five levels: "whole plant → unit project (e.g., main plant building) → sub-unit project (e.g., boiler room) → sub-section project (e.g., boiler foundation) → sub-item project", which directly corresponds to the work breakdown structure of thermal power projects. Each level of coding adopts a ten-digit fixed-length coding structure of "professional code (2 digits) + system code (3 digits) + process code (2 digits) + serial number (3 digits)" to ensure the uniqueness and scalability of the coding in the multi-professional environment of thermal power.

[0016] In view of the characteristics of thermal power EPC projects, which are characterized by strong systemicity and complex cross-disciplinary features, this invention divides the second level into "unit projects" and further divides them into professional systems such as steam turbine, boiler, electrical, thermal control, chemical, and fuel. The third level, "sub-unit projects", is divided into system functional modules (such as steam turbine body system, condensate system, and feedwater system). The fourth level, "sub-projects", corresponds to equipment installation procedures (such as foundation acceptance, equipment placement, alignment and leveling, and secondary grouting). The fifth level, "item projects", is refined to the installation work of a single piece of equipment or a single section of pipeline.

[0017] (1.2) QBS coding: It corresponds one-to-one with the WBS level, and synchronously divides the quality inspection and evaluation units and control points to form quality inspection standards for each construction process of thermal power projects. In thermal power EPC projects, the quality inspection and evaluation units are not simply applied using the WBS structure, but are based on the "Typical Outline for Quality Inspection of Power Construction Projects" and the "Classification Table for Quality Acceptance of Thermal Power Generation Projects". The quality inspection and evaluation units are divided into four levels: "Unit Project → Sub-project → Item Project → Inspection Batch". Among them, the unit project, sub-project, and item project correspond one-to-one with the second, fourth, and fifth levels of the WBS coding. At the same time, the item project is further subdivided into inspection batches (such as "Rotor hoisting inspection batch", "Cylinder assembly inspection batch", "Bearing installation inspection batch", etc. under the "No. 1 steam turbine body installation" item project). The QBS coding adopts the same structure as the WBS coding, with the first seven digits being the same and the last three digits being the quality inspection serial number. That is, the coding structure is: "professional code (2 digits) + system code (3 digits) + process code (2 digits) + quality inspection serial number (3 digits), which realizes automatic association at the coding level."

[0018] (1.3) KKS Coding: Established according to the "GBT 50549-2020 Power Plant Identification System Coding Standard" in the hierarchy of "Building and Area Classification → System Classification → Equipment Classification → Equipment Number". Considering the special characteristics of civil engineering in thermal power EPC projects, this invention specifically extends the application of KKS coding in the civil engineering field, establishing a four-layer coding structure to achieve refined positioning and quality assessment of buildings and structures, namely: plant-wide code (2 digits) + individual building code (5 symbols) + area code (15 symbols) + sub-project and sub-sub-project code (4 digits). The following is a detailed explanation: ① Plant-wide code (H1H2, 2 digits): Based on unit affiliation, 00 represents all plant-wide common systems and buildings (such as the central control building and water treatment building), 01 represents Unit 1 system, 02 represents Unit 2 system, and so on. This coding solves the problem of identifying the affiliation of the same type of building in different unit areas in multi-unit power plants.

[0019] ② Building Unit Code (S1S2S3S4S5, 5-digit symbol): The first three digits, S1S2S3, are letters, determined according to Appendix A of GB / T50546-2020 "Power Plant Identification System Coding Standard" to classify the functional categories of buildings (structures). S1 is represented by U for buildings (structures) and areas within the power plant's production system, and by Z for buildings (structures) and areas outside the power plant's production system. S2 is a group code indicating the main process system served by the building (e.g., UH for buildings and structures used in the heat generation system, UG for buildings and structures used in water supply and drainage). S3 is a subgroup code, specifying the building (structure) type (e.g., UMA for turbine hall, UHF for coal bunker). The last two digits, S4S5, are numbers, representing the number of the building (e.g., 01 for the first building). ③ Area Code (R1-R15, 15-digit symbol): Three-dimensional spatial positioning is achieved through floor codes and axis codes. Floor Code (R1R2R3, 3 digits): R1 is F for floors at ±0.000 meters and above, and B for floors at ±0.000 meters and below; R2 represents the main floor number (1 for the first floor, 2 for the second floor, and 1 for the basement); R3 represents the mezzanine number (R3 is 0 for the main floor, and mezzanines are numbered 1, 2, 3… according to elevation from low to high), with the foundation floor being B00 and the roof floor being FRF. Axis code (R4-R15, 12 digits): A three-digit coding system is used. R4R5R6 are the left vertical axes, R7R8R9 are the adjacent right vertical axes, R10R11R12 are the lower horizontal axes, and R13R14R15 are the adjacent upper horizontal axes. The four axes together divide a rectangular area in the horizontal direction. It is suitable for various axis numbering formats such as pure numbers, pure letters, letter + number combinations, and number + letter combinations.

[0020] ④ Sub-project Code + Sub-sub-project Code (T1T2T3T4, 4 digits): QBS coding is directly adopted. T1T2 corresponds to the sub-project number in the QBS code, and T3T4 corresponds to the sub-sub-project number. Refer to the "Full Life Cycle Digital Smart Power Plant Management QBS and Compilation Instructions". For example, 0102 represents the pile foundation sub-project in the foundation and substructure sub-project, and 0201 represents the main cast-in-place concrete sub-project in the main plant structure sub-project. This design achieves a direct fourth-level correspondence between civil engineering KKS coding and QBS quality assessment coding, eliminating the need for additional mapping and conversion, fundamentally solving the technical challenge of connecting civil engineering quality data through KKS coding. Through the above four-layer coding structure, the KKS coding of civil engineering achieves a complete hierarchical decomposition from the whole plant → individual buildings → spatial areas → sub-items of the project. Coding example: 00-UHF01-B00.M02M03&M0GM0H-0102 (represents the foundation and foundation pile foundation sub-project of the area enclosed by the M-2 / M-3 axis and the MG / MH axis of the foundation layer of the common coal bunker of the whole plant), 02-UMA01-F21.018019&00A01A-0201 (represents the main cast-in-place concrete sub-project of the main plant structure of the 12.000-meter level of the No. 2 turbine hall, enclosed by the 18 / 19 axis and the A / 1A axis).

[0021] (1.4) Equipment and Material Coding: Associated with KKS codes, it includes attributes such as equipment classification, model, specifications, material, and supplier, forming material information closely related to the physical equipment. Existing material coding usually adopts an independent classification coding system (such as "major category + intermediate category + minor category + serial number"), which is disconnected from equipment design coding, resulting in the inability to directly associate design parameters during the procurement stage. The material coding of this invention adopts the structure of "KKS core code + attribute extension code (8 digits)," namely, the whole plant code (2 digits) + building unit code (5 symbols) + area code (15 symbols) + sub-project and sub-sub-project code (4 digits) + attribute extension code (8 digits).

[0022] The attribute extension code includes: equipment classification code (2 digits, based on the DL / T 700 power material classification standard), model specification code (3 digits, using a mapping table of model first letter abbreviation + numerical sequence), material code (1 digit, such as C=carbon steel, S=stainless steel, A=aluminum alloy), and supplier code (2 digits). This coding structure allows the material code to naturally carry a KKS identifier, and the design parameters associated with the KKS (such as design pressure, design temperature, flow rate, etc.) can be directly extracted when the procurement requirement is generated, without the need for manual secondary entry. At the same time, a 2-digit version number field is reserved in the code for managing material specification changes caused by design changes, realizing version traceability throughout the entire life cycle of the material.

[0023] Step 1.2: Establish automatic mapping rules between codes: In this step, the automatic mapping and linkage rules between codes are centered on KKS, namely: establishing a hierarchical correspondence between KKS and QBS (one KKS device corresponds to one QBS quality unit), a hierarchical correspondence between WBS and QBS (workload and quality tasks are associated), and directly referencing KKS device codes as core fields for equipment and material codes. Through this linkage mechanism with KKS as the bridge, the unification of "what to do (WBS) where (KKS)", "what quality requirements (QBS)", and "what materials to use (equipment and material codes)" is achieved, ensuring that data changes in any stage trigger synchronous verification and updates of other codes, achieving true data linkage. Specifically: (2.1) KKS and QBS hierarchical peer mapping: Establish a direct correspondence between KKS encoding and QBS encoding. Establish a KKS-QBS mapping table, using a dual mechanism of "primary key association + rule engine".

[0024] a. Primary Key Association Mechanism: For equipment-level KKS codes (e.g., 10LAC11AP001, representing condensate pump No. 1), the corresponding QBS quality inspection unit code (e.g., steam turbine specialty - condensate system - pump installation - condensate pump No. 1 installation inspection batch) is directly associated in the mapping relationship table. The mapping relationship table is stored in the project's central database, and its fields include: KKS code, QBS code, mapping type (1:1 or 1:N), mapping rule number, and effective timestamp.

[0025] b. Rule Engine Mechanism: For system-level KKS codes (e.g., 10LAC, representing a condensate system), since a system contains multiple devices, a "hierarchical inheritance + conditional matching" rule is used to automatically derive the mapping relationship. The rule engine is configured as follows: If the KKS system code = "10LAC" and the device category code = "AP" (pump), then all inspection batches under "Steam Turbine Specialty - Condensate System - Pump Equipment Installation" in the QBS are automatically associated; if the KKS device code contains "AP001", then it is further precisely associated with the inspection batch of a single device.

[0026] c. Mapping conflict resolution mechanism: When the same KKS code corresponds to multiple QBS units (such as one piece of equipment involving multiple sub-projects), a priority field is set to sort the data according to the priority order of "equipment body installation > auxiliary equipment installation > pipe connection > electrical wiring" to ensure the accuracy of quality data collection.

[0027] d. Dynamic mapping maintenance mechanism: When design changes lead to changes in KKS codes, the system automatically triggers the mapping relationship update process, associates the old and new KKS codes through the change order number (ECN), and synchronously updates the QBS association relationship to maintain real-time consistency of the mapping relationship.

[0028] (2.2) Correspondence between WBS and QBS levels: In principle, WBS is established uniformly according to QBS classification to ensure that each quality assessment unit (QBS) can correspond to a specific work task package (WBS), realizing a one-to-one mapping between "quality activities" and "workload".

[0029] (2.3) Mapping between equipment material codes and KKS codes: The material code directly references the KKS equipment code as the core field. The coding mapping architecture of "KKS primary key embedding + attribute extension" is adopted.

[0030] i. Core Field Mapping: The first 12 digits of the material code directly reference the KKS equipment code, serving as a unique identifier for the material throughout the design, procurement, and construction phases. For example, the material code corresponding to KKS code "10LAC11AP001" (Condensate Pump No. 1) is "10LAC11AP001-PM001-V1", where "10LAC11AP001" is the core identifier, "PM" indicates pump type material, "001" is the model specification number, and "V1" is the version number.

[0031] ii. Many-to-One Mapping: For standard parts and general-purpose materials (such as bolts, washers, and cables) without independent KKS codes, a derived coding rule of "system KKS code + material classification code + serial number" is adopted. For example, the M24 bolts used in the condensate system (10LAC) have a material code of "10LAC-FS-024-001", where "FS" represents fasteners and "024" represents M24 specification. In the mapping table, this material code is associated with the system KKS code "10LAC" and the mapping type is marked as "N:1" (multiple materials to one system).

[0032] iii. Purchase Package Mapping Rules: During the procurement phase, all material codes within the same purchase package are aggregated using the "Purchase Package Number," and a link is established between the purchase package number and the KKS system code. For example, purchase package "PB-LAC-2024-001" (condensate system pump set purchase package) contains 3 condensate pumps (10LAC11AP001~003). In the mapping relationship table, the "Purchase Package Number" is set as an intermediate linking field to achieve a four-level penetration query of "Purchase Package → KKS System → Individual Equipment → Material Details."

[0033] iv. Arrival and Acceptance Mapping: When materials arrive, the system automatically parses the KKS core code by scanning the material code and associates it with the corresponding QBS quality inspection unit, automatically generating the arrival inspection batch for the material (such as "equipment unpacking inspection" or "appearance quality inspection"), thus realizing the automatic triggering of material entry and quality inspection.

[0034] Step 1.3: Encoding drives the seamless integration of data throughout the entire lifecycle.

[0035] Step 1.3.1, Design Phase: Based on the BIM model, assign KKS and WBS codes to each component, generating uniquely identified design data, which is then automatically transferred to the procurement and construction phases. Specific technical implementation process: Step 1.3.1.1, BIM Model Encoding Embedding: In 3D design software (such as PDMS, Revit, Bentley), develop an encoding plugin to embed KKS encoding as a component attribute into the BIM model. For each piece of equipment, each section of pipe, and each valve, store a complete data package in the model consisting of "KKS encoding + design parameters (design pressure, temperature, flow rate, material, specifications) + spatial coordinates (X,Y,Z) + logical connection relationship (upstream / downstream equipment KKS)".

[0036] Step 1.3.1.2 Automatic extraction of design data: When the design is completed and published, the BIM model is automatically scanned through the code extraction interface (API), and the design data sheets are exported in batches according to the KKS code level, including the equipment list, piping list, valve list, and design parameter summary table.

[0037] Step 1.3.1.3, Automatic Data Transfer Mechanism: The design data table is automatically pushed to the procurement management system and construction management system via the Project DataBus. The transfer process adopts "code matching + data mapping" technology: using KKS codes as the matching key, the design parameters are automatically filled into the procurement requirement template (such as "Design Pressure → Procurement Technical Specification Pressure Parameters", "Material → Procurement Material Requirements") and the construction technical briefing template (such as "Installation Coordinates → Construction Layout Data", "Logical Connection Relationship → Construction Sequence Basis").

[0038] Step 1.3.1.4, Transfer Trigger Conditions: Automatic trigger conditions are set for design data transfer. When the BIM model status is marked as "Approved" and the KKS code passes the verification rules (hierarchical integrity, logical consistency), the system automatically generates a Data Transfer Note (DTN). The DTN includes the source system (design system), the target system (procurement / construction system), the KKS code list, the data field mapping table, and the transfer timestamp to ensure the traceability of data transfer.

[0039] Step 1.3.1.5 Automatic Synchronization of Design Changes: When a design change occurs (such as modification of equipment model or adjustment of KKS code), the system automatically identifies the scope of the change (by comparing the differences between the old and new KKS code sets), generates a change impact analysis report, and only pushes the associated data of the affected KKS codes to the relevant systems, avoiding the duplicate transmission of all data and improving synchronization efficiency.

[0040] Step 1.3.2, Procurement Stage: Procurement personnel generate a Request for Procurement (MR / MTO) based on the combination of "KKS code + equipment / material code" output from the design, ensuring that the procured materials accurately match the design requirements and construction location. Specific technical implementation process: Step 1.3.2.1: Automatic Generation of Procurement Requirements: After receiving the KKS code and design parameters pushed by the design system, the procurement management system automatically triggers the procurement requirements generation process. The system first queries the KKS-material code mapping database to determine whether a corresponding material code already exists for the KKS code. If it does, the system directly calls the existing material code and associates it with the latest design parameters. If it does not exist, the system automatically generates a new material code based on "KKS core code + material classification rules + model specification mapping table" and writes it into the mapping database.

[0041] Step 1.3.2.2: Automatic Compilation of Procurement Technical Specifications: The system automatically fills the procurement technical specification template based on the KKS design parameters associated with the material code. For example, the design parameters "flow rate = 800 m³ / h, head = 320 m, material = duplex stainless steel" for KKS code "10LAC11AP001" (No. 1 condensate pump) are automatically mapped to the corresponding fields in the technical specification, generating a complete technical specification that includes technical parameters, inspection standards, and performance test requirements.

[0042] Step 1.3.2.3, Procurement Package Assembly: Based on the system classification code of the KKS code (e.g., 10LAC represents the condensate system) and the equipment classification code of the material code, the system automatically aggregates multiple material codes into a procurement package according to the packaging rule of "same system, same supplier, same delivery date". For example, the system automatically categorizes the 3 condensate pumps (10LAC11AP001~003) and 2 condensate booster pumps (10LAC12AP001~002) of the condensate system into procurement package "PB-LAC-PUMP-001" and generates a procurement package.

[0043] Step 1.3.2.4, Procurement Requirement Approval Flow: The generated procurement requirements (including material codes, KKS codes, technical specifications, and procurement package numbers) are approved online according to the preset approval process (procurement engineer → professional head → project manager). After approval, the subsequent public bidding process begins.

[0044] Step 1.3.3, Construction Phase: WBS coding drives the construction schedule, and QBS coding drives quality inspection and evaluation. The two are synchronized in real time through coding mapping. A multi-level nested planning system is established with the overall control schedule as the core, divided into four schedule plan levels. The first level plan serves as the company's overall decision-making milestone, the second level is the project's control plan, and the third and fourth level plans are the construction unit's construction plans. Using the multi-level nested planning management model, work items in the upstream plan can be distributed to the downstream and decomposed into several sub-work items. Through hierarchical decomposition and distribution, the work is allocated to the participating parties. The quality inspection unit is used as the smallest unit of work decomposition, forming the fourth level schedule plan. BIM data is simultaneously bound to the schedule plan along with the quality inspection unit, making schedule management visible.

[0045] Step 1.3.4, Settlement Stage: The system automatically verifies the QBS code status bound to the engineering quantity unit. Only when the quality assessment is determined to be "qualified" will the system generate a monthly settlement application, eliminating the risk of settlement for unqualified quality.

[0046] Step 2: Multi-level schedule management based on the integration of BIM-PDCA technology.

[0047] Step 2.1: Establish a four-level nested planning system as the data structure for the planning phase in the integration of BIM-PDCA technologies: Level 1: Company-wide overall decision-making milestone plan; Level 2: Project Management Plan; Levels 3 and 4: The construction unit executes the plan.

[0048] Step 2.2: Using the inspection unit as the smallest work decomposition unit, the BIM model data is technically bound to the inspection unit and schedule data through the unique code of the BIM model component, thus establishing the data association of the BIM-PDCA planning stage.

[0049] Step 2.3: Based on the integration of BIM-PDCA technology, the BIM model is driven by the time axis to perform dynamic simulation of construction progress. The component data of the BIM model is automatically associated with the actual progress data of the PDCA execution stage, the critical path is automatically calculated, the planned and actual progress are compared, and deviation warning and earned value analysis curves are generated through data association calculation.

[0050] Step 2.4: Based on the integration of BIM-PDCA technology, support the planning, issuance, feedback, version upgrade, and approval closed loop. The mobile terminal collects progress data in real time and updates the BIM model component status and PDCA execution phase database synchronously through the data interaction interface.

[0051] Step 3: Closed-loop quality control based on the integration of BIM-PDCA technology.

[0052] PDCA (Plan-Do-Check-Act), as a state cycle model for quality management, is a well-known management methodology. The technical contribution of this invention does not lie in the PDCA management method itself, nor in the independent 3D display function of the BIM model, but in proposing an automatic quality state-driven control technology based on the BIM model. By establishing a data channel between BIM model components and on-site quality inspection data, the BIM model is transformed from a static 3D display carrier into a dynamic data calculation carrier. Embedded with state machine automatic control logic, the state transitions of each stage of quality control are automatically triggered by data conditions, realizing automatic collection, calculation, judgment, feedback, and closed-loop control of quality data.

[0053] Step 3.1: Digital twin model construction and quality attribute pre-configuration (corresponding to the technical implementation of the P phase); Existing BIM models typically only contain geometric and material information, lacking computational attribute fields related to quality inspection, making them difficult to use directly as a benchmark data source for quality judgment. Quality inspection plans often rely on manual preparation based on drawings and specifications, resulting in issues such as omissions in inspection items, incorrect reference to acceptance criteria, and discrepancies between inspection units and component correspondences.

[0054] To address this, this invention extends the Quality Attribute Schema (QAS) to the existing IFC model data schema through secondary development interfaces on BIM platforms (such as the Autodesk Revit API and Bentley iTwinSDK). This adds calculated attribute fields to each component, including: component type code, design geometric parameter vector (length / width / height / elevation / slope / axis coordinates), design material strength grade, associated acceptance specification number, associated QBS code, quality control point identifier (H / W / R), and allowable deviation threshold vector. These attribute fields are stored in the component attribute table of the BIM model database, serving as the baseline input for subsequent automatic comparison calculations.

[0055] The system reads the quality attributes of all components in the BIM model database and executes an automatic aggregation algorithm to generate inspection units. The automatic aggregation algorithm works as follows: it iterates through all components, groups them by the first 8 digits of their QBS code (sub-item code), calculates the number of components N for each group of the same type, automatically calculates the sampling quantity according to the acceptance specifications (e.g., GB 50300 requires n=max(3, ceil(N×10%))), generates an inspection unit code, and writes the GUID of the sampled components into the component list field of the inspection unit. This algorithm reduces the subjectivity and risk of omissions in manually preparing inspection plans.

[0056] The system writes the generated inspection unit code, planned inspection time, and associated WBS code into the inspection plan table of the project database. Simultaneously, it adds a "following inspection unit code" field to the WBS work package record in the schedule database, establishing a foreign key constraint relationship at the database level. When the construction schedule reaches this WBS work package, the system automatically checks the status of the associated inspection unit. Only when the inspection unit status is "qualified" is the WBS work package status allowed to be updated to "complete." This constraint is implemented through an automatic verification mechanism at the database transaction level.

[0057] Step 3.2: Real-time acquisition and digital twin synchronization of on-site quality inspection data (corresponding to the technical implementation of stage D).

[0058] Traditional quality inspection relies on construction workers filling in measured data on paper record sheets. The data has no technical connection with the BIM model or specific components, and cannot reflect the construction quality status in real time. There is a risk of retroactive recording and data falsification.

[0059] This invention employs an encoding-driven on-site data acquisition method: On-site quality inspection personnel scan QR codes or RFID tags on the surface of components using mobile terminals. The RFID tags contain KKS and QBS codes. After parsing the codes, the mobile terminal initiates a data query request to the central server via a 4G / 5G network or project WiFi. The server returns the component's BIM model design parameters as the inspection benchmark, which are displayed on the mobile terminal interface. Inspection personnel use total stations, laser scanners, rebound hammers, ultrasonic flaw detectors, and other testing instruments to conduct on-site measurements. The measured data is transmitted back to the mobile terminal in real time via Bluetooth 5.0 or WiFi. The mobile terminal binds the measured data with the component's QBS code and uploads it to the edge computing node via HTTPS protocol.

[0060] Edge computing nodes are deployed on-site to run data preprocessing services, including data format standardization (converting heterogeneous data formats from different instruments into a unified JSON format), data validity verification (checking the reasonableness of numerical ranges, such as whether elevation values ​​are within a reasonable range; if they exceed the range, they are marked as abnormal data), and timestamp alignment (aligning data from different instruments to a unified timeline according to the acquisition timestamp). The preprocessed data is then asynchronously pushed to the central database via a message queue.

[0061] After receiving the measured data, the central database automatically calls the BIM platform's write API through the QBS encoding → BIM component GUID mapping relationship. This writes the measured data into the "Measured Attributes" field of the corresponding component in the BIM model database, including the measured geometric parameter vector, measured material strength, testing timestamp, testing instrument number, and testing personnel's digital signature. This write operation directly updates the persistent storage of the BIM model database, enabling synchronization of the BIM model from a static design model to a dynamic digital twin model.

[0062] For continuous process parameters such as concrete pouring temperature, welding current and voltage, and steel structure strain, data are collected in real time by temperature sensors, current sensors, and strain sensors deployed on the construction site. The sensor data is uploaded to the edge computing node at a preset frequency. The node is automatically associated with the BIM model components through the KKS code of the sensor installation location, realizing real-time mapping of construction process data.

[0063] Step 3.3: Multi-dimensional automatic comparison and judgment algorithm based on digital twin model (corresponding to the technical implementation of stage C).

[0064] Traditional quality assessment relies on supervisors manually comparing measured data with specifications, which is highly subjective, inefficient, and difficult to comprehensively assess multiple parameters such as geometric dimensions, material strength, and appearance quality.

[0065] This invention deploys a Quality Judgment Engine (QJE) on the server side. It takes the design parameter vectors and acceptance standard thresholds stored in the BIM digital twin model as input and the on-site measured data vectors as comparison objects, automatically performing multi-dimensional comparison calculations. The Quality Judgment Engine includes three calculation sub-modules: a geometric dimension calculation sub-module calculates deviation values; if the deviation value is within the allowable deviation threshold, it is judged as "qualified"; otherwise, it is "unqualified." A material strength calculation sub-module performs statistical judgment, calculating the minimum and average values ​​of the measured strength samples and comparing them with design requirements. A visual quality calculation sub-module performs image recognition, receiving surface photos of components uploaded by mobile terminals, automatically identifying defect types (honeycomb, pitting, cracks, exposed reinforcement) and defect levels through a pre-trained convolutional neural network model, and then comparing them with the allowable standards in the specifications.

[0066] An inspection unit typically includes multiple inspection items (e.g., frame column inspection includes axis position, verticality, cross-sectional dimensions, concrete strength, and protective layer thickness). The quality judgment algorithm engine executes comprehensive judgment logic: if the judgment results of all sub-modules for the inspection items are "qualified," the inspection unit status is "Passed"; if there are general non-conformities and the geometric dimensional deviation is within 1.5 times the allowable deviation, the status is "Repairable"; if there are serious non-conformities or the material strength does not meet the requirements, the status is "Rejected." This judgment logic is dynamically maintained through a rule configuration table in the database, and can adapt to the requirements of different acceptance specifications (national standards, industry standards, enterprise standards) without modifying the source code.

[0067] After the assessment is completed, the system automatically calls the BIM platform API to write the assessment result into the "Quality Status" attribute field of the corresponding component and triggers a model visualization update: qualified is displayed in green, repairable is displayed in yellow, and unqualified is displayed in red. This color change is driven by the model attribute value and is automatically rendered by the BIM platform's color rule engine.

[0068] Step 3.4: Automatic state transition and downstream business linkage based on the judgment result (corresponding to the technical implementation of Phase A).

[0069] Traditional rectification processes rely on manual initiation of rectification notices, tracking of rectification progress, and verification of rectification results. These processes are time-consuming, and rectification records are difficult to accurately link to the original components, making traceability challenging. Furthermore, the state transitions between each stage of the PDCA cycle depend on manual judgment and operation, making it difficult to achieve automated closed-loop management.

[0070] The present invention models the quality control process as a finite state machine, defining four states: P (Plan state), D (Do state), C (Check state), and A (Act state), as well as state transition conditions. The state transition rules are: the trigger condition for P→D is "WBS work package start signal"; the trigger condition for D→C is "all measured data are fully collected and pass validity verification"; the trigger condition for C→A is "the determination algorithm outputs a status field"; the trigger condition for A→P is "the re-inspection determination status is qualified". This state machine is automatically executed by the event-driven architecture of the system.

[0071] When the output status of the determination algorithm is "Repairable" or "Rejected", the event bus of the system automatically publishes a "QualityCheckFailed" event. The rectification workflow engine that subscribes to this event automatically executes the following operations: reads the QBS code associated with the inspection unit, obtains the responsible WBS work package code through the WBS-QBS mapping table, obtains the responsible construction unit code, and automatically generates a Non-Conformance Report (NCR), where the NCR is automatically associated with the BIM model component GUID, the measured data vector, the determination result, and the number of the specification deviation clause. The NCR is pushed to the mobile terminals of the responsible construction unit and the supervision unit through the message queue.

[0072] After receiving the NCR, the construction unit views the BIM 3D positioning, measured deviation values, and specification requirements of the non-conforming component on the mobile terminal, formulates a rectification plan and fills in the form. During the rectification construction process, the construction unit updates the rectification status in real time through the mobile terminal, and the system writes this status back to the "Rectification Status" attribute field of the BIM model component through an API, so that the color of the component in the model changes to purple. After the rectification is completed, the construction unit uploads the post-rectification measured data through the mobile terminal, and the system automatically publishes a "RepairCompleted" event to trigger the re-inspection process, that is, re-executes the determination algorithm in step 3.3.

[0073] After the re-inspection is determined to be qualified, the system automatically executes a cascading update operation: through QBS-WBS mapping, the status field of the corresponding work package in the WBS database is automatically updated to "Completed" to release the schedule lock; through QBS-BOQ mapping, the component quantities associated with this inspection unit are automatically included in the settlement measurement scope, and the "Measurable Quantities" field in the settlement database is updated; through code association, the quality statistics database is automatically updated (updating the pass rate, rectification rate, and problem type distribution). The above cascading updates are automatically executed through database triggers and stored procedures without manual intervention.

[0074] The entire rectification process data (original measured values, judgment results, NCR number, rectification plan, post-rectification measured values, re-inspection results, responsible person, timestamp) is automatically written into the quality history table of the project database according to QBS coding, forming a component-level quality full life cycle data chain, which supports reverse querying of its complete quality history record through any component in the BIM model.

[0075] Step 4: Link quality verification and assessment with measurement and settlement based on the integration of BIM-PDCA technology.

[0076] Step 4.1: Settlement Trigger: The measurement and settlement process can only be triggered when the quality inspection unit evaluation data associated with the BIM model component passes the judgment. The quality inspection results serve as an auxiliary basis for the engineering measurement and settlement.

[0077] Step 4.2: Verification and Assisted Measurement: The platform uses the component codes of the BIM model to associate quality verification and evaluation data to perform technical verification and assisted review of the quantities of work submitted by the contractor, and no longer uses the automatically extracted quantities of work from the BIM model as the basis for measurement.

[0078] Step 4.3: Process Approval: After the contractor submits the work quantity, the supervisor reviews it with the quality inspection results as an auxiliary basis for verification, the follow-up audit reviews it with the quality data as an auxiliary basis for verification, and the owner reviews it in conjunction with the quality inspection technical data for confirmation.

[0079] Step 4.4: Auxiliary Accounting: Summarize the contractor's reported quantity data after quality inspection and verification according to the list number, and generate measurement sheets, monthly settlement payments and accounts payable data based on the quality inspection and verification results.

[0080] Step 4.5: Data Linkage: The settlement results are automatically synchronized to the contract, investment, and progress modules through the data interaction interface, forming a closed loop of "quality qualified - progress completed - settlement and pricing".

[0081] Technical differences between this invention and existing technologies and prior art: Existing technologies typically use BIM models as a visual representation of quality information and PDCA (Plan-Do-Check-Act) as an abstract description of management processes, lacking a deep data connection at the technical level. For example, existing technologies may disclose the concepts of "displaying quality problems on BIM models" or "managing quality according to the PDCA process," but fail to disclose the following technical solutions: BIM model quality attribute extension mode and automatic aggregation algorithm for inspection units; data channel between on-site measured data and BIM model database; multi-dimensional automatic comparison and judgment algorithm engine based on BIM design parameters and measured data; and state machine-driven automatic state transition and downstream business cascading update mechanism.

[0082] This invention uses a coding system (WBS / QBS / KKS) as a data bridge to move the BIM model from the "display layer" to the "data calculation layer," and transforms PDCA from the "management process layer" to the "automatic driving layer." Through an event-driven architecture and state machine, it achieves automatic data flow and state transitions between different stages of quality control, rather than manual management operations. This is the essential difference between this invention and existing technologies, and it is also the core inventive point of this patent.

[0083] The above description is only a preferred embodiment of the present invention. It should be noted that those skilled in the art can make several changes and improvements without departing from the overall concept of the present invention, and these should also be considered within the scope of protection of the present invention.

Claims

1. A method for integrated intelligent management and control of thermal power plant infrastructure progress, quality, and settlement using BIM, characterized in that: It includes the following steps: Step 1: Construct a multi-dimensional business coding system integrating BIM-PDCA technologies and bind it to the BIM model; Step 2: Multi-level schedule management based on the integration of BIM and PDCA technologies; Step 3: Closed-loop quality management based on the integration of BIM and PDCA technologies; Step 3.1: Digital twin model construction and quality attribute pre-configuration; Step 3.2: Real-time acquisition and digital twin synchronization of on-site quality inspection data: Through the secondary development interface of the BIM platform, the quality attribute model is extended based on the IFC model data model. Calculated attribute fields are added to each component, including: component type code, design geometric parameter vector, design material strength grade, associated acceptance specification number, associated QBS code, quality control point identifier, and allowable deviation threshold vector. These attribute fields are stored in the component attribute table of the BIM model database, serving as the benchmark input for subsequent automatic comparison calculations. The system writes the generated inspection unit code, planned inspection time, and associated WBS code into the inspection plan table of the project database. Simultaneously, a "post-inspection unit code" field is added to the WBS work package record in the schedule database, establishing a foreign key constraint relationship at the database level. When the construction progress reaches this WBS work package, the system automatically checks the status of the associated inspection unit. Only when the inspection unit status is "qualified" is the WBS work package status allowed to be updated to "completed." This constraint is implemented through an automatic verification mechanism at the database transaction level. Step 3.3: Multi-dimensional Automatic Comparison and Judgment Algorithm Based on Digital Twin Model: Deploy a quality judgment algorithm engine on the server side. Using the design parameter vector and acceptance standard threshold stored in the BIM digital twin model as input, and the actual measured data vector as the comparison object, automatically perform multi-dimensional comparison calculations. The quality judgment algorithm engine includes three calculation sub-modules: the geometric dimension calculation sub-module calculates deviation values; if the deviation value is within the allowable deviation threshold range, it is judged as "qualified"; otherwise, it is "unqualified." The material strength calculation sub-module performs statistical judgment, calculating the minimum and average values ​​of the measured strength samples and comparing them with the design requirements. The appearance quality calculation sub-module performs image recognition, receiving component surface photos uploaded by mobile terminals, automatically identifying defect types and defect levels through a pre-trained convolutional neural network model, and then comparing them with the allowable standards in the specifications. The quality assessment algorithm engine executes comprehensive assessment logic: if the assessment results of all sub-modules of the inspection items are "passed", the inspection unit status is "passed"; if there are general non-conformities and the geometric dimensional deviation is within 1.5 times the allowable deviation, the status is "repairable"; if there are serious non-conformities or the material strength does not meet the requirements, the status is "rejected". Step 3.4: Automatic state transition based on judgment results and linkage with downstream business; The quality control process is modeled as a finite state machine, defining four states: P, D, C, and A, and state transition conditions. The state transition rules are as follows: the trigger condition for P→D is "WBS work package start signal"; the trigger condition for D→C is "all measured data have been collected and passed the validity verification"; the trigger condition for C→A is "judgment algorithm outputs the state field"; the trigger condition for A→P is "re-inspection judgment status is qualified". This state machine is automatically executed by the system's event-driven architecture. When the algorithm outputs a status of "Repairable" or "Rejected", the system's event bus automatically publishes a "QualityCheckFailed" event. The rectification workflow engine that subscribes to this event automatically executes the following: reads the QBS code associated with the inspection unit, obtains the responsible WBS work package code and the responsible construction unit code through the WBS-QBS mapping table, automatically generates a Non-Conformance Report (NCR), and automatically associates the BIM model component GUID, measured data vector, judgment result, and specification deviation clause number. The NCR is then pushed to the responsible construction unit's mobile terminal and the supervisor's mobile terminal via a message queue. After receiving the NCR, the construction unit views the BIM 3D positioning, measured deviation value, and specification requirements of the non-conforming component on a mobile terminal, formulates a rectification plan and fills it in. During the rectification construction, the construction unit updates the rectification status in real time through the mobile terminal. The system writes the status back to the "rectification status" attribute field of the BIM model component through API. After the rectification is completed, the construction unit uploads the measured data after rectification through the mobile terminal. The system automatically publishes the "RepairCompleted" event, triggering the re-inspection process, that is, re-executes the judgment algorithm in step 3.

3. After the re-inspection is deemed qualified, the system automatically performs cascading update operations: through QBS-WBS mapping, it automatically updates the status field of the work package in the WBS database to "Completed" and releases the progress lock; through QBS-BOQ mapping, it automatically includes the component quantities associated with the inspection unit into the settlement measurement scope and updates the "Measurable Quantities" field in the settlement database; through code association, it automatically updates the quality statistics database. The data of the entire rectification process is automatically written into the quality history table of the project database according to the QBS code, forming a component-level quality life cycle data chain, which supports reverse querying of the complete quality history record of any component in the BIM model. Step 4: Link quality verification and assessment with measurement and settlement based on the integration of BIM-PDCA technology.

2. The integrated intelligent management and control method for thermal power infrastructure progress, quality, and settlement based on BIM as described in claim 1, characterized in that: In step 3.2, the system reads the quality attributes of all components in the BIM model database, executes an automatic aggregation algorithm to generate inspection units, and the automatic aggregation algorithm is as follows: traverse all components, group them according to the sub-item code of QBS code, calculate the number of components N of the same type in each group, automatically calculate the sampling quantity according to the acceptance specification, generate the inspection unit code, and write the GUID of the sampled components into the component list field of the inspection unit.

3. The integrated intelligent management and control method for thermal power infrastructure progress, quality, and settlement based on BIM as described in claim 1, characterized in that: Step 4 specifically includes: Step 4.1: Settlement Trigger: The measurement and settlement process can only be triggered when the quality inspection unit evaluation data associated with the BIM model component passes the judgment. The quality inspection and evaluation results serve as an auxiliary basis for the engineering measurement and settlement. Step 4.2: Verification and Assisted Measurement: The platform uses the component codes of the BIM model to associate quality verification and evaluation data to perform technical verification and assisted review of the quantities of work submitted by the contractor, and no longer uses the automatically extracted quantities of work from the BIM model as the basis for measurement. Step 4.3: Process Approval: After the contractor submits the work quantity, the supervisor reviews it with the quality inspection results as an auxiliary basis for verification, the follow-up audit reviews it with the quality data as an auxiliary basis for verification, and the owner reviews it in conjunction with the quality inspection technical data for confirmation; Step 4.4: Auxiliary Accounting: Summarize the contractor's reported quantity data after auxiliary verification by the list number, and generate measurement sheets, monthly settlement payments and accounts payable data based on the quality verification results; Step 4.5: Data Linkage: The settlement results are automatically synchronized to the contract, investment, and progress modules through the data interaction interface, forming a closed loop of "quality qualified - progress completed - settlement and pricing".

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