Digital delivery management platform and method based on BIM technology

Abstract

The application discloses a digital delivery management platform and method based on BIM technology, and relates to the technical field of digital delivery, which comprises the following steps: according to an LOD-LOR rule dictionary and a progress mapping table, performing geometric and logical consistency checking on BIM models by components, identifying missing items and conflicts, and generating a high-trust model after repair; based on the high-trust model, combining professional zoning and work breakdown structure WBS to divide delivery units and generate a delivery dataset; performing field normalization, hierarchical hashing and signature operation on the delivery dataset to generate a verifiable delivery package with a digital fingerprint, and obtaining the digital fingerprint, signature record and hash index table; based on the digital fingerprint and signature record, importing the verifiable delivery package into a digital delivery platform, verifying consistency by combining the hash index table, generating a delivery verification report and storing the report as a digital archived achievement. The application makes the BIM digital delivery process have high trustworthiness and verifiability.

Description

Technical Field

[0001] This invention relates to the field of digital delivery technology, and in particular to a digital delivery management platform and method based on BIM technology. Background Technology

[0002] With the deepening application of Building Information Modeling (BIM) technology in the engineering construction field, digital management of the entire building lifecycle has become a key direction for the digital transformation of the construction industry. BIM technology integrates and expresses multi-source data such as building geometry, component attributes, construction procedures, schedules, and cost information through three-dimensional information models, providing a unified data carrier and semantic support for project design, construction, and operation and maintenance. In recent years, with the integration of information technology and engineering management, the application of BIM models in the project delivery phase has gradually expanded to collaborative design, construction organization, project acceptance, and operation and maintenance management, realizing the transformation from two-dimensional delivery to three-dimensional digital delivery.

[0003] Existing digital delivery technologies primarily focus on the aggregation of component information and the standardization of file formats, but they still have shortcomings in terms of delivery integrity verification, component logical consistency, and delivery data traceability. Firstly, existing delivery processes lack a dynamic consistency verification mechanism based on the LOD-LOR dual-dimensional standard, making it impossible to comprehensively assess component geometric accuracy, task relevance, and process logic, resulting in deliverables that fail to accurately reflect the project's implementation status. Secondly, existing delivery data is mostly generated through manual export and static archiving, lacking digital signature and hash verification mechanisms, making it impossible to achieve tamper-proof verification and traceability auditing of delivery packages, thus posing risks to authenticity and integrity in data transmission and platform integration. Summary of the Invention

[0004] In view of the aforementioned existing problems, the present invention is proposed.

[0005] Therefore, this invention provides a digital delivery management system based on BIM technology to solve the problem of insufficient authenticity and traceability of delivery data in existing technologies.

[0006] To solve the above-mentioned technical problems, the present invention provides the following technical solution:

[0007] In a first aspect, the present invention provides digital delivery management based on BIM technology, which includes,

[0008] Collect the BIM model and project schedule from the design phase, extract component tag numbers, task numbers, process codes and geometric attributes, combine the delivery requirements of each phase, obtain the LOD-LOR rule dictionary, and establish a schedule mapping table corresponding to component tag numbers and task numbers.

[0009] Based on the LOD-LOR rule dictionary and schedule mapping table, the geometric and logical consistency of the BIM model is checked for each component, and missing items and conflicts are identified to generate a repaired, highly reliable model.

[0010] Based on a high-reliability model, delivery units are divided by combining professional partitioning and the Work Breakdown Structure (WBS) to generate a delivery dataset.

[0011] Perform field normalization, hierarchical hashing, and signature operations on the delivery dataset to generate a verifiable delivery package with a digital fingerprint, and obtain the digital fingerprint, signature record, and hash index table;

[0012] Based on digital fingerprints and signature records, verifiable delivery packages are imported into the digital delivery platform, and consistency is verified using a hash index table. Delivery verification reports are then generated and stored as digital archive results.

[0013] As a preferred embodiment of the BIM-based digital delivery management method of the present invention, the specific steps for obtaining the LOD-LOR rule dictionary and establishing a progress mapping table corresponding to component tag numbers and task numbers are as follows.

[0014] Extract component tag numbers, process codes, and geometric attributes from the BIM model, and create a component information table using the component tag number as the primary key;

[0015] Extract task numbers and task progress information from the project plan and build a task hierarchy tree structure;

[0016] Read the delivery requirements for each stage, extract the LOD level and LOR type required for each stage from the delivery requirements, and construct an LOD-LOR rule dictionary;

[0017] Pair the component tag number in the component information table with the task number in the task hierarchy tree structure to generate a progress mapping table.

[0018] As a preferred embodiment of the BIM-based digital delivery management method of the present invention, the specific steps for performing geometric and logical consistency verification on each component of the BIM model are as follows:

[0019] Based on the LOD–LOR rule dictionary and schedule mapping table, the component tag number, geometric attributes, process code and task number in the BIM model are extracted to generate a component processing list;

[0020] Identify components from the component processing list that do not meet the LOD level and record them as geometric missing items;

[0021] Based on the geometric vertex information in the Shape_Representation node, the boundary dimensions and volume of components with missing geometric items are calculated and the results are recorded to form a geometric integrity verification result table.

[0022] As a preferred embodiment of the BIM-based digital delivery management method of the present invention, the specific steps for identifying missing items and conflicts and generating a repaired, highly reliable model are as follows:

[0023] Based on the schedule mapping table, records with missing task numbers, inconsistent time intervals, and duplicate matching are identified in the component processing list, forming a logical association verification result table.

[0024] Summarize the geometric integrity check results table and the logical association check results table, generate a discrepancy report, update the component processing list, and write it back to the BIM model to obtain the repaired high-reliability model.

[0025] As a preferred embodiment of the BIM-based digital delivery management method of the present invention, the specific steps for dividing delivery units and generating delivery datasets are as follows:

[0026] Extract the component tag number, professional partition identifier, WBS number, geometric attribute and task number fields from the high-confidence model, and build a component index table according to the component tag number to generate a set of professional partitions;

[0027] Within each professional zone set, the component sets with the same WBS number are taken as delivery units;

[0028] The component tag number, geometric attribute, process code and task number fields in the component set of the delivery unit are standardized in terms of field format and unit to form a delivery unit attribute table.

[0029] Calculate the total number of components and geometric volume for each delivery unit, and summarize them with the delivery unit attribute table to form a delivery dataset.

[0030] As a preferred embodiment of the BIM-based digital delivery management method of the present invention, the specific steps for performing field normalization, hierarchical hashing, and signature operations on the delivery dataset are as follows:

[0031] The delivered dataset is standardized in terms of unit and time according to the field order, and then concatenated into a standardized record sequence using UTF-8 encoding and a fixed delimiter;

[0032] Perform SHA-256 operation on each record in the normalized record sequence to generate leaf hash values ​​and leaf hash lists;

[0033] Using the leaf hash list as the bottom layer, perform SHA-256 generation layer by layer to generate the parent node hash and obtain the root hash value;

[0034] The standardized record sequence, leaf hash list, hierarchical structure, and root hash value are encapsulated into a verifiable delivery package.

[0035] As a preferred embodiment of the BIM-based digital delivery management method of the present invention, the specific steps for obtaining digital fingerprints, signature records, and hash index tables are as follows:

[0036] The SM2 algorithm is used to digitally sign the root hash value and delivery metadata, forming a digital fingerprint and signature record.

[0037] The leaf hash values, their hierarchical positions, and the authentication paths to the root are aggregated to form a hash index table.

[0038] As a preferred embodiment of the BIM-based digital delivery management method of the present invention, the specific steps for generating the delivery verification report are as follows:

[0039] Based on digital fingerprints and signature records, controlled registration entries are established in the digital delivery platform, recording the root hash value, public key identifier, delivery time and registration number, and binding verifiable delivery packages and hash index tables.

[0040] Perform SM2 signature verification according to the public key identifier in the controlled registration entry, and generate a list of signature verification results;

[0041] Based on the hash index table, the SHA-256 hash value of each verifiable delivery package is recalculated and combined with the root authentication path to obtain a list of hash consistency results;

[0042] Based on the delivery metadata field template, the field order, unit, and time format of the standardized record sequence are compared for consistency, and a list of metadata consistency results is generated.

[0043] As a preferred embodiment of the BIM-based digital delivery management method of the present invention, the storage refers to digital archiving results, and the specific steps are as follows.

[0044] The signature verification result list, hash consistency result list, and metadata consistency result list are compiled into a delivery verification report;

[0045] The delivery verification report, along with digital fingerprints, signature records, verifiable delivery packages, and hash index tables, are stored together as digital archive results.

[0046] Secondly, this invention provides a digital delivery management platform based on BIM technology, comprising,

[0047] The data acquisition module is used to collect BIM models and project schedules during the design phase, extract component tag numbers, task numbers, process codes and geometric attributes, obtain the LOD-LOR rule dictionary in combination with the delivery requirements of each phase, and establish a schedule mapping table corresponding to component tag numbers and task numbers.

[0048] The model verification module is used to perform geometric and logical consistency verification on the BIM model component by component according to the LOD-LOR rule dictionary and schedule mapping table, identify missing items and conflicts, and generate a repaired high-reliability model.

[0049] The unit generation module is used to divide delivery units based on a high-reliability model, combined with professional partitioning and the Work Breakdown Structure (WBS), and generate delivery datasets.

[0050] The data encapsulation module is used to perform field normalization, hierarchical hashing, and signature operations on the delivery dataset to generate a verifiable delivery package with a digital fingerprint, and to obtain the digital fingerprint, signature record, and hash index table.

[0051] The verification and archiving module is used to import verifiable delivery packages into the digital delivery platform based on digital fingerprints and signature records, verify consistency using a hash index table, generate a delivery verification report, and store it as a digital archive result.

[0052] The beneficial effects of this invention are as follows: by using the LOD–LOR dual-dimensional verification steps, the geometric accuracy of components and the task logic are simultaneously verified, ensuring the integrity and consistency of the BIM model; by generating verifiable delivery packages through field normalization, hierarchical hashing and digital signatures, the anti-tampering verification and source traceability of delivery data are realized, and the BIM digital delivery process has high credibility and verifiability. Attached Figure Description

[0053] To more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings used in the following description of the embodiments will be briefly introduced. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0054] Figure 1 This is a flowchart of a digital delivery management method based on BIM technology.

[0055] Figure 2 This is a schematic diagram of a digital delivery management platform based on BIM technology.

[0056] Figure 3 A flowchart for establishing the LOD–LOR rule dictionary and progress mapping.

[0057] Figure 4A flowchart for professional zoning and WBS partitioning. Detailed Implementation

[0058] To make the above-mentioned objects, features and advantages of the present invention more apparent and understandable, the specific embodiments of the present invention will be described in detail below with reference to the accompanying drawings.

[0059] Many specific details are set forth in the following description in order to provide a full understanding of the invention. However, the invention may also be practiced in other ways different from those described herein, and those skilled in the art can make similar extensions without departing from the spirit of the invention. Therefore, the invention is not limited to the specific embodiments disclosed below.

[0060] Secondly, the term "one embodiment" or "embodiment" as used herein refers to a specific feature, structure, or characteristic that may be included in at least one implementation of the present invention. The phrase "in one embodiment" appearing in different places in this specification does not necessarily refer to the same embodiment, nor is it a single or selective embodiment that is mutually exclusive with other embodiments.

[0061] Reference Figures 1-4 This is one embodiment of the present invention, which provides digital delivery management based on BIM technology, including the following steps:

[0062] S1: Collect the BIM model and project schedule from the design phase, extract component tag numbers, task numbers, process codes and geometric attributes, combine the delivery requirements of each phase, obtain the LOD-LOR rule dictionary, and establish a schedule mapping table corresponding to component tag numbers and task numbers.

[0063] S1.1: Collect BIM models and project plans from the design phase;

[0064] Furthermore, BIM model files from the design phase are exported from the project's BIM data management platform. These files are IFC structured files and contain the 3D geometric information, attribute information, and coding information of the components. To ensure the reliability of the data source, the file generation time, version number, and BIM model development stage identifier are recorded during the export operation. Project schedule files are obtained from the project schedule management platform. These files are in XLSX format and contain task numbers, task names, planned start times, planned end times, and task hierarchy information. Both types of files are loaded into a unified data acquisition environment, uniformly encoded in UTF-8 format, and the consistency between the time field format and the number format is checked. Finally, the BIM model and project schedule are output.

[0065] It should be noted that the project BIM data management platform is a digital management environment used in engineering projects for centralized storage, management, and collaborative processing of BIM model data and related engineering information. Throughout the project lifecycle, the project BIM data management platform plays a role in data aggregation and sharing, capable of receiving BIM model files, schedule documents, and deliverables submitted by design, construction, and supervision parties, achieving unified management of component information, task information, schedule information, and professional zoning information. As the primary data source for BIM models and project schedules during the design phase, the project BIM data management platform supports data management and version traceability throughout the entire process of component information extraction, rule dictionary construction, delivery verification, and digital archiving.

[0066] S1.2: Extract component tag numbers, process codes, and geometric attributes from the BIM model, and establish a component information table using the component tag number as the primary key;

[0067] Furthermore, component tag numbers, process codes, and geometric attribute information are extracted from the BIM model component by component. The component tag number is used to uniquely identify an individual component, the process code indicates the construction sequence of the component, and the geometric attributes include geometric type, dimensions, volume, and spatial coordinate range. During the extraction process, attribute fields are read from the IFCProduct class node in the IFC structured file, and the component code field is used as the index key to create a component information table in the database based on the component tag number. If any geometric attribute fields are missing, the boundary dimensions and volume are calculated using the geometric vertex coordinates of the Shape_Representation node in the IFC structured file and added to the component information table. The final output component information table contains fields such as component tag number, process code, geometric type, dimensions, volume, and spatial location.

[0068] S1.3: Extract task numbers and task progress information from the project plan table, and establish a task hierarchy tree structure;

[0069] Furthermore, based on the task hierarchy field in the project plan, a parent-child hierarchical relationship is established between tasks. Task numbers under the same parent node are sorted chronologically to form a task hierarchy tree structure. Each task hierarchy node records the task number, task start time, task end time, and the number of its parent task, reflecting the dependencies and temporal relationships between tasks. If a task hierarchy field is missing, its position is deduced and added based on the prefix structure of the task number and the time interval sequence. The final task hierarchy tree structure is then used for subsequent component-task matching.

[0070] S1.4: Read the delivery requirements of each stage, extract the LOD level and LOR type required for each stage from the delivery requirements, and construct the LOD-LOR rule dictionary;

[0071] Furthermore, the delivery phase name, start and end times, LOD level, and LOR type fields are extracted from the delivery requirements document. The LOD level is used to define the geometric accuracy requirements of the delivery phase, and the LOR type is used to define the strength of the association between components and tasks, processes, and schedules. Based on the matching relationship between delivery phases and task time intervals, the LOD level and LOR type corresponding to each delivery phase are registered as entries. Each entry includes the delivery phase name, LOD level, LOR type, and applicable professional scope. All entries are compiled and organized to form an LOD-LOR rule dictionary.

[0072] It should be noted that the delivery requirements document is a normative document used in engineering projects to specify the content, accuracy standards, and related requirements of deliverables at each stage. It is formulated by the project owner or management unit at the beginning of project implementation. This document typically includes the division of delivery stages, the start and end times of each stage, the corresponding LOD level requirements, LOR type requirements, applicable professional scope, and inspection and acceptance conditions. It guides the accuracy control and logical consistency verification of BIM data deliverables in the design, construction, and delivery stages, and serves as the original basis for constructing the LOD-LOR rule dictionary.

[0073] S1.5: Pair the component tag number in the component information table with the task number in the task hierarchy tree structure and register them to generate a progress mapping table;

[0074] Furthermore, using the process code in the component information table as the matching condition, the set of task numbers corresponding to the process code in the task hierarchy tree structure is retrieved. The update time recorded in the component information table is compared with the task time interval recorded in the task hierarchy tree structure, and task numbers with overlapping or closest times are filtered out, establishing a one-to-one correspondence with the corresponding component tag number. For component tag numbers that do not match, interpolation is performed according to the task numbers and time distribution of adjacent components. After registration, the component tag number, task number, process code, task start time, and task end time are recorded to generate a progress mapping table.

[0075] S2: Based on the LOD-LOR rule dictionary and schedule mapping table, perform geometric and logical consistency checks on each component of the BIM model, identify missing items and conflicts, and generate a repaired, highly reliable model.

[0076] S2.1: Based on the LOD–LOR rule dictionary and schedule mapping table, extract the component tag number, geometric attributes, process code and task number in the BIM model to generate a component processing list;

[0077] Furthermore, based on the LOD–LOR rule dictionary and schedule mapping table, the component tag number, geometric attributes, process code, and task number fields are extracted sequentially from the BIM model. During extraction, the GlobalId field of the component is read as the component tag number by traversing the IFCProduct class nodes of the BIM model; the geometric type, dimensions, volume, and spatial location of the Shape_Representation node are read as geometric attributes; the process codes recorded in the attribute set are read; and the corresponding task numbers are matched according to the schedule mapping table. The extracted field information is recorded in component tag number order and integrated into a structured table, where each row uniquely corresponds to one component, and a component processing list is output.

[0078] S2.2: Identify components that do not meet the LOD level from the component processing list and record them as geometric missing items;

[0079] Furthermore, based on the LOD level requirements defined in the LOD-LOR rule dictionary, the geometric attribute fields of each component are checked from the component processing list. The check items corresponding to the LOD level include geometric type completeness, dimensional accuracy, and volume calculation accuracy. When a component lacks a field required by the LOD level, has an empty field value, or its field value does not conform to the specified accuracy, the component's tag number is recorded, and it is marked as a geometric missing item in the component processing list. The verification results simultaneously record the missing field type, corresponding LOD level, and inspection time, forming a preliminary missing item list.

[0080] S2.3: Based on the geometric vertex information in the Shape_Representation node, calculate the boundary dimensions and volume of components with missing geometric items and fill in the results to form a geometric integrity check result table;

[0081] Furthermore, the minimum enclosing cube boundary size of the component is calculated using vertex coordinate data, and volume parameters are calculated based on the geometry type. If the geometry type is a composite structure, the volume is calculated by piecewise integration according to the component vertex set and then summed. The calculated dimensions and volume data are filled into the corresponding fields in the component processing list, and the field status is updated to "added". After the addition is completed, the addition status, calculation source, and addition status of each component are summarized to form a geometric integrity verification result table.

[0082] It should be noted that components with a composite geometry refer to complex components in the BIM model formed by combining multiple independent geometric units. These components typically contain geometries of different shapes or material properties, and their geometric boundaries cannot be fully described by a single entity. Examples include reinforced concrete beam-slab joints, equipment foundations with embedded parts, exterior wall components with multi-layered cladding structures, or installation units formed by combining pipes and supports. In IFC files, these components are usually recorded as multiple Shape_Representation nodes, each containing an independent geometric description. Therefore, when calculating the volume, piecewise integration of the vertex sets of each geometric unit is required, followed by summing the volumes of all units to obtain the total volume of the complete component.

[0083] S2.4: Based on the schedule mapping table, identify records with missing task numbers, inconsistent time intervals, and duplicate matching in the component processing list, and form a logical association verification result table;

[0084] Furthermore, the system checks if the task number field contains null values; if so, it marks the task number as missing. It compares the task time interval recorded in the progress mapping table with the component's update time field; if the two are not within a reasonable range, it records a time interval mismatch. It also checks if the same component tag number corresponds to multiple task numbers; if duplicate matches exist, it records a conflict. Components with missing task numbers, mismatched time intervals, and duplicate matches are registered separately, and a logical association verification result table is generated.

[0085] It should be noted that the reasonable range refers to the allowable deviation range within which a component should maintain consistency with its corresponding task time interval during the project execution cycle. This range is used to determine the logical match between the component update time and the planned task time. Specifically, if the component update time falls between the task start time and task end time recorded in the schedule mapping table for its corresponding task number, or within a small allowable time offset range (such as a certain buffer period before and after the task start), the time relationship is considered reasonable. If the update time is significantly earlier than the planned task start time or significantly later than the planned task end time, it is determined that the time interval is inconsistent. This reasonable range is used to identify the synchronicity between component update behavior and task progress, preventing schedule logic errors or task association confusion.

[0086] S2.5: Summarize the geometric integrity check results table and the logical association check results table, generate a discrepancy report, update the component processing list, write back to the BIM model, and obtain the repaired high-reliability model;

[0087] Furthermore, the geometric integrity verification results table and the logical association verification results table are summarized to form a discrepancy report. The discrepancy report includes component tag number, missing item type, supplementation status, task logic anomaly type, and repair suggestions. Based on the discrepancy report, the fields that have been supplemented or corrected in the component processing list are updated, and the updated component information is written back to the corresponding IFCProduct node in the BIM model. The update operation includes overwriting the modified geometric attributes and task number fields in the BIM model and updating the update timestamps of the fields. After the update is completed, the repaired high-confidence model is output.

[0088] S3: Based on a high-reliability model, delivery units are divided using professional partitioning and the Work Breakdown Structure (WBS) to generate a delivery dataset.

[0089] S3.1: Extract the component tag number, professional partition identifier, WBS number, geometric attribute and task number fields from the high-confidence model, and build a component index table according to the component tag number;

[0090] Furthermore, based on the high-reliability model, the component tag number, professional zone identifier, WBS number, geometric attributes, and task number fields are extracted for each component. The component tag number is used to uniquely identify the component object; the professional zone identifier is used to distinguish between professional categories such as structural, architectural, and electrical; the WBS number is used to reflect the task decomposition hierarchy; and the geometric attributes include geometric type, dimensions, volume, and coordinate range. By traversing the IFCProduct class nodes in the high-reliability model, the corresponding fields are read and field indexes are established. All extracted component data are organized using the component tag number as the primary key to generate a component index table. The component index table records the spatial, professional, and task-level association information of components, providing a data foundation for subsequent delivery unit division.

[0091] S3.2: Based on the professional partition identifier in the component index table, group all components to generate a set of professional partitions;

[0092] Furthermore, based on the component index table, the professional partition identifier field corresponding to each component is read. Components are classified according to the value of the professional partition identifier, and components with the same professional partition identifier are grouped together to form a professional partition set. The professional partition set contains all components belonging to the same professional scope and their corresponding component tag number, WBS number, geometric attribute, and task number fields. If a component is not marked with a professional partition identifier, it is inferred and added based on the floor where the component's geometric attributes are located, the component category, and its WBS parent number. The final output is multiple professional partition sets, each set representing an independent professional component group.

[0093] S3.3: In each professional partition set, the set of components with the same WBS number shall be used as the delivery unit;

[0094] Furthermore, the WBS number field corresponding to each component is read from each professional partition set, and components with the same WBS number are grouped into the same delivery unit. A delivery unit represents a set of components belonging to the same engineering task scope under the same work breakdown structure. The division of delivery units is based on the WBS number as an index, and the component tag number, geometric attributes, operation code, and task number fields are retained within the set to trace the task origin of the component. If a component's WBS number is missing, it is supplemented based on the spatial location and task number of adjacent components to ensure that all components are assigned to a specific delivery unit. The output is a set of delivery units organized by WBS number.

[0095] S3.4: Standardize the field format and unit of the component tag number, geometric attribute, process code and task number fields in the component set within the delivery unit to form a delivery unit attribute table;

[0096] Furthermore, for each delivery unit's component set, the component tag number, geometric attributes, process code, and task number fields are read, and the field format and units are standardized. Specifically, this includes converting length, area, and volume fields to a unified unit system, standardizing the time field to a standard time format, and arranging field names and order according to a standard template. After standardization, a delivery unit attribute table is output, organized by delivery unit. The delivery unit attribute table records the number of components, geometric features, and task-related fields contained in each delivery unit, used for subsequent delivery data statistics and summarization.

[0097] It should be noted that a standard template refers to the pre-defined field organization and data format specifications during the delivery data generation phase, used to unify the structured expression of component data from different sources or different specialties. The standard template clearly specifies the order, names, data types, units of measurement, and time format requirements of each field in the delivery unit attribute table, ensuring consistency of attribute data across all delivery units at the field level. For example, a standard template might specify the field order as "component tag number—task number—process code—length—area—volume—update time," and uniformly use the International System of Units (SI) and ISO standard time format. Through standard template constraints, it is ensured that the delivery unit attribute table maintains consistent format, comparability, and automatic verification during subsequent summarization, hash calculation, and digital archiving processes.

[0098] S3.5: Calculate the total number of components and geometric volume for each delivery unit, and summarize them with the delivery unit attribute table to form a delivery dataset;

[0099] Furthermore, based on the delivery unit attribute table, the number of components contained in each delivery unit is counted, and the total geometric volume of all components within the delivery unit is calculated. The volume summary is obtained by summing the volume fields recorded in the geometric attributes of each component. The component quantity and the total geometric volume value are added as new fields to the delivery unit attribute table, and the delivery unit number, professional zone identifier, and task number are organized. Finally, all delivery unit attribute tables are summarized to form a delivery dataset. The delivery dataset is used to describe the component composition, quantity statistics, and task association information of the delivery phase, providing a unified input for subsequent hash encapsulation and digital signatures.

[0100] S4: Perform field normalization, hierarchical hashing, and signature operations on the delivery dataset to generate a verifiable delivery package with a digital fingerprint, and obtain the digital fingerprint, signature record, and hash index table;

[0101] S4.1: Standardize the units and time of the delivered dataset according to the field order, and concatenate them into a standardized record sequence using UTF-8 encoding and a fixed delimiter;

[0102] Furthermore, the units of the numerical fields in the delivery dataset are standardized, converting physical quantities such as length, area, and volume into uniform units of measurement; the time fields in the delivery dataset are standardized by converting all time records into a standardized time format. After unit and time standardization, the field values ​​in each record are concatenated into a string sequence using a fixed delimiter, and then converted into a byte stream using UTF-8 encoding. All encoded string sequences are arranged in order of delivery unit number, outputting a standardized record sequence.

[0103] S4.2: Perform SHA-256 operation on each record in the normalized record sequence to generate leaf hash values ​​and leaf hash lists;

[0104] Furthermore, based on the standardized record sequence, SHA-256 hash operations are performed on each record. Specifically, each UTF-8 encoded record is used as input, its corresponding hash output is calculated, generating a unique 256-bit hash value, which is recorded as a leaf hash value. All leaf hash values ​​are arranged in the order of the input records, forming a leaf hash list. Each leaf hash value corresponds to a delivery data record, used for subsequent construction of a multi-level hash structure.

[0105] S4.3: Using the leaf hash list as the bottom layer, perform SHA-256 generation layer by layer to generate the parent node hash and obtain the root hash value;

[0106] Furthermore, based on the leaf hash list, a multi-level hash structure is constructed and a root hash value is generated. First, adjacent hash values ​​in the leaf hash list are concatenated sequentially to form a new string. The concatenated result is then subjected to SHA-256 computation to generate the parent node hash value. If the number of hashes in the leaf hash list is odd, the last leaf hash value is copied and concatenated with itself before calculation. This process is repeated, concatenating and calculating the parent node hash values ​​generated in the previous layer using adjacent pairings, recursively layer by layer, until a unique top-level hash value is obtained, denoted as the root hash value.

[0107] S4.4: Encapsulate the standardized record sequence, leaf hash list, hierarchical structure, and root hash value into a verifiable delivery package;

[0108] Furthermore, the standardized record sequence, leaf hash list, hierarchical structure from leaf hash to root hash, and root hash value are uniformly encapsulated to form a verifiable delivery package. During the encapsulation process, the path relationship and hash calculation order of each data element are recorded in the form of an index to ensure that the integrity of any record can be independently verified subsequently. After encapsulation, the verifiable delivery package contains both the delivery data ontology and its hash verification structure information.

[0109] It should be noted that the path relationship and hash calculation order originate from the hash structure index information formed during the hierarchical hash generation process, and are automatically generated records as the calculation proceeds layer by layer from the leaf hash values ​​to the root hash value. Specifically, each leaf hash value participates in the concatenation operation with adjacent hash values ​​during the calculation process, and its position (left node or right node) and the index position of the target hash value it is concatenated with are recorded, forming a path mapping from the leaf layer to the root layer. This path relationship identifies the complete calculation link from each leaf hash value to the root hash value, while the hash calculation order records the order of calculation and combination of each node in each layer. The combination of these two can be used to reconstruct the hash calculation process through path backtracking in the subsequent verification stage, independently verifying the integrity and consistency of the entire delivery package from any leaf hash value.

[0110] S4.5: Use the SM2 algorithm to digitally sign the root hash value and delivery metadata to form a digital fingerprint and signature record;

[0111] Furthermore, the SM2 algorithm is used to perform digital signature operations on the root hash value and delivery metadata. First, the SM2 public key identifier and private key information are read, and the root hash value is concatenated with the delivery metadata to form the signature input data. The SM2 algorithm is used to generate the signature output, and the signature output result is recorded as a digital fingerprint. The digital fingerprint, signature time, public key identifier, and signature algorithm information are summarized and registered to generate a signature record.

[0112] S4.6: Summarize the leaf hash values, their hierarchical positions, and the authentication paths to the root to form a hash index table;

[0113] Furthermore, a hash index table is constructed based on the leaf hash values, the hash hierarchy, and the root hash value. Specifically, this involves recording the hierarchical position of each leaf hash value within the hierarchy, extracting the authentication path from the leaf hash value to the root hash value, where each authentication path consists of adjacent hash values ​​calculated sequentially along the parent node. Each leaf hash value, its corresponding hierarchical position, and the authentication path are then organized into index entries and summarized in order of leaf hash values ​​to form the hash index table.

[0114] S5: Based on digital fingerprints and signature records, import verifiable delivery packages into the digital delivery platform, verify consistency using a hash index table, generate a delivery verification report, and store it as a digital archive result;

[0115] S5.1: Based on digital fingerprints and signature records, establish controlled registration entries in the digital delivery platform, record the root hash value, public key identifier, delivery time and registration number, and bind verifiable delivery packages and hash index tables;

[0116] Furthermore, based on digital fingerprints and signature records, controlled registration entries are established in the digital delivery platform. First, the root hash value, public key identifier, and signature time information from the digital fingerprint are read to generate a unique registration number. Then, the verifiable delivery package and hash index table are imported into the digital delivery platform, and file digest values ​​are calculated and compared with the root hash value in the digital fingerprint to confirm data integrity. The registration entry records the root hash value, public key identifier, delivery time, registration number, and digest comparison result, and bidirectionally binds the verifiable delivery package path and hash index table path to the registration number.

[0117] S5.2: Perform SM2 signature verification according to the public key identifier in the controlled registration entry and generate a signature verification result list;

[0118] Furthermore, based on the public key identifier recorded in the controlled registration entry, SM2 signature verification is performed on the root hash value and delivery metadata contained in the digital fingerprint. The signature value and public key identifier in the signature record are read, and the matching public key is used to verify the signature content, outputting the verification result. If the signature matches and verification is successful, it is recorded as valid; otherwise, it is recorded as invalid and an exception message is generated. The verification conclusion, public key identifier, verification time, and signature algorithm are registered as a verification result list for subsequent verification report summarization.

[0119] S5.3: Based on the hash index table, recalculate the SHA-256 hash value of each verifiable delivery packet and combine it with the root authentication path to obtain a list of hash consistency results;

[0120] Furthermore, based on the hash index table, the hash value of each standardized record sequence in the verifiable delivery package is recalculated and path verification is performed. Each record is read sequentially, and SHA-256 operations are performed using UTF-8 encoding as input to generate new leaf hash values. According to the hierarchical position and authentication path recorded in the hash index table, the hash values ​​of parent nodes are concatenated level by level and recalculated until the root hash value is obtained. The recalculated root hash value is compared with the root hash value in the digital fingerprint; if the results match, the verification is marked as passed; otherwise, it is marked as an anomaly. All comparison results are output as a hash consistency result list, indexed by the component number, to characterize the integrity of the verifiable delivery package during transmission and import.

[0121] S5.4: Based on the delivery metadata field template, perform a consistency comparison of the field order, unit, and time format of the standardized record sequence, and generate a list of metadata consistency results;

[0122] Furthermore, based on the delivery metadata field template, a field consistency comparison is performed on the standardized record sequence in the verifiable delivery package. First, the field names, order, data types, units of measurement, and time format standards in the field template are read. Then, each record is compared item by item in terms of field order, data units, and time format. If the field arrangement is inconsistent, the unit system is different, or the time format is mismatched, the differing field names and record index numbers are recorded as discrepancies. All comparison results are compiled and summarized to generate a metadata consistency result list, which is used to verify the structural consistency between the verifiable delivery package and the metadata template.

[0123] S5.5: Summarize the signature verification result list, hash consistency result list, and metadata consistency result list into a delivery verification report;

[0124] Furthermore, the signature verification result list, hash consistency result list, and metadata consistency result list are summarized to generate a delivery verification report. During the summarization process, the three types of result data are matched based on the registration number, and the signature verification conclusion, hash check conclusion, and metadata comparison conclusion are extracted to comprehensively generate the delivery verification status. The report records the registration number, root hash value, public key identifier, generation time, verification status, and conclusion description. The delivery verification report serves as the final result of verifying the trustworthiness and consistency of the delivered data, providing a verification basis for digital archiving.

[0125] S5.6: Store the delivery verification report, digital fingerprint, signature record, verifiable delivery package, and hash index table together as a digital archive result;

[0126] Furthermore, delivery verification reports, digital fingerprints, signature records, verifiable delivery packages, and hash index tables are uniformly stored as digital archive deliverables. During archiving, a storage path and retrieval key are generated for each file. The retrieval key is composed of the registration number, root hash value, and public key identifier, ensuring the unique traceability of each archived file. All archived files are stored using an immutable storage strategy to prevent subsequent modification. After storage is completed, a digital archive is formed for long-term verification and auditing after project delivery.

[0127] This embodiment also provides a digital delivery management platform based on BIM technology, including:

[0128] The data acquisition module is used to collect BIM models and project schedules during the design phase, extract component tag numbers, task numbers, process codes and geometric attributes, obtain the LOD-LOR rule dictionary in combination with the delivery requirements of each phase, and establish a schedule mapping table corresponding to component tag numbers and task numbers.

[0129] The model verification module is used to perform geometric and logical consistency verification on the BIM model component by component according to the LOD-LOR rule dictionary and schedule mapping table, identify missing items and conflicts, and generate a repaired high-reliability model.

[0130] The unit generation module is used to divide delivery units based on a high-reliability model, combined with professional partitioning and the Work Breakdown Structure (WBS), and generate delivery datasets.

[0131] The data encapsulation module is used to perform field normalization, hierarchical hashing, and signature operations on the delivery dataset to generate a verifiable delivery package with a digital fingerprint, and to obtain the digital fingerprint, signature record, and hash index table.

[0132] The verification and archiving module is used to import verifiable delivery packages into the digital delivery platform based on digital fingerprints and signature records, verify consistency using a hash index table, generate a delivery verification report, and store it as a digital archive result.

[0133] In summary, this invention achieves simultaneous verification of component geometric accuracy and task logic through the LOD–LOR dual-dimensional verification steps, ensuring the integrity and consistency of the BIM model; and generates verifiable delivery packages through field normalization, hierarchical hashing, and digital signatures, enabling tamper-proof verification and source traceability of delivery data, and making the BIM digital delivery process highly credible and verifiable.

[0134] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit it. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical solutions of the present invention without departing from the spirit and scope of the technical solutions of the present invention, and all such modifications or substitutions should be covered within the scope of the claims of the present invention.

Claims

1. A digital delivery management method based on BIM technology, characterized by: include, The process involves collecting the BIM model and project schedule from the design phase, extracting component tag numbers, task numbers, process codes, and geometric attributes, and combining this with the delivery requirements of each phase to obtain a LOD-LOR rule dictionary. A schedule mapping table corresponding to component tag numbers and task numbers is then established. The specific steps are as follows: Extract component tag numbers, process codes, and geometric attributes from the BIM model, and create a component information table using the component tag number as the primary key; Extract task numbers and task progress information from the project plan and build a task hierarchy tree structure; Read the delivery requirements for each stage, extract the LOD level and LOR type required for each stage from the delivery requirements, and construct an LOD-LOR rule dictionary; Pair the component tag number in the component information table with the task number in the task hierarchy tree structure to generate a progress mapping table; Based on the LOD-LOR rule dictionary and schedule mapping table, the BIM model is checked for geometric and logical consistency on a component-by-component basis, and missing items and conflicts are identified. A repaired, highly reliable model is then generated. The specific steps are as follows. Based on the LOD–LOR rule dictionary and schedule mapping table, the component tag number, geometric attributes, process code and task number in the BIM model are extracted to generate a component processing list; Identify components from the component processing list that do not meet the LOD level and record them as geometric missing items; Based on the geometric vertex information in the Shape_Representation node, calculate the boundary dimensions and volume of components with missing geometric items and fill in the results to form a geometric integrity check result table; Based on the schedule mapping table, records with missing task numbers, inconsistent time intervals, and duplicate matching are identified in the component processing list, forming a logical association verification result table. Summarize the geometric integrity check results table and the logical association check results table, generate a discrepancy report, update the component processing list, write it back to the BIM model, and obtain the repaired high-reliability model; Based on a high-reliability model, delivery units are divided by combining professional partitioning and the Work Breakdown Structure (WBS) to generate a delivery dataset. Perform field normalization, hierarchical hashing, and signature operations on the delivery dataset to generate a verifiable delivery package with a digital fingerprint, and obtain the digital fingerprint, signature record, and hash index table; Based on digital fingerprints and signature records, verifiable delivery packages are imported into the digital delivery platform, and consistency is verified using a hash index table. Delivery verification reports are then generated and stored as digital archive results.

2. The digital delivery management method based on BIM technology as described in claim 1, characterized in that: The specific steps for dividing the delivery units and generating the delivery dataset are as follows. Extract the component tag number, professional partition identifier, WBS number, geometric attribute and task number fields from the high-reliability model, and build a component index table according to the component tag number to generate a set of professional partitions; Within each professional zone set, the component sets with the same WBS number are taken as delivery units; The component tag number, geometric attribute, process code and task number fields in the component set of the delivery unit are standardized in terms of field format and unit to form a delivery unit attribute table. Calculate the total number of components and geometric volume for each delivery unit, and summarize them with the delivery unit attribute table to form a delivery dataset.

3. The digital delivery management method based on BIM technology as described in claim 2, characterized in that: The specific steps for performing field normalization, hierarchical hashing, and signature operations on the delivered dataset are as follows. The delivered dataset is standardized in terms of unit and time according to the field order, and then concatenated into a standardized record sequence using UTF-8 encoding and a fixed delimiter; Perform SHA-256 operation on each record in the normalized record sequence to generate leaf hash values ​​and leaf hash lists; Using the leaf hash list as the bottom layer, perform SHA-256 generation layer by layer to generate the parent node hash and obtain the root hash value; The standardized record sequence, leaf hash list, hierarchical structure, and root hash value are encapsulated into a verifiable delivery package.

4. The digital delivery management method based on BIM technology as described in claim 3, characterized in that: The specific steps for obtaining the digital fingerprint, signature record, and hash index table are as follows. The SM2 algorithm is used to digitally sign the root hash value and delivery metadata, forming a digital fingerprint and signature record. The leaf hash values, their hierarchical positions, and the authentication paths to the root are aggregated to form a hash index table.

5. The digital delivery management method based on BIM technology as described in claim 4, characterized in that: The specific steps for generating the delivery verification report are as follows: Based on digital fingerprints and signature records, controlled registration entries are established in the digital delivery platform, recording the root hash value, public key identifier, delivery time and registration number, and binding verifiable delivery packages and hash index tables. Perform SM2 signature verification according to the public key identifier in the controlled registration entry, and generate a list of signature verification results; Based on the hash index table, the SHA-256 hash value of each verifiable delivery package is recalculated and combined with the root authentication path to obtain a list of hash consistency results; Based on the delivery metadata field template, the field order, unit, and time format of the standardized record sequence are compared for consistency, and a list of metadata consistency results is generated.

6. The digital delivery management method based on BIM technology as described in claim 5, characterized in that: The storage refers to digital archiving results, and the specific steps are as follows. The signature verification result list, hash consistency result list, and metadata consistency result list are compiled into a delivery verification report; The delivery verification report, along with digital fingerprints, signature records, verifiable delivery packages, and hash index tables, are stored together as digital archive results.

7. A digital delivery management platform based on BIM technology, based on the digital delivery management method based on BIM technology as described in any one of claims 1 to 6, characterized in that: include, The data acquisition module is used to collect BIM models and project schedules during the design phase, extract component tag numbers, task numbers, process codes and geometric attributes, obtain the LOD-LOR rule dictionary in combination with the delivery requirements of each phase, and establish a schedule mapping table corresponding to component tag numbers and task numbers. The model verification module is used to perform geometric and logical consistency verification on the BIM model component by component according to the LOD-LOR rule dictionary and schedule mapping table, identify missing items and conflicts, and generate a repaired high-reliability model. The unit generation module is used to divide delivery units based on a high-reliability model, combined with professional partitioning and the Work Breakdown Structure (WBS), and generate delivery datasets. The data encapsulation module is used to perform field normalization, hierarchical hashing, and signature operations on the delivery dataset to generate a verifiable delivery package with a digital fingerprint, and to obtain the digital fingerprint, signature record, and hash index table. The verification and archiving module is used to import verifiable delivery packages into the digital delivery platform based on digital fingerprints and signature records, verify consistency using a hash index table, generate a delivery verification report, and store it as a digital archive result.

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