BIM file incremental transmission updating method, system and device based on self-correction dynamic partitioning and storage medium

Abstract

The invention provides a BIM file incremental transmission updating method, system and device based on self-correction dynamic partitioning and a medium. The method comprises the following steps that S1, a BIM file three-dimensional fuzzy classification model is established; s2, creating a network six-element evaluation system; s3, making a dynamic partitioning strategy; s4, constructing a block number calculation model; s5, establishing a file information base containing multi-dimensional features; and S6, constructing a file block transmission increment updating method. Compared with the prior art, through innovative design and function optimization in multiple aspects such as refined file classification, dynamic matching of file changes, real-time dynamic adjustment of file blocks and self-optimization based on historical data, the method shows remarkable advantages in multiple aspects such as file transmission efficiency, adaptability, reliability and usability. Meanwhile, data integrity is guaranteed based on hash value verification, and diversified and high-standard file transmission requirements in a modern digital environment can be better met.

Description

Technical Field

[0001] The present invention belongs to the technical field of BIM incremental update, and specifically relates to a method, system, device and storage medium for incremental transmission and update of BIM files based on self-correcting dynamic block. Background Art

[0002] A BIM model is a three-dimensional digital model that contains detailed information such as geometric shapes, component properties, spatial relationships, material information, and construction processes. BIM collaborative design is a design method based on the Building Information Model (BIM). It allows project stakeholders, including designers, constructors, and maintenance personnel, to collaborate and communicate in real time on the same BIM model through a shared digital platform, achieving efficient transitions from the design phase to the construction phase and then to the maintenance phase.

[0003] During incremental model file transmission, the fixed block-based transmission strategy suffers from low transmission efficiency, data loss, and corruption due to differences in file format, compression, and network environment. Different file formats have vastly different data structures and encoding methods, resulting in distinct transmission requirements. Whether or not a file is compressed can significantly alter its transmission characteristics. The complexity and dynamic nature of the network environment also pose significant challenges to file transmission. Summary of the Invention

[0004] The first purpose of the present invention is to address the above-mentioned problems and provide a method for incremental transmission and update of BIM files based on self-correcting dynamic blocking, combining technical tools and reasonable planning to achieve dynamic network adaptation, accurate file classification, reasonable transmission blocking, historical optimization and integrity hash verification, and improve the stability of model file transmission.

[0005] To this end, the above-mentioned purpose of the present invention is achieved through the following technical solutions:

[0006] A method for incremental transmission and updating of BIM files based on self-correcting dynamic block division includes the following steps:

[0007] S1. Construct a three-dimensional fuzzy classification evaluation cube model method for BIM file categories based on the three factors of file size, file format and compression;

[0008] S2. Construct a six-factor network status critical judgment method based on the six-factor good / bad critical standard based on the six factors of download bandwidth, upload bandwidth, bandwidth utilization, RTT (round-trip time), packet loss rate, and jitter;

[0009] S3. Classify the model files and build a dynamic block strategy based on the network level based on the optimal block strategy that can be supported for the transmission of each category of model files;

[0010] S4. A method for calculating the number of file blocks based on a critical judgment method for the six elements of network status and a three-dimensional fuzzy classification evaluation Rubik's Cube model, as well as a dynamic block strategy based on network level;

[0011] S5. Establish a file information library, which includes multiple files and their block information, as well as the file code, name, size, hash value, transmission time, integrity check result, network level, group type, abnormal events, and block information including sequence number, size, and hash value corresponding to each file information;

[0012] S6. Based on the historical operation data and the safety control line method, the method for calculating the number of file blocks is revised, and accordingly, a method for incremental updating of file block transmission is constructed.

[0013] While adopting the above technical solutions, the present invention may also adopt or combine the following technical solutions:

[0014] As a preferred technical solution of the present invention: Step S1 further includes the following sub-steps:

[0015] S11. Determine the domain of three factors: file size, file format, and whether to compress;

[0016] S12, determining a fuzzy set of three factors: file size, file format, and whether to compress;

[0017] S13. Construct a three-dimensional fuzzy classification evaluation Rubik's Cube model method based on the comprehensive membership calculation formula of three factors: file size, file format and compression.

[0018] As a preferred technical solution of the present invention: step S2 further includes the following sub-steps:

[0019] S21. Determine good / bad critical standards for six factors: download bandwidth, upload bandwidth, bandwidth utilization, RTT (round trip time), packet loss rate, and jitter;

[0020] S22. Construct a critical judgment method for the six factors of network status based on the six-factor good and bad critical standards of download bandwidth, upload bandwidth, bandwidth utilization, RTT (round-trip time), packet loss rate and jitter.

[0021] As a preferred technical solution of the present invention: step S3 further includes the following sub-steps:

[0022] S31. Prepare sample data for the three-dimensional model file block transmission experiment based on the classification of twenty groups of files using the three-dimensional fuzzy classification evaluation method of the Rubik's Cube model;

[0023] S32. Based on experimental data, historical operation data and expert experience data, the optimal block partitioning strategy that can be supported under the good and bad levels of network status is obtained.

[0024] As a preferred technical solution of the present invention: step S4 further includes the following sub-steps:

[0025] S41. Obtain the current network status based on the critical judgment method of the six elements of the network status;

[0026] S42, determining the grouping category of the three-dimensional model file based on the three-dimensional fuzzy classification evaluation magic cube model method;

[0027] S43. A dynamic block strategy based on the network level is used to obtain a file block strategy for the current network level and the corresponding BIM file grouping category;

[0028] S44. Based on the file segmentation strategy, calculate the number of segments of the current 3D model file.

[0029] As a preferred technical solution of the present invention: step S5 further includes the following sub-steps:

[0030] S51. Establish a document information database, determine the scope of the document information database, design the key information recording structure of the document information database, and plan key information;

[0031] S52. Create a database table based on the key information record structure of the file information library, and record the key information of the file and the associated block information.

[0032] As a preferred technical solution of the present invention: step S6 further includes the following sub-steps:

[0033] S61. Obtain the current number of file blocks based on the modified file block number calculation formula;

[0034] S62, processing the file blocks according to the number of current file blocks, and updating the current file increment to the file server;

[0035] S63: Merge the divided files and perform a difference check between the hash value of the merged file and the hash value of the current file;

[0036] S64. Construct a block-by-block incremental retransmission mechanism for the 3D model file based on the hash verification result.

[0037] The second object of the present invention is to provide a BIM file incremental transmission and update system based on self-correcting dynamic block segmentation, comprising the following modules:

[0038] A three-dimensional fuzzy classification and evaluation Rubik's Cube model construction module is used to construct a three-dimensional fuzzy classification and evaluation Rubik's Cube model method based on fuzzy evaluation of BIM file categories based on three factors: file size, file format, and compression;

[0039] A module for constructing a method for determining the critical quality of six network status factors: this module is used to construct a method for determining the critical quality of six network status factors based on a six-factor good / bad critical standard, based on the six factors of download bandwidth, upload bandwidth, bandwidth utilization, RTT, packet loss rate, and jitter.

[0040] A dynamic block strategy construction module is used to classify model files and construct a dynamic block strategy based on the network level based on the optimal block strategy that can be supported by the transmission of each category of model files;

[0041] A module for calculating the number of file blocks is built, based on a critical judgment method for the six elements of network status and a three-dimensional fuzzy classification evaluation Rubik's Cube model, as well as a dynamic block strategy based on network level.

[0042] A file information library establishment module is used to establish a file information library including multiple files and block information;

[0043] The file block transmission incremental update method construction module amends the file block number calculation method based on historical operation data and the security control line method, and constructs the file block transmission incremental update method accordingly.

[0044] The third object of the present invention is to provide an electronic device, comprising a processor, a communication interface, a memory, and a communication bus, wherein the processor, the communication interface, and the memory communicate with each other via the communication bus, and wherein:

[0045] a memory for storing a computer program;

[0046] A processor is used to execute the computer program stored in the memory to implement the steps of the self-correcting dynamic block-based BIM file incremental transmission and update method as described above.

[0047] Another object of the present invention is to provide a non-volatile storage medium, in which an executable program is stored. When the executable program is executed by a processor, the steps of the incremental transmission and update method of the self-correcting dynamic block BIM file are implemented as described above.

[0048] Compared with the prior art, the present invention has the following beneficial effects:

[0049] 1) A three-dimensional fuzzy classification and evaluation Rubik's Cube model method based on fuzzy assessment of file categories is constructed to achieve more refined file classification, and the file categories can be re-evaluated at any time and the transmission strategy can be adjusted accordingly;

[0050] 2) Construct a critical judgment method for the six elements of network status based on the six-factor good / bad critical standard. This method can provide a comprehensive and in-depth understanding of the real-time network status and dynamically change key parameters such as the size and number of file blocks based on the real-time monitoring of the six elements of the network.

[0051] 3) Using hash values ​​of files and blocks for verification, by calculating and comparing hash values, it is possible to accurately detect whether there is data loss or tampering during the file transmission process, thus ensuring the final integrity and accuracy of the file;

[0052] 4) Based on historical operation data and the safety control line method, the method for calculating the number of file blocks is revised, and has the characteristics of intelligent learning and self-optimization.

[0053] In summary, the present invention, based on a self-correcting dynamic block strategy, presents a method, system, device, and storage medium for incremental BIM file transmission and update. Through innovative design and functional optimization, including refined file classification, dynamic matching of file changes, real-time dynamic adjustment of file block, and self-optimization based on historical data, it demonstrates significant advantages over existing technologies in terms of file transmission efficiency, adaptability, reliability, and ease of use. Furthermore, hash value verification ensures data integrity, better meeting the diverse and high-standard file transmission requirements of the modern digital environment. BRIEF DESCRIPTION OF THE DRAWINGS

[0054] Figure 1 This is a flowchart of the incremental transmission and update method of BIM files based on self-correcting dynamic blocking provided by the present invention. DETAILED DESCRIPTION

[0055] The present invention will be further described in detail below with reference to the accompanying drawings and specific embodiments.

[0056] like Figure 1 As shown, a method for incremental transmission and updating of BIM files based on self-correcting dynamic block division specifically includes the following steps:

[0057] S1. Construct a three-dimensional fuzzy classification evaluation cube model method for BIM file categories based on the three factors of file size, file format and compression;

[0058] S11. Determine the domain of three factors: file size, file format, and whether to compress. In this embodiment, the specific process is as follows:

[0059] S111. Determine the file size domain. According to the actual application scenario, the file size range is determined to be 0 to 5 GB, and the file size domain is [0, 1024*1024*1024].

[0060] S112. Determine the file format domain. According to the actual application scenario, determine that bim and dwg are numbered 1, nwd and nwc are numbered 2, skp, fbx and 3mx are numbered 3, ifc and dgn are numbered 4, rvt is numbered 5, and the file size format is {1, 2, 3, 4, 5};

[0061] S113. Determine whether to compress the domain. According to the actual application scenario, determine whether to compress the domain to 0 if it is not compressed and 1 if it is compressed. Whether to compress the domain to {0,1}.

[0062] S12: Determine a fuzzy set of three factors: file size, file format, and whether to compress. In this embodiment, the specific process is as follows:

[0063] S121. Determine a fuzzy set of file sizes, classify files into four categories based on actual application scenarios: small files (0-1M), medium files (1M-100M), large files (100M-1G), and very large files (1G-5G), and define a fuzzy set and membership function for each category of files.

[0064] S122. Determine a fuzzy set of file formats, classify the files into category 1 files, category 2 files, category 3 files, category 4 files, and category 5 files according to actual application scenarios, and define a fuzzy set and membership function for each category of files;

[0065] S123. Determine the fuzzy set of whether to compress or not. When the file is uncompressed, the value is 0. When the file is compressed, the value is 1. Define the fuzzy set of whether to compress or not and the membership function.

[0066] S13, constructing a three-dimensional fuzzy classification evaluation magic cube model method based on the comprehensive membership calculation formula of the three factors of file size, file format and compression. In this embodiment, the specific process is as follows:

[0067] S131, determining twenty classification combinations based on four file size categories, five file format categories, and one compression category;

[0068] S132. Determine, based on experience or data analysis, the weights of the membership functions of file size, file format, and compression in each combination, representing the relative importance of the factors in the classification, and ensuring that the sum of the weights is 1.

[0069] S133. Construct a comprehensive membership calculation formula based on the sum of the membership functions and weight products of file size, file format, and compression, and select the combination with the largest comprehensive membership among the classification combinations as the current file category.

[0070] S2. Construct a six-factor network status critical judgment method based on the six-factor good / bad critical standard based on the six factors of download bandwidth, upload bandwidth, bandwidth utilization, RTT (round-trip time), packet loss rate, and jitter;

[0071] S21. Determine the good / bad critical standards for six factors: download bandwidth, upload bandwidth, bandwidth utilization, RTT (round trip time), packet loss rate, and jitter. In this embodiment, the specific process is as follows:

[0072] S211. Determine the critical standards for download bandwidth: when the download bandwidth is greater than 100 Mbps, the network status is rated as excellent; if the download bandwidth is in the range of 20 Mbps to 100 Mbps, the network status is rated as good; and if the download bandwidth is less than 20 Mbps, the network status is rated as poor.

[0073] S212. Determine the critical standards for upload bandwidth: when the upload bandwidth is greater than 50 Mbps, the network status is rated as excellent; if the upload bandwidth is in the range of 10 Mbps to 50 Mbps, the network status is rated as good; and if the upload bandwidth is less than 10 Mbps, the network status is rated as poor.

[0074] S213. Determine the critical standards for bandwidth utilization: when the bandwidth utilization is less than 30%, the network status is rated as excellent; if the bandwidth utilization is between 30% and 70%, the network status is rated as good; and once the bandwidth utilization is higher than 70%, the network status is rated as poor.

[0075] S214. Determine the critical standard for RTT (round-trip time), where the network status is rated as excellent when the RTT (round-trip time) is less than 50ms; the network status is rated as good when the RTT (round-trip time) is between 50ms and 200ms; and the network status is rated as poor when the RTT (round-trip time) is greater than 200ms.

[0076] S215. Determine the critical standard for packet loss rate, where the network status is rated as excellent when the packet loss rate is less than 1%; the network status is rated as good when the packet loss rate is between 1% and 5%; and the network status is rated as poor when the packet loss rate is greater than 5%.

[0077] S216. Determine the critical standard for good or poor jitter. When the jitter is less than 20ms, the network status is rated as excellent; if the jitter is in the range of 20ms to 50ms, the level is good; and once the jitter is greater than 50ms, the network status is classified as poor.

[0078] S22. Construct a method for determining the quality of six network status factors based on the six-factor quality criteria of download bandwidth, upload bandwidth, bandwidth utilization, RTT (round trip time), packet loss rate, and jitter. In this embodiment, the specific methods are as follows:

[0079] According to the six-factor good / bad critical standard, when the download bandwidth, upload bandwidth, bandwidth utilization, RTT (round-trip time), packet loss rate and jitter all meet the excellent standard, the network status is comprehensively evaluated as excellent;

[0080] According to the six-factor good / bad critical standard, if none of the six factors (download bandwidth, upload bandwidth, bandwidth utilization, RTT (round-trip time), packet loss rate, and jitter) meet the poor standard and at least one of them meets the good standard, the network status is comprehensively assessed as good.

[0081] According to the six-factor good-bad critical standard, when one of the six factors, including download bandwidth, upload bandwidth, bandwidth utilization, RTT (round-trip time), packet loss rate, and jitter, reaches a poor standard, the overall network status is assessed as poor.

[0082] S3. Classify the model files and build a dynamic block strategy based on the network level based on the optimal block strategy that can be supported for the transmission of each category of model files;

[0083] S31. Prepare experimental sample data for three-dimensional model file block transmission based on the three-dimensional fuzzy classification method for evaluating the Rubik's Cube model by classifying twenty groups of files. In this embodiment, the specific process is as follows:

[0084] S311, prepare m document samples for each group of document classification;

[0085] S32. Classify small files and the groups of files numbered 1 to 5, and prepare instances with 2, 4, and 8 blocks for each sample to obtain an experiment for the optimal block strategy;

[0086] S313, classify the medium-sized files and the file groups numbered 1 to 5, and prepare instances of block sizes of 512KB, 1MB, 2MB, 4MB, 6MB, 8MB, 10MB, 12MB, and 16MB for each sample to obtain the optimal block strategy experiment;

[0087] S314, classify the large files and the groups of files numbered 1 to 5, and prepare instances of block sizes of 8MB, 16MB, 24MB, 32MB, 48MB, 64MB, 80MB, 96MB, and 128MB for each sample to obtain the optimal block strategy experiment;

[0088] S315. Classify the oversized files and the groups of files numbered 1 to 5, and prepare instances with block sizes of 64MB, 96MB, 128MB, 200MB, 256MB, 384MB, 512MB, 768MB, and 1024MB for each sample to obtain the optimal block strategy experiment.

[0089] S32. Based on experimental data, historical operation data and expert experience data, the optimal block partitioning strategy that can be supported under the good and bad network status is obtained. In this embodiment, the specific process is as follows:

[0090] S321, copy k copies of each file sample instance, conduct experiments simultaneously, and record the file transfer time;

[0091] S322, taking the average of the transmission time of k sample files in each file sample instance;

[0092] S323: The optimal blocking strategy is the one that takes the minimum file transfer time for the m samples in each file classification group.

[0093] S324. According to the above steps, the optimal block strategy for each file category under the good or bad network status is obtained, and a three-dimensional relationship data table describing the network level, file grouping category, optimal block strategy and file transfer time is established.

[0094] S4. A method for calculating the number of file blocks based on a critical judgment method for the six elements of network status and a three-dimensional fuzzy classification evaluation Rubik's Cube model, as well as a dynamic block strategy based on network level;

[0095] S41. Obtain the current network status based on the critical judgment method of the six elements of the network status;

[0096] In this embodiment, the values ​​of six network indicators, namely, current download bandwidth, upload bandwidth, bandwidth utilization, RTT (round trip time), packet loss rate, and jitter, are read, and the current network status is obtained based on the critical judgment method of the six elements of network status.

[0097] S42, determining the grouping category of the three-dimensional model file based on the three-dimensional fuzzy classification evaluation magic cube model method;

[0098] In this embodiment, the three file attribute values ​​of the file size, file format and whether it is compressed of the 3D model file are read, and the grouping category of the 3D model file is obtained based on the 3D fuzzy classification evaluation magic cube model method.

[0099] S43. A dynamic block strategy based on the network level is used to obtain a file block strategy for the current network level and the corresponding BIM file grouping category;

[0100] In this embodiment, the file block strategy of the current network level and the corresponding file group category is obtained according to the network level and group category data and based on the dynamic block strategy of the network level.

[0101] S44. Based on the file segmentation strategy, calculate the number of segments of the current 3D model file.

[0102] In this embodiment, based on the current network level and the file segmentation strategy of the corresponding file grouping category, the number of segments of the 3D model file is accurately calculated according to the file size and the segment size in the segmentation strategy.

[0103] S5. Establish a file information library, which includes multiple files and their block information, as well as the file encoding, name, size, hash value, transmission time, integrity check result, network level, group category, abnormal events, and block information including sequence number, size, and hash value corresponding to each file information;

[0104] S51. Establish a document information database, determine the scope of the document information database, design the key information recording structure of the document information database, and plan key information;

[0105] In this embodiment, the multiple files contained in the file information library are clearly defined. The file information library records in detail the key information such as the file name, file number, file size, hash value and block information corresponding to each file. At the same time, the key information recording structure of the file information library is designed, and key information is planned for each type.

[0106] S52. Create a database table based on the key information record structure of the file information library, and record the key information of the file and the associated block information.

[0107] In this embodiment, according to the designed key information record structure, the MySQL relational database is selected to create a corresponding database table to store file information. At the same time, the relevant information of the file is recorded in the file information library according to the designed format and requirements.

[0108] S6. Based on the historical operation data and the safety control line method, the method for calculating the number of file blocks is revised, and accordingly, a method for incremental updating of file block transmission is constructed.

[0109] S61. Based on the modified formula for calculating the number of file blocks, obtain the current number of file blocks. In this embodiment, the specific process is as follows:

[0110] S611: Obtain the latest ten historical operation data and extract key information related to the block strategy;

[0111] In this embodiment, key information records including transmission time, data integrity check results, and block strategy are extracted from the latest ten historical operation data that are consistent with the current network level and BIM file grouping category.

[0112] S612: Determine the superiority of the block strategy based on historical operation data and the safety control line method;

[0113] In this embodiment, the safety control line is the file transfer time corresponding to the network-level dynamic block strategy. If the average transfer time of the last ten historical running data is lower than the safety control line and the data integrity reaches or exceeds 99.9%, the block strategy can be judged to have good transmission efficiency and high superiority. Otherwise, the block strategy can be judged to have defects and low superiority.

[0114] S613: Construct a method for calculating the number of file blocks based on historical operation data and the safety control line method. The details are as follows:

[0115] If the block strategy is judged to be superior, it will remain as it is;

[0116] If the block strategy is judged to have low superiority and the network level is excellent or good, the block size in the block strategy is doubled;

[0117] If the block strategy is judged to be less superior and the network level is poor, the block size in the block strategy is reduced to half of the original size;

[0118] S614: Calculate the number of blocks of the current 3D model file based on the file block strategy.

[0119] In this embodiment, based on historical operation data and the safety control line method, the number of blocks of the three-dimensional model file is accurately calculated according to the revised method for calculating the number of file blocks.

[0120] If it is a new file, the current number of file blocks is obtained based on the revised file block number calculation formula;

[0121] If it is an old file, the current file block number and the hash value of the corresponding block are obtained based on the current file record information in the file information library.

[0122] S62: Process the file blocks according to the current number of file blocks, and update the current file increment to the file server; in this embodiment, the details are as follows:

[0123] If it is a new file, the file will be divided into blocks according to the current number of file blocks, and the block files will be uploaded to the file storage service concurrently using the network file stream, and the file and block information will be recorded in the file information library.

[0124] If it is an old file, the file will be divided into blocks according to the current number of file blocks, and the difference will be compared with the block hash value returned by the server. The difference block files will be uploaded to the file storage service concurrently using the network file stream.

[0125] S63: Merge the divided files and perform a difference check between the hash value of the merged file and the hash value of the current file;

[0126] In this embodiment, the block files successfully uploaded to the file storage service are merged according to the block sequence information and association rules. During the merging process, the hash value of the file is calculated using a hash algorithm and compared with the current file hash value for verification.

[0127] S64. Construct a block-by-block incremental retransmission mechanism for the 3D model file based on the hash verification result.

[0128] In this embodiment, if the hash check fails and the number of retransmissions is less than a preset value, the 3D model block file is re-uploaded. If the hash value difference is small, the block file hash values ​​are compared and the different blocks are retransmitted. If the hash value difference is large, all blocks of the file are retransmitted. Finally, the number of retransmissions, time, and block information involved are recorded in the file information library.

[0129] Example 1: Application of the three-dimensional fuzzy classification evaluation magic cube model method

[0130] In a certain pumped storage project, the collaborative update of BIM files of multiple disciplines such as architecture, electrical, and water machines is involved. The traditional method only classifies and transmits files according to file type (such as *.rvt, *.dgn), which leads to low efficiency of complex electromechanical models due to the single transmission strategy. The present invention uses a three-dimensional fuzzy classification model to comprehensively consider the three dimensions of file size, format, and whether it is compressed, and subdivides BIM files into 20 categories. For example, for a 1M small model, overall transmission is adopted; for a 5G super-large model, a block check priority transmission method is adopted. After implementation, the accuracy of project file classification has been significantly improved, and the efficiency of large file transmission has been greatly improved.

[0131] Example 2: Dynamically adjust the blocks based on the six elements of network status

[0132] In a certain pumped storage project, the construction site transfers BIM files via wireless network and cloud services. When network monitoring shows bandwidth fluctuations (8Mbps→2Mbps) and an increase in packet loss rate (0.5%→3%), the system automatically adjusts the original 10MB block size to 3MB based on the six-factor judgment method and adds redundant check blocks. Compared with the traditional fixed block solution, under the same network conditions, the present invention significantly improves the file transfer success rate and greatly improves the efficiency of large file transfers. After the network becomes stable again, the system automatically resumes large block transmission, balancing efficiency and reliability.

[0133] Example 3: Hash value verification to ensure data integrity

[0134] In a pumped storage project, when designers transmitted a BIM file containing design changes to a cloud service, the system calculated a SHA-256 hash value for each 5MB block. During transmission, a network failure caused data corruption in two blocks. Upon verification, the receiving end discovered a mismatch in the hash values ​​and immediately requested retransmission of these two blocks. Traditional transmission methods, lacking block-by-block verification, require retransmission of the entire 150MB file. While ensuring data integrity, the solution presented in this invention reduces the amount of retransmitted data by 98.7%, significantly improving transmission efficiency and reliability.

[0135] Example 4: Self-optimizing block strategy based on historical data

[0136] In a pumped-storage project, designers used this system to transfer BIM files to a cloud service over 2,000 times. Analyzing historical data, the system discovered that during the peak network hour of 10:00 AM, adjusting the block size from the default 8MB to 6MB significantly improved the transfer success rate. Based on this, the system automatically optimized the block size algorithm, significantly improving the subsequent transfer success rate during the same time period compared to the initial strategy. This self-correcting capability enables the system to continuously optimize over time, making it particularly suitable for long-term, complex project environments.

[0137] It can be seen from the above examples that the present invention, through its multi-dimensional innovative design, is significantly superior to existing technologies in terms of file classification accuracy, network adaptability, data integrity and self-optimization capabilities, effectively meeting the core requirements of efficient and reliable transmission of BIM files in modern engineering construction.

[0138] The present invention also provides a BIM file incremental transmission and update system based on self-correcting dynamic block division, comprising the following modules:

[0139] A three-dimensional fuzzy classification and evaluation Rubik's Cube model construction module is used to construct a three-dimensional fuzzy classification and evaluation Rubik's Cube model method based on fuzzy evaluation of BIM file categories based on three factors: file size, file format, and compression;

[0140] A module for constructing a method for determining the critical quality of six network status factors, which is based on the six factors of download bandwidth, upload bandwidth, bandwidth utilization, RTT (round-trip time), packet loss rate, and jitter, to construct a method for determining the critical quality of six network status factors based on the six-factor good / bad critical standard.

[0141] A dynamic block strategy construction module is used to classify model files and construct a dynamic block strategy based on the network level based on the optimal block strategy that can be supported by the transmission of each category of model files;

[0142] A module for calculating the number of file blocks is built, based on a critical judgment method for the six elements of network status and a three-dimensional fuzzy classification evaluation Rubik's Cube model, as well as a dynamic block strategy based on network level.

[0143] A file information library establishment module is used to establish a file information library including multiple files and block information;

[0144] The file block transmission incremental update method construction module amends the file block number calculation method based on historical operation data and the security control line method, and constructs the file block transmission incremental update method accordingly.

[0145] The present invention also provides an electronic device, which includes a processor, a communication interface, a memory and a communication bus. The processor, the communication interface and the memory communicate with each other via the communication bus.

[0146] Memory, memory is used to store computer programs;

[0147] The processor is used to execute the computer program stored in the memory to implement the steps of the self-correcting dynamic block-based BIM file incremental transmission and update method as described above.

[0148] The present invention also provides a non-transitory readable storage medium and a non-volatile storage medium, in which an executable program is stored. When the executable program is executed by a processor, the steps of the incremental transmission and update method of the self-correcting dynamic block BIM file as described above are implemented.

[0149] Thus far, the technical solutions of the present invention have been described in conjunction with the specific experimental processes shown in the accompanying drawings. However, the scope of protection of the present invention is not limited to these specific embodiments. Without departing from the principles of the present invention, those skilled in the art may make equivalent changes or substitutions to the relevant technical features, and the technical solutions after such changes or substitutions will fall within the scope of protection of the present invention.

Claims

1. A method for incremental transmission and updating of BIM files based on self-correcting dynamic block partitioning, characterized in that: The steps include: S1. Construct a three-dimensional fuzzy classification and evaluation cube model method for BIM file categories based on the three factors of file size, file format and compression; S2. Construct a six-factor network status critical judgment method based on the six-factor good / bad critical standard based on the six factors of download bandwidth, upload bandwidth, bandwidth utilization, RTT, packet loss rate, and jitter; S3. Classify the model files and build a dynamic block strategy based on the network level based on the optimal block strategy that can be supported for the transmission of each category of model files; S4. A method for calculating the number of file blocks based on a critical judgment method for the six elements of network status and a three-dimensional fuzzy classification evaluation Rubik's Cube model, as well as a dynamic block strategy based on network level; S5. Establish a file information library, which includes multiple files and their block information, as well as the file code, name, size, hash value, transmission time, integrity check result, network level, group type, abnormal events, and block information including sequence number, size, and hash value corresponding to each file information; S6. Based on the historical operation data and the safety control line method, the method for calculating the number of file blocks is revised, and accordingly, a method for incremental updating of file block transmission is constructed.

2. The method according to claim 1, wherein: Step S1 also includes the following sub-steps: S11. Determine the domain of three factors: file size, file format, and whether to compress; S12, determining a fuzzy set of three factors: file size, file format, and whether to compress; S13. Construct a three-dimensional fuzzy classification evaluation Rubik's Cube model method based on the comprehensive membership calculation formula of three factors: file size, file format and compression.

3. The method according to claim 1, wherein: Step S2 also includes the following sub-steps: S21. Determine the good / bad critical standards for six factors: download bandwidth, upload bandwidth, bandwidth utilization, RTT, packet loss rate, and jitter; S22. Construct a critical judgment method for the six factors of network status based on the six-factor good and bad critical standards of download bandwidth, upload bandwidth, bandwidth utilization, RTT, packet loss rate and jitter.

4. The method according to claim 1, wherein: Step S3 also includes the following sub-steps: S31. Classify twenty groups of files according to the three-dimensional fuzzy classification method to evaluate the magic cube model and prepare sample data for the three-dimensional model file block transmission experiment; S32. Based on experimental data, historical operation data and expert experience data, the optimal block partitioning strategy that can be supported under the good and bad levels of network status is obtained.

5. The method according to claim 1, wherein: Step S4 also includes the following sub-steps: S41. Obtain the current network status based on the critical judgment method of the six elements of the network status; S42. Determine the grouping category of the three-dimensional model file based on the three-dimensional fuzzy classification and evaluation method of the magic cube model; S43. A dynamic block strategy based on the network level is used to obtain a file block strategy for the current network level and the corresponding BIM file grouping category; S44. Based on the file segmentation strategy, calculate the number of segments of the current 3D model file.

6. The method according to claim 1, wherein: Step S5 also includes the following sub-steps: S51. Establish a document information database, determine the scope of the document information database, design the key information recording structure of the document information database, and plan key information; S52. Create a database table based on the key information record structure of the file information library, and record the key information of the file and the associated block information.

7. The method according to claim 1, wherein: Step S6 also includes the following sub-steps: S61. Obtain the current number of file blocks based on the modified file block number calculation formula; S62, processing the file blocks according to the current number of file blocks, and updating the current file increment to the file server; S63: Merge the divided files and perform a difference check between the hash value of the merged file and the hash value of the current file; S64. Construct a block-by-block incremental retransmission mechanism for the 3D model file based on the hash verification result.

8. A BIM file incremental transmission and update system based on self-correcting dynamic block, characterized by: Includes the following modules: A three-dimensional fuzzy classification and evaluation Rubik's Cube model construction module is used to construct a three-dimensional fuzzy classification and evaluation Rubik's Cube model method based on fuzzy evaluation of BIM file categories based on three factors: file size, file format, and compression; A module for constructing a method for determining the critical quality of six network status factors: this module is used to construct a method for determining the critical quality of six network status factors based on a six-factor good / bad critical standard, based on the six factors of download bandwidth, upload bandwidth, bandwidth utilization, RTT, packet loss rate, and jitter. A dynamic block strategy construction module is used to classify model files and construct a dynamic block strategy based on the network level based on the optimal block strategy that can be supported by the transmission of each category of model files; A module for calculating the number of file blocks is built, based on a critical judgment method for the six elements of network status and a three-dimensional fuzzy classification evaluation Rubik's Cube model, as well as a dynamic block strategy based on network level. A file information library establishment module is used to establish a file information library including multiple files and block information; The file block transmission incremental update method construction module amends the file block number calculation method based on historical operation data and the security control line method, and constructs the file block transmission incremental update method accordingly.

9. An electronic device comprising a processor, a communication interface, a memory, and a communication bus, wherein the processor, the communication interface, and the memory communicate with each other via the communication bus, wherein: a memory for storing a computer program; A processor, the processor being configured to execute a computer program stored in a memory to implement the steps of the method for incremental transmission and updating of BIM files based on self-correcting dynamic block partitioning as described in any one of claims 1 to 6.

10. A non-volatile storage medium, characterized in that: The non-volatile storage medium stores an executable program, and when the executable program is executed by the processor, it implements the steps of the incremental transmission and update method of the self-correcting dynamic block BIM file according to any one of claims 1 to 7.

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