Railway precast beam full-period digital delivery and disease tracing method and system

Abstract

The invention discloses a railway precast beam full-period digital delivery and disease tracing method and system, and the method comprises the following steps: S1, collecting and sorting precast beam data, and building an IFC entity model based on the data; s2, pre-burying a two-dimensional code plate and an RFID tag on the precast beam, and recording the digital identity of the precast beam; s3, obtaining the completion coordinate of the precast beam, and binding the digital identity of the precast beam with the completion coordinate at one time; s4, performing block chain evidence storage on the application data of the precast beam; s5, developing a front-end APP, and judging whether the precast beam meets a traceability condition or not; s6, all data of the precast beam meeting the traceability condition are called, and root cause judgment is conducted based on the IFC entity model. According to the method, by establishing the IFC standard data link which runs through design-production-operation and maintenance, data barriers of links of design, production and operation and maintenance can be broken through, data run-through is achieved, data islands are avoided, and comparison time consumption is greatly shortened.

Description

Technical Field

[0001] This invention relates to the field of railway precast beam management technology, specifically a method and system for full-cycle digital delivery and defect tracing of railway precast beams. Background Technology

[0002] The railway precast beam defect tracing system is a system that utilizes modern information technology to monitor, diagnose, and trace potential defects in railway precast beams during production, transportation, installation, and subsequent operation. The system aims to ensure the safety and reliability of railway bridges, promptly detect and address defects, and extend the service life of the bridges. However, traditional railway precast beam defect tracing systems still have the following problems: 1. Data silos: Design, production, and operation and maintenance data are scattered across independent systems such as Revit / Tekla / MES (with incompatible formats). Tracing the source of beam defects requires manual comparison of data from multiple platforms, which takes an average of 3-5 days.

[0003] 2. Information gap: Traditional BIM models lack key parameters of the production process (such as pouring temperature and tension deviation), resulting in 75% of defects being unable to be linked to their root causes. 3. Difficulty in determining responsibility: Paper records are easily altered, and only 68% of quality problems can be accurately traced back to the responsible party; 4. Lack of standards: There is no unified IFC extension specification for railway beam-specific attributes (such as the anti-arch control value L / 3000), and the model reuse rate is less than 40%.

[0004] To address these issues, this invention provides a method and system for full-cycle digital delivery and defect tracing of precast railway beams. Summary of the Invention

[0005] To address the shortcomings of existing technologies, this invention provides a method and system for full-cycle digital delivery and defect tracing of precast railway beams, solving the aforementioned problems.

[0006] To achieve the above objectives, the present invention provides a method for full-cycle digital delivery and defect tracing of precast railway beams, comprising the following steps: S1. Collect and organize precast beam data, and build an IFC solid model based on the data; S2, embed QR code panels and RFID tags on the precast beams to record the digital identity of the precast beams; S3, obtain the as-built coordinates of the precast beam, and bind the digital identity of the precast beam to the as-built coordinates in one go; S4, the application data of the precast beams will be stored on the blockchain for evidence; S5, develop a front-end APP to determine whether the precast beams meet the traceability conditions; S6: Retrieve all data of precast beams that meet the traceability conditions, and determine the root cause based on the IFC solid model to identify the responsible party; S7 generates a traceability report.

[0007] Preferably, the step of storing the application data of the precast beams on the blockchain is as follows: S1 generates hash values ​​from the casting temperature, tensioning records, steam curing curve, digital identity, and as-built coordinates of the precast beam; S2 uses the Hyperledger Fabric blockchain for on-chain evidence storage; S3 establishes a BIM database and synchronizes the data from S2 to the BIM database to form a unified data foundation.

[0008] Preferably, the step of storing the application data of the precast beams on the blockchain is as follows: S1 generates hash values ​​from the casting temperature, tensioning records, steam curing curve, digital identity, and as-built coordinates of the precast beam; S2 uses the Hyperledger Fabric blockchain for on-chain evidence storage; S3 establishes a BIM database and synchronizes the data from S2 to the BIM database to form a unified data foundation.

[0009] Preferably, the step of determining whether the precast beam meets the traceability conditions is as follows: S1. Scan the QR code of the precast beam to obtain its digital identity and correspond it to the IFC entity model; S2. Compare the coordinates of the IFC physical model and the on-site RFID tag coordinates to determine if there is a coordinate deviation. S3, if there is a deviation in the coordinates, output a misalignment warning and re-verify after rectification; if there is no deviation in the coordinates, the traceability condition is met.

[0010] Preferably, the root cause determination steps are as follows: S1, make a preliminary judgment on the cause of the disease based on the crack diagnosis rules; S2, based on a digital model, prioritizes and predicts the importance of precast beam features; S3 verifies S1 and S2, derives the root cause determination results, and optimizes the digital model based on the data to prevent similar problems.

[0011] Preferably, the source tracing report includes: location of the disease, cause analysis, determination of the responsible party, and recommended measures.

[0012] A full-cycle digital delivery and defect tracing system for precast railway beams includes: The data processing unit is used to process and transform the data of the precast beams; The IFC entity model is built based on a data processing unit and is used to provide a digital twin root node. Memory, used to store IFC entity models; The traceability module is used to scan the QR codes on the surface of precast beams and determine the causes of defects and the responsible parties based on the IFC solid model. Preferably, the data processing unit includes: The IFC parsing engine is used to convert precast beam data into a unified IFC4.3 format; A blockchain-based evidence storage engine is used to generate hash values ​​from key process data to assist in subsequent accountability. The BIM database is used to synchronize precast beam data, forming a unified data foundation.

[0013] Preferably, the traceability module includes: A scanning module is used to scan the QR code on the precast beam to obtain precast beam information; The coordinate comparison module is used to compare the as-built coordinates of the precast beams with the coordinates on the IFC solid model to determine whether there is a deviation in the coordinates. The scheduling module is used to output a misalignment warning command when there is a coordinate deviation, and to output a tracing command when the coordinates are accurate. The data retrieval module is used to retrieve data from the entire process of design, production, and construction of the precast beam based on the traceability quality. The root cause analysis module is used to separate and determine the precast beams; The source tracing report output module is used to output a source tracing report that includes the location of the disease, cause analysis, determination of the responsible party, and recommended measures.

[0014] Preferably, the root cause analysis module includes: A rule base is used to make preliminary judgments based on crack diagnosis rules; The XGBoost model is used to rank and predict the importance of precast beams based on their characteristics.

[0015] Beneficial effects This invention provides a method and system for full-cycle digital delivery and defect tracing of precast railway beams. Compared with existing technologies, it has the following advantages: (1) The full-cycle digital delivery and defect tracing method and system for railway precast beams, by establishing an IFC standard data chain that connects design, production and operation, can break down the data barriers between design, production and operation, achieve data connectivity, avoid data silos, and greatly shorten the comparison time.

[0016] (2) The method and system for full-cycle digital delivery and defect tracing of railway precast beams generates hash values ​​for key process data to ensure that the data is tamper-proof, thereby enabling accurate tracing of the responsible party.

[0017] This method and system for full-cycle digital delivery and defect tracing of precast railway beams defines a unique attribute set for railway beams, unifies the IFC extended specifications, covers 20+ process parameters, and achieves precise positioning of precast beams in both time and space, effectively improving the overall reuse rate. Attached Figure Description

[0018] Figure 1 This is a flowchart of the entire invention; Figure 2 This is a traceability flowchart of the present invention. Detailed Implementation

[0019] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0020] Example 1: Please see Figure 1-2 A method for full-cycle digital delivery and defect tracing of precast railway beams, comprising the following steps: S1. Collect and organize precast beam data, and build an IFC solid model based on the data; S2, embed QR code panels and RFID tags on the precast beams to record the digital identity of the precast beams; S3, obtain the as-built coordinates of the precast beam, and bind the digital identity of the precast beam to the as-built coordinates in one go; S4, the application data of the precast beams will be stored on the blockchain for evidence; S5, develop a front-end APP to determine whether the precast beams meet the traceability conditions; S6: Retrieve all data of precast beams that meet the traceability conditions, and determine the root cause based on the IFC solid model to identify the responsible party; S7, generate a traceability report; In summary, the above steps form a closed-loop process of "data integration + intelligent analysis + reliable evidence storage + rapid response," enabling the standardization, intelligence, reliability, and efficiency of full-cycle digital delivery and defect tracing of railway precast beams.

[0021] The more detailed steps for collecting and organizing the core data of precast beams are as follows: S1 extracts design, production, and construction data from Revit, Tekla, and MES systems; S2 converts design, production, and construction data into the IFC4.3 standard; S3 defines a dedicated entity class IfcRailBeam for precast beams and extends its attribute set; For example, the timeline perspective is shown in the table below:

[0022] For example, the technical chart perspective is shown in the table below:

[0023] In summary, the above data is then mapped to IfcRailBeam, expanding the attribute set as shown in the table below:

[0024] Next, the geometry and properties are assembled, following these steps: First step, copy the original IfcBeam geometry → create a new entity IfcRailBeam; The second step is to attach all properties of IfcRailBeam, the extended property set, to Pset_Production, Pset_Transport, and Pset_4DContext; The third step is to assign a unique GlobalID to the entire beam to form a digital identity, which will be recognized by subsequent scanning, blockchain, and AI. Finally, an integrity check is performed. If one of the 20 mandatory attributes is missing, an error is reported and uploading is prohibited. At the same time, the final IFC file is SHA-256 encoded and prepared for blockchain storage. In summary, by transforming all fragmented information into a standard IFC4.3 digital twin beam file, a unique, complete, and machine-readable data matrix can be provided for subsequent blockchain evidence storage, AI traceability, and coordinate comparison. More detailed steps for storing the application data of precast beams on the blockchain are as follows: S1 generates hash values ​​from the casting temperature, tensioning records, steam curing curve, digital identity, and as-built coordinates of the precast beam; S2 uses the Hyperledger Fabric blockchain for on-chain evidence storage; S3: Establish a BIM database and synchronize the data in S2 to the BIM database to form a unified data foundation; In summary, after scanning the code, the backend automatically queries the blockchain and retrieves the original data of the precast beam. Then, it recalculates the hash and compares it with the original text in the database. If they match, it means that the data has not been tampered with. If they do not match, the original text has been modified and is rejected from subsequent root cause analysis. In more detail, the steps to determine whether a precast beam meets the traceability criteria are as follows: S1. Scan the QR code of the precast beam to obtain its digital identity and correspond it to the IFC entity model; S2. Compare the coordinates of the IFC physical model and the on-site RFID tag coordinates to determine if there is a coordinate deviation. S3, if there is a deviation in the coordinates, output a misalignment warning and re-verify after rectification; if there is no deviation in the coordinates, the traceability condition is met. In summary, the formula for determining whether there is a deviation in the coordinates is as follows: ; Wherein: Due to longitude difference, Due to latitude difference, This is the difference in elevation. Understandable. In the latitudinal direction, the length of the Earth's meridian is approximately 40008 km → 1° ≈ 40008 km / 360 = 111.13 km, which is independent of longitude and has an error of <0.1%. In the longitude direction, 1° of longitude at the equator corresponds to an arc length of ≈111.32km; at 39°N, scaling by cos(39°) → 111.32×cos(39°)≈86.6km.

[0025] However, for a single precast railway beam segment less than 100m, a difference of 0.0001° is approximately 8.6m (11.1m at the equator). Using a uniform estimate based on 111km, the deviation is less than 2.5m, which is sufficient to trigger an "installation misalignment" warning. The more detailed steps for root cause determination are as follows: S1, make a preliminary judgment on the cause of the disease based on the crack diagnosis rules; S2, based on a digital model, prioritizes and predicts the importance of precast beam features; S3 verifies S1 and S2, obtains the root cause determination results, and optimizes the digital model based on the data to prevent similar problems; In summary, crack diagnosis is implemented based on a rule base containing over 200 crack diagnosis rules. The digital model is the XGBoost machine learning model, which is based on an ensemble learning algorithm using decision trees. It iteratively trains a series of decision trees, with each tree attempting to correct the errors of the previous tree. This process is accomplished by minimizing a loss function. A more detailed source tracing report includes: location of the disease, cause analysis, determination of the responsible party, and recommended measures; Specific examples: Source of web diagonal cracks: a. Scan the QR code on the corresponding precast beam to obtain the beam's digital identity; b. Retrieve the production data of the precast beam, such as: pouring temperature 32.5℃ (specification ≤30℃), tension holding time less than 80%, crack location, 31% span from the beam end; c. Root cause determination: The crack is located at 31% span from the beam end. The pouring temperature was 32.5℃, exceeding the standard by 30℃. The steam curing heating rate was 6.2℃ / h, exceeding the standard by 5℃ / h. Based on the rule base and machine learning, the main cause is determined to be temperature stress (confidence level 80%). The responsible party is the production department. d. Report generation time.

[0026] In summary, taking the Beijing-Xiong'an Intercity Railway as an example, this embodiment and the defect tracing system have the following advantages over traditional methods in terms of defect location time, accuracy of responsibility determination, maintenance costs, and prevention rate of similar problems:

[0027] As shown in the table above, the quality of the precast railway beams in this project has been significantly improved, mainly in the following two aspects: (1) The rework rate was reduced from 18% to 5% (saving RMB 2.3 million annually); (2) The pass rate of beams leaving the factory reached 99.97% (the highest level in the industry).

[0028] In summary, by defining a dedicated attribute set for railway beams (Pset_RailBeam) covering 20+ process parameters and establishing an IFC standard data chain connecting design, production, and operation and maintenance, it is possible to accurately trace the source of defects within 10 minutes. At the same time, by storing key data through blockchain, it is possible to ensure traceability of responsibility.

[0029] Example 2: This embodiment, based on Embodiment 1, provides a full-cycle digital delivery and defect tracing system for precast railway beams, including: The data processing unit is used to process and transform the data of the precast beams; The IFC entity model is built upon data processing units and is used to provide digital twin root nodes. Memory, used to store IFC entity models; The traceability module is used to scan the QR code on the surface of the precast beam and determine the cause of the defect and the responsible party based on the IFC solid model; More specifically, the data processing units include: The IFC parsing engine is used to convert precast beam data into a unified IFC4.3 format; A blockchain-based evidence storage engine is used to generate hash values ​​from key process data to assist in subsequent accountability. The BIM database is used to synchronize precast beam data and form a unified data foundation. More specifically, the traceability module includes: The scanning module is used to scan the QR code on the precast beam to obtain the precast beam information; The coordinate comparison module is used to compare the as-built coordinates of the precast beams with the coordinates on the IFC solid model to determine whether there is a deviation in the coordinates. The scheduling module is used to output a misalignment warning command when there is a coordinate deviation, and to output a tracing command when the coordinates are accurate. The data retrieval module is used to retrieve data from the entire process of design, production, and construction of the precast beam based on the traceability quality. The root cause analysis module is used to separate and determine the precast beams; The source tracing report output module is used to output a source tracing report that includes the location of the disease, cause analysis, determination of the responsible party, and recommended measures; More specifically, the root cause analysis module includes: A rule base is used to make preliminary judgments based on crack diagnosis rules; The XGBoost model is used to rank and predict the importance of precast beams based on their characteristics.

[0030] Furthermore, any content not described in detail in this specification is existing technology known to those skilled in the art.

[0031] It should be noted that, in this document, relational terms such as "first" and "second" are used only to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such process, method, article, or apparatus.

[0032] Although embodiments of the invention have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and alterations can be made to these embodiments without departing from the principles and spirit of the invention, the scope of which is defined by the appended claims and their equivalents.

Claims

1. A method for full-cycle digital delivery and defect tracing of precast railway beams, characterized in that: The steps are as follows: S1. Collect and organize precast beam data, and build an IFC solid model based on the data; S2, embed QR code panels and RFID tags on the precast beams to record the digital identity of the precast beams; S3, obtain the as-built coordinates of the precast beam, and bind the digital identity of the precast beam to the as-built coordinates in one go; S4, the application data of the precast beams will be stored on the blockchain for evidence; S5, develop a front-end APP to determine whether the precast beams meet the traceability conditions; S6: Retrieve all data of precast beams that meet the traceability conditions, and determine the root cause based on the IFC solid model to identify the responsible party; S7 generates a traceability report.

2. The method for full-cycle digital delivery and defect tracing of precast railway beams according to claim 1, characterized in that: The steps for collecting and organizing the core data of the precast beams are as follows: S1 extracts design, production, and construction data from Revit, Tekla, and MES systems; S2 converts design, production, and construction data into the IFC4.3 standard; S3 defines a dedicated entity class IfcRailBeam for precast beams and extends its attribute set.

3. The method for full-cycle digital delivery and defect tracing of precast railway beams according to claim 1, characterized in that: The steps for storing the application data of the precast beams on the blockchain are as follows: S1 generates hash values ​​from the casting temperature, tensioning records, steam curing curve, digital identity, and as-built coordinates of the precast beam; S2 uses the Hyperledger Fabric blockchain for on-chain evidence storage; S3 establishes a BIM database and synchronizes the data from S2 to the BIM database to form a unified data foundation.

4. The method for full-cycle digital delivery and defect tracing of precast railway beams according to claim 1, characterized in that: The steps for determining whether a precast beam meets the traceability criteria are as follows: S1. Scan the QR code of the precast beam to obtain its digital identity and correspond it to the IFC entity model; S2. Compare the coordinates of the IFC physical model and the on-site RFID tag coordinates to determine if there is a coordinate deviation. S3, if there is a deviation in the coordinates, output a misalignment warning and re-verify after rectification; if there is no deviation in the coordinates, the traceability condition is met.

5. The method for full-cycle digital delivery and defect tracing of precast railway beams according to claim 1, characterized in that: The steps for determining the root cause are as follows: S1, make a preliminary judgment on the cause of the disease based on the crack diagnosis rules; S2, based on a digital model, prioritizes and predicts the importance of precast beam features; S3 verifies S1 and S2, derives the root cause determination results, and optimizes the digital model based on the data to prevent similar problems.

6. The method for full-cycle digital delivery and defect tracing of precast railway beams according to claim 1, characterized in that: The source tracing report includes: location of the disease, cause analysis, determination of the responsible party, and recommended measures.

7. A full-cycle digital delivery and defect tracing system for precast railway beams, characterized in that: include: The data processing unit is used to process and transform the data of the precast beams; The IFC entity model is built based on a data processing unit and is used to provide a digital twin root node. Memory, used to store IFC entity models; The traceability module is used to scan the QR code on the surface of the precast beam and determine the cause of the defect and the responsible party based on the IFC solid model.

8. The full-cycle digital delivery and defect tracing system for precast railway beams according to claim 7, characterized in that: The data processing unit includes: The IFC parsing engine is used to convert precast beam data into a unified IFC 4.3 format; A blockchain-based evidence storage engine is used to generate hash values ​​from key process data to assist in subsequent accountability. The BIM database is used to synchronize precast beam data, forming a unified data foundation.

9. A full-cycle digital delivery and defect tracing system for precast railway beams according to claim 7, characterized in that: The traceability module includes: A scanning module is used to scan the QR code on the precast beam to obtain precast beam information; The coordinate comparison module is used to compare the as-built coordinates of the precast beams with the coordinates on the IFC solid model to determine whether there is a deviation in the coordinates. The scheduling module is used to output a misalignment warning command when there is a coordinate deviation, and to output a tracing command when the coordinates are accurate. The data retrieval module is used to retrieve data from the entire process of design, production, and construction of the precast beam based on the traceability quality. The root cause analysis module is used to separate and determine the precast beams; The source tracing report output module is used to output a source tracing report that includes the location of the disease, cause analysis, determination of the responsible party, and recommended measures.

10. A full-cycle digital delivery and defect tracing system for precast railway beams according to claim 9, characterized in that: The root cause analysis module includes: A rule base is used to make preliminary judgments based on crack diagnosis rules; The XGBoost model is used to rank and predict the importance of precast beams based on their characteristics.

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