Method, computer equipment and medium for integrating information of steel bar raw materials for prefabricated components

Abstract

The present invention discloses a method, computer equipment, and medium for integrating information on steel bar raw materials for prefabricated components, belonging to the technical field of building management data processing, comprising: obtaining the steel bar batch number and mechanical and physical parameters of the steel bar raw materials to obtain raw data, entering the raw data parameters into a field mapping table to generate an initial data set; establishing a structured database having a relationship between the steel bar batch number and the mechanical and physical parameters based on the initial data set; calculating the steel bar configuration scheme in the BIM model based on the mechanical and physical parameters in the structured database; generating a configuration parameter table for the steel bar configuration scheme; and performing RFID association between the prefabricated component number and the steel bar batch number in the configuration parameter table to generate a digital production task order. The method for integrating information on steel bar raw materials for prefabricated components solves the problems of high input error rate, low efficiency, difficulty in information tracing, and deviation in matching between raw material information and design requirements in existing methods.

Description

Technical Field

[0001] The present invention relates to the technical field of building management data processing, and in particular to a method for integrating steel bar raw material information of prefabricated components, computer equipment and media. Background Art

[0002] As a core component of building industrialization, the production efficiency and quality control of prefabricated components are crucial to promoting the modernization of the construction industry. Rebar, the primary load-bearing material in prefabricated components, requires precise management and integration of its raw material information, which directly determines the mechanical properties and structural safety of the components. Currently, the collection and management of rebar raw material information primarily relies on manual recording or semi-automated systems. These methods suffer from high data entry error rates, low efficiency, and difficulty in information traceability. Especially in the production of complex components, deviations often occur between raw material information and design requirements, making quality control more difficult. Summary of the Invention

[0003] In order to overcome the defects of the prior art, the present invention provides a method for integrating steel bar raw material information of prefabricated components to solve the above problems.

[0004] The technical solution adopted by the present invention to solve the technical problem is: a method for integrating steel bar raw material information of prefabricated components, comprising the following steps:

[0005] S1: Obtain the steel bar batch number and mechanical and physical parameters of the steel bar raw material to obtain the original data, and enter the original data parameters into the field mapping table to generate the initial data set;

[0006] S2: establishing a structured database having a correspondence between steel bar batch numbers and mechanical and physical parameters based on the initial data set;

[0007] S3: Calculate the reinforcement configuration scheme in the BIM model based on the mechanical and physical parameters in the structured database; generate a configuration parameter table of prefabricated components and reinforcement for the reinforcement configuration scheme;

[0008] S4: The prefabricated component number and the steel bar batch number in the configuration parameter table are associated with RFID to generate a digital production task order.

[0009] Preferably, the mechanical and physical parameters include tensile strength, yield strength and diameter;

[0010] In the step S1, in the field mapping table, the steel bar batch number field is mapped to batch_id, the tensile strength field is mapped to tensile_strength, the yield strength field is mapped to yield_strength, and the diameter field is mapped to diameter;

[0011] The values ​​of the steel bar batch number, tensile strength, yield strength and diameter are extracted from the raw data and entered into a field mapping table to generate an initial data set.

[0012] Optionally, in step S1, a barcode scanning device is used to read a QR code on the steel bar raw material to obtain text data containing the steel bar batch number;

[0013] The tensile strength and yield strength of the steel bars are collected using a pressure sensor, and the diameter of the steel bars is collected using a laser rangefinder.

[0014] Specifically, in step S2, a B+ tree index algorithm is used to construct a joint index for the steel bar batch number, tensile strength, yield strength and diameter fields.

[0015] It is worth noting that in step S3, the volume parameters and load data of the prefabricated components are obtained through the API interface of the BIM model;

[0016] The parameter ranges of tensile strength, yield strength, and diameter suitable for the current volume parameters are obtained by table lookup. Based on the parameter ranges, the batch numbers of steel bars with tensile strength, yield strength, and diameter within the parameter ranges are obtained from a structured database using SQL query language. These steel bar batch numbers are combined into a number set.

[0017] According to the interval in which the load data of the prefabricated component is located, the consideration priorities of the three data parameters of tensile strength, yield strength and diameter corresponding to the interval are obtained, the data with the highest consideration priority is selected as the consideration basis, and the steel bar batch number with the highest consideration basis value is screened from the number set to form an association relationship set;

[0018] From the set of association relationships, an association relationship in which the ratio of the tensile strength to the volume parameter of the prefabricated component is greater than or equal to a preset tensile strength threshold and the ratio of the yield strength to the volume parameter of the prefabricated component is greater than or equal to the corresponding preset yield strength threshold is screened out as a reinforcement configuration scheme for the prefabricated component.

[0019] Preferably, in step S3, a configuration parameter table of prefabricated components and steel bars is generated for the steel bar configuration scheme, wherein the configuration parameter table includes the prefabricated component number, the steel bar batch number and the matching parameters; wherein the matching parameters include the tensile strength, yield strength and diameter parameters of the steel bars and the volume parameters of the prefabricated components.

[0020] Optionally, in step S4, the prefabricated component number and the steel bar batch number are obtained from the configuration parameter table;

[0021] Generate a unique identification code according to the preset RFID coding rules;

[0022] The unique identification code is embedded into the RFID tag of the corresponding steel bar batch by an RFID writing device, and then a digital association set is generated according to the prefabricated component number, the steel bar batch number and the RFID tag;

[0023] Extracting the prefabricated component number, steel bar batch number and RFID tag from the digital associated set to generate a digital production task order;

[0024] The digital production task order includes the prefabricated component number, the steel bar batch number, the RFID tag and matching parameters.

[0025] Specifically, in step S4, the preset RFID coding rule is to concatenate the prefabricated component number and the steel bar batch number.

[0026] A computer device includes a memory and a processor, wherein the memory stores a computer program, and the processor implements the above-mentioned method for integrating steel bar raw material information of prefabricated components when executing the computer program.

[0027] A computer-readable storage medium stores a computer program, which, when executed by a processor, implements the above-mentioned method for integrating steel bar raw material information of a prefabricated component.

[0028] The beneficial effects of the present invention are as follows: in the method for integrating steel bar raw material information for prefabricated components, by obtaining the batch number and mechanical parameters of the steel bar raw material, a structured database is established to achieve the correspondence between batch and performance, the steel bar configuration plan in the BIM model is calculated based on the database parameters, and the component code and the steel bar batch number are associated with RFID to generate a digital production task order. The present invention realizes digital management of the entire process from raw materials to production, reduces the error rate of data entry and improves data entry efficiency, and improves the traceability of steel bar raw material information, ensuring that the matching between raw material information and design requirements will not deviate. BRIEF DESCRIPTION OF THE DRAWINGS

[0029] Figure 1 Flowchart of a method for integrating steel bar raw material information of prefabricated components in one embodiment of the present invention;

[0030] Figure 2 A step-by-step flow chart of step S1 in one embodiment of the present invention;

[0031] Figure 3 A step-by-step flow chart of step S3 in one embodiment of the present invention;

[0032] Figure 4 FIG. 4 is a step-by-step flow chart of step S4 in one embodiment of the present invention. DETAILED DESCRIPTION

[0033] The following is a further description of specific embodiments of the present invention in conjunction with the accompanying drawings. It should be noted that the description of these embodiments is intended to facilitate understanding of the present invention and does not constitute a limitation of the present invention. In addition, the technical features involved in the various embodiments of the present invention described below may be combined with each other as long as they do not conflict with each other.

[0034] like Figure 1-4 As shown, a method for integrating steel bar raw material information of prefabricated components includes the following steps:

[0035] S1: Obtain the steel bar batch number and mechanical and physical parameters of the steel bar raw material to obtain the original data, and enter the original data parameters into the field mapping table to generate the initial data set;

[0036] S2: establishing a structured database having a correspondence between steel bar batch numbers and mechanical and physical parameters based on the initial data set;

[0037] S3: Determine the reinforcement configuration scheme in the BIM model based on the mechanical and physical parameters in the structured database; generate a configuration parameter table of prefabricated components and reinforcement for the reinforcement configuration scheme;

[0038] S4: The prefabricated component number and the steel bar batch number in the configuration parameter table are associated with RFID to generate a digital production task order.

[0039] In the described method for integrating rebar raw material information for prefabricated components, by obtaining the batch numbers and mechanical parameters of the rebar raw materials, a structured database is established to establish a correspondence between batches and performance. The rebar configuration plan in the BIM model is calculated based on the database parameters, and the component code and rebar batch number are linked via RFID to generate a digital production order. This method achieves digital management of the entire process from raw materials to production, reducing the error rate and improving data entry efficiency. It also enhances the traceability of rebar raw material information and ensures that the matching between raw material information and design requirements is not deviated.

[0040] It is worth noting that the mechanical and physical parameters include tensile strength, yield strength and diameter;

[0041] In the step S1, in the field mapping table, the steel bar batch number field is mapped to batch_id, the tensile strength field is mapped to tensile_strength, the yield strength field is mapped to yield_strength, and the diameter field is mapped to diameter;

[0042] The values ​​of the steel bar batch number, tensile strength, yield strength and diameter are extracted from the raw data and entered into a field mapping table to generate an initial data set.

[0043] In one embodiment, the original data is generated in JSON format and includes fields such as steel bar batch number, tensile strength, yield strength and diameter. For example, the JSON data is {"batch":"A12345","tensile":600,"yield":400,"diameter":20.05}. Through a preset template, the fields are mapped to standardized batch_id, tensile_strength, yield_strength and diameter. For example, "batch" is mapped to batch_id and "tensile" is mapped to tensile_strength. This mapping method unifies the data format and facilitates subsequent processing and storage. Extracted from the above JSON, batch_id is "A12345", tensile_strength is 600MPa, yield_strength is 400MPa, and diameter is 20.05mm; this extraction process is automatically completed through scripts, reducing manual intervention and improving data processing efficiency.

[0044] Optionally, in step S1, a barcode scanning device is used to read a QR code on the steel bar raw material to obtain text data containing the steel bar batch number;

[0045] The tensile strength and yield strength of the steel bars are collected using a pressure sensor, and the diameter of the steel bars is collected using a laser rangefinder.

[0046] Specifically, using a barcode scanner to read the QR code on the rebar raw material and obtain information such as the rebar batch number is an efficient data collection method. For example, the scanning device can be a handheld QR code scanner. It scans the QR code on the rebar packaging and obtains text data containing the rebar batch number, production date, and specifications. For example, the scan result is "Batch: A12345, Date: 2025-03-15, Spec: 20mm," where the rebar batch number "A12345" is extracted as a key field. This method has the advantages of being fast and accurate, avoiding manual input errors, and improving data collection efficiency. In one possible implementation, a pressure sensor is used to collect rebar mechanical parameters, such as tensile strength and yield strength. Specifically, a rebar sample is placed in a tensile testing machine, and the pressure sensor records the force changes during the tensile process in real time. For example, the tensile strength of a rebar sample is 600 MPa and the yield strength is 400 MPa. This data is directly transmitted to the data acquisition system via the sensor, ensuring the accuracy of the mechanical parameters. It should be noted that the high sensitivity of the pressure sensor can capture tiny mechanical changes, which helps to improve data reliability and provide a basis for subsequent quality analysis. Preferably, a laser rangefinder is used to collect physical parameters of steel bars, such as diameter. The laser rangefinder calculates the cross-sectional diameter of the steel bar by emitting a laser beam and measuring the reflection time. For example, the diameter of a certain steel bar is measured to be 20.05mm, with an accuracy of up to 0.01mm. This non-contact measurement method avoids the errors that may be caused by traditional caliper measurements and is particularly suitable for batch inspection scenarios. The efficiency and high precision of the laser rangefinder significantly improve the level of automation of physical parameter collection.

[0047] Preferably, in step S2, a B+ tree index algorithm is used to construct a joint index for the steel bar batch number, tensile strength, yield strength and diameter fields in the structured database.

[0048] Specifically, the B+ tree index algorithm constructs a joint index for the steel bar batch number, tensile strength, yield strength, and diameter fields. For example, in a steel bar inspection scenario, the steel bar batch number identifies the production batch, the tensile strength and yield strength reflect the material properties, and the diameter reflects the size of the material. The joint index combines these fields to generate an index mapping table. For example, when querying records with a tensile strength greater than 800MPa in a batch, the B+ tree index can quickly locate the target data and avoid a full table scan. Preferably, the joint index also supports range queries, such as querying records with a yield strength between 400-600MPa.

[0049] It is worth noting that in step S3, the volume parameters and load data of the prefabricated components are obtained through the API interface of the BIM model;

[0050] The parameter ranges of tensile strength, yield strength, and diameter suitable for the current volume parameters are obtained by table lookup. Based on the parameter ranges, the batch numbers of steel bars with tensile strength, yield strength, and diameter within the parameter ranges are obtained from a structured database using SQL query language. These steel bar batch numbers are combined into a number set.

[0051] According to the interval in which the load data of the prefabricated component is located, the consideration priorities of the three data parameters of tensile strength, yield strength and diameter corresponding to the interval are obtained, the data with the highest consideration priority is selected as the consideration basis, and the steel bar batch number with the highest consideration basis value is screened from the number set to form an association relationship set;

[0052] From the set of association relationships, an association relationship in which the ratio of the tensile strength to the volume parameter of the prefabricated component is greater than or equal to a preset tensile strength threshold and the ratio of the yield strength to the volume parameter of the prefabricated component is greater than or equal to the corresponding preset yield strength threshold is screened out as a reinforcement configuration scheme for the prefabricated component.

[0053] In one possible implementation, the geometric and load data of prefabricated components are obtained through the API interface of the BIM model. For example, the volume of a beam component is extracted as 0.5 cubic meters and the load is 100 kN using the Revit API interface.

[0054] When using the SQL query language to extract data from a structured database, the range of tensile strength, yield strength and diameter parameters suitable for the current volume parameters is obtained based on a table lookup, and records that meet the conditions can be quickly located. In this embodiment, the table queried records the parameter ranges of tensile strength, yield strength and diameter corresponding to different volume parameter ranges. When these parameter ranges are met, it can be ensured that the prefabricated components meet the requirements of building production. For example, tensile strength greater than 800MPa, yield strength greater than 400MPa and diameter between 12-20mm are suitable for components with a volume greater than 0.4 cubic meters. For prefabricated components with a volume of 0.5 cubic meters, the parameter ranges obtained based on a table lookup are tensile strength greater than 800MPa, yield strength greater than 400MPa and diameter between 12-20mm. The query returns a record of steel bars containing batch number A001, with a tensile strength of 850MPa, a yield strength of 420MPa and a diameter of 16mm. It should be noted that the SQL query implements conditional filtering through the WHERE clause, combines indexes to optimize query efficiency, and ensures that results are returned quickly. This method facilitates the extraction of specific parameter sets from large-scale data.

[0055] In one embodiment, the matching process considers the load data of the prefabricated components. For example, the data with the highest consideration priority for the prefabricated components with a load data interval of [80kN, 100kN] is the yield strength; for another example, the data with the highest consideration priority for the prefabricated components with a load data interval of [60kN, 80kN] is the tensile strength; and for another example, the data with the highest consideration priority for the prefabricated components with a load data interval of [40kN, 60kN] is the diameter; in the case where the data with the highest consideration priority is the yield strength, among all the steel bar batch numbers that meet the parameter range, the batch of steel bars with the highest yield strength will be given priority to generate an association relationship set.

[0056] It's understood that the association set must meet tensile strength and yield strength thresholds. For example, the preset tensile strength threshold requires the ratio of tensile strength to prefabricated component volume to be greater than 1600 MPa / m³. The ratio of the tensile strength of the steel bars in batch A001 to 0.5 cubic meters of prefabricated components is 1700 MPa / m³. If these conditions are met, the association is determined to be valid and used as the reinforcement configuration plan for the prefabricated components.

[0057] Preferably, in step S3, a configuration parameter table of prefabricated components and steel bars is generated for the steel bar configuration scheme, wherein the configuration parameter table includes the prefabricated component number, the steel bar batch number and the matching parameters; wherein the matching parameters include the tensile strength, yield strength and diameter parameters of the steel bars and the volume parameters of the prefabricated components.

[0058] For example, the generated configuration parameter table contains fields such as prefabricated component B001, steel bar batch number A001, and tensile strength 850MPa. This tabular output clearly presents the matching results, making it convenient for designers to refer to. In one embodiment, the configuration parameter table can also be expanded to support multiple prefabricated component scenarios. For example, for a group of prefabricated components, steel bars from batches A001 and A002 are matched respectively, and a configuration table containing multiple records is generated, each of which clearly defines the correspondence between prefabricated components and steel bars. This expansion solution enriches the flexibility of configuration and adapts to complex building design requirements.

[0059] Specifically, in step S4, a prefabricated component number and a steel bar batch number are obtained from the configuration parameter table, where the prefabricated component number and the steel bar batch number respectively identify the prefabricated component and the steel bar batch;

[0060] Generate a unique identification code according to the preset RFID coding rules;

[0061] The unique identification code is embedded into the RFID tag of the corresponding steel bar batch by an RFID writing device, and then a digital association set is generated according to the prefabricated component number, the steel bar batch number and the RFID tag;

[0062] Extracting the prefabricated component number, steel bar batch number and RFID tag from the digital associated set to generate a digital production task order;

[0063] The digital production task order includes the prefabricated component number, the steel bar batch number, the RFID tag and matching parameters.

[0064] For example, a rebar configuration plan stores records for precast components numbered C001 and rebar batch numbered S001. This numbering system lays the foundation for subsequent RFID coding, ensuring data traceability. Unique identification codes C001-S001 are then generated based on pre-set RFID coding rules.

[0065] For example, using a handheld RFID writing device to write the unique identification code C001-S001 onto a tag results in an RFID tag named C001-S001. A digital association set is generated based on the prefabricated component number C001, the rebar batch number S001, and the RFID tag C001-S001. This association set is stored in a table format, containing the fields: prefabricated component number C001, rebar batch number S001, and RFID tag C001-S001. This set provides the data foundation for production tasks, ensuring accurate matching of components and rebar.

[0066] Specifically, a digital production order is generated by extracting data from an associated set. For example, a order might include prefabricated component number C001, rebar batch number S001, and RFID tag C001-S001, along with matching parameters for the rebar batch number S001, such as a 12mm diameter and 820MPa tensile strength. The digital production order is output as an electronic document, clearly listing the required production information. Production personnel can quickly verify order content by scanning the RFID tag, improving production efficiency.

[0067] In one embodiment, the order in which production tasks are executed is determined based on the prefabricated component numbers and RFID tags in the task order. For example, prefabricated component number C001 is prioritized because it is scheduled earlier in the construction plan. RFID tags C001-S001 are used for on-site verification to ensure that rebar batch S001 is correctly assigned to component C001. Preferably, the extended solution supports multi-component scenarios. For example, a task order may contain prefabricated component numbers C001 and C002, matching rebar batches S001 and S002, respectively. RFID tags C001-S001 and C002-S002 are embedded in the corresponding rebars, ensuring that production tasks are executed one by one in the order in which the components are assembled. This approach improves the management flexibility of complex projects. It is understood that the application of RFID technology simplifies the tracking process for components and rebar. For example, an RFID reader can scan the tags on the construction site to confirm the matching status of the rebar batch and component in real time, avoiding the tedious manual verification. This digital management approach improves the collaborative efficiency of production and construction.

[0068] Preferably, in step S4, the preset RFID coding rule is to concatenate the prefabricated component number and the steel bar batch number.

[0069] In one possible implementation, the RFID encoding rule generates a unique identification code by concatenating the prefabricated component number and the rebar batch number. For example, the prefabricated component number C001 and the rebar batch number S001 are concatenated to form C001-S001, which serves as the unique identification code for the RFID tag. After the code is generated, the identification code is embedded into the RFID tag of the rebar batch using an RFID writing device.

[0070] A computer device includes a memory and a processor, wherein the memory stores a computer program, and the processor implements the above-mentioned method for integrating steel bar raw material information of prefabricated components when executing the computer program.

[0071] A computer-readable storage medium stores a computer program, which, when executed by a processor, implements the above-mentioned method for integrating steel bar raw material information of a prefabricated component.

[0072] The embodiments of the present invention are described in detail above with reference to the accompanying drawings, but the present invention is not limited to the described embodiments. It is apparent to those skilled in the art that various changes, modifications, substitutions, and variations to these embodiments may be made without departing from the principles and spirit of the present invention, and the changes still fall within the scope of protection of the present invention.

Claims

1. A method for integrating steel bar raw material information of prefabricated components, characterized in that: The following steps are involved: S1: Obtain the steel bar batch number and mechanical and physical parameters of the steel bar raw material to obtain the original data, and enter the original data parameters into the field mapping table to generate the initial data set; S2: establishing a structured database having a correspondence between steel bar batch numbers and mechanical and physical parameters based on the initial data set; S3: Calculate the reinforcement configuration scheme in the BIM model based on the mechanical and physical parameters in the structured database; generate a configuration parameter table of prefabricated components and reinforcement for the reinforcement configuration scheme; In step S3, the volume parameters and load data of the prefabricated components are obtained through the API interface of the BIM model; The parameter ranges of tensile strength, yield strength, and diameter suitable for the current volume parameters are obtained by table lookup. Based on the parameter ranges, the batch numbers of steel bars with tensile strength, yield strength, and diameter within the parameter ranges are obtained from a structured database using SQL query language. These steel bar batch numbers are combined into a number set. According to the interval in which the load data of the prefabricated component is located, the consideration priorities of the three data parameters of tensile strength, yield strength and diameter corresponding to the interval are obtained, the data with the highest consideration priority is selected as the consideration basis, and the steel bar batch number with the highest consideration basis value is screened from the number set to form an association relationship set; Filtering, from the set of association relationships, an association relationship in which the ratio of the tensile strength to the volume parameter of the prefabricated component is greater than or equal to a preset tensile strength threshold and the ratio of the yield strength to the volume parameter of the prefabricated component is greater than or equal to the corresponding preset yield strength threshold, and selecting the association relationship as a reinforcement configuration scheme for the prefabricated component; Generate a configuration parameter table for prefabricated components and steel bars based on the steel bar configuration plan, the configuration parameter table including the prefabricated component number, steel bar batch number, and matching parameters; the matching parameters include the tensile strength, yield strength, and diameter parameters of the steel bars and the volume parameters of the prefabricated components; S4: RFID is used to associate the prefabricated component number and the steel bar batch number in the configuration parameter table to generate a digital production task order; In step S4, the prefabricated component number and the steel bar batch number are obtained from the configuration parameter table; Generate a unique identification code according to the preset RFID coding rules; The unique identification code is embedded into the RFID tag of the corresponding steel bar batch by an RFID writing device, and then a digital association set is generated according to the prefabricated component number, the steel bar batch number and the RFID tag; Extracting the prefabricated component number, steel bar batch number and RFID tag from the digital associated set to generate a digital production task order; The digital production task order includes the prefabricated component number, the steel bar batch number, the RFID tag and matching parameters.

2. The method for integrating steel bar raw material information of prefabricated components according to claim 1, characterized in that: The mechanical and physical parameters include tensile strength, yield strength and diameter; In the step S1, in the field mapping table, the steel bar batch number field is mapped to batch_id, the tensile strength field is mapped to tensile_strength, the yield strength field is mapped to yield_strength, and the diameter field is mapped to diameter; The values ​​of the steel bar batch number, tensile strength, yield strength and diameter are extracted from the raw data and entered into a field mapping table to generate an initial data set.

3. The method for integrating steel bar raw material information of prefabricated components according to claim 2, characterized in that: In step S1, a barcode scanning device is used to read the QR code on the steel bar raw material to obtain text data containing the steel bar batch number; The tensile strength and yield strength of the steel bars are collected using a pressure sensor, and the diameter of the steel bars is collected using a laser rangefinder.

4. The method for integrating steel bar raw material information of prefabricated components according to claim 3, characterized in that: In step S2, a B+ tree index algorithm is used to construct a joint index for the steel bar batch number, tensile strength, yield strength and diameter fields.

5. The method for integrating steel bar raw material information of prefabricated components according to claim 4, characterized in that: In step S4, the preset RFID coding rule is to concatenate the prefabricated component number and the steel bar batch number.

6. A computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the processor executes the computer program, the method for integrating steel bar raw material information of prefabricated components according to any one of claims 1 to 5 is implemented.

7. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, a method for integrating steel bar raw material information of a prefabricated component according to any one of claims 1 to 5 is implemented.

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