Steel bar raw material information integration method of prefabricated part, computer equipment and medium

Abstract

The invention discloses a reinforcing steel bar raw material information integration method of a prefabricated part, computer equipment and a medium, and belongs to the technical field of building management data processing.The method comprises the steps that reinforcing steel bar batch numbers and mechanical physical parameters of reinforcing steel bar raw materials are obtained to obtain original data, and the original data parameters are input into a field mapping table to generate an initial data set; according to the initial data set, establishing a structured database with the relationship between the batch numbers of the reinforcing steel bars and the mechanical physical parameters; calculating a steel bar configuration scheme in the BIM model according to the mechanical physical parameters in the structured database; generating a configuration parameter table according to the steel bar configuration scheme; and performing RFID association on the prefabricated part number and the steel bar batch number in the configuration parameter table to generate a digital production task list. The reinforcing steel bar raw material information integration method of the prefabricated part solves the problems that an existing method is high in input error rate, low in efficiency and difficult in information tracing, and matching between raw material information and design requirements has deviation.

Description

Technical Field

[0001] The present invention relates to the technical field of building management data processing, and particularly relates to a method for integrating steel bar raw material information of precast components, a computer device, and a medium. Background Art

[0002] As a core component of building industrialization, the production efficiency and quality control of precast components are crucial for promoting the modernization of the construction industry. As the main load-bearing material of precast components, the precise management and integration of the raw material information of steel bars directly determine the mechanical properties and structural safety of the components. Currently, the collection and management of steel bar raw material information mainly rely on manual records or semi-automated systems. These methods have problems such as high data entry error rates, low efficiency, and difficulty in information traceability. Especially in the production of complex components, there are often deviations between the raw material information and the design requirements, resulting in increased difficulty in quality control. Summary of the Invention

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

[0004] The technical solution adopted by the present invention to solve its technical problems is: A method for integrating steel bar raw material information of precast components, comprising the following steps: S1: Obtain the steel bar batch number and mechanical and physical parameters of the steel bar raw materials to obtain the original data, and enter the original data parameters into the field mapping table to generate an initial data set; S2: Establish a structured database with the corresponding relationship between the steel bar batch number and the mechanical and physical parameters according to the initial data set; S3: Calculate the steel bar configuration plan in the BIM model according to the mechanical and physical parameters in the structured database; for the steel bar configuration plan, generate a configuration parameter table of the precast component and the steel bar; S4: Perform RFID association on the precast component number and the steel bar batch number in the configuration parameter table to generate a digital production task sheet.

[0005] Preferably, the mechanical and physical parameters include tensile strength, yield strength, and diameter; In the step S1, in the field mapping table, map the steel bar batch number field to batch_id, the tensile strength field to tensile_strength, the yield strength field to yield_strength, and the diameter field to diameter; Extract the values of the steel bar batch number, tensile strength, yield strength, and diameter from the original data, and enter them into the field mapping table to generate an initial data set.

[0006] Optionally, in step S1, a two-dimensional code on the steel bar raw material is read by a bar code scanning device to obtain text data containing the steel bar batch number; A pressure sensor is used to collect the tensile strength and yield strength of the steel bar, and a laser rangefinder is used to collect the diameter of the steel bar.

[0007] 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.

[0008] It should be noted that in step S3, the volume parameter and load data of the precast component are obtained through the API interface of the BIM model; The parameter ranges of the tensile strength, yield strength, and diameter suitable for the current volume parameter are obtained by looking up a table. Based on the parameter ranges, the steel bar batch numbers with the tensile strength, yield strength, and diameter all within the parameter ranges are obtained from the structured database using the SQL query language, and these steel bar batch numbers are combined into a number set; According to the interval where the load data of the precast component is located, the consideration priorities for the three data of the tensile strength, yield strength, and diameter parameters corresponding to the interval are obtained. The data with the highest consideration priority is selected as the consideration basis, and the steel bar batch numbers with the highest value of the consideration basis are screened out from the number set to form an association relationship set; In the association relationship set, the association relationships where the ratio of the tensile strength to the volume parameter of the precast component is greater than or equal to the preset tensile strength threshold and the ratio of the yield strength to the volume parameter of the precast component is greater than or equal to the corresponding preset yield strength threshold are selected as the steel bar configuration scheme for the precast component.

[0009] Preferably, in step S3, for the steel bar configuration scheme, a configuration parameter table of the precast component and the steel bar is generated. The configuration parameter table includes the precast component number, the steel bar batch number, and the matching parameters; where the matching parameters include the tensile strength, yield strength, and diameter parameters of the steel bar and the volume parameter of the precast component.

[0010] Optionally, in step S4, the precast component number and the steel bar batch number are obtained from the configuration parameter table; A unique identification code is generated according to the preset RFID coding rule; The unique identification code is embedded into the RFID tag of the corresponding steel bar batch through the RFID writing device, and then a digital association set is generated according to the precast component number, the steel bar batch number, and the RFID tag; The precast component number, the steel bar batch number, and the RFID tag are extracted from the digital association set to generate a digital production task list; The digital production task list includes the precast component number, the steel bar batch number, the RFID tag, and the matching parameters.

[0011] Specifically, in step S4, the preset RFID coding rule is to splice the precast component number and the steel bar batch number.

[0012] A computer device includes a memory and a processor. The memory stores a computer program, and when the processor executes the computer program, it implements the above-mentioned method for integrating the information of the steel bar raw materials of a precast component.

[0013] A computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, it implements the above-mentioned method for integrating the information of the steel bar raw materials of a precast component.

[0014] The beneficial effects of the present invention are as follows: In the method for integrating the information of the steel bar raw materials of a precast component, by obtaining the steel bar raw material batch number and mechanical parameters, a structured database is established to realize the corresponding relationship between batches and performance. According to the database parameters, the steel bar configuration scheme in the BIM model is calculated, and the component code is associated with the steel bar batch number through RFID to generate a digital production task list. The present invention realizes the digital management of the whole process from raw materials to production, reduces the error rate of data entry and improves the data entry efficiency, and improves the traceability of the steel bar raw material information, ensuring that there is no deviation in the matching between the raw material information and the design requirements. Description of the Drawings

[0015] Figure 1 is a flowchart of the method for integrating the information of the steel bar raw materials of a precast component in an embodiment of the present invention; Figure 2 is a sub-step flowchart of step S1 in an embodiment of the present invention; Figure 3 is a sub-step flowchart of step S3 in an embodiment of the present invention; Figure 4 is a sub-step flowchart of step S4 in an embodiment of the present invention. Detailed Embodiments

[0016] The following further describes the specific embodiments of the present invention in conjunction with the drawings. It should be noted here that the description of these embodiments is used to help understand the present invention, but does not constitute a limitation to the present invention. In addition, the technical features involved in the various embodiments of the present invention described below can be combined with each other as long as they do not conflict with each other.

[0017] As Figures 1-4 shown, a method for integrating the information of the steel bar raw materials of a precast component includes the following steps: S1: Obtain the steel bar batch number and mechanical and physical parameters of the steel bar raw materials to get the original data, and input the original data parameters into the field mapping table to generate an initial data set; S2: Establish a structured database with the corresponding relationship between the steel bar batch number and the mechanical and physical parameters according to the initial data set; S3: Determine the steel bar configuration plan in the BIM model according to the mechanical and physical parameters in the structured database; for the steel bar configuration plan, generate a configuration parameter table of precast components and steel bars; S4: Perform RFID association on the precast component numbers and steel bar batch numbers in the configuration parameter table to generate a digital production task order.

[0018] In the method for integrating the steel bar raw material information of the precast component, by obtaining the steel bar raw material batch number and mechanical parameters, establishing a structured database to realize the corresponding relationship between batches and performance, calculating the steel bar configuration plan in the BIM model according to the database parameters, and performing RFID association on the component code and the steel bar batch number to generate a digital production task order. The present invention realizes the digital management of the whole process from raw materials to production, reduces the error rate of data input and improves the efficiency of data input, and improves the traceability of the steel bar raw material information, ensuring that there is no deviation in the matching between the raw material information and the design requirements.

[0019] It should be noted that the mechanical and physical parameters include tensile strength, yield strength and diameter; In the step S1, in the field mapping table, map the steel bar batch number field to batch_id, the tensile strength field to tensile_strength, the yield strength field to yield_strength, and the diameter field to diameter; Extract the values of the steel bar batch number, tensile strength, yield strength and diameter from the original data, and input them into the field mapping table to generate an initial data set.

[0020] In one embodiment, the original data is generated in JSON format and contains fields such as the 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, facilitating subsequent processing and storage. The batch_id is extracted as "A12345", the tensile_strength is 600 MPa, the yield_strength is 400 MPa, and the diameter is 20.05 mm from the above JSON; this extraction process is automatically completed by a script, reducing manual intervention and improving data processing efficiency.

[0021] Optionally, in step S1, a two-dimensional code on the steel bar raw material is read by a barcode scanning device to obtain text data containing the steel bar batch number; A pressure sensor is used to collect the tensile strength and yield strength of the steel bar, and a laser rangefinder is used to collect the diameter of the steel bar.

[0022] Specifically, reading the QR code on the steel bar raw material through a barcode scanning device to obtain information such as the steel bar batch number is an efficient data collection method. Exemplarily, a handheld QR code scanning gun can be used as the scanning device to scan the QR code on the steel bar packaging to obtain text data including the steel bar batch number, production date, and specifications. For example, the scanning result is "Batch:A12345,Date:2025-03-15,Spec:20mm", and the steel bar batch number "A12345" is extracted as the key field. The advantage of this method lies in its speed and accuracy, avoiding manual input errors and improving data collection efficiency. In a possible implementation, a pressure sensor is used to collect the mechanical parameters of the steel bar, such as the tensile strength and yield strength. Specifically, the steel bar sample is placed in a tensile testing machine, and the pressure sensor records the change in force value during the tensile process in real time. For example, the tensile strength of a certain steel bar sample is 600 MPa, and the yield strength is 400 MPa. These data are directly transmitted to the data collection system through the sensor to ensure the accuracy of the mechanical parameters. It should be noted that the high sensitivity of the pressure sensor can capture minute mechanical changes, which helps to improve data reliability and provides a basis for subsequent quality analysis. Preferably, a laser rangefinder is used to collect the physical parameters of the steel bar, such as the 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 measured diameter of a certain steel bar is 20.05 mm, and the accuracy can reach 0.01 mm. This non-contact measurement method avoids the errors that may be brought by traditional caliper measurements, especially suitable for batch detection scenarios. The high efficiency and high precision of the laser rangefinder significantly improve the automation level of physical parameter collection.

[0023] Preferably, in the step S2, a B+ tree index algorithm is used to construct a composite index for the steel bar batch number, tensile strength, yield strength, and diameter fields in the structured database.

[0024] Specifically, the B+ tree index algorithm constructs a composite index for the steel bar batch number, tensile strength, yield strength, and diameter fields. Exemplarily, in the steel bar detection 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 composite index combines these fields to generate an index mapping table. For example, when querying records with a tensile strength greater than 800 MPa for a certain batch, the B+ tree index can quickly locate the target data and avoid a full table scan. Preferably, the composite index also supports range queries, such as querying records with a yield strength between 400 - 600 MPa.

[0025] It is worth noting that in the step S3, the volume parameters and load data of the precast component are obtained through the API interface of the BIM model; Obtain the parameter ranges of the tensile strength, yield strength, and diameter suitable for the current volume parameter according to the method of looking up a table. Based on the parameter ranges, use the SQL query language to obtain the steel bar batch numbers in the structured database where the tensile strength, yield strength, and diameter are all within the parameter ranges, and combine these steel bar batch numbers into a number set; According to the interval where the load data of the precast component is located, obtain the consideration priorities corresponding to the three data of the tensile strength, yield strength, and diameter parameters for the interval, select the data with the highest consideration priority as the consideration basis, and filter out the steel bar batch numbers of the steel bars with the highest value of the consideration basis from the number set to form an association relationship set; In the association relationship set, filter out the association relationships where the ratio of the tensile strength to the volume parameter of the precast component is greater than or equal to the preset tensile strength threshold and the ratio of the yield strength to the volume parameter of the precast component is greater than or equal to the corresponding preset yield strength threshold as the steel bar configuration scheme of the precast component.

[0026] In a possible implementation manner, obtain the geometric data and load data of the precast component through the API interface of the BIM model. For example, use the API interface of Revit to extract that the volume of the beam component is 0.5 cubic meters and the load is 100 kN.

[0027] When using the SQL query language to extract data from the structured database, based on the method of looking up a table, obtain the ranges of the tensile strength, yield strength, and diameter parameters suitable for the current volume parameter, which can quickly locate the records that meet the conditions. In this embodiment, the records in the queried table record the parameter ranges of the tensile strength, yield strength, and diameter corresponding to different volume parameter ranges. When these parameter ranges are met, it can ensure that the precast component meets the requirements of building production. For example, a tensile strength greater than 800 MPa, a yield strength greater than 400 MPa, and a diameter between 12 - 20 mm are applicable to components with a volume greater than 0.4 cubic meters. For a precast component with a volume of 0.5 cubic meters, based on the method of looking up a table, the parameter range is obtained as a tensile strength greater than 800 MPa, a yield strength greater than 400 MPa, and a diameter between 12 - 20 mm. The query returns a steel bar record with a batch number of A001, a tensile strength of 850 MPa, a yield strength of 420 MPa, and a diameter of 16 mm. It should be noted that the SQL query realizes condition filtering through the WHERE clause, combines index optimization to improve query efficiency, and ensures quick return of results. This method is convenient for extracting specific parameter sets from large-scale data.

[0028] In one embodiment, the matching process takes into account the load data of precast components. For example, for precast components with a load data range of [80 kN, 100 kN], the data with the highest consideration priority is the yield strength. Another example is that for precast components with a load data range of [60 kN, 80 kN], the data with the highest consideration priority is the tensile strength. And for precast components with a load data range of [40 kN, 60 kN], the data with the highest consideration priority 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 preferentially selected to generate an association relationship set.

[0029] It can be understood that the association relationship set needs to meet the tensile strength threshold and yield strength threshold checks. For example, the preset tensile strength threshold requires that the ratio of the tensile strength to the volume of the precast component is greater than 1600 MPa / cubic meter. The ratio of the tensile strength of the steel bars of batch A001 to a 0.5 cubic meter precast component is 1700 MPa / cubic meter. If the condition is met, it is determined as a valid association relationship, and these valid association relationships are used as the steel bar configuration plan for the precast component.

[0030] Preferably, in step S3, for the steel bar configuration plan, a configuration parameter table of the precast component and the steel bars is generated. The configuration parameter table includes the precast component number, the steel bar batch number, and the matching parameters. Among them, the matching parameters include the tensile strength, yield strength, and diameter parameters of the steel bars, as well as the volume parameter of the precast component.

[0031] For example, the generated configuration parameter table contains fields such as precast component B001, steel bar batch number A001, and tensile strength 850 MPa. This tabular output clearly presents the matching results and is convenient for designers to refer to. In one embodiment, the configuration parameter table can also be extended to support multi-precast component scenarios. For example, for a group of precast components, the steel bars of batches A001 and A002 are respectively matched to generate a configuration table containing multiple records, and each record clearly defines the corresponding relationship between the precast component and the steel bars. This extended solution enriches the flexibility of the configuration and adapts to the requirements of complex building designs.

[0032] Specifically, in step S4, the precast component number and the steel bar batch number are obtained from the configuration parameter table. The precast component number and the steel bar batch number respectively identify the precast component and the steel bar batch. Generate a unique identification code according to the preset RFID coding rule. Embed the unique identification code into the RFID tag of the corresponding steel bar batch through an RFID writing device, and then generate a digital association set according to the precast component number, the steel bar batch number, and the RFID tag. Extract the precast component number, steel bar batch number, and RFID tag from the digitalized associated set to generate a digital production work order; The digital production work order includes a precast component number, a steel bar batch number, an RFID tag, and matching parameters.

[0033] For example, the steel bar configuration plan stores the record of the precast component with the precast component number C001 and the steel bar with the steel bar batch number S001. This numbering system lays the foundation for subsequent RFID coding and ensures data traceability. Then, a unique identification code C001-S001 is generated according to the preset RFID coding rule.

[0034] Another example is that the RFID tag obtained by writing the unique identification code C001-S001 into the tag using a handheld RFID writing device is C001-S001; a digitalized associated set is generated based on the precast component number C001, the steel bar batch number S001, and the RFID tag C001-S001. The associated set is stored in tabular form, including fields: precast component number C001, steel bar batch number S001, and RFID tag C001-S001. This set provides a data basis for production tasks and ensures the accurate matching of components and steel bars.

[0035] Specifically, the digital production work order is generated by extracting data from the associated set. For example, the work order includes the precast component number C001, the steel bar batch number S001, and the RFID tag C001-S001, as well as the matching parameters of the steel bar corresponding to the steel bar batch number S001, such as the steel bar diameter of 12 mm and the tensile strength of 820 MPa. The digital production work order is output in the form of an electronic document, clearly listing the information required for production. Production personnel can quickly check the content of the work order by scanning the RFID tag, improving production efficiency.

[0036] In one embodiment, the execution order of production tasks is determined according to the precast component numbers and RFID tags in the work order. For example, the precast component with the precast component number C001 is processed first because it has an earlier schedule in the construction plan. The RFID tag C001-S001 is used for on-site verification to ensure that the steel bar batch S001 is correctly configured for the C001 component. Preferably, the extended solution supports multi-component scenarios. For example, the work order contains the precast component numbers C001 and C002, which are respectively matched with the steel bar batches S001 and S002. The RFID tags C001-S001 and C002-S002 are respectively embedded in the corresponding steel bars to ensure that the production tasks are executed one by one in the component order. This method improves the management flexibility of complex projects. It can be understood that the application of RFID technology simplifies the tracking process of components and steel bars. For example, at the construction site, the tags are scanned by an RFID reader to confirm the matching status of the steel bar batch and the component in real time, avoiding the tedious manual verification. This digital management method improves the coordination efficiency of production and construction.

[0037] Preferably, in the step S4, the preset RFID coding rule is to splice the precast component number and the steel bar batch number.

[0038] In a possible implementation manner, the RFID coding rule generates a unique identification code by splicing the precast component number and the steel bar batch number. For example, the precast component number C001 and the steel bar batch number S001 are spliced into C001-S001 as the unique identification code of the RFID tag. After the coding is generated, the identification code is embedded into the RFID tag of the steel bar batch through an RFID writing device.

[0039] A computer device includes a memory and a processor. The memory stores a computer program, and when the processor executes the computer program, it implements the above-mentioned method for integrating the steel bar raw material information of precast components.

[0040] A computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, it implements the above-mentioned method for integrating the steel bar raw material information of precast components.

[0041] The above has described the embodiments of the present invention in detail with reference to the accompanying drawings, but the present invention is not limited to the described embodiments. For those skilled in the art, without departing from the principles and spirit of the present invention, various changes, modifications, substitutions, and variations made to these embodiments still fall within the protection scope of the present invention.

Claims

1. An integrated method for the information of steel bar raw materials of precast components, characterized in that, It includes the following steps: S1: Obtain the steel bar batch number and mechanical and physical parameters of the steel bar raw material to get the original data, and enter the original data parameters into the field mapping table to generate the initial data set; S2: Establish a structured database with the corresponding relationship between the steel bar batch number and the mechanical and physical parameters according to the initial data set; S3: Calculate the steel bar configuration plan in the BIM model according to the mechanical and physical parameters in the structured database; for the steel bar configuration plan, generate a configuration parameter table of precast components and steel bars; S4: Perform RFID association on the precast component number and the steel bar batch number in the configuration parameter table to generate a digital production work order.

2. The method for integrating the steel bar raw material information of a precast component according to claim 1, wherein: The mechanical and physical parameters include tensile strength, yield strength and diameter; In the step S1, in the field mapping table, map the steel bar batch number field to batch_id, the tensile strength field to tensile_strength, the yield strength field to yield_strength, and the diameter field to diameter; Extract the values of the steel bar batch number, tensile strength, yield strength and diameter from the original data, and enter them into the field mapping table to generate the initial data set.

3. The integrated method for steel bar raw material information of a precast component according to claim 2, characterized in that: In the step S1, read the QR code on the steel bar raw material through a barcode scanning device to obtain the text data containing the steel bar batch number; Use a pressure sensor to collect the tensile strength and yield strength of the steel bar, and use a laser rangefinder to collect the diameter of the steel bar.

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

5. A method for integrating steel bar raw material information of precast components according to claim 4, characterized in that: In the step S3, obtain the volume parameters and load data of the precast component through the API interface of the BIM model; Obtain the parameter ranges of the tensile strength, yield strength and diameter suitable for the current volume parameters by means of look-up tables, and use the SQL query language to obtain the steel bar batch numbers whose tensile strength, yield strength and diameter are all within the parameter ranges from the structured database, and combine these steel bar batch numbers into a number set; According to the interval where the load data of the precast component is located, obtain the consideration priorities corresponding to the interval for the three data of the tensile strength, yield strength and diameter parameters, select the data with the highest consideration priority as the consideration basis, and screen out the steel bar batch numbers with the highest value of the consideration basis from the number set to form an association relationship set; In the association relationship set, screen out the association relationships where the ratio of the tensile strength to the volume parameter of the precast component is greater than or equal to the preset tensile strength threshold and the ratio of the yield strength to the volume parameter of the precast component is greater than or equal to the corresponding preset yield strength threshold as the steel bar configuration plan of the precast component.

6. The integrated method for steel bar raw material information of a prefabricated component according to claim 5, characterized in that: In the step S3, for the steel bar configuration plan, generate a configuration parameter table of precast components and steel bars, and the configuration parameter table includes the precast component number, the steel bar batch number and the matching parameters; where the matching parameters include the tensile strength, yield strength and diameter parameters of the steel bar and the volume parameter of the precast component.

7. A method for integrating the information of steel bar raw materials of prefabricated components according to claim 6, characterized in that: In the step S4, obtain the precast component number and the steel bar batch number from the configuration parameter table; Generate a unique identification code according to the preset RFID coding rule; Embed the unique identification code into the RFID tag of the corresponding steel bar batch through the RFID writing device, and then generate a digital association set according to the precast component number, the steel bar batch number, and the RFID tag; Extract the precast component number, the steel bar batch number, and the RFID tag from the digital association set to generate a digital production task list; The digital production task list includes a precast component number, a steel bar batch number, an RFID tag, and matching parameters.

8. A method for integrating the information of steel bar raw materials of precast components according to claim 7, characterized in that: In the step S4, the preset RFID coding rule is to splice the precast component number and the steel bar batch number.

9. A computer device, comprising a memory and a processor, the memory storing a computer program, characterized in that, When the processor executes the computer program, it implements a method for integrating the information of the steel bar raw materials of a precast component according to any one of claims 1 to 8.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, it implements a method for integrating the information of the steel bar raw materials of a precast component according to any one of claims 1 to 8.

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