Fabricated building structure quality monitoring method based on BIM

Abstract

The invention discloses a BIM-based fabricated building structure quality monitoring method, and belongs to the technical field of building engineering quality monitoring, and the method comprises the following steps: constructing a fabricated building BIM model, and obtaining reference data corresponding to a fabricated building through simulation calculation; in the production, transportation and construction processes of the component, real-time data of the component is collected through a sensor; comparing the data, collected by the sensor, of each process of the corresponding component with the reference data JZi, if the difference value exceeds the deviation range, generating a corresponding alarm for early warning, and generating a corresponding modification suggestion; according to the invention, the reference data of the corresponding component is obtained through simulation calculation, the reference data is fed back to a factory for production of the corresponding component, and the corresponding component is monitored in real time during production, storage, transportation and construction through data acquisition of a sensor, so that the detection efficiency and precision are improved, and the detection cost is reduced. And the fabricated building is ensured to meet the construction requirements after being formed.

Description

Technical Field

[0001] The present invention belongs to the technical field of construction engineering quality monitoring, and specifically relates to a method for monitoring the quality of prefabricated building structures based on BIM. Background Art

[0002] Prefabricated structure is the abbreviation of prefabricated concrete structure. It is a concrete structure composed of prefabricated components as the main load-bearing components through assembly / connection. Compared with cast-in-place construction, prefabricated construction is more in line with the requirements of green construction such as land conservation, energy conservation, material conservation, water conservation and environmental protection, and reduces the negative impact on the environment.

[0003] The invention patent with application number CN202010374139.8 discloses a BIM-based method for monitoring the grouting quality of prefabricated building nodes. This method can realize the comprehensive application of multiple BIM technologies, and monitor the grouting quality of prefabricated building nodes from multiple aspects such as worker education and training, virtual simulation guidance, and slurry flow monitoring, thereby greatly improving the grouting quality of prefabricated building nodes.

[0004] Although the above method applies BIM technology to architectural design and construction management, there are still deficiencies in how to combine BIM with the Internet of Things and sensor technology to achieve real-time quality monitoring. In addition, prefabricated buildings have quality risks in the production, transportation, lifting and construction of components. Traditional manual inspection is inefficient and has poor accuracy. At the same time, existing technologies lack the ability to trace the entire process and dynamically analyze the quality of prefabricated building structures. Therefore, it is necessary to address the deficiencies of existing technologies. Summary of the Invention

[0005] The purpose of the present invention is to provide a BIM-based prefabricated building structure quality monitoring method to solve the problems of the existing technology of using BIM to achieve real-time quality detection, the poor efficiency and low accuracy of manual inspection of prefabricated components, and the lack of full-process traceability and dynamic analysis capabilities of component quality.

[0006] The purpose of the present invention can be achieved through the following technical solutions:

[0007] The BIM-based prefabricated building structure quality monitoring method includes the following methods:

[0008] S1. Build a BIM model of the prefabricated building and obtain the corresponding benchmark data of the prefabricated building through simulation calculation;

[0009] S2. During the component production, transportation and construction process, real-time data of the components are collected through sensors;

[0010] S3. Compare the data collected by the sensor at each process of the corresponding component with the benchmark data JZi. If the difference exceeds the deviation range, generate a corresponding alarm for early warning and generate corresponding modification suggestions;

[0011] S4. Obtain the specific data of the corresponding component within the deviation range, and use simulation calculations to determine whether the specific values ​​of the data of the corresponding component at each process meet the requirements, and dynamically update the calculation results.

[0012] As a further solution of the present invention, step S1 specifically includes the following steps:

[0013] S11. Obtain component dimensions and shape parameters through design drawings, establish a BIM model, and obtain component dimension data and strength data through CAE simulation calculations;

[0014] S12. Generate a component reference data link and a mapping table, wherein the reference data link includes QR code, size, and strength, and the mapping table records component position information;

[0015] S13. Obtain the dimension deviation value CC and the strength deviation value QD according to industry standards, and store the benchmark data and deviation values ​​in the cloud database.

[0016] As a further solution of the present invention, step S2 comprises the following steps:

[0017] S21. During the production process, collect curing temperature and humidity, dimensions, and flaw detection data, generate production data SCi, and embed it into a QR code;

[0018] S22. During the transportation process, vibration, inclination, flaw detection and GPS positioning data are collected to generate pre-transportation data YQi and post-transportation data YHi;

[0019] S23. During the construction process, collect inclination, flaw detection, size and strength data to generate construction data SGi.

[0020] As a further solution of the present invention, step S3 includes the following steps:

[0021] S31. If the production data SCi≤JZi-CC or SCi≤JZi-QD, the component is eliminated and a production process modification suggestion is generated;

[0022] S32. If the pre-transportation data YQi or post-transportation data YHi ≤ JZi-CC / QD, return to the factory and generate storage or transportation modification suggestions;

[0023] S33. If the construction data SGi≤JZi-CC / QD, generate a construction modification suggestion.

[0024] As a further solution of the present invention, the transport modification suggestion includes: generating a flat transport route through GPS positioning, selecting a route with the lowest transport cost, and enhancing the vehicle's anti-seismic performance or adding a shock-absorbing insulation layer.

[0025] As a further solution of the present invention, step S4 specifically includes the following steps:

[0026] Obtain the specific data of components within the deviation range and dynamically adjust the benchmark data JZi through simulation calculations;

[0027] Extract the size and intensity data of SCi, YQi, YHi, and SGi;

[0028] Through simulation calculation, it is determined whether the data meets the requirements. If not, the correction values ​​XZ1, XZ2 and the threshold ranges [XZ1, JZi], [XZ2, JZi] are generated;

[0029] Store the threshold range in the cloud and remove components that do not meet the threshold range during production.

[0030] As a further embodiment of the present invention, the method of the present invention further comprises:

[0031] Generate component traceability tables based on benchmark data mapping tables, and generate dynamic data tables based on monitoring data;

[0032] S51. Supplement the mapping table information to generate a traceability table for tracing quality issues;

[0033] S52. After de-dimensionalizing SCi, YQi, YHi, and SGi, the product of the two de-dimensionalized values ​​is recorded as the comprehensive performance value. Then, a dynamic data table for the corresponding component at each process is generated with time as the horizontal axis and the comprehensive performance value as the vertical axis.

[0034] S53. Store the traceability table and dynamic data table in the cloud for retrieval, traceability and accountability.

[0035] As a further solution of the present invention, the traceability table and dynamic data table are encrypted and stored using blockchain and timestamp technology to ensure that the data cannot be tampered with.

[0036] A prefabricated building component quality monitoring system, used to implement the above method, comprising:

[0037] BIM modeling module, used to construct prefabricated building models and generate benchmark data;

[0038] Sensor networks are used to collect real-time data from production, transportation, and construction;

[0039] Cloud database for storing benchmark data, deviation values ​​and monitoring data;

[0040] Analysis and early warning module, used to compare data and generate alerts and modification suggestions;

[0041] Dynamic optimization module, used to adjust the threshold range of benchmark data;

[0042] The traceability module is used to generate traceability tables and dynamic data tables.

[0043] Beneficial effects of the present invention:

[0044] The present invention obtains the benchmark data of the corresponding components through simulation calculations, and feeds the benchmark data back to the factory for the production of the corresponding components. At the same time, the corresponding components during production, storage, transportation and construction are monitored in real time through data collection by sensors, which not only improves the detection efficiency and accuracy, but also ensures that the prefabricated building meets the construction requirements after it is formed.

[0045] The present invention determines whether the specific values ​​of the corresponding components in the deviation range meet the overall construction requirements through simulation calculation. If not, a threshold range is generated to select the corresponding components with specific values ​​within the threshold range for assembly of prefabricated buildings.

[0046] By generating a traceability table and a dynamic data table for the corresponding components, the present invention can facilitate the rapid determination of the time node or corresponding process when the problem occurs when the quality of the corresponding components changes, and can make rapid and targeted modifications, thereby facilitating the improvement of production, storage, transportation, and construction efficiency and reducing overall costs. BRIEF DESCRIPTION OF THE DRAWINGS

[0047] The present invention will be further described below with reference to the accompanying drawings.

[0048] Figure 1 Flow chart of the method of the present invention.

[0049] Figure 2 This is a mapping table of the benchmark data of the present invention.

[0050] Figure 3 It is the component tracing table of the present invention. DETAILED DESCRIPTION

[0051] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making any creative efforts shall fall within the scope of protection of the present invention.

[0052] See also Figure 1-3 , the present invention provides a method for monitoring the quality of prefabricated building structures based on BIM:

[0053] Example 1

[0054] S1. Build a BIM model of the prefabricated building and obtain the corresponding benchmark data of the prefabricated building through simulation calculation;

[0055] S11. Obtain the dimensions and shape parameters of the components from the design drawings, and establish a BIM model for the prefabricated building. Obtain the dimensional data and strength data required for the corresponding components of the prefabricated building through simulation calculations, wherein the dimensional data includes the external dimensions of the components themselves and the corresponding positions and dimensions of the embedded parts in the prefabricated building. The simulation calculations are performed using a CAE simulation model.

[0056] S12, generating a reference data link for the component and its corresponding mapping table;

[0057] S121. Generate a reference data chain for the component, such as QR code, size, and strength, based on the required size and strength data of the corresponding component and the corresponding mounting area, wherein the mounting area is used to carry the QR code and corresponds to the location of the QR code;

[0058] S122. Record the obtained reference data chain as the reference data JZi of the corresponding component, where 1≤i≤n, n represents a total of n components, and the value of i in JZi also represents the specific position of the corresponding component in the prefabricated building;

[0059] S123. Generate a mapping table for corresponding components based on the value of i in the reference data JZi;

[0060] Obtain the shape and size parameters of the corresponding components through the design drawings of the prefabricated building, generate the BIM model corresponding to the prefabricated building, obtain the required strength data of the corresponding components at each position through simulation calculation, modify the shape and size parameters of the corresponding components at each position, obtain the required size data of the corresponding components, and number the corresponding components at each position, with the number range from 1 to n;

[0061] S13. Obtain the dimension deviation value CC and strength deviation value QD corresponding to the component according to the quality requirements in the industry specifications, and transmit the dimension deviation value CC, strength deviation value QD, benchmark data JZi, and mapping table to a cloud database via a 4G / 5G network for storage. For example, the dimension deviation value and strength deviation value of the component may be obtained by converting the quality requirements in the "Technical Standard for Prefabricated Concrete Buildings" into the corresponding values.

[0062] S2. During the component production, transportation and construction process, real-time data of the components is collected through pre-installed sensors to monitor whether the corresponding components at each process meet the requirements;

[0063] S21. During the component production process, sensors are installed to collect temperature and humidity data, dimensional data, and flaw detection data during component maintenance in real time. Dimensional and strength data of the corresponding component after production is completed are also obtained. A QR code is generated with relevant information such as the production batch and person in charge of the corresponding component. The QR code, dimensional data, and strength data are then combined to form a production data chain, which is recorded as production data SCi. The QR code is embedded in a hidden location on the prefabricated wallboard using laser engraving. All collected data is then transmitted to a cloud database for storage.

[0064] S22. When transporting components, sensors and GPS positioning equipment are set up to collect vibration data, inclination data, flaw detection data, and real-time position data of the component transportation, and obtain strength data and dimensional data of the corresponding component before and after transportation. Then, combined with the QR code of the corresponding component, pre-transportation data YQi and post-transportation data YHi are generated, and all collected data are transmitted to the cloud database for storage;

[0065] S23. When assembling components, sensors are set to collect inclination data, flaw detection data, dimensional data, and strength data of the corresponding components. After assembly, the same method as in steps S21 and S22 is used to obtain construction data SGi, and all collected data is transmitted to the cloud database for storage;

[0066] S3. Compare the data collected by the sensor at each process of the corresponding component with the benchmark data JZi. If the difference exceeds the deviation range, generate a corresponding alarm for early warning and generate corresponding modification suggestions. The specific methods of alarm warning include sound and light alarm and network message push to the person in charge;

[0067] S31. Determine whether JZi-CC≤SCi≤JZi and JZi-QD≤SCi≤JZi are true. If any one of SCi≤JZi-CC and SCi≤JZi-QD is true, remove the corresponding component, generate a corresponding alarm for early warning, and generate modification suggestions for the production process, such as extending the curing time, changing the reinforcement information, increasing the vibration intensity to make the concrete structure denser and more water-retaining, and promptly repairing the honeycombed surface during pouring. Otherwise, no action is taken.

[0068] It should be noted that when calculating size-related data, JZi represents the size data in the benchmark data chain, and when calculating strength-related data, JZi represents the strength data in the benchmark data. This is the case for the following.

[0069] S32. Determine whether JZi-CC≤YQi≤JZi, JZi-QD≤YQi≤JZi, and JZi-CC≤YHi≤JZi, JZi-QD≤YHi≤JZi hold true;

[0070] S321. If any of YQi≤JZi-CC and YQi≤JZi-QD is true, the corresponding component is returned to the factory, a corresponding alarm is generated for early warning, and storage modification suggestions are generated, such as adjusting the temperature and humidity of the storage area, adjusting the stacking height of the corresponding components during storage, and correcting the storage placement angle. Otherwise, no action is taken;

[0071] S322. If any of the following conditions holds true: YHi≤JZi-CC or YHi≤JZi-QD, the corresponding component will be returned to the factory, a corresponding alarm will be generated for early warning, and suggestions for transportation modifications will be generated, such as enhancing the seismic performance of the transport vehicle, adding a shock-absorbing layer to enhance the seismic protection of the component during transportation, or adjusting the vehicle transportation route. Otherwise, no action will be taken.

[0072] The transportation route is adjusted by using GPS positioning equipment to obtain all roads and corresponding road information between the transportation starting point and the end point. Based on the road information, several relatively flat transportation routes are generated to reduce the impact of road bumps on the components. The transportation route with the lowest transportation cost is selected as the regular route for the transportation of all components.

[0073] S33. Determine whether JZi-CC≤SGi≤JZi and JZi-QD≤SGi≤JZi are established. If any one of SGi≤JZi-CC and SGi≤JZi-QD is established, generate modification suggestions for the construction, such as adjusting the lifting angle, lifting sequence, lifting release speed, etc. Otherwise, no action is taken.

[0074] Example 2

[0075] Based on the first embodiment, this embodiment further discloses a method for adjusting the constructed memory data JZi after step S3, which specifically includes the following steps:

[0076] S4. Obtain specific data of the corresponding component within the deviation range, and use simulation calculations to determine whether the specific values ​​of the data of the corresponding component at each process meet the requirements, and dynamically update the calculation results;

[0077] S41. Obtain specific values ​​corresponding to the strength data and size data of SCi, YQi, YHi, and SGi in JZi-CC≤SCi, YQi, YHi, and SGi<JZi;

[0078] S42, using the corresponding specific values ​​obtained in S41 to determine whether the specific values ​​of the corresponding component size data and strength data meet the requirements through simulation calculation, and if so, no processing is performed; if not, the corresponding strength correction value and size correction value XZ1 and XZ2 are obtained, and the threshold ranges [XZ1, JZi] and [XZ2, JZi] of the component are generated at the same time;

[0079] S43. The obtained threshold ranges [XZ1, JZi] and [XZ2, JZi] are transmitted to the cloud database for storage, and the size data and strength data of the corresponding components are controlled within the threshold range during production, that is, the corresponding components of the same batch whose size data and strength data are not within the threshold range are eliminated.

[0080] Through simulation calculations, the specific values ​​of the component's benchmark data JZi are dynamically adjusted to improve overall efficiency and reduce costs, while also ensuring that the quality of the building after construction meets the requirements.

[0081] Example 3

[0082] After step S4, this embodiment further discloses a method for tracing the source of construction-related data, which specifically includes the following steps:

[0083] S5. Generate a traceability table for the corresponding component based on the mapping table of the benchmark data JZi, and generate a dynamic data table for the corresponding component based on the monitoring data collected by the sensor;

[0084] S51. Obtain a mapping table for the reference data JZi and supplement the information in the mapping table to obtain a traceability table for the corresponding component.

[0085] By setting up a traceability table for corresponding components, when quality problems occur in components, the source of the problem can be found in time and timely modifications can be made to avoid the same problem in subsequent corresponding components, thereby reducing production and construction costs and improving production and construction efficiency;

[0086] S52. Obtain specific values ​​of production data SCi, pre-transportation data YQi, post-transportation data YHi, and construction data SGi, and perform dimension-reducing processing on the corresponding dimensional data and strength data in each set of specific values. The product of the two dimension-reduced values ​​is recorded as the comprehensive performance value. Then, a dynamic data table for the corresponding component at each process is generated with time as the horizontal axis and the comprehensive performance value as the vertical axis.

[0087] S53. The generated traceability table and dynamic data table of the corresponding component are transmitted to the cloud database for storage, so that the responsible personnel can review, trace and determine responsibilities;

[0088] As a preferred method, reference can be made to the method of S52. When the components are cast and cured, data is collected by sensors to generate data charts about the casting pressure and curing records, so as to quickly determine the time or process corresponding to the data change, and thus make targeted modifications to ensure that the formed components meet the requirements. At the same time, the stored information can be encrypted and irreversible through blockchain technology and timestamp technology.

[0089] The above contents are merely examples and explanations of the present invention. Those skilled in the art may make various modifications or additions to the described specific embodiments or replace them in similar ways. As long as they do not deviate from the invention or exceed the scope defined by the claims, they should all fall within the scope of protection of the present invention.

Claims

1. A BIM-based prefabricated building structure quality monitoring method, characterized in that: The following methods are included: S1. Build a BIM model of the prefabricated building and obtain the corresponding benchmark data of the prefabricated building through simulation calculation; S2. During the component production, transportation and construction process, real-time data of the components are collected through sensors; S3. Compare the data collected by the sensor at each process of the corresponding component with the benchmark data JZi. If the difference exceeds the deviation range, generate a corresponding alarm for early warning and generate corresponding modification suggestions; S4. Obtain the specific data of the corresponding component within the deviation range, and use simulation calculations to determine whether the specific values ​​of the data of the corresponding component at each process meet the requirements, and dynamically update the calculation results.

2. The BIM-based prefabricated building structure quality monitoring method according to claim 1, characterized in that: Step S1 specifically includes the following steps: S11. Obtain component dimensions and shape parameters through design drawings, establish a BIM model, and obtain component dimension data and strength data through CAE simulation calculations; S12. Generate a component reference data link and a mapping table, wherein the reference data link includes QR code, size, and strength, and the mapping table records component position information; S13. Obtain the dimension deviation value CC and the strength deviation value QD according to industry standards, and store the benchmark data and deviation values ​​in the cloud database.

3. The BIM-based prefabricated building structure quality monitoring method according to claim 1, characterized in that: Step S2 comprises the following steps: S21. During the production process, collect curing temperature and humidity, dimensions, and flaw detection data, generate production data SCi, and embed it into a QR code; S22. During the transportation process, vibration, inclination, flaw detection and GPS positioning data are collected to generate pre-transportation data YQi and post-transportation data YHi; S23. During the construction process, collect inclination, flaw detection, size and strength data to generate construction data SGi.

4. The BIM-based prefabricated building structure quality monitoring method according to claim 1, characterized in that: Step S3 includes the following steps: S31. If the production data SCi≤JZi-CC or SCi≤JZi-QD, the component is eliminated and a production process modification suggestion is generated; S32. If the pre-transportation data YQi or post-transportation data YHi ≤ JZi-CC / QD, return to the factory and generate storage or transportation modification suggestions; S33. If the construction data SGi≤JZi-CC / QD, generate a construction modification suggestion.

5. The BIM-based prefabricated building structure quality monitoring method according to claim 4, characterized in that: The transport modification suggestions include: generating a flat transport route through GPS positioning, selecting a route with the lowest transport cost, and enhancing the seismic performance of the vehicle or adding a shock-absorbing layer.

6. The BIM-based prefabricated building structure quality monitoring method according to claim 1, characterized in that: Step S4 specifically includes the following steps: Obtain the specific data of components within the deviation range and dynamically adjust the benchmark data JZi through simulation calculations; Extract the size and intensity data of SCi, YQi, YHi, and SGi; Through simulation calculation, it is determined whether the data meets the requirements. If not, the correction values ​​XZ1, XZ2 and the threshold ranges [XZ1, JZi], [XZ2, JZi] are generated; Store the threshold range in the cloud and remove components that do not meet the threshold range during production.

7. The BIM-based prefabricated building structure quality monitoring method according to claim 1, characterized in that: Also includes: Generate component traceability tables based on benchmark data mapping tables, and generate dynamic data tables based on monitoring data; S51. Supplement the mapping table information to generate a traceability table for tracing quality issues; S52. After de-dimensionalizing SCi, YQi, YHi, and SGi, the product of the two de-dimensionalized values ​​is recorded as the comprehensive performance value. Then, a dynamic data table for the corresponding component at each process is generated with time as the horizontal axis and the comprehensive performance value as the vertical axis. S53. Store the traceability table and dynamic data table in the cloud for retrieval, traceability and accountability.

8. The BIM-based prefabricated building structure quality monitoring method according to claim 7, characterized in that: The traceability table and dynamic data table are encrypted and stored using blockchain and timestamp technology to ensure that the data cannot be tampered with.

9. A quality monitoring system for assembled building components, characterized in that: Used to implement the method according to any one of claims 1 to 9, comprising: BIM modeling module, used to construct prefabricated building models and generate benchmark data; Sensor networks are used to collect real-time data from production, transportation, and construction; Cloud database for storing benchmark data, deviation values ​​and monitoring data; Analysis and early warning module, used to compare data and generate alerts and modification suggestions; Dynamic optimization module, used to adjust the threshold range of benchmark data; The traceability module is used to generate traceability tables and dynamic data tables.

Images