A quality analysis and evaluation method and device for plain concrete

Abstract

The present invention discloses a quality analysis and evaluation method and equipment for plain concrete, and relates to the technical field of concrete evaluation. The method comprises: partially framing the architectural design information of the building to be constructed; collecting environmental data to obtain associated environmental data; loading the test building model into the environmental simulation system initialized by the associated environmental data; driving the environmental simulation system to track the evolution of concrete quality of the coated building model, and outputting the concrete defect data of the construction period and the concrete defect data of the service period; performing defect evolution analysis on the concrete defect data of the construction period and the concrete defect data of the service period, and outputting the full-cycle quality evaluation result. The technical problem that the quality evaluation of plain concrete is not comprehensive enough in the prior art, resulting in insufficient evaluation accuracy, is solved. By tracking and evolving the quality of plain concrete during the construction period and the service period, the technical effect of improving the comprehensiveness and accuracy of the quality evaluation of plain concrete is achieved.

Description

Technical Field

[0001] The invention relates to the technical field of concrete evaluation, and in particular to a quality analysis and evaluation method and equipment for plain concrete. Background Art

[0002] As a building material that uses the texture and color of concrete as a decorative surface, fair-faced concrete has been widely used in the construction field in recent years. Its unique appearance and excellent physical properties make it an important element in modern architectural design. However, the quality evaluation of fair-faced concrete has always been a major challenge facing the construction industry. Traditional methods for evaluating the quality of fair-faced concrete mainly focus on the construction process, but these methods are often limited to local quality inspections and fail to fully consider the performance of concrete in long-term service. In addition, the lack of a comprehensive evaluation system based on environmental factors and architectural design information makes it difficult for existing technologies to accurately track the quality evolution of fair-faced concrete during the construction and service periods, and to detect potential defects or problems in a timely manner. Summary of the invention

[0003] The present application provides a quality analysis and evaluation method and equipment for plain concrete, which solves the technical problem in the prior art that the quality evaluation of plain concrete is not comprehensive enough, resulting in insufficient evaluation accuracy.

[0004] In a first aspect of the present application, a quality analysis and evaluation method for plain concrete is provided, the method comprising:

[0005] Taking the decorative coating area of ​​plain concrete as a constraint, the architectural design information of the building to be constructed is partially framed; the coating design information is interactively obtained, and environmental data is collected based on the coating design information and the architectural design information to obtain associated environmental data; after constructing a test building model according to the architectural design information, the test building model is loaded into an environmental simulation system initialized by the associated environmental data; in the process of performing small-scale coating on the test building model according to the coating design information to obtain a coated building model, the environmental simulation system is driven to track the evolution of concrete quality of the coated building model, and the concrete defect data of the construction period and the concrete defect data of the service period are output; the defect evolution analysis of the concrete defect data of the construction period and the concrete defect data of the service period is performed, and the full-cycle quality evaluation result is output.

[0006] The second aspect of the present application provides a quality analysis and evaluation device for plain concrete, the device comprising:

[0007] A framing information module is used to partially frame the architectural design information of the building to be constructed with the decorative coating area of ​​the plain concrete as a constraint; a data acquisition module is used to interactively obtain the coating design information, and to collect environmental data based on the coating design information and the architectural design information to obtain associated environmental data; a loading module is used to load the test building model into the environmental simulation system initialized by the associated environmental data after constructing the test building model according to the architectural design information; a quality tracking module is used to drive the environmental simulation system to track the evolution of concrete quality of the coated building model during the process of performing small-scale coating on the test building model according to the coating design information to obtain the coated building model, and output the construction period concrete defect data and the service period concrete defect data; a defect evolution analysis module is used to perform defect evolution analysis on the construction period concrete defect data and the service period concrete defect data, and output the full-cycle quality evaluation result.

[0008] One or more technical solutions provided in this application have at least the following technical effects or advantages:

[0009] First, the architectural design information of the building to be constructed is partially framed with the decorative coating area of ​​the plain concrete as a constraint. Then, the coating design information is obtained interactively, and environmental data is collected based on the coating design information and the architectural design information to obtain associated environmental data. After constructing the test building model according to the architectural design information, the test building model is loaded into the environmental simulation system initialized by the associated environmental data. Then, in the process of obtaining the coated building model by coating the test building model on a small scale according to the coating design information, the environmental simulation system is driven to track the evolution of the concrete quality of the coated building model, and the concrete defect data of the construction period and the concrete defect data of the service period are output. Finally, the defect evolution analysis of the concrete defect data of the construction period and the concrete defect data of the service period is performed, and the full-cycle quality evaluation results are output. The technical problem that the quality evaluation of plain concrete is not comprehensive enough in the prior art, resulting in insufficient evaluation accuracy, is solved. By tracking and analyzing the quality evolution of plain concrete during the construction period and the service period, the technical effect of improving the comprehensiveness and accuracy of the quality evaluation of plain concrete is achieved. BRIEF DESCRIPTION OF THE DRAWINGS

[0010] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0011] Figure 1 A schematic flow chart of a quality analysis and evaluation method for plain concrete provided in an embodiment of the present application;

[0012] Figure 2 A schematic diagram of the structure of a quality analysis and evaluation device for plain concrete provided in an embodiment of the present application.

[0013] Explanation of the reference numerals: framing information module 11 , data acquisition module 12 , loading module 13 , quality tracking module 14 , defect evolution analysis module 15 . DETAILED DESCRIPTION

[0014] The embodiments of the present application provide a method and device for analyzing and evaluating the quality of plain concrete, thereby solving the technical problem in the prior art that the quality evaluation of plain concrete is not comprehensive enough, resulting in insufficient evaluation accuracy.

[0015] The following will be combined with the drawings in the embodiments of the present application to clearly and completely describe the technical solutions in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, rather than all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of this application.

[0016] It should be noted that the terms "including" and "having" are intended to cover non-exclusive inclusions. For example, a process, method, system, product or server that includes a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or modules that are not explicitly listed or are inherent to these processes, methods, products or devices.

[0017] Embodiment 1, as Figure 1 As shown, the embodiment of the present application provides a quality analysis and evaluation method for plain concrete, wherein the method comprises:

[0018] The decorative coating area of ​​the fair-faced concrete is used as a constraint to partially frame the architectural design information of the building to be constructed.

[0019] During the construction of plain concrete, the specific area of ​​the building that involves the decorative coating of plain concrete is first identified, and the relevant architectural design information is determined using this area as the key constraint. Specifically, the decorative coating area of ​​plain concrete usually includes the exterior facades, walls, columns and other parts that have been coated. These parts are not only crucial to the aesthetic appearance of the building, but also have strict requirements on the durability and long-term performance of concrete. Therefore, the decorative coating area in the architectural design drawings is framed to obtain the architectural design information of the building to be constructed, including the location, shape, size and corresponding construction requirements of the coating area. By using the decorative coating area as a constraint, the specific requirements of the area in the construction can be accurately defined, and the accuracy of subsequent environmental simulation and concrete quality assessment can be ensured, thereby providing basic data support for the realization of full-cycle quality evaluation.

[0020] The coating design information is interactively obtained, and environmental data is collected based on the coating design information and the building design information to obtain associated environmental data.

[0021] By interacting with relevant designers, coating design information can be obtained, including the type of coating material, coating thickness, coating method, and coating time requirements.

[0022] Based on the coating design information obtained, environmental data is collected in combination with the building design information to obtain external environmental factors that may affect the quality of the plain concrete coating, such as climatic conditions such as temperature, humidity, and wind speed, as well as relevant environmental data such as the building's geographical location and construction stage. Through these environmental data, we can have a more comprehensive understanding of the changes in the construction environment and provide the necessary basic data for subsequent environmental simulation and quality tracking. Finally, the coating design information is combined with the building design information, and various environmental parameters obtained through environmental data collection form associated environmental data. These associated environmental data can provide multi-dimensional data support for the evolution analysis of concrete quality, making subsequent quality tracking and defect prediction more accurate, and can be dynamically adjusted and optimized under different construction environments.

[0023] Further, interactively obtaining coating design information, and collecting environmental data based on the coating design information and the building design information to obtain associated environmental data, the method includes:

[0024] Extracting coating construction time from the coating design information, wherein the coating design information includes a coating quality requirement set, a concrete mix ratio, coating construction parameters and the coating construction time; extracting building space coordinates from the building design information; performing a cross-search of environmental data using the coating construction time as a retrieval time constraint and the building space coordinates as a retrieval space constraint, and outputting the associated environmental data, wherein the associated environmental data includes construction environment data and extreme environment data.

[0025] First, the coating construction time is extracted from the coating design information. The coating design information includes a coating quality requirement set, concrete mix ratio, coating construction parameters and the coating construction time, which together define the specific requirements for coating construction. Next, the building space coordinates are extracted from the architectural design information. The architectural design information provides the specific design drawings and spatial layout of the building. The architectural space coordinates indicate the relative positions of various parts in the building. By extracting these coordinate information, the building parts related to the coating area can be accurately located, and the spatial distribution of these areas in actual construction can be determined. Then, a cross-search of environmental data is performed in combination with the coating construction time and the building space coordinates; the coating construction time is used as a retrieval time constraint to indicate the construction activities carried out within a specific time period, and the building space coordinates are used as a retrieval space constraint to limit the specific building areas that need to be considered; in this way, environmental data related to the construction time and spatial location can be screened out from the environmental database to obtain accurate associated environmental data, and the associated environmental data obtained include construction environmental data and extreme environmental data; construction environmental data usually include conventional environmental parameters such as temperature, humidity, wind speed, etc., which usually have a more direct impact on the quality of concrete; and extreme environmental data involves possible extreme climatic conditions, such as high temperature, low temperature, strong wind and other extreme weather data, which can help predict the performance and potential problems of concrete quality in extreme environments.

[0026] After constructing the test building model according to the building design information, the test building model is loaded into the environment simulation system initialized by the associated environment data.

[0027] Architectural design information includes the building's facade design, structural layout, spatial distribution and other specific contents related to construction and design. Based on this information, the constructed experimental building model can reflect the overall structure of the building and the detailed design of each construction site, including the size, shape and position of the bare concrete decorative coating area in the building.

[0028] After the test building model is constructed, it is loaded into the environmental simulation system, which is a computer system that can simulate real environmental conditions and can simulate the virtual environment of the building based on the previously collected associated environmental data (including construction environment data and extreme environment data). By loading the test building model, the environmental simulation system combines the physical structure of the building with the environmental conditions to create a dynamic environmental simulation scene. By loading the test building model into the environmental simulation system initialized with associated environmental data, real-time monitoring and tracking of the concrete coating quality can be achieved. The environmental simulation system simulates various influencing factors in the real construction environment, providing a virtual and accurate experimental platform for subsequent concrete quality analysis.

[0029] Furthermore, after constructing the test building model according to the building design information, the test building model is loaded into the environment simulation system initialized by the construction environment data, and the method includes:

[0030] Preset a test scaling ratio; perform twin modeling according to the building design information to generate a regional virtual model; perform scaling and printing of the regional virtual model according to the test scaling ratio to obtain the test building model; decompose the construction environment data, obtain the construction period environment time series data, and use the construction period environment time series data to initialize the construction period simulation unit in the environmental simulation system; perform state transfer analysis on the extreme environment data, output the service period environment time series data, and initialize the service period simulation unit in the environmental simulation system according to the construction period environment time series data; load the test building model into the initialized environmental simulation system.

[0031] In environmental simulation, the actual building model usually needs to be scaled to adapt to the operation and display of the simulation system. The preset test scaling ratio ensures that the test building model can be effectively presented and operated in the computer system, while maintaining the proportional relationship with the actual building to ensure the accuracy of the simulation results. Based on the architectural design information, digital twin technology is used for twin modeling to generate the regional virtual model corresponding to the building; the regional virtual model is scaled and printed according to the preset test scaling ratio to obtain the actual test building model.

[0032] After the experimental building model is constructed, the construction environment data is processed. Specifically, first, the construction environment data is decomposed and the construction period environment time series data is extracted. These data include environmental factors such as temperature, humidity, wind speed, etc. that may appear during the construction process, and are recorded in chronological order; these construction period environment time series data are used to initialize the construction period simulation unit in the environmental simulation system to ensure that the simulation system can accurately reflect the impact of environmental changes during the construction period on the quality of concrete; then, the state transition analysis of extreme environmental data is carried out. This analysis helps to predict extreme weather or environmental changes that may be encountered during the use of the building, such as high temperature, severe cold, strong wind, etc. The service period environment time series data obtained by analysis provides initialization data for the service period simulation unit in the environmental simulation system, so that the system can simulate the various extreme environmental conditions that the building may be affected by during its service; finally, after the construction period and service period simulation units are initialized, the experimental building model is loaded into the initialized environmental simulation system. At this time, the environmental simulation system already has environmental data support for the construction period and service period, and can accurately simulate the environmental conditions of the building throughout its life cycle.

[0033] Furthermore, the state transition analysis is performed on the extreme environment data to output the service environment time series data, and the method includes:

[0034] The extreme environmental data are normalized to obtain K extreme environmental states; the building space coordinates are used as a single search condition to retrieve environmental data to obtain historical environmental data; the K extreme environmental states are used to traverse the historical environmental data, and K groups of environmental state transition probabilities are calculated and output; an environmental state prediction model is constructed according to the K extreme environmental states and the K groups of environmental state transition probabilities; after extracting the final environmental data of the construction period from the environmental time series data of the construction period, the final environmental data of the construction period is loaded into the environmental state prediction model to predict the state probability change, and an environmental state change sequence is output; the environmental state change sequence is smoothed to output the service period environmental time series data.

[0035] Specifically, the extreme environmental data are normalized so that different environmental data can be unified into the same dimension for subsequent analysis. The normalized data can convert different extreme environmental conditions such as high temperature, severe cold, strong wind, etc. into a set of standardized data, thereby obtaining K extreme environmental states. Each extreme environmental state represents a possible extreme environmental condition, such as extremely high temperature, extremely low temperature, strong wind, etc. This processing method enables various extreme environmental factors to be compared and analyzed under a unified framework; next, the building space coordinates are used as retrieval conditions, and the coordinates are used to retrieve environmental data to obtain historical environmental data related to specific buildings; by locating the spatial position of the building, the historical environmental data is retrieved to ensure that the analyzed data is closely related to the actual geographical environment of the building. These historical data provide a record of past environmental changes in the area where the building is located, providing the necessary basis for subsequent state transition analysis.

[0036] After obtaining the historical environmental data, K extreme environmental states are used to traverse the historical environmental data, and K groups of environmental state transition probabilities are calculated. Specifically, by analyzing the historical data under each extreme environmental state, the transition probabilities between these states are calculated, that is, the possibility of changing from one extreme environmental state to another. These transition probabilities provide an important basis for the construction of the subsequent environmental state prediction model, which can reflect the regularity and trend of environmental changes. Based on the above K extreme environmental states and K groups of environmental state transition probabilities, an environmental state prediction model is constructed. The model can predict the possible changes in environmental states in the future based on the current environmental state, and simulate the evolution trend of different environmental factors during the service life of the building according to the transfer law of historical environmental data. Through the environmental state prediction model, the environmental conditions that the building may experience during its service life can be simulated, long-term environmental predictions can be provided, and guidance can be provided for the evolution of concrete quality. Next, the data at the end of the construction period are extracted from the environmental time series data during the construction period. These data represent the final environmental state at the end of the construction; these data are loaded into the environmental state prediction model, and the model predicts future environmental changes based on the environmental state at the end of the construction period. In this way, an environmental state change sequence can be generated to simulate the environmental changes that a building may experience during its service life and help predict the potential impact of extreme environments on building quality. Finally, the output environmental state change sequence is smoothed to reduce noise and unstable factors in the data, making the prediction results more stable and reliable. Through this smoothing process, the final service environment time series data can provide accurate environmental predictions for the environmental simulation system, help the system evaluate the environmental impacts that bare concrete may be subject to during its entire service life, and thus provide a scientific basis for concrete quality monitoring, defect warning and maintenance strategies.

[0037] In the process of performing small-scale coating on the test building model according to the coating design information to obtain the coated building model, the environmental simulation system is driven to track the evolution of concrete quality of the coated building model, and outputs construction period concrete defect data and service period concrete defect data.

[0038] In the process of coating the test building model on a small scale according to the coating design information and obtaining the coated building model, it is first necessary to determine the specific coating parameters based on the coating design information, such as the type of coating material, coating thickness, coating method, and coating time. These coating design information provides a detailed construction basis for subsequent operations, ensuring that the evolution of concrete quality during construction and service life can be truly reflected in the simulation process. Based on this information, the test building model is coated on a small scale, which simulates the operation of coating plain concrete in actual buildings.

[0039] After the coating is completed, the coated building model is then loaded into the environmental simulation system to drive the system to track the evolution of concrete quality; the environmental simulation system uses the previously obtained construction environment data and extreme environment data, combined with the coating design information, to simulate the curing and durability changes of concrete under different environmental conditions. In this way, the system can dynamically track the quality evolution of concrete during the construction period and service period, analyze the performance of the coated building model under different environmental conditions, and output the corresponding concrete defect data. Specifically, the system will simulate the changes in the construction environment of the building during the construction period, such as fluctuations in factors such as temperature and humidity, which will affect the early strength and curing process of concrete. During the construction period simulation process, the system will monitor and record concrete defects such as cracks, voids, bubbles, etc. in real time to form construction period concrete defect data, which provides strong support for quality control and timely adjustments during construction. When simulating entering the service period, the environmental simulation system will further consider factors such as extreme weather changes, temperature and humidity fluctuations that the building may experience during use, and simulate the long-term durability, aging process and possible defects of concrete. The system will simulate problems such as concrete crack expansion and material aging based on these environmental changes, and output concrete defect data during service. These data can provide early warning for the long-term maintenance and repair of the building, helping to detect and solve potential problems in a timely manner.

[0040] Furthermore, in the process of performing small-scale coating on the test building model according to the coating design information to obtain the coated building model, the environmental simulation system is driven to track the concrete quality evolution of the coated building model, and the construction period concrete defect data and the service period concrete defect data are outputted. The method includes:

[0041] The concrete mix ratio and coating construction parameters are extracted from the coating design information; after pre-treating the plain concrete according to the concrete mix ratio, a small-scale coating of plain concrete is performed on the surface of the test building model according to the coating construction parameters; in the process of performing small-scale coating on the test building model to obtain a coated building model, the construction period simulation unit is driven to perform initial evolution of concrete quality on the coated building model, and the construction period concrete defect data is output; the service period environment time series data is used to drive the service period simulation unit to perform long-term evolution of concrete quality on the coated building model, and the service period concrete defect data is output.

[0042] In the process of conducting small-scale coating on the test building model according to the coating design information to obtain the coated building model, it is first necessary to extract the concrete mix ratio and coating construction parameters from the coating design information. These parameters are crucial to the preparation and coating process of concrete. The concrete mix ratio determines the material composition and properties of the concrete, while the coating construction parameters specify the specific operations in the coating process, such as coating thickness, coating method, and construction time.

[0043] After extracting the concrete mix ratio and coating construction parameters, the plain concrete will be pretreated according to the concrete mix ratio. The pretreatment steps usually include mixing and stirring of materials to ensure that the concrete can meet the required performance standards. After the pretreatment is completed, a small-scale coating is carried out on the surface of the test building model according to the requirements of the coating construction parameters to obtain a coated building model. The coated building model refers to a test building model coated with plain concrete.

[0044] During the coating process, the construction simulation unit is driven to perform the initial evolution of the concrete quality of the coated building model. The construction simulation unit tracks the evolution of concrete quality in real time according to the environmental conditions during the construction period (such as temperature, humidity, etc.), and outputs the construction period concrete defect data. These defect data include common quality problems during the construction period, such as cracks, voids, bubbles, etc., to help analyze the defects that may occur in the concrete during the construction process and provide a reference for the quality management during the construction period. After completing the construction period simulation, the service period simulation unit is driven by the service period environmental time series data to perform the long-term evolution of concrete quality; the service period environmental time series data includes the extreme environmental changes that the building may encounter during use, such as temperature fluctuations, humidity changes, etc.; the service period simulation unit simulates how the concrete ages, cracks expand, and other possible quality deterioration during long-term use based on these environmental data; through this process, the output service period concrete defect data provides important early warning information for the long-term maintenance and repair of the building, and helps identify quality problems that may occur during the use of the building.

[0045] Further, the construction period simulation unit is driven to perform initial evolution of concrete quality on the coated building model and output the construction period concrete defect data, the method comprising:

[0046] The construction period simulation unit is driven to perform initial evolution of concrete quality on the coated building model, and output a construction period building model; the coating defect source analysis is performed on the coating quality requirement set, and M quality detection types are set according to the analysis results; M data acquisition devices are scheduled according to the M quality detection types to perform multi-dimensional data acquisition of the construction period building model, and M quality analysis data are obtained; the coating quality requirement set is extracted and called from the coating design information, and a coating defect recognition network is constructed based on the coating quality requirement set, wherein the coating defect recognition network includes M coating defect detection channels corresponding to the M quality detection types, and the M coating defect detection channels are connected in parallel; the M quality analysis data are mapped and loaded into the M coating defect detection channels of the coating defect recognition network, and the construction period concrete defect data is analyzed and output, wherein the construction period concrete defect data includes M groups of quality defect feature data, and the quality defect feature data includes quality defect position feature, quality defect size feature and quality defect type feature.

[0047] In the process of driving the construction period simulation unit to perform initial concrete quality evolution on the coated building model and outputting the concrete defect data during the construction period, the construction period simulation unit is first driven to perform initial concrete quality evolution on the coated building model. Through the control of the environmental simulation system, the simulation unit performs real-time concrete quality evolution on the coated building model according to the environmental conditions (such as temperature, humidity, etc.) during the construction period, simulates the quality problems that may occur during the coating process, and finally generates a construction period building model, which reflects the overall state of the concrete in the initial construction stage. Next, the defect source analysis of the coating quality requirement set is performed. The coating quality requirement set includes various requirements for concrete quality during the coating process, such as thickness, density, surface finish, etc.; through the analysis of the coating quality requirement set, potential sources that may cause coating defects are identified, such as changes in the construction environment, improper coating process, etc.; according to the analysis results, M types of quality inspection types are set to perform special inspections for different types of defects, such as crack inspection, bubble inspection, thickness uniformity inspection, etc. Subsequently, according to the M types of quality inspection, the corresponding M types of data acquisition equipment are dispatched. These equipment may include temperature and humidity sensors, visual inspection equipment, laser rangefinders, etc., which are used to collect multi-dimensional data on the building model during the construction period, and obtain M quality analysis data. These data cover various quality characteristics that may appear during the construction process, such as temperature changes, humidity fluctuations, coating thickness, surface defects, etc. Through comprehensive data collection, it is ensured that all aspects of coating quality can be captured. Then, the coating quality requirement set is extracted from the coating design information, and a coating defect recognition network is constructed based on these requirements. The network includes M coating defect detection channels, each channel corresponds to a quality inspection type, such as crack detection channel, bubble detection channel, surface finish detection channel, etc.; all M detection channels work in parallel to collaboratively analyze different quality data, and each detection channel is specifically responsible for processing quality data related to its type, ensuring that the identification of concrete defects is more accurate. Finally, the M quality analysis data are mapped and loaded into the M coating defect detection channels of the coating defect recognition network. The system analyzes the collected data through these channels and finally outputs the construction period concrete defect data. The output defect data includes M groups of quality defect characteristic data. Each group of data includes quality defect location characteristics, quality defect size characteristics and quality defect type characteristics. These characteristic data can accurately describe the defect conditions of concrete during the construction period and provide a scientific basis for subsequent quality assessment and repair measures.

[0048] Defect evolution analysis is performed on the concrete defect data during the construction period and the concrete defect data during the service period, and a full-cycle quality evaluation result is output.

[0049] After obtaining the concrete defect data during the construction and service period, the quality changes of concrete throughout the life cycle are evaluated through the evolution analysis of these data. The defect evolution analysis not only takes into account the occurrence time and degree of defects, but also analyzes the long-term evolution trend of defects by simulating different environmental influencing factors. Finally, a full-cycle quality evaluation result is output to provide data support for the construction phase and subsequent use, helping to discover potential problems and provide effective early warnings.

[0050] Furthermore, defect evolution analysis is performed on the concrete defect data during construction and the concrete defect data during service, and a full-cycle quality evaluation result is output. The method includes:

[0051] The service period simulation unit is driven to perform long-term evolution of concrete quality on the construction period building model, and H service stage building models are output; after multi-dimensional data collection is performed on the H service stage building models, the data collection results are analyzed via the coating defect recognition network, and the service period concrete defect data is output, wherein the service period concrete defect data includes H service stage defect data; taking the construction period concrete defect data as the starting point and the M quality inspection types as the constraints, the construction period concrete defect data and the H service stage defect data are analyzed for defect expansion time series, and M groups of defect expansion speed sequences are output; time series extreme value extraction is performed on the M groups of defect expansion speed sequences to obtain M defect expansion extreme value sequences; the M quality inspection types and the M defect expansion extreme value sequences are stored in association, and output as the full-cycle quality evaluation result.

[0052] Specifically, the service life simulation unit is driven to perform long-term evolution of concrete quality on the building model during construction. This process is simulated by the simulation system, under the control of the service life simulation unit, based on the concrete defect data during construction and historical environmental data, to simulate the quality change of concrete during service. Through this evolution process, the system outputs H service stage building models, which correspond to the state of the building at different service stages, reflecting the evolution of concrete quality from initial service to long-term service. After obtaining H service stage building models, multi-dimensional data collection is carried out next. These data include environmental conditions (such as temperature, humidity, wind force, etc.), as well as the physical properties of concrete (such as crack width, strength change, surface corrosion, etc.). These data are the basis for evaluating the changing trend of concrete quality at different service stages. After data collection, the service period concrete defect data is identified and extracted through analysis of the coating defect recognition network. The analysis results include H service stage defect data, reflecting the concrete defects and their evolution at each service stage. On this basis, the system will take the concrete defect data of the construction period as the starting point, and combine M types of quality inspection to constrain and conduct defect expansion time series analysis. This analysis process involves the gradual expansion of the defect data of the construction period and H service stage defect data. Through the time series analysis of these data, M groups of defect expansion speed sequences can be obtained. This sequence reflects the expansion rate of various defects in different time periods and reveals the expansion trend of different defects during the service period. The time series extreme value extraction of the M groups of defect expansion speed sequences can obtain M defect expansion extreme value sequences. The time series extreme value extraction process analyzes the maximum and minimum values ​​in each group of expansion speed sequences to find out the extreme conditions of defect expansion. These extreme values ​​reflect the most serious degree of concrete defect expansion during the service period, which provides an important basis for subsequent quality prediction and maintenance. Finally, the M types of quality inspection are associated with the M defect expansion extreme value sequences and stored, and output as the full-cycle quality evaluation results. These results provide a complete evaluation of the quality of the building during the construction period and service period, revealing the expansion trend, extreme changes and potential risks of concrete defects, providing timely warnings for engineers and maintenance personnel, and providing a scientific basis for long-term quality management and maintenance decisions.

[0053] In summary, the embodiments of the present application have at least the following technical effects:

[0054] First, the architectural design information of the building to be constructed is partially framed with the decorative coating area of ​​the plain concrete as a constraint. Then, the coating design information is obtained interactively, and environmental data is collected based on the coating design information and the architectural design information to obtain associated environmental data. After constructing the test building model according to the architectural design information, the test building model is loaded into the environmental simulation system initialized by the associated environmental data. Then, in the process of obtaining the coated building model by coating the test building model on a small scale according to the coating design information, the environmental simulation system is driven to track the evolution of the concrete quality of the coated building model, and the concrete defect data of the construction period and the concrete defect data of the service period are output. Finally, the defect evolution analysis of the concrete defect data of the construction period and the concrete defect data of the service period is performed, and the full-cycle quality evaluation results are output. The technical problem that the quality evaluation of plain concrete is not comprehensive enough in the prior art, resulting in insufficient evaluation accuracy, is solved. By tracking and analyzing the quality evolution of plain concrete during the construction period and the service period, the technical effect of improving the comprehensiveness and accuracy of the quality evaluation of plain concrete is achieved.

[0055] Embodiment 2, based on the same inventive concept as the quality analysis and evaluation method for plain concrete in the above embodiment, Figure 2 As shown, the present application provides a quality analysis and evaluation device for plain concrete. The device includes:

[0056] The framing information module 11 is used to partially frame the architectural design information of the building to be constructed with the decorative coating area of ​​the plain concrete as a constraint; the data acquisition module 12 is used to interactively obtain the coating design information, and to collect environmental data based on the coating design information and the architectural design information to obtain associated environmental data; the loading module 13 is used to load the test building model into the environmental simulation system initialized by the associated environmental data after constructing the test building model according to the architectural design information; the quality tracking module 14 is used to drive the environmental simulation system to track the evolution of concrete quality of the coated building model during the process of performing small-scale coating on the test building model according to the coating design information to obtain the coated building model, and output the construction period concrete defect data and the service period concrete defect data; the defect evolution analysis module 15 is used to perform defect evolution analysis on the construction period concrete defect data and the service period concrete defect data, and output the full-cycle quality evaluation result.

[0057] Furthermore, the data acquisition module 12 is used to perform the following method:

[0058] Extracting coating construction time from the coating design information, wherein the coating design information includes a coating quality requirement set, a concrete mix ratio, coating construction parameters and the coating construction time; extracting building space coordinates from the building design information; performing a cross-search of environmental data using the coating construction time as a retrieval time constraint and the building space coordinates as a retrieval space constraint, and outputting the associated environmental data, wherein the associated environmental data includes construction environment data and extreme environment data.

[0059] Furthermore, the loading module 13 is used to execute the following method:

[0060] Preset a test scaling ratio; perform twin modeling according to the building design information to generate a regional virtual model; perform scaling and printing of the regional virtual model according to the test scaling ratio to obtain the test building model; decompose the construction environment data, obtain the construction period environment time series data, and use the construction period environment time series data to initialize the construction period simulation unit in the environmental simulation system; perform state transfer analysis on the extreme environment data, output the service period environment time series data, and initialize the service period simulation unit in the environmental simulation system according to the construction period environment time series data; load the test building model into the initialized environmental simulation system.

[0061] Furthermore, the loading module 13 is used to execute the following method:

[0062] The extreme environmental data are normalized to obtain K extreme environmental states; the building space coordinates are used as a single search condition to retrieve environmental data to obtain historical environmental data; the K extreme environmental states are used to traverse the historical environmental data, and K groups of environmental state transition probabilities are calculated and output; an environmental state prediction model is constructed according to the K extreme environmental states and the K groups of environmental state transition probabilities; after extracting the final environmental data of the construction period from the environmental time series data of the construction period, the final environmental data of the construction period is loaded into the environmental state prediction model to predict the state probability change, and an environmental state change sequence is output; the environmental state change sequence is smoothed to output the service period environmental time series data.

[0063] Furthermore, the quality tracking module 14 is used to perform the following method:

[0064] The concrete mix ratio and coating construction parameters are extracted from the coating design information; after pre-treating the plain concrete according to the concrete mix ratio, a small-scale coating of plain concrete is performed on the surface of the test building model according to the coating construction parameters; in the process of performing small-scale coating on the test building model to obtain a coated building model, the construction period simulation unit is driven to perform initial evolution of concrete quality on the coated building model, and the construction period concrete defect data is output; the service period environment time series data is used to drive the service period simulation unit to perform long-term evolution of concrete quality on the coated building model, and the service period concrete defect data is output.

[0065] Furthermore, the quality tracking module 14 is used to perform the following method:

[0066] The construction period simulation unit is driven to perform initial evolution of concrete quality on the coated building model, and output a construction period building model; the coating defect source analysis is performed on the coating quality requirement set, and M quality detection types are set according to the analysis results; M data acquisition devices are scheduled according to the M quality detection types to perform multi-dimensional data acquisition of the construction period building model, and M quality analysis data are obtained; the coating quality requirement set is extracted and called from the coating design information, and a coating defect recognition network is constructed based on the coating quality requirement set, wherein the coating defect recognition network includes M coating defect detection channels corresponding to the M quality detection types, and the M coating defect detection channels are connected in parallel; the M quality analysis data are mapped and loaded into the M coating defect detection channels of the coating defect recognition network, and the construction period concrete defect data is analyzed and output, wherein the construction period concrete defect data includes M groups of quality defect feature data, and the quality defect feature data includes quality defect position feature, quality defect size feature and quality defect type feature.

[0067] Furthermore, the defect evolution analysis module 15 is used to perform the following method:

[0068] The service period simulation unit is driven to perform long-term evolution of concrete quality on the construction period building model, and H service stage building models are output; after multi-dimensional data collection is performed on the H service stage building models, the data collection results are analyzed via the coating defect recognition network, and the service period concrete defect data is output, wherein the service period concrete defect data includes H service stage defect data; taking the construction period concrete defect data as the starting point and the M quality inspection types as the constraints, the construction period concrete defect data and the H service stage defect data are analyzed for defect expansion time series, and M groups of defect expansion speed sequences are output; time series extreme value extraction is performed on the M groups of defect expansion speed sequences to obtain M defect expansion extreme value sequences; the M quality inspection types and the M defect expansion extreme value sequences are stored in association, and output as the full-cycle quality evaluation result.

[0069] It should be noted that the above-mentioned sequence of the embodiments of the present application is only for description and does not represent the advantages and disadvantages of the embodiments. And the above-mentioned specific embodiments of this specification are described. The processes depicted in the accompanying drawings do not necessarily require the specific order or continuous order shown to achieve the desired results. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0070] The above description is only a preferred embodiment of the present application and is not intended to limit the present application. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present application shall be included in the protection scope of the present application.

[0071] This specification and drawings are merely exemplary illustrations of the present application and are deemed to cover any and all modifications, variations, combinations or equivalents within the scope of the present application. Obviously, a person skilled in the art may make various modifications and variations to the present application without departing from the scope of the present application. Thus, if these modifications and variations of the present application fall within the scope of the present application and its equivalents, the present application intends to include these modifications and variations.

Claims

1. A quality analysis and evaluation method for plain concrete, characterized in that: The method comprises: The architectural design information of the building to be constructed is partially framed with the decorative coating area of ​​the bare concrete as a constraint; Interactively obtain coating design information, and collect environmental data based on the coating design information and building design information to obtain associated environmental data; After constructing a test building model according to the building design information, loading the test building model into an environment simulation system initialized by the associated environment data; In the process of performing small-scale coating on the test building model according to the coating design information to obtain the coated building model, the environmental simulation system is driven to track the evolution of concrete quality of the coated building model, and outputs the concrete defect data during the construction period and the concrete defect data during the service period; Defect evolution analysis is performed on the concrete defect data during the construction period and the concrete defect data during the service period, and a full-cycle quality evaluation result is output.

2. The quality analysis and evaluation method for plain concrete according to claim 1, characterized in that: Interactively obtain coating design information, and collect environmental data based on the coating design information and architectural design information to obtain associated environmental data, the method comprising: Extracting coating construction time from the coating design information, wherein the coating design information includes a coating quality requirement set, a concrete mix ratio, coating construction parameters and the coating construction time; Extracting architectural space coordinates from the architectural design information; The coating construction time is used as a search time constraint and the building space coordinates are used as a search space constraint to perform a cross-search of the environmental data, and the associated environmental data is output, wherein the associated environmental data includes construction environmental data and extreme environmental data.

3. The quality analysis and evaluation method for plain concrete according to claim 2, characterized in that: After constructing a test building model according to the building design information, loading the test building model into an environment simulation system initialized by the construction environment data, the method comprises: Preset test scaling; Performing twin modeling according to the architectural design information to generate a regional virtual model; Performing scaling printing of the regional virtual model according to the test scaling ratio to obtain the test building model; After decomposing the construction environment data to obtain construction period environment time series data, the construction period environment time series data is used to initialize the construction period simulation unit in the environment simulation system; Performing state transition analysis on the extreme environment data, outputting service period environment time series data, and initializing the service period simulation unit in the environment simulation system according to the construction period environment time series data; The test building model is loaded into the initialized environmental simulation system.

4. The quality analysis and evaluation method for plain concrete according to claim 3, characterized in that: Performing state transition analysis on the extreme environment data and outputting service environment time series data, the method includes: Normalizing the extreme environment data to obtain K extreme environment states; Using the building space coordinates as a single search condition to search for environmental data, and obtain historical environmental data; Using the K extreme environmental states to traverse the historical environmental data, calculate and output K groups of environmental state transition probabilities; Constructing an environmental state prediction model according to the K extreme environmental states and K groups of environmental state transition probabilities; After extracting the final data of the construction period environment from the construction period environment time series data, the final data of the construction period environment is loaded into the environmental state prediction model to predict the state probability change, and output the environmental state change sequence; The environmental state change sequence is smoothed and the service period environmental time series data is output.

5. The quality analysis and evaluation method for plain concrete according to claim 4, characterized in that: In the process of performing small-scale coating on the test building model according to the coating design information to obtain the coated building model, the environmental simulation system is driven to track the concrete quality evolution of the coated building model, and the construction period concrete defect data and the service period concrete defect data are output. The method includes: Extracting the concrete mix ratio and coating construction parameters from the coating design information; After pre-treating the plain concrete according to the concrete mix ratio, a small-scale coating of the plain concrete is performed on the surface of the test building model according to the coating construction parameters; In the process of performing small-scale coating on the test building model to obtain the coated building model, driving the construction period simulation unit to perform initial evolution of concrete quality on the coated building model and outputting the construction period concrete defect data; The service period environment time series data is used to drive the service period simulation unit to perform long-term evolution of concrete quality on the coated building model, and the service period concrete defect data is output.

6. The quality analysis and evaluation method for plain concrete according to claim 5, characterized in that: The construction period simulation unit is driven to perform initial evolution of concrete quality on the coated building model, and the construction period concrete defect data is outputted. The method comprises: driving the construction period simulation unit to perform initial evolution of concrete quality on the coated building model, and outputting a construction period building model; Analyzing coating defect sources on the coating quality requirement set, and setting M quality inspection types according to the analysis results; According to the M types of quality inspection, M types of data acquisition equipment are dispatched to collect multi-dimensional data of the building model during the construction period to obtain M quality analysis data; Extracting and calling the coating quality requirement set from the coating design information, and constructing a coating defect recognition network based on the coating quality requirement set, wherein the coating defect recognition network includes M coating defect detection channels corresponding to the M quality detection types, and the M coating defect detection channels are connected in parallel; The M quality analysis data are mapped and loaded into the M coating defect detection channels of the coating defect recognition network, and the construction period concrete defect data are analyzed and output, wherein the construction period concrete defect data includes M groups of quality defect feature data, and the quality defect feature data includes quality defect position feature, quality defect size feature and quality defect type feature.

7. The quality analysis and evaluation method for plain concrete according to claim 6, characterized in that: Performing defect evolution analysis on the concrete defect data during construction and the concrete defect data during service, and outputting a full-cycle quality evaluation result, the method includes: driving the service period simulation unit to perform long-term evolution of concrete quality on the building model during the construction period, and outputting H service stage building models; After multi-dimensional data collection is performed on the H service stage building models, the data collection results are analyzed by the coating defect recognition network to output the service period concrete defect data, wherein the service period concrete defect data includes H service stage defect data; Taking the concrete defect data of the construction period as the starting point and the M types of quality inspection as the constraints, the defect expansion time series analysis is performed on the concrete defect data of the construction period and the H service stage defect data, and M groups of defect expansion speed sequences are output; Extracting time series extreme values ​​of the M groups of defect expansion speed sequences to obtain M defect expansion extreme value sequences; The M quality detection types and the M defect extension extreme value sequences are stored in association and output as the full-cycle quality evaluation result.

8. A quality analysis and evaluation device for plain concrete, characterized in that: The device is used to implement a quality analysis and evaluation method for plain concrete according to any one of claims 1 to 7, comprising: A frame information module is used to partially frame the architectural design information of the building to be constructed by taking the decorative coating area of ​​the plain concrete as a constraint; A data acquisition module, used to interactively obtain coating design information, and to collect environmental data based on the coating design information and architectural design information to obtain associated environmental data; A loading module, configured to load the test building model into an environment simulation system initialized by the associated environment data after constructing the test building model according to the building design information; A quality tracking module is used to drive the environmental simulation system to track the concrete quality evolution of the coated building model and output the concrete defect data of the construction period and the concrete defect data of the service period during the process of performing small-scale coating on the test building model according to the coating design information to obtain the coated building model; The defect evolution analysis module is used to perform defect evolution analysis on the concrete defect data during the construction period and the concrete defect data during the service period, and output a full-cycle quality evaluation result.

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