Concrete production digital management method and system

Abstract

The invention discloses a concrete production digital management method and system, and relates to the technical field of concrete production processing, the method uses a three-dimensional modeling technology to simulate a concrete structure after pouring, and the application of the Internet of Things technology makes automatic uploading and real-time processing of cement hydration result data possible; in the aspect of risk assessment, based on threshold comparison of the hydration degree coefficient Scxs, an effective means is provided for early warning of the cracking risk, so that potential problems can be recognized in time in the initial setting stage of concrete, corresponding quality inspection measures are taken, and the cost of subsequent maintenance and rework is reduced. Besides, in the step S4, analysis of internal stress caused by temperature change is combined with construction of a fluctuation difference coefficient, and deep evaluation of the stability of the concrete is provided. Through comprehensive analysis of internal stress and fluctuation difference, the system can more comprehensively understand behaviors of concrete in the curing process.

Description

Technical Field

[0001] The present invention relates to the technical field of concrete production and processing, and in particular to a digital management method and system for concrete production. Background Art

[0002] In modern construction projects, the application of digital management technology is rapidly changing the traditional production model, especially in the field of concrete production. As the basis of building materials, the precise management of the production process of concrete directly affects the quality and safety of the project. Specifically, during the curing stage of concrete, the dynamic changes of cement hydration reaction significantly affect the physical properties and long-term performance of concrete. Therefore, monitoring the changes brought about by cement hydration reaction, especially the differences in changes during different monitoring periods, is crucial to evaluating the stability of concrete.

[0003] However, there are still some shortcomings in the current concrete production management. First, traditional monitoring methods often rely on manual observation and offline testing, which affects the accuracy of concrete stability assessment. Secondly, there are omissions in the dynamic grasp of cement hydration reaction, especially at different time points in the curing stage, there is a lack of systematic real-time monitoring and evaluation mechanism. Due to these defects, problems such as cracks and insufficient strength may occur in concrete production, thus affecting the safety and durability of the entire construction project. Therefore, a concrete production system based on digital management is urgently needed to be developed to solve the current problems of insufficient monitoring and delayed evaluation, and to achieve more accurate and efficient production management. Summary of the invention

[0004] In view of the deficiencies in the prior art, the present invention provides a digital management method and system for concrete production, which solves the problems in the above-mentioned background technology.

[0005] To achieve the above objectives, the present invention is implemented through the following technical solutions: a digital management method for concrete production, comprising the following steps:

[0006] S1. Use 3D modeling technology to simulate the poured concrete structure in advance to obtain a 3D model, monitor the cement hydration reaction in the initial setting stage based on the 3D model, monitor the relevant cement hydration results data of the concrete in real time, and monitor the relevant material property data of the concrete at the same time;

[0007] S2. Use the Internet of Things technology to automatically upload relevant cement hydration results data and related material property data to the cloud platform, and generate a production process data set after data preprocessing and dimensionless processing;

[0008] S3. Based on the relevant cement hydration results data in the production process data set, the hydration degree coefficient Scxs in each monitoring period is constructed, and a threshold is set in advance. The threshold is compared with the hydration degree coefficient Scxs to preliminarily determine whether there is a cracking risk for the concrete in the current initial setting stage. If so, a stage property inspection instruction is issued externally;

[0009] S4. After receiving the stage property inspection instruction, the concrete in the initial setting stage is subjected to a time series analysis to construct a fluctuation difference coefficient Byxs, and the internal stress Nyz caused by temperature changes during the solidification process is analyzed according to the relevant material property data. Based on the fluctuation difference coefficient Byxs and the internal stress Nyz, the stability evaluation index Wgzs is obtained by fitting;

[0010] S5. Preset an evaluation threshold value P, and compare and analyze the stability evaluation index Wgzs with the evaluation threshold value P to estimate the stability of the current concrete.

[0011] Preferably, S1 specifically includes:

[0012] S11. Use 3D modeling technology and select 3D modeling software in advance to simulate the concrete structure after pouring to obtain a 3D model, and collect relevant parameters of the concrete before pouring, including the proportion of various raw materials, the quality of various raw materials, and the water-cement ratio when the raw materials are mixed;

[0013] S12. Monitor the cement hydration reaction in the initial setting stage based on the three-dimensional model to monitor the relevant cement hydration results data of the concrete in real time, wherein the relevant cement hydration results data include the amount of hydration products generated Shcz, porosity Kxz, density, etc. in each monitoring period. and water-cement ratio; at the same time, monitor the relevant material properties of concrete, among which the relevant material properties include the elastic modulus of concrete , Thermal expansion coefficient of concrete at different temperatures , the temperature of concrete when it is poured into the mold and the temperature of the concrete during each monitoring period during the initial setting stage.

[0014] Preferably, S2 specifically includes:

[0015] S21. Use IoT technology to automatically upload relevant cement hydration results data and related material property data to the cloud platform via wireless network, and create real-time dashboards and reports to allow managers to remotely monitor production progress and adjust parameters in real time to deal with emergencies;

[0016] S22. Identify and remove noise duplicate values ​​and outliers in relevant cement hydration results data and relevant material property data, process missing values ​​through interpolation, and convert data of different scales into the same scale based on dimensionless processing technology.

[0017] Preferably, S3 specifically includes:

[0018] S31. Based on the relevant cement hydration results data in the production process data set, the porosity Kxz and the amount of hydration product Shcz are correlated, and after dimensionless processing, the hydration degree coefficient Scxs in each monitoring period is calculated, which is specifically obtained according to the following formula:

[0019]

[0020] In the formula, Expressed as density, and are weight values, Expressed as the first correction constant.

[0021] Preferably, S3 also includes:

[0022] S32. Preset a threshold value and compare the threshold value with the hydration degree coefficient Scxs in each monitoring period to preliminarily determine whether there is a risk of cracking of concrete in the initial setting stage in the corresponding period. The specific determination content is as follows:

[0023] If the hydration degree coefficient Scxs exceeds the threshold, it is preliminarily judged that there is no risk of cracking of concrete in the initial setting stage during the corresponding period;

[0024] If the hydration degree coefficient Scxs does not exceed the threshold, it is preliminarily judged that there is a risk of cracking of concrete in the initial setting stage within the corresponding period, and a stage property inspection instruction is issued.

[0025] Preferably, S4 specifically includes:

[0026] S41. After receiving the stage property inspection instruction, the concrete is subjected to a time series analysis based on the difference between the hydration degree coefficients Scxs in each monitoring period of the initial setting stage, and after dimensionless processing, the fluctuation difference coefficient Byxs is constructed, which is obtained in the following manner:

[0027]

[0028] Where n represents the number of intervals between adjacent monitoring periods, i=1, 2, 3, ..., n, It is expressed as the difference in hydration coefficient between the i-th adjacent monitoring periods, Expressed as the average hydration degree coefficient, It is expressed as the difference in water-cement ratio between the i-th adjacent monitoring periods, Expressed as the difference in average water-cement ratio.

[0029] Preferably, S4 also includes:

[0030] S42. According to the relevant material property data, analyze and obtain the internal stress Nyz caused by temperature changes during the curing process. The specific contents are as follows:

[0031]

[0032] In the formula, Expressed as the elastic modulus of concrete, Expressed as the coefficient of thermal expansion, Expressed as temperature change.

[0033] Preferably, S4 also includes:

[0034] S43. Convolutional neural network technology is used to construct a stability prediction model, and the fluctuation difference coefficient Byxs and the internal stress Nyz are input into the stability prediction model to obtain the stability evaluation index Wgzs by fitting, which is specifically obtained in the following manner:

[0035]

[0036] In the formula, and are weight values, Expressed as the second correction constant.

[0037] Preferably, S5 specifically includes:

[0038] S51. By comparing and analyzing the stability evaluation index Wgzs with the evaluation threshold P, the stability of the current concrete is estimated. The specific estimation contents are as follows:

[0039] If the stability evaluation index Wgzs falls within the evaluation threshold P, it is estimated that the stability of the current concrete is in an abnormal state. At this time, the water-cement ratio of the raw material mix will be dynamically adjusted according to the monitoring results, and the temperature and humidity will be fine-tuned according to the difference between the hydration degree coefficients Scxs in each monitoring period. At the same time, the maintenance frequency will be increased to 0.5 times the original frequency to ensure that the concrete is fully hydrated and solidified. The maintenance methods include covering the concrete surface with a wet cloth, sprinkling water, and using a curing agent;

[0040] If the stability evaluation index Wgzs does not fall within the evaluation threshold P, it is estimated that the stability of the current concrete is not in an abnormal state.

[0041] A digital management system for concrete production, comprising a production stage monitoring module, a data processing module, a hydration reaction analysis module, a curing stability analysis module and a production management module;

[0042] The production stage monitoring module is used to simulate the poured concrete structure in advance using the three-dimensional modeling technology to obtain a three-dimensional model, and monitor the cement hydration reaction in the initial setting stage based on the three-dimensional model to monitor the relevant cement hydration results data of the concrete in real time, and monitor the relevant material property data of the concrete at the same time;

[0043] The data processing module is used to automatically upload relevant cement hydration results data and relevant material property data to the cloud platform using the Internet of Things technology, and generate a production process data set after data preprocessing and dimensionless processing;

[0044] The hydration reaction analysis module is used to construct the hydration degree coefficient Scxs in each monitoring period based on the relevant cement hydration results data in the production process data set, and pre-set the threshold value, compare the threshold value with the hydration degree coefficient Scxs, so as to preliminarily judge whether there is a risk of cracking of concrete in the current initial setting stage. If so, a stage property inspection instruction is issued externally;

[0045] The curing stability analysis module is used to perform a time series analysis on the concrete in the initial setting stage after receiving the stage property inspection instruction, so as to construct the fluctuation difference coefficient Byxs, and analyze the internal stress Nyz caused by the temperature change during the curing process according to the relevant material property data, and obtain the stability evaluation index Wgzs by fitting based on the fluctuation difference coefficient Byxs and the internal stress Nyz;

[0046] The production management module is used to pre-set an evaluation threshold value P, and compare and analyze the stability evaluation index Wgzs with the evaluation threshold value P to estimate the stability of the current concrete.

[0047] The present invention provides a digital management method and system for concrete production, which has the following beneficial effects:

[0048] (1) This method uses three-dimensional modeling technology to simulate the concrete structure after pouring. It can not only monitor the progress of cement hydration reaction in real time, but also obtain relevant material property data of concrete. This method effectively solves the limitations of traditional monitoring methods, further avoids potential risks caused by data lag, and lays the foundation for the dynamic evaluation of concrete performance. Secondly, the application of Internet of Things technology makes it possible to automatically upload and process cement hydration results data in real time; in terms of risk assessment, based on the threshold comparison of the hydration degree coefficient Scxs, it provides an effective means for early warning of cracking risk, which enables potential problems to be identified in time during the initial setting stage of concrete, so that corresponding quality inspection measures can be taken, reducing the cost of subsequent maintenance and rework. In addition, the analysis of internal stress caused by temperature changes in step S4, combined with the construction of fluctuation difference coefficient, provides an in-depth evaluation of concrete stability. Through the comprehensive analysis of internal stress and fluctuation difference, the system can have a more comprehensive understanding of the behavior of concrete during the curing process. This multi-dimensional data analysis method not only improves the accuracy of concrete stability assessment, but also provides a scientific basis for concrete performance optimization. Finally, combined with the comparative analysis of the stability assessment index, it provides managers with a clear basis for decision-making, allowing the system to respond quickly when faced with abnormal conditions, effectively reducing the risks in concrete production.

[0049] (2) The hydration coefficient Scxs is calculated based on the production process data set, which can realize real-time monitoring and dynamic evaluation of the initial setting stage of concrete, and can more accurately reflect the state of concrete. And through the comparison and analysis of numerical values, the system can quickly determine whether there is a risk of cracking in concrete during real-time monitoring. This mechanism provides an active risk management strategy that can issue staged quality inspection instructions in a timely manner to prevent potential damage.

[0050] (3) Through the time series analysis of the hydration degree coefficient Scxs, the changing trend of concrete between different monitoring periods can be effectively revealed. This analysis method combines the differences between adjacent monitoring periods, not only providing a more comprehensive dynamic monitoring capability, but also timely identifying potential risk points. This difference analysis can help managers understand the stability of cement hydration reaction more clearly, and then optimize the concrete mix and construction strategy. Secondly, using the analysis of internal stress Nyz, the system can quantify the internal stress caused by temperature changes during the curing process. This analysis can provide in-depth insights into the physical properties of concrete by considering the effects of elastic modulus and thermal expansion coefficient. BRIEF DESCRIPTION OF THE DRAWINGS

[0051] Figure 1 A schematic diagram of a process flow of a digital management method for concrete production according to the present invention;

[0052] Figure 2This is a block diagram of a digital management system for concrete production according to the present invention. DETAILED DESCRIPTION

[0053] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. 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 creative work are within the scope of protection of the present invention.

[0054] Example 1

[0055] See also Figure 1 The present invention provides a digital management method for concrete production, comprising the following steps:

[0056] S1. Use 3D modeling technology to simulate the poured concrete structure in advance to obtain a 3D model, monitor the cement hydration reaction in the initial setting stage based on the 3D model, monitor the relevant cement hydration results data of the concrete in real time, and monitor the relevant material property data of the concrete at the same time;

[0057] S2. Use the Internet of Things technology to automatically upload relevant cement hydration results data and related material property data to the cloud platform, and generate a production process data set after data preprocessing and dimensionless processing;

[0058] S3. Based on the relevant cement hydration results data in the production process data set, the hydration degree coefficient Scxs in each monitoring period is constructed, and a threshold is set in advance. The threshold is compared with the hydration degree coefficient Scxs to preliminarily determine whether there is a cracking risk for the concrete in the current initial setting stage. If so, a stage property inspection instruction is issued externally;

[0059] S4. After receiving the stage property inspection instruction, the concrete in the initial setting stage is subjected to a time series analysis to construct a fluctuation difference coefficient Byxs, and the internal stress Nyz caused by temperature changes during the solidification process is analyzed according to the relevant material property data. Based on the fluctuation difference coefficient Byxs and the internal stress Nyz, the stability evaluation index Wgzs is obtained by fitting;

[0060] S5. Preset an evaluation threshold value P, and compare and analyze the stability evaluation index Wgzs with the evaluation threshold value P to estimate the stability of the current concrete.

[0061] After pouring, concrete will go through initial setting and final setting processes. Initial setting indicates that the cement begins to hydrate and the concrete becomes no longer fluid; final setting means that the concrete hardens to a certain extent and can no longer be manipulated.

[0062] In this embodiment, firstly, by real-time monitoring of cement hydration reaction and related material property data through three-dimensional modeling technology, the curing state of concrete can be further accurately grasped, thereby effectively improving the transparency and controllability of the concrete production process. Secondly, the data is automatically uploaded to the cloud platform using the Internet of Things technology. Combined with data preprocessing and dimensionless processing, the generated production process data set can provide a reliable basis for subsequent analysis and ensure the accuracy and effectiveness of the data. In addition, by constructing the hydration degree coefficient Scxs and setting the evaluation threshold, the system can timely judge the cracking risk of concrete in the initial setting stage and issue quality inspection instructions to prevent potential quality problems. After the staged quality inspection, the timing analysis helps to evaluate the changes and fluctuations in the internal stress of concrete during the curing process. Finally, through the fitting of the stability evaluation index, the stability of concrete is evaluated in many aspects, thereby further reducing the risks caused by concrete quality problems.

[0063] Example 2

[0064] Please refer to Figure 1 , specifically: S1 specifically includes:

[0065] S11. Use 3D modeling technology and select 3D modeling software, such as AutoCAD, Revit, ANSYS or SAP2000, to simulate the concrete structure after pouring in advance to obtain a 3D model and collect relevant parameters of the concrete before pouring, including the proportion of various raw materials, the quality of various raw materials and the water-cement ratio when the raw materials are mixed;

[0066] S12. Monitor the cement hydration reaction in the initial setting stage based on the three-dimensional model to monitor the relevant cement hydration results data of the concrete in real time, wherein the relevant cement hydration results data include the amount of hydration products generated Shcz, porosity Kxz, density, etc. in each monitoring period. and water-cement ratio; at the same time, monitor the relevant material properties of concrete, among which the relevant material properties include the elastic modulus of concrete , Thermal expansion coefficient of concrete at different temperatures , the temperature of concrete when it is poured into the mold and the temperature of the concrete during each monitoring period during the initial setting stage.

[0067] S2 specifically includes:

[0068] S21. Use IoT technology to automatically upload relevant cement hydration results data and related material property data to the cloud platform via wireless network to ensure the real-time and accuracy of the data, and create real-time dashboards and reports to allow managers to remotely monitor the production process and adjust parameters in real time to deal with emergencies;

[0069] S22. Identify and remove noise duplicate values ​​and outliers in the relevant cement hydration results data and related material properties data, and process the missing values ​​through interpolation, identify and delete duplicate records in the data set, and ensure that each data point is unique. And according to the dimensionless processing technology, convert data of different scales to the same scale, usually using z-score standardization or min-max normalization.

[0070] In this embodiment, first, using three-dimensional modeling technology and related software, the concrete structure can be accurately simulated and detailed pre-casting parameters can be obtained, which lays the foundation for subsequent cement hydration reaction monitoring. Real-time monitoring of hydration results data and material property data further ensures that managers can obtain the state changes of concrete in different monitoring periods in a timely manner, so as to better control the concrete performance during the curing process. Secondly, the application of Internet of Things technology enables data to be uploaded to the cloud platform in real time to ensure the real-time and accuracy of the data, which not only improves the transparency of the production process, but also allows managers to monitor remotely and quickly adjust production parameters when emergencies occur, effectively reducing the occurrence of potential problems. In addition, through data preprocessing and dimensionless processing, the system can effectively remove noise and outliers, ensure the quality of the data set, and improve the reliability of the analysis results. This series of measures will ultimately improve the stability and safety of concrete production, reduce production costs, and enhance market competitiveness.

[0071] Example 3

[0072] Please refer to Figure 1 , specifically: S3 specifically includes:

[0073] S31. Based on the relevant cement hydration results data in the production process data set, the porosity Kxz and the amount of hydration product Shcz are correlated, and after dimensionless processing, the hydration degree coefficient Scxs in each monitoring period is calculated, which is specifically obtained according to the following formula:

[0074]

[0075] In the formula, Expressed as density, and are weight values, Expressed as the first correction constant, where 0 < ≤1,0< ≤1, and + =1.

[0076] The porosity Kxz mentioned above refers to the ratio of the void volume in concrete to the total volume. Low porosity usually indicates that the cement is well hydrated and the hydrate contained in the pores increases, which helps to improve the strength and durability of the concrete. The porosity Kxz can be monitored and obtained by nitrogen adsorption method;

[0077] The amount of hydration products Shcz refers to the amount of hydrated silicate and calcium hydroxide produced. The solid products after cement hydration can be quantitatively analyzed by X-ray diffraction (XRD), and the type and content of hydration products can be determined by the diffraction pattern.

[0078] Density It refers to the mass of concrete per unit volume, usually expressed by the dry density of concrete. High density means that hydrates and aggregates in the concrete are closely arranged and the pores are effectively filled, thereby enhancing the overall structural stability of the concrete.

[0079] Cement hydration refers to the chemical process by which cement reacts with water to form a hydrated cementitious substance that gives concrete its strength and durability.

[0080] S3 also includes:

[0081] S32. Preset a threshold value and compare the threshold value with the hydration degree coefficient Scxs in each monitoring period to preliminarily determine whether there is a risk of cracking of concrete in the initial setting stage in the corresponding period. The specific determination content is as follows:

[0082] If the hydration degree coefficient Scxs exceeds the threshold, it is preliminarily judged that there is no risk of cracking of concrete in the initial setting stage during the corresponding period;

[0083] If the hydration degree coefficient Scxs does not exceed the threshold, it is preliminarily judged that there is a risk of cracking of concrete in the initial setting stage within the corresponding period, and a stage property inspection instruction is issued.

[0084] The setting of the threshold is obtained in the following way: statistics are collected on the hydration degree coefficient Scxs in each monitoring period, and the average hydration degree coefficient and the standard deviation of the hydration degree coefficient are obtained. Based on the average hydration degree coefficient and the standard deviation of the hydration degree coefficient, the threshold is set: threshold = average hydration degree coefficient + k* standard deviation of hydration degree coefficient; k is a constant, usually with a value of 1-3, corresponding to different confidence levels, and the specific value is set by the user (according to the actual situation);

[0085] In this embodiment, first, the porosity and the amount of hydration product generated are related by dimensionless processing technology, and the hydration degree coefficient Scxs is calculated, which can achieve a more accurate hydration assessment. This method allows the hydration conditions in different monitoring periods to be compared on the same scale, thereby improving the reliability of data analysis. And a weighted average method is adopted to consider the importance of different parameters, so that the calculation of the hydration degree coefficient is more in line with the actual situation. Secondly, the comparison and analysis of the set threshold and the hydration degree coefficient Scxs provides a scientific basis for the preliminary judgment of the cracking risk of concrete. When the hydration degree coefficient Scxs exceeds the set threshold, the system can immediately feedback that the stability of the concrete is good, otherwise it will issue a stage quality inspection instruction. This mechanism not only improves the monitoring efficiency, but also can take preventive measures in time to reduce potential quality risks. The innovation of this method is that by dynamically adjusting the threshold, it can adapt to the production needs under different environments and conditions, thereby enhancing the flexibility of the system. Finally, combined with real-time data monitoring and feedback mechanism, the system can identify potential cracking risks at an early stage when effectively monitoring concrete in the initial setting stage. This forward-looking risk management measure not only helps to reduce the rework rate and material waste, but also can extend the service life of concrete structures. By comprehensively utilizing data analysis and real-time monitoring technologies, the system promotes the intelligent upgrade of the concrete production process. In short, these beneficial effects and innovations not only improve the quality control capabilities of concrete production, but also provide technical support for more efficient and intelligent building materials production.

[0086] Example 4

[0087] Please refer to Figure 1 , specifically: S4 specifically includes:

[0088] S41. After receiving the stage property inspection instruction, the concrete is subjected to a time series analysis based on the difference between the hydration degree coefficients Scxs in each monitoring period of the initial setting stage, and after dimensionless processing, the fluctuation difference coefficient Byxs is constructed, which is obtained in the following manner:

[0089]

[0090] Where n represents the number of intervals between adjacent monitoring periods, i=1, 2, 3, ..., n, It is expressed as the difference in hydration coefficient between the i-th adjacent monitoring periods, Expressed as the average hydration degree coefficient, It is expressed as the difference in water-cement ratio between the i-th adjacent monitoring periods, Expressed as the difference in average water-cement ratio.

[0091] The water-cement ratio is the ratio between the mass of water and the mass of cement;

[0092] Due to fluctuations in the degree of hydration, it is difficult to accurately control the water-cement ratio, which may lead to reduced workability and strength of the concrete.

[0093] S4 also includes:

[0094] S42. According to the relevant material property data, analyze and obtain the internal stress Nyz caused by temperature changes during the curing process. The specific contents are as follows:

[0095]

[0096] In the formula, Expressed as the elastic modulus of concrete, Expressed as the coefficient of thermal expansion, Expressed as temperature change.

[0097] Modulus of elasticity of concrete The elastic modulus of concrete can be obtained through compression testing;

[0098] Coefficient of thermal expansion Through thermal expansion testing, the volume change of concrete at different temperatures is measured using a thermal analyzer (such as DSC) to determine the thermal expansion coefficient.

[0099] Temperature change Monitor the temperature changes of concrete in real time through temperature sensors such as thermocouples or infrared thermometers.

[0100] In this embodiment, firstly, the construction of the fluctuation difference coefficient Byxs can effectively capture the changing trend of the hydration degree coefficient Scxs in different monitoring periods. Through dimensionless processing, this coefficient not only simplifies the data comparison process, but also enables the hydration performance of different monitoring periods to be analyzed under the same standard. The difference between adjacent monitoring periods not only provides in-depth insights into the hydration process, but also helps engineers identify potential cracking risks, so as to take preventive measures more timely. Secondly, the analysis of internal stress Nyz combines the elastic modulus and thermal expansion coefficient of concrete. This process provides an in-depth understanding of the thermal effect during the concrete curing process. The effect of temperature change on internal stress is an important factor in the performance of concrete. By quantifying this effect, the prediction of concrete behavior is more accurate, and the system can provide a scientific basis for the crack resistance and overall stability of concrete. In addition, the analysis of the fluctuation difference coefficient and internal stress not only provides a basis for the immediate quality assessment of concrete, but also lays a foundation for the prediction of long-term performance, which means that in the future production and use of concrete, better maintenance and repair decisions can be made, maintenance costs can be reduced, and the service life of the structure can be extended. In summary, these steps not only further improve the scientific and intelligent level of the concrete production process, but also provide support for the sustainable development of the industry.

[0101] Example 5

[0102] Please refer to Figure 1 Specifically, S4 also includes:

[0103] S43. Convolutional neural network technology is used to construct a stability prediction model, and the fluctuation difference coefficient Byxs and the internal stress Nyz are input into the stability prediction model to obtain the stability evaluation index Wgzs by fitting, which is specifically obtained in the following manner:

[0104]

[0105] In the formula, and are weight values, Expressed as the second correction constant, where 0 < ≤1,0< ≤1, and + =1.

[0106] S5 specifically includes:

[0107] S51. By comparing and analyzing the stability evaluation index Wgzs with the evaluation threshold P, the stability of the current concrete is estimated. The specific estimation contents are as follows:

[0108] If the stability evaluation index Wgzs falls within the evaluation threshold P, it is estimated that the stability of the current concrete is in an abnormal state. At this time, the water-cement ratio of the raw material mix will be dynamically adjusted according to the monitoring results to improve the workability and strength of the concrete after curing. According to the difference between the hydration degree coefficients Scxs in each monitoring period, the temperature and humidity will be fine-tuned to avoid uneven hydration caused by excessively high or low temperatures. At the same time, the maintenance frequency will be increased to 0.5 times the original frequency to ensure that the concrete is fully hydrated and cured. The maintenance methods include covering the concrete surface with a wet cloth, sprinkling water, and using a curing agent to prevent the water from evaporating too quickly.

[0109] If the stability evaluation index Wgzs does not fall within the evaluation threshold P, it is estimated that the stability of the current concrete is not in an abnormal state.

[0110] In this embodiment, the in-depth analysis of concrete stability is realized through the fitting process of the stability evaluation index Wgzs. This method not only improves the accuracy of the evaluation, but also can effectively capture the slight changes of concrete during the curing process, so that managers can identify potential quality problems in a timely manner. Secondly, by dynamically adjusting the water-cement ratio in the raw material ratio, the system further realizes the real-time optimization of concrete workability and strength. This adjustment mechanism combines the real-time monitoring results, so that the adjustment of the water-cement ratio depends not only on the theoretical value, but is based on the specific conditions monitored in the actual production process, thereby improving the comprehensive performance of concrete. Furthermore, the fine-tuning of temperature and humidity further optimizes the curing environment and avoids the problem of uneven hydration. Finally, the system increases the maintenance frequency to 0.5 times the original frequency, which not only ensures the stability of concrete, but also improves the maintenance efficiency, making the maintenance process more flexible and efficient, and can adapt to different construction site conditions, thereby improving the construction quality. In summary, the system not only improves the stability and strength of concrete through advanced algorithms and dynamic adjustment mechanisms, but also optimizes the maintenance strategy in the production process, providing solid technical support for the intelligent and precise development of the concrete production industry.

[0111] Example 6

[0112] Please refer to Figure 2 ,Specifically: A digitized management system for concrete production, including a production stage monitoring module, a data processing module, a hydration reaction analysis module, a curing stability analysis module and a production management module;

[0113] The production stage monitoring module is used to simulate the poured concrete structure in advance using the three-dimensional modeling technology to obtain a three-dimensional model, and monitor the cement hydration reaction in the initial setting stage based on the three-dimensional model to monitor the relevant cement hydration results data of the concrete in real time, and monitor the relevant material property data of the concrete at the same time;

[0114] The data processing module is used to automatically upload relevant cement hydration results data and relevant material property data to the cloud platform using the Internet of Things technology, and generate a production process data set after data preprocessing and dimensionless processing;

[0115] The hydration reaction analysis module is used to construct the hydration degree coefficient Scxs in each monitoring period based on the relevant cement hydration results data in the production process data set, and pre-set the threshold value, compare the threshold value with the hydration degree coefficient Scxs, so as to preliminarily judge whether there is a risk of cracking of concrete in the current initial setting stage. If so, a stage property inspection instruction is issued externally;

[0116] The curing stability analysis module is used to perform a time series analysis on the concrete in the initial setting stage after receiving the stage property inspection instruction, so as to construct the fluctuation difference coefficient Byxs, and analyze the internal stress Nyz caused by the temperature change during the curing process according to the relevant material property data, and obtain the stability evaluation index Wgzs by fitting based on the fluctuation difference coefficient Byxs and the internal stress Nyz;

[0117] The production management module is used to pre-set an evaluation threshold value P, and compare and analyze the stability evaluation index Wgzs with the evaluation threshold value P to estimate the stability of the current concrete.

[0118] Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present invention, and that the scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. A digital management method for concrete production, characterized in that: The following steps are included: S1. Use 3D modeling technology to simulate the poured concrete structure in advance to obtain a 3D model, monitor the cement hydration reaction in the initial setting stage based on the 3D model, monitor the relevant cement hydration results data of the concrete in real time, and monitor the relevant material property data of the concrete at the same time; S2. Use the Internet of Things technology to automatically upload relevant cement hydration results data and related material property data to the cloud platform, and generate a production process data set after data preprocessing and dimensionless processing; S3. Based on the relevant cement hydration results data in the production process data set, the hydration degree coefficient Scxs in each monitoring period is constructed, and a threshold is set in advance. The threshold is compared with the hydration degree coefficient Scxs to preliminarily determine whether there is a cracking risk for the concrete in the current initial setting stage. If so, a stage property inspection instruction is issued externally; S4. After receiving the stage property inspection instruction, the concrete in the initial setting stage is subjected to a time series analysis to construct a fluctuation difference coefficient Byxs, and the internal stress Nyz caused by temperature changes during the solidification process is analyzed according to the relevant material property data. Based on the fluctuation difference coefficient Byxs and the internal stress Nyz, the stability evaluation index Wgzs is obtained by fitting; S5. Preset an evaluation threshold value P, and compare and analyze the stability evaluation index Wgzs with the evaluation threshold value P to estimate the stability of the current concrete.

2. A digital management method for concrete production according to claim 1, characterized in that: S1 specifically includes: S11. Use 3D modeling technology and select 3D modeling software in advance to simulate the concrete structure after pouring to obtain a 3D model, and collect relevant parameters of the concrete before pouring, including the proportion of various raw materials, the quality of various raw materials, and the water-cement ratio when the raw materials are mixed; S12. Monitor the cement hydration reaction in the initial setting stage based on the three-dimensional model to monitor the relevant cement hydration results data of the concrete in real time, wherein the relevant cement hydration results data include the amount of hydration products generated Shcz, porosity Kxz, density, etc. in each monitoring period. and water-cement ratio; at the same time, monitor the relevant material property data of concrete, among which the relevant material property data include the elastic modulus of concrete , Thermal expansion coefficient of concrete at different temperatures , the temperature of concrete when it is poured into the mold and the temperature of the concrete during each monitoring period during the initial setting stage.

3. A digital management method for concrete production according to claim 1, characterized in that: S2 specifically includes: S21. Use IoT technology to automatically upload relevant cement hydration results data and related material property data to the cloud platform via wireless network, and create real-time dashboards and reports to allow managers to remotely monitor production progress and adjust parameters in real time to deal with emergencies; S22. Identify and remove noise duplicate values ​​and outliers in relevant cement hydration results data and relevant material property data, process missing values ​​through interpolation, and convert data of different scales into the same scale based on dimensionless processing technology.

4. A digital management method for concrete production according to claim 2, characterized in that: S3 specifically includes: S31. Based on the relevant cement hydration results data in the production process data set, the porosity Kxz and the amount of hydration product Shcz are correlated, and after dimensionless processing, the hydration degree coefficient Scxs in each monitoring period is calculated, which is specifically obtained according to the following formula: In the formula, Expressed as density, and are weight values, Expressed as the first correction constant.

5. A digital management method for concrete production according to claim 4, characterized in that: S3 also includes: S32. Preset a threshold value and compare the threshold value with the hydration degree coefficient Scxs in each monitoring period to preliminarily determine whether there is a risk of cracking of concrete in the initial setting stage in the corresponding period. The specific determination content is as follows: If the hydration degree coefficient Scxs exceeds the threshold, it is preliminarily judged that there is no risk of cracking of concrete in the initial setting stage during the corresponding period; If the hydration degree coefficient Scxs does not exceed the threshold, it is preliminarily judged that there is a risk of cracking of concrete in the initial setting stage within the corresponding period, and a stage property inspection instruction is issued.

6. A digital management method for concrete production according to claim 5, characterized in that: S4 specifically includes: S41. After receiving the stage property inspection instruction, the concrete is subjected to a time series analysis based on the difference between the hydration degree coefficients Scxs in each monitoring period of the initial setting stage, and after dimensionless processing, the fluctuation difference coefficient Byxs is constructed, which is obtained in the following manner: Where n represents the number of intervals between adjacent monitoring periods, i=1, 2, 3, ..., n, It is expressed as the difference in hydration coefficient between the i-th adjacent monitoring periods, Expressed as the average hydration degree coefficient, It is expressed as the difference in water-cement ratio between the i-th adjacent monitoring periods, Expressed as the difference in average water-cement ratio.

7. A digital management method for concrete production according to claim 2, characterized in that: S4 also includes: S42. According to the relevant material property data, analyze and obtain the internal stress Nyz caused by temperature changes during the curing process. The specific contents are as follows: In the formula, Expressed as the elastic modulus of concrete, Expressed as the coefficient of thermal expansion, Expressed as temperature change.

8. A digital management method for concrete production according to claim 1, characterized in that: S4 also includes: S43. Convolutional neural network technology is used to construct a stability prediction model, and the fluctuation difference coefficient Byxs and the internal stress Nyz are input into the stability prediction model to obtain the stability evaluation index Wgzs by fitting, which is specifically obtained in the following manner: In the formula, and are weight values, Expressed as the second correction constant.

9. A digital management method for concrete production according to claim 1, characterized in that: S5 specifically includes: S51. By comparing and analyzing the stability evaluation index Wgzs with the evaluation threshold P, the stability of the current concrete is estimated. The specific estimation contents are as follows: If the stability evaluation index Wgzs falls within the evaluation threshold P, it is estimated that the stability of the current concrete is in an abnormal state. At this time, the water-cement ratio of the raw material mix will be dynamically adjusted according to the monitoring results, and the temperature and humidity will be fine-tuned according to the difference between the hydration degree coefficients Scxs in each monitoring period. At the same time, the maintenance frequency will be increased to 0.5 times the original frequency to ensure that the concrete is fully hydrated and solidified. The maintenance methods include covering the concrete surface with a wet cloth, sprinkling water, and using a curing agent; If the stability evaluation index Wgzs does not fall within the evaluation threshold P, it is estimated that the stability of the current concrete is not in an abnormal state.

10. A digital management system for concrete production, used to implement a digital management method for concrete production as claimed in any one of claims 1 to 9, characterized in that: It includes production stage monitoring module, data processing module, hydration reaction analysis module, curing stability analysis module and production management module; The production stage monitoring module is used to simulate the poured concrete structure in advance using the three-dimensional modeling technology to obtain a three-dimensional model, and monitor the cement hydration reaction in the initial setting stage based on the three-dimensional model to monitor the relevant cement hydration results data of the concrete in real time, and monitor the relevant material property data of the concrete at the same time; The data processing module is used to automatically upload relevant cement hydration results data and relevant material property data to the cloud platform using the Internet of Things technology, and generate a production process data set after data preprocessing and dimensionless processing; The hydration reaction analysis module is used to construct the hydration degree coefficient Scxs in each monitoring period based on the relevant cement hydration results data in the production process data set, and pre-set the threshold value, compare the threshold value with the hydration degree coefficient Scxs, so as to preliminarily judge whether there is a risk of cracking of concrete in the current initial setting stage. If so, a stage property inspection instruction is issued externally; The curing stability analysis module is used to perform a time series analysis on the concrete in the initial setting stage after receiving the stage property inspection instruction, so as to construct the fluctuation difference coefficient Byxs, and analyze the internal stress Nyz caused by the temperature change during the curing process according to the relevant material property data, and obtain the stability evaluation index Wgzs by fitting based on the fluctuation difference coefficient Byxs and the internal stress Nyz; The production management module is used to pre-set an evaluation threshold value P, and compare and analyze the stability evaluation index Wgzs with the evaluation threshold value P to estimate the stability of the current concrete.

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