A method for tracking and measuring the increase in concrete strength

Abstract

This invention provides a method for tracking and measuring the strength growth of concrete. The method mainly includes the following steps: collecting concrete raw material samples; conducting performance tests on the samples; performing orthogonal experiments on the samples; using computer regression analysis; collecting factors influencing concrete strength; establishing a calculation model based on these factors; inputting the method into production to obtain tracking and monitoring patterns; and iteratively forming an accurate prediction dataset. This method can intuitively and accurately obtain the concrete strength growth status of the structural entity after on-site pouring, solving the problem of large-scale, continuous, and three-dimensional tracking and monitoring of the strength growth of concrete materials used in civil engineering. Furthermore, it provides a scientific basis for project quality supervision and acceptance, construction process optimization, and the rational use of materials, which is beneficial for judging the final safety of the main structure, improving the controllability of the construction process, reducing engineering accidents, reducing construction costs, and improving project quality.

Description

Technical Field

[0001] This invention belongs to the field of concrete strength measurement technology, and in particular relates to a method for tracking and measuring the growth of concrete strength. Background Technology

[0002] Concrete is a man-made structural material with a series of advantages, such as low price, wide availability of raw materials, strong plasticity (shape, strength, density, etc.), good durability, and mature production technology. Therefore, it is widely used as a main structural material or filling material in civil engineering construction.

[0003] Concrete strength is one of the most important indicators determining concrete performance. Concrete strength increases from zero to a relatively stable level after a certain period (around 60 days). Before reaching its final strength, the increase in concrete strength is influenced by many factors, including the properties and quality of raw materials, concrete mix proportions, concrete production and transportation methods, concrete pouring methods, and curing conditions and methods for the components. The scope and degree of influence of these factors on the final concrete strength are interconnected, and many factors are in a state of constant dynamic change (such as temperature), making them difficult to accurately predict and control.

[0004] Currently, the main methods for judging the strength growth of concrete in actual engineering structures include: on-site compression testing of test blocks cured under the same conditions, rebound testing of structural surfaces, and core sampling of structural concrete. However, these methods have many drawbacks: there are significant differences between the test blocks cured under the same conditions and the structural body in terms of molding quality and curing conditions; the rebound method can only reflect local strength, especially surface strength; core drilling can damage the structure, and the drilled core samples are easily damaged; existing methods are time-consuming and labor-intensive from test preparation to results. These shortcomings make it difficult to conduct comprehensive, three-dimensional, and continuous monitoring of the strength of solid concrete, resulting in many projects failing to detect concrete strength quality defects in a timely manner, or leading to conservative designs that waste a lot of manpower and resources. Sometimes, misjudgments of concrete strength can even lead to major safety accidents. Summary of the Invention

[0005] The purpose of this invention is to provide a method for tracking and measuring the strength growth of concrete, which aims to solve the problem of continuous tracking and measuring the strength growth of concrete materials used in civil engineering, and to provide a scientific basis for engineering quality supervision and acceptance, construction process optimization, and rational use of materials.

[0006] This invention is implemented as follows: a method for tracking and measuring the increase in concrete strength includes the following steps:

[0007] S1. Configure a hardware system for analyzing, collecting, calculating, and presenting results throughout the entire concrete production process;

[0008] S2. Establish an analysis model for raw materials, including a raw material performance analysis model, a mix proportion comprehensive analysis model, a production and transportation condition analysis model, and a casting and curing condition analysis model;

[0009] S3. Based on the performance indicators in the raw material performance analysis model, collect a large number of concrete raw material samples covering various standardized and serialized performance indicators;

[0010] S4. Conduct performance tests on the collected concrete raw material samples to obtain the approximate range and frequency of performance indicators corresponding to each raw material performance analysis model in a certain area, and input them into the computer for later use through manual or automatic interfaces.

[0011] S5. Conduct orthogonal experiments using collected concrete raw material samples, with the concrete strength after standard curing at 3d, 7d, 14d, and 28d as the target, design the mix proportion reasonably according to regional market demand, set the water-cement ratio, water-cement ratio, and sand ratio, analyze the influence of each factor and level on the concrete strength, and input the tested concrete strength values ​​into the computer for later use.

[0012] S6. Use a computer program to perform regression analysis on the performance indicators and strength growth values ​​of the concrete raw material samples, and preliminarily establish the correlation between raw material performance, mix proportion indicators and concrete strength;

[0013] S7. Collect typical influencing factors of concrete pouring and curing process in the area, and input them into the computer for later use according to the rules determined by the pouring and curing condition analysis model; at the same time, conduct test tests on the strength growth law of typical concrete types according to the influencing factors, and preliminarily determine the degree and law of influence of concrete strength within a certain range of pouring and curing conditions; present the results in real time, and make the result judgment as required.

[0014] S8. Integrate the basic laws of multiple factors and multiple levels affecting concrete strength, introduce artificial intelligence computer programs, and establish a calculation model with self-optimization capabilities;

[0015] S9. Put the entire software and hardware system into actual production trials. Through multiple sets of parallel hardware equipment, continuously collect key information from concrete raw material sample tests, concrete production and transportation, concrete pouring and curing processes in a certain area, as well as strength data from on-site test blocks, rebound and core samples of concrete under the same conditions. Continuously revise the data in the same software model to obtain a general concrete strength growth tracking and monitoring pattern for that area.

[0016] Furthermore, the method of the present invention also includes the following steps:

[0017] S10. The entire software and hardware system is put into use. For each project, each part, and each type of concrete, under specific raw material, production and transportation conditions, pouring and curing conditions, the system can quickly provide an accurate prediction of concrete strength. Through the combination of system prediction and feedback from on-site experimental results, the system is continuously iterated to form an accurate prediction dataset.

[0018] Furthermore, in step S1 above, the hardware system includes various measuring instruments required for measuring concrete raw material samples according to national standard test methods; various machines and tools required for concrete mix design and on-site concrete placement quality testing; various temperature, humidity, time, stress, and strain sensors installed during concrete production, transportation, pouring, and curing processes to collect key information; various wires, radio transmitting and receiving devices installed to summarize various types of information; a computer for processing information, installing and calculating software, and presenting results; and a printer and display screen for outputting calculation results.

[0019] Furthermore, in step S2 above, establishing the comprehensive analysis model for the mix proportion includes classifying and categorizing important indicators such as water-cement ratio, water-cement ratio, sand ratio, amount of cementitious materials, amount of cement, type of admixture, slump and slump retention value, forming a standardized information source that can be easily input and managed.

[0020] Furthermore, in step S2 above, establishing the production and transportation condition analysis model includes classifying and categorizing important indicators such as mixer type, mixing time, feeding sequence, transportation time, transportation method, and transportation temperature to form a standardized information source that can be easily input and managed.

[0021] Furthermore, in step S3 above, the information corresponding to the material collection includes cement strength grade and manufacturer; sand type and origin; gravel type and origin; admixture type and manufacturer; and water-reducing agent type and manufacturer.

[0022] Furthermore, in step S3 above, the performance indicators in the raw material performance analysis model include the average measured standard curing strength of cement at 3d / 7d / 14d / 28d; fineness modulus, mud content, and mud lump content of sand; mud content, mud lump content, and crushing value of gravel; activity index, fineness, and water requirement ratio of admixtures; and water reduction rate of water-reducing agent.

[0023] Furthermore, in step S7 above, the influencing factors include pouring method, pouring time, pouring temperature, vibration method, curing method, structural form, formwork form, covering method, external temperature, internal temperature of concrete, and component size.

[0024] Furthermore, in step S7 above, the method for collecting the influencing factors includes determining the influencing factors and reasonably classifying the influence levels; some information in the method can be manually input, while some information can be automatically collected by instruments.

[0025] Furthermore, in step S8 above, the calculation model includes qualitative analysis results of the influencing factors of concrete strength growth under certain conditions, obtained through mathematical calculation; quantitative analysis results of the main influencing factors of concrete strength growth under certain conditions; and a calculation software model that is universally applicable to the prediction of concrete strength growth under different conditions.

[0026] Compared with the prior art, the beneficial effects of this invention are as follows:

[0027] This invention provides a method for tracking and measuring the strength growth of concrete. This method can intuitively and accurately obtain the strength growth status of the concrete in a structural entity after on-site pouring, solving the problem of large-scale, continuous, and three-dimensional tracking and monitoring of the strength growth of concrete materials used in civil engineering. This provides a scientific basis for project quality supervision and acceptance, construction process optimization, and the rational use of materials. It is beneficial for judging the final safety of the main structure, improving the controllability of the construction process, reducing the occurrence of engineering accidents, reducing construction costs, and improving project quality. Attached Figure Description

[0028] Figure 1 This is a flowchart of a method for tracking and measuring the increase in concrete strength provided in an embodiment of the present invention. Detailed Implementation

[0029] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the invention.

[0030] Please refer to Figure 1 This embodiment illustrates a method for tracking and measuring the increase in concrete strength, comprising the following steps:

[0031] S1. Configure a hardware system for analyzing, collecting, calculating, and presenting results throughout the entire concrete production process; the hardware system includes various measuring instruments required for measuring concrete raw material samples according to national standard test methods; various machines and tools required for concrete mix design and on-site concrete placement quality testing; various temperature, humidity, time, stress, and strain sensors installed during concrete production, transportation, pouring, and curing processes to collect key information; various wires, radio transmitters and receivers installed to aggregate various types of information; a computer for processing information, installing and calculating software, and presenting results; and a printer and display screen for outputting calculation results.

[0032] S2. Establish an analysis model for raw materials, including a raw material performance analysis model, a mix proportion comprehensive analysis model, a production and transportation condition analysis model, and a pouring and curing condition analysis model.

[0033] Specifically, establishing the comprehensive analysis model for the mix proportion involves classifying and categorizing important indicators such as water-cement ratio, water-cement ratio, sand ratio, amount of cementitious materials, amount of cement, type of admixtures, slump, and slump retention value to form a standardized information source that can be easily input and managed.

[0034] Specifically, establishing the production and transportation condition analysis model involves classifying and categorizing important indicators such as mixer type, mixing time, feeding sequence, transportation time, transportation method, and transportation temperature to form a standardized information source that can be easily input and managed.

[0035] S3. Based on the performance indicators in the raw material performance analysis model, collect a large number of concrete raw material samples covering various standardized and serialized performance indicators.

[0036] Because the raw materials used in concrete are not suitable for long-distance transportation, the performance indicators of these raw materials are usually regional. For example, the Yangtze River Delta and the Pearl River Delta are considered as one region, but data must be collected separately for each region. The information collected for these materials includes cement strength grade and manufacturer; sand type and origin; aggregate type and origin; admixture type and manufacturer; and water-reducing agent type and manufacturer.

[0037] Specifically, the performance indicators in the raw material performance analysis model include the average measured standard curing strength of cement at 3d / 7d / 14d / 28d; fineness modulus, mud content, and mud lump content of sand; mud content, mud lump content, and crushing value of gravel; activity index, fineness, and water requirement ratio of admixtures; and water reduction rate of water-reducing agents.

[0038] S4. Conduct performance tests on the collected concrete raw material samples to obtain the approximate range and frequency of performance indicators corresponding to each raw material performance analysis model in a certain area, and input them into the computer for later use via manual or automatic interface.

[0039] S5. Conduct orthogonal experiments using collected concrete raw material samples, with the concrete strength after standard curing at 3d, 7d, 14d, and 28d as the target. Design the mix proportion reasonably according to regional market demand, set the water-cement ratio, water-cement ratio, and sand ratio, analyze the influence of each factor and level on the concrete strength, and input the tested concrete strength values ​​into the computer for later use.

[0040] S6. Using a computer program, regression analysis is performed on the performance indicators and strength growth values ​​of the concrete raw material samples to preliminarily establish the correlation between raw material performance, mix proportion indicators and concrete strength.

[0041] S7. Collect typical influencing factors of concrete pouring and curing process in the area, and input them into the computer for later use according to the rules determined by the pouring and curing condition analysis model; at the same time, conduct test tests on the strength growth law of typical concrete types (such as ordinary C30, slump 200mm) according to the influencing factors, and preliminarily determine the degree of influence and law of concrete strength under certain pouring and curing conditions; present the results in real time, and make the result judgment as required.

[0042] Specifically, the computer automatically generates real-time values ​​of concrete strength growth under input conditions, and these values ​​can be converted into images or output in paper form. The final calculation result can be a theoretical inference of concrete strength value under certain conditions, or a strength growth prediction and verification combined with on-site conditions. The calculation result can be compared and judged with the design value and the on-site measured value.

[0043] Specifically, the influencing factors include pouring method, pouring time, pouring temperature, vibration method, curing method, structural form, formwork form, covering method, external temperature, internal temperature of concrete, and component size; the method for collecting the influencing factors includes determining the influencing factors and reasonably classifying the influence level; some information in the method can be manually input, while some information can be automatically collected by instruments.

[0044] S8. Integrate the basic laws governing the influence of multiple factors and levels on concrete strength, introduce artificial intelligence computer programs, and establish a calculation model with self-optimization capabilities.

[0045] Specifically, the calculation model includes qualitative analysis results of the influencing factors of concrete strength growth under certain conditions, obtained through mathematical calculations; quantitative analysis results of the main influencing factors of concrete strength growth under certain conditions; and a calculation software model that is universally applicable to predicting concrete strength growth under different conditions.

[0046] S9. The entire hardware and software system is put into actual production testing. Multiple sets of parallel hardware equipment continuously collect key information from concrete raw material sample tests, concrete production and transportation, and concrete pouring and curing processes within a specific area. This information, along with strength data from on-site test blocks, rebound hammers, and core samples, is then continuously refined within a single software model to obtain a universally applicable concrete strength growth tracking and monitoring pattern for the region. This pattern can provide quantitative results on concrete strength when any factor affecting concrete strength growth changes, and the results can be presented through data and images.

[0047] S10. The entire software and hardware system is put into use. For each project, each part, and each type of concrete, under specific raw material, production and transportation conditions, pouring and curing conditions, the system can quickly provide accurate predictions of concrete strength. By combining system predictions with feedback from on-site experimental results, it continuously iterates to form an accurate prediction dataset, thereby continuously improving the accuracy and precision of the method.

[0048] In summary, this embodiment provides a method for tracking and measuring the strength growth of concrete. This method can intuitively and accurately obtain the concrete strength growth status of the structural entity after on-site pouring, solving the problem of large-scale, continuous, and three-dimensional tracking and monitoring of the strength growth of concrete materials used in civil engineering. This provides a scientific basis for project quality supervision and acceptance, construction process optimization, and the rational use of materials, which is beneficial for judging the final safety of the main structure, improving the controllability of the construction process, reducing the occurrence of engineering accidents, reducing construction costs, and improving project quality.

[0049] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A method for tracking and measuring the increase in concrete strength, characterized in that, Includes the following steps: S1. Configure a hardware system for analyzing, collecting, calculating, and presenting results throughout the entire concrete production process; S2. Establish an analysis model for raw materials, including a raw material performance analysis model, a mix proportion comprehensive analysis model, a production and transportation condition analysis model, and a casting and curing condition analysis model; S3. Based on the performance indicators in the raw material performance analysis model, collect a large number of concrete raw material samples covering various standardized and serialized performance indicators; S4. Conduct performance tests on the collected concrete raw material samples to obtain the approximate range and frequency of performance indicators corresponding to each raw material performance analysis model in a certain area, and input them into the computer for later use through manual or automatic interfaces. S5. Conduct orthogonal experiments using collected concrete raw material samples, with the concrete strength after standard curing at 3d, 7d, 14d, and 28d as the target, design the mix proportion reasonably according to regional market demand, set the water-cement ratio, water-cement ratio, and sand ratio, analyze the influence of each factor and level on the concrete strength, and input the tested concrete strength values ​​into the computer for later use. S6. Use a computer program to perform regression analysis on the performance indicators and strength growth values ​​of the concrete raw material samples, and preliminarily establish the correlation between raw material performance, mix proportion indicators and concrete strength; S7. Collect typical influencing factors of concrete pouring and curing process in the area, and input them into the computer for later use according to the rules determined by the pouring and curing condition analysis model; at the same time, conduct test tests on the strength growth law of typical concrete types according to the influencing factors, and preliminarily determine the degree and law of influence of concrete strength within a certain range of pouring and curing conditions; present the results in real time, and make the result judgment as required. S8. Integrate the basic laws of multiple factors and multiple levels affecting concrete strength, introduce artificial intelligence computer programs, and establish a calculation model with self-optimization capabilities; S9. Put the entire software and hardware system into actual production trials. Through multiple sets of parallel hardware equipment, continuously collect key information from concrete raw material sample tests, concrete production and transportation, concrete pouring and curing processes in a certain area, as well as strength data from on-site test blocks, rebound and core samples of concrete under the same conditions. Continuously revise the data in the same software model to obtain a general concrete strength growth tracking and monitoring pattern for that area.

2. The tracking and measurement method as described in claim 1, characterized in that, It also includes the following steps: S10. The entire software and hardware system is put into use. For each project, each part, and each type of concrete, under specific raw material, production and transportation conditions, pouring and curing conditions, the system can quickly provide an accurate prediction of concrete strength. Through the combination of system prediction and feedback from on-site experimental results, the system is continuously iterated to form an accurate prediction dataset.

3. The tracking and measurement method as described in claim 1, characterized in that, In step S1, the hardware system includes various measuring instruments required for measuring concrete raw material samples according to national standard test methods; various machines and tools required for concrete mix design and on-site concrete placement quality testing; various temperature, humidity, time, stress, and strain sensors installed during concrete production, transportation, pouring, and curing processes to collect key information; various wires, radio transmitting and receiving devices installed to summarize various types of information; a computer for information processing, software installation and calculation, and result presentation; and a printer and display screen for outputting calculation results.

4. The tracking and measurement method as described in claim 1, characterized in that, In step S2, establishing the comprehensive analysis model for the mix proportion includes classifying and categorizing important indicators such as water-cement ratio, water-cement ratio, sand ratio, amount of cementitious materials, amount of cement, type of admixture, slump and slump retention value, forming a standardized information source that can be easily input and managed.

5. The tracking and measurement method as described in claim 1, characterized in that, In step S2, establishing the production and transportation condition analysis model includes classifying and categorizing important indicators such as mixer type, mixing time, feeding sequence, transportation time, transportation method, and transportation temperature to form a standardized information source that can be easily input and managed.

6. The tracking and measurement method as described in claim 1, characterized in that, In step S3, the information collected during material collection includes cement strength grade and manufacturer; sand type and origin; gravel type and origin; admixture type and manufacturer; and water-reducing agent type and manufacturer.

7. The tracking and measurement method as described in claim 1, characterized in that, In step S3, the performance indicators in the raw material performance analysis model include the average measured standard curing strength of cement at 3d / 7d / 14d / 28d; fineness modulus, mud content, and mud lump content of sand; mud content, mud lump content, and crushing value of gravel; activity index, fineness, and water requirement ratio of admixtures; and water reduction rate of water-reducing agent.

8. The tracking and measurement method as described in claim 1, characterized in that, In step S7, the influencing factors include pouring method, pouring time, pouring temperature, vibration method, curing method, structural form, formwork form, covering method, external temperature, internal temperature of concrete, and component size.

9. The tracking and measurement method as described in claim 1, characterized in that, In step S7, the method for collecting the influencing factors includes determining the influencing factors and reasonably classifying the influence levels; some information can be manually input, while other information can be automatically collected by instruments.

10. The tracking and measurement method as described in claim 1, characterized in that, In step S8, the calculation model includes qualitative analysis results of the influencing factors of concrete strength growth under certain conditions, obtained through mathematical calculation; quantitative analysis results of the main influencing factors of concrete strength growth under certain conditions; and a calculation software model that is universally applicable to the prediction of concrete strength growth under different conditions.

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