System for Evaluating Strength of Fast-Setting Concrete

Abstract

The present invention relates to a strength evaluation system for rapid-hardening concrete, comprising: a surface temperature measuring unit for measuring the surface temperature of poured concrete; a time measuring unit for measuring elapsed time; an ambient temperature acquiring unit for acquiring ambient temperature; a database storing a maturity relationship equation with surface temperature, elapsed time, and ambient temperature as variables; and a strength prediction unit for predicting and outputting the concrete compressive strength using the said maturity relationship equation. Through this, the compressive strength of the entire concrete surface can be predicted non-destructively and quickly at the site, thereby strengthening quality control and accurately determining the timing for early traffic opening.

Description

Technology Field

[0001] The present invention relates to a strength evaluation system for rapid-hardening concrete, and more specifically, to a system, method, and apparatus for non-destructively and in real-time predicting the compressive strength of cast rapid-hardening concrete using the concept of concrete maturity. Background Technology

[0002] Unless otherwise indicated in this specification, the contents described in this identification item are not prior art for the claims of this application, and are not recognized as prior art simply because they are described in this identification item.

[0003] In general, rapid-hardening concrete that develops high strength early is widely used at sites requiring rapid construction, such as bridge deck repair. Since rapid-hardening concrete must achieve a strength sufficient to open traffic within a few hours of pouring, on-site quality control is critical.

[0004] Conventional quality control of rapid-hardening concrete has been carried out by using sample specimens prepared on-site to evaluate whether the compressive strength at a specific age, for example, at the time of traffic opening, meets the standard value (e.g., 21 MPa). However, this method has several problems.

[0005] First, since strength is measured by destroying test specimens, the testing process is cumbersome and time-consuming, and specimens cannot be reused after being tested. Second, due to the lack of clear standards regarding specimen fabrication and curing management, it is difficult to regard the specimens as accurately representing the strength of the entire concrete structure actually poured. Third, strength evaluation using specimens is merely a point assessment of specific locations, which limits the ability to uniformly manage the overall quality of concrete pavements poured over large areas. Fourth, it is difficult to detect and address localized areas of poor curing or abnormalities that may occur during the curing process in real time.

[0006] Due to these issues, when traffic is opened prematurely while the actual structural strength falls short of standards, early damage such as concrete cracking or breakage occurs, becoming a major cause of reduced structural durability. Therefore, there is a need to develop new quality control technologies capable of non-destructively, rapidly, and accurately evaluating the strength of the entire rapid-hardening concrete cast on-site. Prior art literature

[0007] Patent Document 1: KR101586416B1 Patent Document 2: KR102010278B1 Patent Document 3: KR100696313B1 The problem to be solved

[0008] The embodiment of the present invention has been devised to solve the above-mentioned problems and aims to provide a strength evaluation system for rapid-hardening concrete that can improve quality control and prevent premature failure by non-destructively, rapidly, and accurately evaluating the strength of the entire laid surface at a site where rapid-hardening concrete is poured. means of solving the problem

[0009] To solve the above-mentioned problem, the present invention provides a strength evaluation system for rapid-hardening concrete characterized by comprising: a surface temperature measuring unit for measuring the surface temperature of poured concrete; a time measuring unit for measuring the elapsed time from the start of curing of the concrete; an environmental temperature acquisition unit for measuring or receiving the environmental temperature of the site where the concrete is poured; a database storing a maturity relationship equation with the surface temperature, elapsed time, and environmental temperature as variables; and a strength prediction unit that, when the elapsed time is input, predicts and outputs the compressive strength of the concrete at a corresponding time point using the maturity relationship equation.

[0010] It is preferable that the above surface temperature measuring unit includes a thermal imaging camera.

[0011] The above maturity relationship is effective when generated by performing regression analysis on test data regarding curing time, surface temperature, and compressive strength derived from indoor tests conducted under multiple different environmental temperature conditions.

[0012] The above regression analysis includes AI-based analysis, and it is desirable to perform it by selecting the model with the highest reliability among linear, logarithmic, or polynomial functions.

[0013] The above maturity relationship is based on an environmental temperature of 5 to 40 It is effective to have an integrated maturity relationship applicable to the entire range.

[0014] It is preferable that the above strength prediction unit be configured to predict early strength within 4 hours after concrete pouring.

[0015] It is effective for the above system to further include a user interface that collects surface temperature data measured at the site in real time and visually displays the curing status of the concrete paving surface.

[0016] It is preferable that the above user interface be a web-based interface executable on a tablet PC or mobile terminal.

[0017] The above system is effective if it further includes a data log that stores the measured surface temperature, ambient temperature, elapsed time, and predicted intensity along with field location information.

[0018] It is preferable that the above system further includes a judgment unit that determines whether traffic opening is possible or if there is a quality defect in the concrete based on the strength prediction result and provides a notification to the user.

[0019] The present invention, in another category, provides a method for evaluating the strength of rapid-hardening concrete, characterized by comprising: (a) a step of measuring the surface temperature of poured concrete using a thermal imaging camera; (b) a step of measuring the curing time of the concrete from the time of measuring the surface temperature; (c) a step of measuring or inputting the ambient temperature of the site where the concrete is poured; (d) a step of applying a maturity relationship equation with the surface temperature, elapsed time, and ambient temperature as variables; and (e) a step of predicting and outputting the compressive strength of the concrete corresponding to the elapsed time based on the maturity relationship equation.

[0020] It is preferable that the above maturity relationship be generated by analyzing data between curing time, surface temperature, and compressive strength derived from indoor tests conducted under multiple different environmental temperature conditions using artificial intelligence-based regression analysis.

[0021] The above regression analysis is effectively performed by selecting the function model with the highest reliability among linear, logarithmic, or polynomial functions based on the correlation coefficient or error value.

[0022] The above maturity relationship is based on an environmental temperature of 5 to 40 It is desirable to have an integrated maturity relationship applicable to the entire range.

[0023] The above predicted compressive strength is effective if it includes the early strength within 4 hours after concrete placement.

[0024] It is desirable to further include a step of determining whether traffic opening is possible or if there is a quality defect in the concrete based on the predicted compressive strength above.

[0025] The present invention provides a strength evaluation device for rapid-hardening concrete, characterized in that it comprises, in another category, a thermal imaging camera for measuring the surface temperature of poured concrete; a time input unit for receiving or automatically calculating the curing elapsed time of the concrete; an ambient temperature input unit for receiving the ambient temperature of the site where the concrete is poured; a storage unit for storing a maturity relationship equation with surface temperature, elapsed time, and ambient temperature as variables; and a strength calculation unit for predicting and outputting the concrete compressive strength at a corresponding point in time using the maturity relationship equation when the elapsed time is input.

[0026] It is preferable that the above maturity relationship equation be generated by processing indoor test results performed under multiple environmental temperature conditions using artificial intelligence-based regression analysis.

[0027] The above strength calculation unit is effective when configured to predict the compressive strength within 4 hours after concrete placement.

[0028] It is desirable that the above strength evaluation device outputs strength prediction results through a web-based interface executable on a tablet PC or mobile terminal.

[0029] The above strength evaluation device is effective if it further includes a data recorder that stores the predicted compressive strength along with field location information. Effects of the invention

[0030] According to the means for solving the problem of the present invention as described above, various effects including the following can be expected. However, the present invention is not required to exhibit all of the following effects to be valid.

[0031] According to the strength evaluation system for rapid-hardening concrete of the present invention, the surface temperature of the poured concrete is measured non-destructively and applied to a pre-derived maturity relationship to predict compressive strength in real time, thereby enabling rapid and efficient on-site quality control compared to conventional destructive specimen testing methods.

[0032] In addition, by using a thermal imaging camera to measure the temperature distribution over a wide area at once, it is possible to uniformly evaluate the quality of the entire concrete paving surface, and there is an advantage in being able to quickly identify localized areas of poor curing and take immediate action.

[0033] Furthermore, by using a highly reliable maturity relationship derived through AI-based regression analysis, the accuracy of compressive strength prediction is enhanced. By determining the timing of traffic opening based on objective data, this effectively prevents premature structural failure and ensures long-term durability.

[0034] In addition, since all measured data can be systematically managed and tracked by creating a database along with location information, it has the advantage of improving the reliability and objectivity of quality control.

[0035] Furthermore, implementing the system on a web basis on general-purpose devices such as tablet PCs or mobile terminals maximizes the usability and accessibility for field workers. Brief explanation of the drawing

[0036] FIG. 1 and below illustrate embodiments of the present invention, Figure 1 is a configuration diagram of a strength evaluation system for rapid-hardening concrete. Figure 2 is a configuration diagram of a strength evaluation device for rapid-hardening concrete. Figures 3 to 5 are photographs of the experimental process for obtaining experimental data of the maturity relationship equation. Figures 6 and 7 are graphs showing the relationship between surface temperature, elapsed time, and ambient temperature obtained by measuring the surface temperature and actual compressive strength over time while curing rapid-hardening concrete specimens at 7℃, 21℃, and 35℃. Figures 8 and 9 are graphs obtained by artificial intelligence (AI)-based regression analysis. FIGS. 10 to 13 are photographs of a prototype of a strength evaluation device for rapid-hardening concrete. Specific details for implementing the invention

[0037] Hereinafter, specific embodiments of the present invention will be described in detail with reference to the drawings.

[0038] A strength evaluation system for rapid-hardening concrete according to one embodiment of the present invention comprises a surface temperature measuring unit (100) for measuring the surface temperature of poured concrete, a time measuring unit (200) for measuring the elapsed time from the start of curing of the concrete, an environment temperature acquisition unit (300) for measuring or receiving the environment temperature of the site where the concrete is poured, a database (400) in which a maturity relationship equation is stored, and a strength prediction unit (500) for predicting and outputting the concrete compressive strength using the maturity relationship equation.

[0039] The surface temperature measuring unit (100) above serves to measure the surface temperature of the poured rapid-hardening concrete. Since concrete generates heat during the hydration reaction process, the surface temperature is closely related to the degree of internal hydration progress and strength development. In the present invention, in order to measure a large area quickly and non-destructively, it is preferable that the surface temperature measuring unit (100) include a thermal imaging camera (10). Since the thermal imaging camera (10) detects infrared energy emitted from the concrete surface and converts the temperature distribution into a visual image, the site manager can intuitively understand the curing status across the entire surface of the concrete paving.

[0040] The time measuring unit (200) measures the elapsed time from the time concrete pouring, i.e., curing, begins until the present. Since the strength of concrete is closely related to the curing time, the elapsed time is an important variable for strength prediction. The time measuring unit (200) can automatically measure time through a timer function implemented within the system.

[0041] The above-mentioned ambient temperature acquisition unit (300) acquires the ambient temperature, i.e., the ambient temperature, at the site where the concrete is poured. Since the external ambient temperature affects the hydration reaction rate of the concrete, it acts as an important variable in the development of strength. The above-mentioned ambient temperature acquisition unit (300) can be implemented by measuring the ambient temperature in real time through a temperature sensor or by a user directly inputting it through the user interface of the system.

[0042] The above database (400) stores a maturity relationship equation in which surface temperature, elapsed time, and ambient temperature are independent variables and compressive strength is a dependent variable. This maturity relationship equation is a core technology of the present invention and is derived based on experimental data performed in advance. Specifically, a vast amount of test data is obtained by curing rapid-hardening concrete specimens under multiple different ambient temperature conditions (e.g., 7℃, 21℃, 35℃) and measuring the surface temperature and actual compressive strength according to elapsed time. Subsequently, regression analysis is performed on the obtained test data to generate a relationship equation that represents the optimal correlation between the variables. At this time, an artificial intelligence (AI)-based analysis tool can be used for the regression analysis, and among various models such as linear functions, logarithmic functions, and polynomial functions, the model with the highest correlation coefficient (R²) and the lowest error, which has the highest reliability, is selected to derive the final maturity relationship equation. In particular, it is desirable to generate an integrated maturity relationship that is not limited to a specific temperature but is generally applicable to a wide range of environmental temperatures such as 5°C to 40°C, and store it in a database (400) so that it can be applied to various field environments such as the four seasons of Korea.

[0043] Figures 3 to 5 show the experimental process for obtaining the above experimental data, and are photographs of the hydration heat measurement process, surface temperature measurement process, and compressive strength measurement process, respectively.

[0044] Figures 6 and 7 are graphs showing the relationship between surface temperature, elapsed time, and ambient temperature obtained by measuring the surface temperature and actual compressive strength over time while curing rapid-hardening concrete specimens at 7℃, 21℃, and 35℃.

[0045] Figures 8 and 9 are graphs obtained by artificial intelligence (AI)-based regression analysis.

[0046]

[0047] Table 1 is a maturity relationship derived for ambient temperatures of 7℃, 21℃, and 35℃.

[0048]

[0049] Table 2 is an integrated maturity relationship derived for ambient temperatures from 5℃ to 40℃.

[0050]

[0051] Table 3 compares the measured compressive strength of concrete with the estimated compressive strength derived from the above maturity relationship.

[0052] It can be confirmed that there is some error when the ambient temperature is low (7℃), but the error is extremely small when it is higher.

[0053] The strength prediction unit (500) receives surface temperature, elapsed time, and ambient temperature values ​​from the surface temperature measuring unit (100), time measuring unit (200), and ambient temperature acquisition unit (300), respectively. Then, by substituting these values ​​into a maturity relationship equation stored in the database (400), it calculates and predicts the concrete compressive strength at the corresponding point in time. In particular, since securing early strength is important for rapid-hardening concrete, the strength prediction unit (500) can be configured to accurately predict the early strength within 4 hours after concrete pouring. The strength prediction unit (500) can be implemented with at least one processor, circuit, etc.

[0054] The system of the present invention may further include a user interface for user convenience. The user interface collects surface temperature data measured at the site in real time and displays it in the form of a thermal image, and clearly shows predicted compressive strength values ​​as numbers, thereby enabling the user to easily visually recognize the curing status of the concrete paving surface. Considering portability at the site, it is effective to implement such a user interface as a web-based interface executable on a tablet PC or mobile terminal.

[0055] Additionally, the system of the present invention may further include a data recording unit (600). The data recording unit (600) stores the measured surface temperature, ambient temperature, elapsed time, and predicted compressive strength values ​​in conjunction with site location information (e.g., GPS coordinates) on a server or in an internal storage space. Through this, the quality control history can be systematically databased and utilized for future data analysis and tracking management.

[0056] Furthermore, the system of the present invention may further include a judgment unit (700). The judgment unit (700) compares the predicted strength value output from the strength prediction unit (500) with a preset reference strength (e.g., 21 MPa for traffic opening). As a result of the comparison, if the predicted strength is greater than or equal to the reference strength, it notifies the user of a 'traffic opening possible' signal. If the predicted strength falls below the reference strength or if the thermal image analysis results indicate that the temperature of a specific area is significantly low and a quality defect is suspected, it provides the user with a notification such as 'caution' or 'curing reinforcement needed' to induce prompt on-site action. The judgment unit (700) may be implemented with at least one processor, circuit, etc.

[0057] A method for evaluating the strength of rapid-hardening concrete, which is another category of the present invention, using a system configured as described above, comprises the following steps. First, (a) a thermal imaging camera (10) is directed toward the surface of the poured concrete to measure the surface temperature. Next, (b) the curing elapsed time from the time of pouring the concrete to the present is measured, and (c) the ambient temperature at the site is measured or input. Next, (d) the system applies a pre-stored maturity relationship equation, (e) predicts the compressive strength of the concrete corresponding to the measured surface temperature, elapsed time, and ambient temperature, and outputs it through a user interface. Through this method, the user can quickly and accurately check the strength development status of the concrete at the site.

[0058] A strength evaluation device for rapid-hardening concrete, which is another category of the present invention, refers to a physical device for implementing the system and method described above, and may be configured to include a thermal imaging camera (10), a time input unit (20), an ambient temperature input unit (30), a storage unit (40) storing a maturity relationship equation, and a strength calculation unit (50). Here, each component performs substantially the same function as the corresponding component of the system. Such a device may be embedded in or operated in conjunction with a portable device such as a tablet PC or a mobile terminal. (Figs. 2, 10 to 13)

[0059] As described above, according to the strength evaluation system for rapid-hardening concrete of the present invention, the surface temperature of the poured concrete is measured non-destructively and applied to a pre-derived maturity relationship to predict compressive strength in real time. This enables rapid and efficient on-site quality control compared to conventional destructive specimen testing methods. Furthermore, by using a thermal imaging camera to measure the temperature distribution over a wide area at once, the quality of the entire concrete paving surface can be evaluated uniformly, and localized areas of poor curing can be quickly identified to allow for immediate corrective action. Additionally, by using a highly reliable maturity relationship derived through AI-based regression analysis, the accuracy of compressive strength prediction is enhanced. This allows for determining the timing of traffic opening based on objective data, thereby preventing premature structural failure and ensuring long-term durability.

[0060] Although preferred embodiments of the present invention have been described illustratively above, the scope of the present invention is not limited to such specific embodiments and can be appropriately modified within the scope described in the claims. Explanation of the symbols

[0061] 10: Thermal imaging camera 20: Time input section 30: Ambient temperature input section 40: Storage section 50: Strength calculation section 60: Data Record Book 100: Surface temperature measuring unit 200: Time measuring unit 300: Ambient temperature acquisition unit 400: Database 500: Strength prediction section 600: Data Record Book 700: Judgment Department

Claims

Claim 1 A system for evaluating the strength of rapid-hardening concrete comprises: a surface temperature measuring unit (100) for measuring the surface temperature of the poured concrete; a time measuring unit (200) for measuring the elapsed time from the start of curing the concrete; an environment temperature acquisition unit (300) for measuring or receiving the environment temperature of the site where the concrete is poured; a database (400) in which a maturity relationship equation is stored with the surface temperature, elapsed time, and environment temperature as variables; and a strength prediction unit (500) for predicting and outputting the concrete compressive strength at a corresponding time point using the maturity relationship equation when the elapsed time is input. The maturity relationship equation is characterized by being generated by performing regression analysis on test data between curing time, surface temperature, and compressive strength derived from indoor tests performed under multiple different environment temperature conditions. Claim 2 A strength evaluation system for rapid-hardening concrete according to claim 1, wherein the surface temperature measuring unit (100) includes a thermal imaging camera (10). Claim 3 delete Claim 4 A strength evaluation system for rapid-hardening concrete according to claim 1, wherein the regression analysis includes an artificial intelligence-based analysis and is performed by selecting the model with the highest reliability among a linear function, a logarithmic function, or a polynomial function. Claim 5 A strength evaluation system for rapid-hardening concrete according to claim 1, characterized in that the maturity relationship is an integrated maturity relationship applicable to the entire range of ambient temperatures from 5℃ to 40℃. Claim 6 A strength evaluation system for rapid-hardening concrete according to claim 1, wherein the strength prediction unit (500) is configured to predict early strength within 4 hours after concrete pouring. Claim 7 A strength evaluation system for rapid-hardening concrete according to claim 1, further comprising a user interface that collects surface temperature data measured at the site in real time and visually displays the curing status of the concrete paving surface. Claim 8 A strength evaluation system for rapid-hardening concrete according to claim 7, wherein the user interface is a web-based interface executable on a tablet PC or mobile terminal. Claim 9 A strength evaluation system for rapid-hardening concrete according to claim 1, further comprising a data recording unit (600) that stores the measured surface temperature, ambient temperature, elapsed time, and predicted strength together with site location information. Claim 10 A strength evaluation system for rapid-hardening concrete according to claim 1, further comprising a judgment unit (700) that determines whether traffic opening is possible or whether there is a quality defect in the concrete based on the strength prediction result and provides a notification to the user. Claim 11 A method for evaluating the strength of rapid-hardening concrete comprises: (a) a step of measuring the surface temperature of the poured concrete using a thermal imaging camera (10); (b) a step of measuring the curing elapsed time of the concrete from the time of measuring the surface temperature; (c) a step of measuring or inputting the ambient temperature of the site where the concrete is poured; (d) a step of applying a maturity relationship equation with the surface temperature, elapsed time, and ambient temperature as variables; and (e) a step of predicting and outputting the compressive strength of the concrete corresponding to the elapsed time based on the maturity relationship equation; wherein the maturity relationship equation is generated by analyzing data between curing time, surface temperature, and compressive strength derived from indoor tests performed under multiple different ambient temperature conditions using artificial intelligence-based regression analysis. Claim 12 delete Claim 13 A method for evaluating the strength of rapid-hardening concrete according to claim 11, wherein the regression analysis is performed by selecting the function model with the highest reliability based on the correlation coefficient or error value among a linear function, a logarithmic function, or a polynomial function. Claim 14 A method for evaluating the strength of rapid-hardening concrete according to claim 11, characterized in that the maturity relationship is an integrated maturity relationship applicable to the entire range of ambient temperatures from 5℃ to 40℃. Claim 15 A method for evaluating the strength of rapid-hardening concrete according to claim 11, characterized in that the predicted compressive strength includes early strength within 4 hours after concrete placement. Claim 16 A method for evaluating the strength of rapid-hardening concrete according to claim 11, further comprising the step of determining whether traffic opening is possible or whether there is a quality defect of the concrete based on the predicted compressive strength. Claim 17 A device for evaluating the strength of rapid-hardening concrete comprises: a thermal imaging camera (10) for measuring the surface temperature of the poured concrete; a time input unit (20) for receiving or automatically calculating the curing elapsed time of the concrete; an environment temperature input unit (30) for receiving the environment temperature of the site where the concrete is poured; a storage unit (40) for storing a maturity relationship equation with the surface temperature, elapsed time, and environment temperature as variables; and a strength calculation unit (50) for predicting and outputting the concrete compressive strength at a given point in time using the maturity relationship equation when the elapsed time is received, wherein the maturity relationship equation is generated by processing indoor test results performed under multiple environment temperature conditions using artificial intelligence-based regression analysis. Claim 18 delete Claim 19 A strength evaluation device for rapid-hardening concrete according to claim 17, wherein the strength calculation unit (50) is configured to predict the compressive strength within 4 hours after concrete pouring. Claim 20 A strength evaluation device for rapid-hardening concrete according to claim 17, characterized in that the strength evaluation device outputs strength prediction results through a web-based interface executable on a tablet PC or mobile terminal. Claim 21 A strength evaluation device for rapid-hardening concrete according to claim 17, characterized in that the strength evaluation device further includes a data recording unit (60) that stores the predicted compressive strength together with field location information.

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