Concrete rebound strength analysis method and system
By screening actual external factors during concrete curing, correcting rebound strength, and optimizing curing schemes, the problem of low accuracy in concrete rebound strength measurement was solved, enabling more accurate rebound strength prediction and test age determination, and reducing the frequency of measurement.
Patent Information
- Application Number
- CN202511201050.0
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-08-26
- Publication Date
- 2025-11-18
AI Technical Summary
Existing concrete rebound strength testing methods suffer from poor reading accuracy due to operational errors and abnormalities in the concrete wall surface. This makes it difficult to accurately reflect the optimal testing age when the concrete strength tends to stabilize, and multiple tests are required, which consumes manpower, resources, and time.
By obtaining the measured rebound strength and external environmental factors during the concrete curing process, actual external factors are screened, rebound strength is corrected, the optimal test age is predicted, and the curing plan is optimized.
It improves the accuracy of rebound strength analysis, reduces the frequency of measurement, and saves manpower, material resources, and time costs.
Smart Images
Figure CN120971241A_ABST
Abstract
Description
Technical Field
[0001] This invention relates to the field of concrete testing technology, and in particular to a method and system for analyzing the rebound strength of concrete. Background Technology
[0002] Concrete rebound strength refers to a method for testing the compressive strength of concrete using the rebound method. The rebound method uses a spring-driven hammer to strike the concrete surface via a strike bar (force transmission bar), and measures the distance the hammer bounces back. The rebound value (the ratio of the rebound distance to the initial length of the spring) is used as a strength-related indicator to estimate the concrete strength.
[0003] Current methods for determining concrete rebound strength typically employ the rebound method, using a rebound hammer to directly read and average the rebound strength values at various test points on the concrete surface. However, operational errors and abnormalities in the concrete wall surface can lead to inaccurate rebound strength measurements, resulting in poor reading precision and an inability to accurately reflect the rebound strength of the concrete at a given time. Furthermore, it is difficult to accurately determine the optimal testing age when the concrete strength tends to stabilize, requiring testing personnel to frequently visit the construction site for measurements, which is extremely costly in terms of manpower, resources, and time. Summary of the Invention
[0004] This invention provides a method and system for analyzing the rebound strength of concrete, which solves the technical problems in the prior art where operational errors, abnormalities in concrete walls, etc., can lead to inaccurate rebound strength measurements, resulting in poor reading accuracy and difficulty in accurately reflecting the rebound strength of concrete at a given time. Furthermore, it is not easy to accurately control the optimal testing age when the concrete strength tends to stabilize when measuring rebound strength.
[0005] To achieve the above and other related objectives, this invention provides a method for analyzing the rebound strength of concrete, comprising: obtaining the measured rebound strength during the concrete curing process; collecting all estimated external factors affecting the measured rebound strength corresponding to the external environment of the concrete; evaluating the estimated external factors based on the measured rebound strength and the cured data of the concrete, and screening out the actual external factors affecting the formation of the measured rebound strength; performing a steady-state evaluation based on the actual external factors and the measured rebound strength to obtain a stable rebound strength value; selecting a corresponding curing scheme based on the stable rebound strength value; and predicting the optimal test age based on the feedback rebound strength corresponding to the curing scheme, the actual external factors, and the measured rebound strength.
[0006] In one embodiment of the present invention, obtaining the measured rebound strength during the concrete curing process includes: obtaining initial measurement data during the concrete curing process, the initial measurement data including the initial rebound strength, a first image data corresponding to the concrete surface before the initial rebound strength measurement, and a second image data corresponding to the concrete surface after the initial rebound strength measurement; based on the first image data and the second image data, correcting and obtaining the pit shape data corresponding to the pit formed during the rebound hammer test; determining a correction coefficient for the initial rebound strength based on the pit shape data; adjusting the initial rebound strength using the correction coefficient to obtain the measured rebound strength during the concrete curing process.
[0007] In one embodiment of the present invention, determining the shape data of the pit formed during the rebound test based on first image data and second image data includes: obtaining initial shape data of the pit in the second image data, the initial shape data including the coordinates of a second center point. and the second region that forms the pit Based on the initial shape data of the pit in the second image data, the coordinates of the first center point of the pit in the first image data are obtained. and the first area range For the first area Feature monitoring was performed to obtain abnormal features. The abnormal features include abnormal pits, abnormal protrusions, abnormal cracks, and abnormal surface roughness on the concrete surface; based on the abnormal features... The eigenvalues are used to obtain the offset influence data that forms the initial shape data. Based on offset impact data Generate adjustment matrix The initial shape data is corrected to determine the shape data of the pit formed during the rebound test.
[0008] In one embodiment of the present invention, the feature value includes the abnormal location and abnormal shape corresponding to the abnormal feature; based on the abnormal feature The eigenvalues are used to obtain the offset influence data that forms the initial shape data. This includes: based on abnormal characteristics Corresponding abnormal location and abnormal shapes The coordinates of the position relative to the first center point are obtained. Abnormal areas in different orientations and abnormal areas Corresponding multiple abnormal shapes Total anomaly volume ; for abnormal areas Anomaly center coordinates Compared to the coordinates of the first center point Calculate the abnormal offset distance at the corresponding offset azimuth to obtain the abnormal offset distance at the corresponding offset azimuth. Based on the abnormal area Corresponding total anomaly volume and abnormal offset distance The abnormal shape offset of the pit along the corresponding offset direction is obtained. and abnormal offset direction Based on the abnormal offset direction corresponding to all offset orientations for each abnormal feature. and shape anomaly offset The offset influence data that forms the initial shape data is obtained. .
[0009] In one embodiment of the present invention, determining a correction coefficient for the initial rebound strength based on the pit shape data includes: comparing the pit shape data with standard pit shape data to obtain the operational error of the rebound hammer in generating the pit shape data during testing. The offset influence data corresponding to the corrected pit shape data. and corresponding influencing moderating factors To obtain the first degree of influence value According to the first degree of influence value and the first correction factor The first correction factor was calculated. Based on operational error Second correction factor The second correction coefficient was calculated. According to the first correction factor Second correction coefficient Determine the correction factor for the initial rebound strength. .
[0010] In one embodiment of the present invention, based on the measured rebound strength and the cured concrete data, the estimated external factors are evaluated, and the actual external factors are screened out, including: comparing at least two consecutive rebound strength measurements to obtain the rebound strength difference. Among them, the two consecutive rebound strength measurements include the previous rebound strength measurement. And the next rebound strength measurement Based on the difference in rebound strength Formation time Compared to the last time the rebound strength was measured The theoretical rebound strength is converted to obtain the next theoretical rebound strength. Based on existing maintenance data Next theoretical rebound strength Next time, measure the rebound strength. and formation time The estimated external factors are evaluated, and the actual external factors are selected.
[0011] In one embodiment of the present invention, based on the maintenance data Next theoretical rebound strength Next time, measure the rebound strength. and formation time The estimated external factors are evaluated, and the actual external factors are screened out, including those based on the formation time. Maintenance data corresponding to a unit maintenance time and coefficient conversion factor This yields the rebound strength for the next measurement. Corrected rebound strength correction factor Based on the rebound strength correction factor For the next measurement of rebound strength Make corrections to obtain the next corrected rebound strength. ; for the next correction of rebound strength and the next theoretical rebound strength Compare and obtain the difference value When the difference value Greater than the preset value Then, all estimated external factors are combined to obtain a factor set; based on the historical impact of the rebound strength corresponding to each estimated external factor in the factor set. and formation time The comprehensive influence value of rebound strength is obtained. The combined impact value of rebound strength corresponding to all factors. and difference value Compare and find the difference value The closest combined impact value of rebound strength ; will be compared with the difference value The closest combined impact value of rebound strength The corresponding set of factors serves as the actual external factors.
[0012] In one embodiment of the present invention, a steady-state assessment is performed based on actual external factors and measured rebound strength to obtain a stable rebound strength value, including: a comprehensive influence value of rebound strength based on the actual external factors that form the measured rebound strength. The theoretical stable value of the rebound strength was obtained. Actual impact reduction Reduce quantity based on actual impact and the theoretical stable value of rebound strength The theoretical stable value of the remaining rebound strength is obtained. Based on actual external factors, the theoretical stable value of the residual rebound strength is obtained. The first predicted impact reduction According to the theoretical stable value of residual rebound strength And the first predicted impact reduction The rebound strength stability value was obtained. .
[0013] In one embodiment of the present invention, the optimal testing age is predicted based on the feedback rebound strength corresponding to the maintenance plan, actual external factors, and measured rebound strength, including: predicting the comprehensive influence value of rebound strength based on the actual external factors corresponding to the measured rebound strength. The theoretical stable value of the rebound strength was obtained. Actual impact reduction The strength difference between the current rebound strength and the previous rebound strength, based on the maintenance plan. The actual impact reduction was obtained. The predicted impact on the increment Based on actual external factors, the reduction in actual impact is obtained. The second predicted impact reduction Reduce quantity based on actual impact Predicting the incremental impact Second prediction impact reduction The rebound strength stability adjustment value was calculated. Adjust the value according to the rebound strength stability. The optimal testing age was predicted.
[0014] To achieve the above and other related objectives, the present invention also provides a concrete rebound strength analysis system, comprising: an acquisition unit for acquiring the measured rebound strength during the concrete curing process; a collection unit for collecting all estimated external factors affecting the measured rebound strength corresponding to the external environment of the concrete; a screening unit for evaluating the estimated external factors based on the measured rebound strength and the cured data of the concrete, and screening out the actual external factors affecting the measured rebound strength; an evaluation unit for performing a steady-state evaluation based on the actual external factors and the measured rebound strength to obtain a stable rebound strength value; a selection unit for selecting a corresponding curing scheme based on the stable rebound strength value; and a prediction unit for predicting the optimal test age based on the feedback rebound strength corresponding to the curing scheme, the actual external factors, and the measured rebound strength.
[0015] The beneficial effects of this invention are as follows: The concrete rebound strength analysis method and system proposed in this invention perform error analysis on the initial rebound strength measurement during the concrete curing process, thereby correcting the measured rebound strength and ensuring the accuracy of the concrete rebound strength analysis. Furthermore, when analyzing the rebound strength measurement, by utilizing pre-calibrated estimated external factors of the external environment during the concrete curing process, the actual external factors affecting the formation of the measured rebound strength can be screened from the estimated external factors. This allows for a more accurate prediction of the stable rebound strength value using accurate actual external factors. Moreover, based on the predicted stable rebound strength value, the curing plan can be adjusted and optimized to achieve rational and continuous curing of the concrete, thereby adjusting the stable rebound strength value to meet the corresponding index requirements. Furthermore, during the curing process using the optimized curing scheme, it is possible to further predict the optimal testing age corresponding to the stable value of the rebound strength based on the measured feedback rebound strength. This optimal testing age can be used to better schedule the determination time of the final stable value of the rebound strength, reduce the frequency of repeated testing of the concrete rebound strength, and save time, manpower, and material costs. Attached Figure Description
[0016] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with this application and, together with the description, serve to explain the principles of this application. It is obvious that the drawings described below are merely some embodiments of this application, and those skilled in the art can obtain other drawings based on these drawings without any inventive effort.
[0017] In the attached diagram: Figure 1 This is a flowchart illustrating the concrete rebound strength analysis method provided in an embodiment of the present invention.
[0018] Figure 2 The diagram shows the state of pits formed when a rebound hammer is used to measure a concrete wall surface according to an embodiment of the present invention.
[0019] Figure 3 The diagram shown is a structural block diagram of a concrete rebound strength analysis system provided in an embodiment of the present invention.
[0020] Figure 4 The diagram shown is a structural schematic of an electronic device according to an embodiment of the present invention.
[0021] The attached figures are labeled as follows: Electronic device 1; Concrete rebound strength analysis system 11; Memory 12; Processor 13; Acquisition unit 111; Collection unit 112; Screening unit 113; Evaluation unit 114; Selection unit 115; Prediction unit 116. Detailed Implementation
[0022] The following specific examples illustrate the implementation of the present invention. Those skilled in the art can easily understand other advantages and effects of the present invention from the content disclosed in this specification. The present invention can also be implemented or applied through other different specific embodiments. Various details in this specification can also be modified or changed based on different viewpoints and applications without departing from the spirit of the present invention. In the absence of conflict, the following embodiments and features in the embodiments can be combined with each other.
[0023] It should be noted that the illustrations provided in the following embodiments are only schematic representations of the basic concept of the present invention. The drawings only show the components related to the present invention and are not drawn according to the actual number, shape and size of the components in the actual implementation. In the actual implementation, the form, quantity and proportion of each component can be arbitrarily changed, and the layout of the components may also be more complex.
[0024] In the following description, numerous details are explored to provide a more thorough explanation of embodiments of the invention. However, it will be apparent to those skilled in the art that embodiments of the invention may be practiced without these specific details. In other embodiments, well-known structures and devices are shown in block diagram form rather than in detail to avoid obscuring embodiments of the invention.
[0025] This invention provides a method for analyzing the rebound strength of concrete. By measuring the rebound strength of concrete during the curing process and considering anticipated external environmental factors, the method can filter out actual external factors affecting the rebound strength measurement. This allows for a more accurate prediction of the stable rebound strength value. Furthermore, based on the obtained stable rebound strength value, the curing plan can be optimized for rational and continuous concrete curing. Moreover, during the optimized curing process, the optimal testing age for a stable rebound strength value can be predicted based on the measured rebound strength. This optimal testing age allows for better scheduling of the final stable rebound strength measurement, reducing the frequency of repeated rebound strength measurements and saving manpower, resources, and time.
[0026] Figure 1 A flowchart of a concrete rebound strength analysis method according to an exemplary embodiment of this application is shown, applied to a concrete rebound strength analysis system, including steps S10-S60. The following will be combined with... Figure 1 The technical solution of this application will be described in detail below.
[0027] First, perform step S10 to obtain the measured rebound strength during the concrete curing process.
[0028] When obtaining the rebound strength of concrete during the curing process using a concrete rebound strength analysis system, the measured rebound strength must be based on the actual measurement results, that is, the initial rebound strength measured by the rebound hammer, and derived through error analysis. During the initial rebound strength measurement of concrete, the concrete surface condition can also affect the measurement, leading to certain errors. Therefore, the initial rebound strength can be further optimized to obtain the final measured rebound strength.
[0029] Please see Figure 2 , Figure 2 In one embodiment, when using a rebound hammer to measure a concrete wall surface using the rebound method, a point-matrix method can be used for selected point measurement, such as... Figure 2 The left image shows the rebound hammer test. During the measurement process, each time the rebound hammer is used at the corresponding point, a pit is formed on the concrete wall surface. Due to abnormalities such as pits, protrusions, cracks, and surface roughness on the concrete wall surface, the position of the pit will deviate from the standard pit. This deviation corresponds to an inaccurate surface in the rebound strength test. Of course, in addition to errors caused by abnormalities in the concrete wall surface, improper operation by the staff can also cause the pit position to shift, such as... Figure 2 The right-hand image shows that the dashed pits represent standardized pits under standard conditions, while the solid lines represent offset pits caused by concrete wall anomalies and / or improper operation. Therefore, by analyzing anomalies in the concrete wall and operational anomalies caused by improper operation, the initial rebound strength measured by the rebound hammer can be corrected. This ensures the accuracy of the rebound strength measured when inputting into the concrete rebound strength analysis system, thereby achieving precision in screening actual external factors, assessing rebound strength stability, selecting curing schemes, and predicting the optimal testing age.
[0030] In step S10, obtaining the measured rebound strength during the concrete curing process may further include: Acquire preliminary test data during the concrete curing process. The preliminary test data includes preliminary rebound strength, first image data of the concrete surface before the preliminary rebound strength is measured, and second image data of the concrete surface after the preliminary rebound strength is measured. Based on the first image data and the second image data, the shape data of the pit corresponding to the pit formed during the rebound test is corrected and obtained. Based on the pit shape data, determine the correction factor for the initial rebound strength. The initial rebound strength is adjusted by a correction factor to obtain the measured rebound strength during the concrete curing process.
[0031] When acquiring rebound strength data, the concrete rebound strength analysis system can first use a rebound hammer to measure the initial rebound strength of the concrete during the curing process, and then upload the data to the system. Images of the concrete surface before the initial rebound strength measurement are taken, and the first image data is uploaded to the system. Images of the concrete surface after the initial rebound strength measurement are taken are also taken, and the second image data is uploaded to the system. Alternatively, the system can actively acquire the first and second image data from the corresponding imaging equipment. After acquiring the first and second image data, the system analyzes the pits formed in the second image data in conjunction with the first image data to determine the shape data of the pits formed during the rebound hammer test. Then, based on the pit analysis and pit shape data formed by the first image data and the second image data, the correction coefficient for the initial rebound strength can be determined to adjust the error of the initial rebound strength. This provides a more accurate data basis for the measured rebound strength as a basis for subsequent screening of actual external factors, evaluation of rebound strength stability, selection of maintenance schemes, and prediction of the optimal test age, thereby reducing data processing errors.
[0032] The process of determining the shape data of the pit formed during the rebound hammer test, based on the first image data and the second image data, may further include: Based on the second image data, the initial shape data of the pit in the second image data is obtained. The initial shape data includes the coordinates of the second center point. and the second region that forms the pit ; Based on the initial shape data of the pit in the second image data, the coordinates of the first center point of the pit in the first image data are obtained. and the first area range ; For the first area Feature monitoring was performed to obtain abnormal features. Abnormal features include abnormal pits, abnormal protrusions, abnormal cracks, and abnormal surface roughness on the concrete surface. Based on abnormal characteristics The eigenvalues are used to obtain the offset influence data that forms the initial shape data. ; Based on offset impact data Generate adjustment matrix The initial shape data is corrected to determine the shape data of the pit formed during the rebound test.
[0033] When determining the shape data of the formed pit in concrete rebound strength analysis system, it can first obtain the initial shape data of the pit after processing by the rebound hammer directly from the second image data. Then, based on the coordinates of the second center point of the pit... and the second region that forms the pit The coordinates corresponding to the position of the second center point are obtained. The coordinates of the first center point of the concrete surface before the pit was formed. and the first region that can form the pit The first area can be utilized. To determine the extent of the first region, we analyze the concrete surface before the formation of pits. abnormal features In deriving anomalous characteristics Then, further analysis can be conducted based on abnormal features. The various feature values are used to offset the data that forms the initial shape. Calculations are performed. Finally, the offset influences the data. Generate adjustment matrix This is used to correct the initial shape data, thereby removing outlier features. The data on the shape of the dent after the effect ensures the adjustment accuracy when adjusting the measured rebound strength using this dent shape data.
[0034] Preferably, the feature values include the abnormal location and abnormal shape corresponding to the abnormal feature.
[0035] Specifically, based on abnormal characteristics The eigenvalues are used to obtain the offset influence data that forms the initial shape data. It may further include: Based on abnormal characteristics Corresponding abnormal location and abnormal shapes The coordinates of the position relative to the first center point are obtained. Abnormal areas in different orientations and abnormal areas Corresponding multiple abnormal shapes Total anomaly volume ; For abnormal areas Anomaly center coordinates Compared to the coordinates of the first center point Calculate the abnormal offset distance at the corresponding offset azimuth to obtain the abnormal offset distance at the corresponding offset azimuth. ; According to the abnormal area Corresponding total anomaly volume and abnormal offset distance The abnormal shape offset of the pit along the corresponding offset direction is obtained. and abnormal offset direction ; Based on the abnormal offset direction corresponding to all offset orientations for each abnormal feature and shape anomaly offset The offset influence data that forms the initial shape data is obtained. .
[0036] Based on abnormal features, the concrete rebound strength analysis system was used. The eigenvalues of the data affect the offset. During the calculation, each anomaly feature can be utilized. Corresponding abnormal location and abnormal shapes In order to identify the corresponding abnormal areas Abnormal areas Compared to the coordinates of the first center point The location and abnormal areas Corresponding multiple abnormal shapes Total anomaly volume In other words, the total abnormal volume The calculation formula is: ,in, Indicated as an abnormal region Each abnormal shape inside The corresponding volume. Simultaneously, in calculating the total anomaly volume... At the same time, it can also be based on the coordinates of the anomaly center. and the coordinates of the first center point This is to achieve the abnormal offset distance under the corresponding offset azimuth. The calculation can be performed using the following formula: Combined with the total abnormal volume and abnormal offset distance This allows us to determine the abnormal shape offset of the pit along the corresponding offset direction. and abnormal offset direction Specifically, this can be achieved by utilizing the total anomalous volume in a constructed concrete simulation model. Abnormal offset distance And the corresponding offset orientation, to simulate and obtain the abnormal shape offset of the pit along the corresponding offset orientation. and abnormal offset direction Of course, it can also be based on the total anomaly volume. Total abnormal volume The corresponding first offset factor Abnormal offset distance and abnormal offset distance The corresponding first offset factor The shape anomaly offset can be directly calculated. The abnormal offset direction This could be the offset direction corresponding to the corresponding offset azimuth. The offset direction corresponding to this offset azimuth can also be understood as the anomaly center coordinates. and the coordinates of the first center point The direction formed by connecting the lines between them. Finally, based on the abnormal offset direction corresponding to all offset orientations for each abnormal feature. and shape anomaly offset The offset of the initial shape data affects the data. Each of them .
[0037] In the formation of offset influence data When the corresponding abnormal features are, they may include at least one of the following: pitting abnormality, protrusion abnormality, crack abnormality, and surface roughness abnormality.
[0038] Preferably, when the abnormal features include pitting anomalies, the calculation of the impact data of pitting offset caused by the pitting anomalies can be performed by obtaining the coordinates relative to the first center point position based on the location and shape of the pitting anomalies. The pit anomaly regions at different orientations, and the total pit anomaly volume composed of multiple pit anomaly shapes corresponding to the pit anomaly regions; the coordinates of the pit anomaly center of the pit anomaly region compared to the coordinates of the first center point. Calculate the abnormal pit offset distance under the corresponding offset azimuth to obtain the abnormal pit offset distance under the corresponding offset azimuth; based on the total abnormal pit volume and abnormal pit offset distance corresponding to the abnormal pit area, obtain the abnormal pit shape offset amount and abnormal pit offset direction along the corresponding offset azimuth; take the abnormal pit offset direction and abnormal pit shape offset amount corresponding to all offset azimuths corresponding to the abnormal pit as the pit offset influence data for forming the initial shape data.
[0039] When the anomalous features include convex anomalies, the calculation of the impact data of the convex offset formed by the convex anomalies can be based on the location and shape of the convex anomalies, obtaining the coordinates relative to the first center point. The convex anomaly regions in different orientations, and the total convex anomaly volume composed of multiple convex anomaly shapes corresponding to the convex anomaly regions; the coordinates of the convex anomaly center of the convex anomaly region compared to the coordinates of the first center point. Calculate the abnormal protrusion offset distance under the corresponding offset orientation to obtain the abnormal protrusion offset distance under the corresponding offset orientation; based on the total abnormal protrusion volume and abnormal pit offset distance corresponding to the abnormal protrusion area, obtain the abnormal protrusion shape offset amount and abnormal protrusion offset direction of the pit along the corresponding offset orientation; take the abnormal protrusion offset direction and abnormal protrusion shape offset amount corresponding to all offset orientations corresponding to the abnormal protrusion as the protrusion offset influence data for forming the initial shape data.
[0040] When the abnormal features include crack anomalies, the calculation of the crack offset influence data formed by the crack anomalies can be based on the crack anomaly location and crack anomaly shape, to obtain the coordinates relative to the first center point position. Crack anomaly regions in different orientations, and the total crack anomaly volume composed of multiple crack anomaly shapes corresponding to the crack anomaly regions; the coordinates of the crack anomaly center of the crack anomaly region compared to the coordinates of the first center point. Calculate the abnormal crack offset distance under the corresponding offset orientation to obtain the abnormal crack offset distance under the corresponding offset orientation; based on the total abnormal crack volume and abnormal crack offset distance corresponding to the abnormal crack area, obtain the abnormal crack shape offset amount and abnormal crack offset direction along the corresponding offset orientation of the pit; take the abnormal crack offset direction and abnormal crack shape offset amount corresponding to all offset orientations corresponding to the abnormal crack as the crack offset influence data for forming the initial shape data.
[0041] When the anomalous features include surface roughness anomalies, the calculation of the impact data of the surface roughness offset formed by the surface roughness anomalies can be performed by obtaining the coordinates relative to the first center point position based on the location and shape of the surface roughness anomalies. The surface roughness anomaly regions at different orientations, and the total surface roughness anomaly volume composed of multiple surface roughness anomaly shapes corresponding to the surface roughness anomaly regions; the coordinates of the surface roughness anomaly center of the surface roughness anomaly region compared to the coordinates of the first center point. Calculate the abnormal surface roughness offset distance under the corresponding offset orientation to obtain the abnormal surface roughness offset distance under the corresponding offset orientation; based on the total abnormal surface roughness volume and abnormal surface roughness offset distance corresponding to the abnormal surface roughness region, obtain the abnormal surface roughness shape offset amount and abnormal surface roughness offset direction of the pit along the corresponding offset orientation; take the abnormal surface roughness offset direction and abnormal surface roughness shape offset amount corresponding to all offset orientations corresponding to the abnormal surface roughness as the surface roughness offset influence data for forming the initial shape data.
[0042] In addition, based on the indentation shape data, the correction factor for the initial rebound strength can be further determined, including: By comparing the pit shape data with standard pit shape data, the operational error of the rebound hammer in generating pit shape data during testing can be obtained. ; Based on the offset influence data corresponding to the corrected pit shape data and corresponding influencing moderating factors To obtain the first degree of influence value ; Based on the first degree of influence value and the first correction factor The first correction factor was calculated. ; Based on operational error Second correction factor The second correction coefficient was calculated. ; According to the first correction factor Second correction coefficient Determine the correction factor for the initial rebound strength. .
[0043] When calculating correction factors using pit shape data in a concrete rebound strength analysis system, the formation of this pit shape data is primarily influenced by operational errors during the use of the rebound hammer and the offset of the concrete surface. Therefore, during the calculation, the corrected pit shape data can be compared with the standard pit shape data under correct operating conditions to determine the operational errors that caused the pit shape data. Utilizing operational errors The corresponding second correction factor This allows for the further determination of the second correction coefficient corresponding to the operational error portion. Furthermore, in deriving the offset effect data... Then, it can be further combined with the corresponding influencing moderating factors. To achieve the effect of offset on data The influence of the formation on the measured rebound strength is calculated, and then the first correction coefficient is obtained. Then, combined with the corresponding first correction factor This allows for the calculation of the first correction factor affecting the data due to offset. Next, based on the first correction factor... Second correction coefficient This allows for a relatively accurate determination of the correction coefficient for adjusting the initial rebound strength. The formula can be expressed as follows: .
[0044] Next, step S20 is performed to collect all estimated external factors that affect the determination of rebound strength in the external environment of the concrete.
[0045] When assessing rebound strength stability, selecting curing schemes, and predicting optimal testing age, concrete rebound strength analysis systems require the use of actual external factors influencing the determination of rebound strength. To derive these actual external factors, manual calibration of the external environmental conditions for concrete curing is necessary beforehand to obtain estimated external factors. These estimated external factors can then be uploaded to the concrete rebound strength analysis system, or the system can actively collect them to gather all estimated external factors affecting the determination of rebound strength. These estimated external factors can include factors that influence concrete rebound strength, such as sunlight, air humidity, and ambient temperature, as well as other external factors.
[0046] Next, step S30 is executed, whereby the estimated external factors are evaluated based on the measured rebound strength and the cured concrete data, and the actual external factors that affect the formation of the measured rebound strength are screened out.
[0047] After collecting all estimated external factors, since artificially calibrated estimated external factors may not have a significant impact on the rebound strength of concrete, further evaluation and screening can be conducted based on the rebound strength measurements taken during the curing process and the cured concrete data to identify the actual external factors that may affect the measured rebound strength. This improves the accuracy of rebound strength stability assessment, curing scheme selection, and optimal test age prediction. The cured concrete data can be obtained through methods such as watering volume, watering frequency, covering with straw mats, spraying with chlorinated polyvinyl chloride resin plastic solution, and insulation.
[0048] In step S30, based on the measured rebound strength and the cured concrete data, the estimated external factors are evaluated, and the actual external factors are screened out, which may further include: The difference in rebound strength is obtained by comparing at least two consecutive measurements. Among them, the two consecutive rebound strength measurements include the previous rebound strength measurement. And the next rebound strength measurement ; Based on the difference in rebound strength Formation time Compared to the last time the rebound strength was measured The theoretical rebound strength is converted to obtain the next theoretical rebound strength. ; Based on existing maintenance data Next theoretical rebound strength Next time, measure the rebound strength. and formation time The estimated external factors are evaluated, and the actual external factors are selected.
[0049] When using a concrete rebound strength analysis system to screen for actual external factors, at least two rebound strength measurements should be taken. Then, the rebound strength measurements from each consecutive pair are compared to obtain the difference in rebound strength between the two measurements. The formula is expressed as Then utilize the difference in resilience strength. Formation time That is, the rebound strength measured last time. Until the next rebound strength measurement The time, combined with the previous rebound strength measurement This allows us to derive the corresponding theoretical rebound strength for the next bounce. For example, if based on The theoretical rebound strength growth rate per unit time is When, then the theoretical rebound strength of the next time The calculation formula is: Then, the theoretical rebound strength will be... Next time, measure the rebound strength. and formation time Based on the maintenance data This allows for the evaluation and screening of actual external factors that meet the requirements among the predicted external factors.
[0050] Specifically, based on the maintenance data Next theoretical rebound strength Next time, measure the rebound strength. and formation time The estimated external factors are evaluated and screened to obtain the actual external factors, which may further include: Based on formation time Maintenance data corresponding to a unit maintenance time and coefficient conversion factor This yields the rebound strength for the next measurement. Corrected rebound strength correction factor ; Based on the rebound strength correction factor For the next measurement of rebound strength Make corrections to obtain the next corrected rebound strength. ; For the next correction of rebound strength and the next theoretical rebound strength Compare and obtain the difference value ; When the difference value Greater than the preset value In this case, all predicted external factors are combined to obtain a factor set; Based on the historical impact of each estimated external factor in the factor set on the rebound strength and formation time The comprehensive influence value of rebound strength is obtained. ; The combined impact value of rebound strength corresponding to all factors and difference value Compare and find the difference value The closest combined impact value of rebound strength ; Will with difference value The closest combined impact value of rebound strength The corresponding set of factors serves as the actual external factors.
[0051] When evaluating and screening actual external factors, concrete rebound strength analysis systems can first consider the formation time. Maintenance data corresponding to a unit maintenance time and each maintenance data Conversion factor for spring strength correction factor This allows for further calculations to determine the rebound strength for the next measurement. Corrected rebound strength correction factor The calculation formula can be expressed as: Then, using the rebound strength correction coefficient... For the next measurement of rebound strength Make corrections to obtain the next corrected rebound strength. That is Then, based on the next correction of the rebound strength... To the next theoretical rebound strength Compare and calculate the difference value. Therefore, based on the difference value Compared with preset value The magnitude of the differences is used to determine whether to combine the various estimated external factors. For example, when the difference value... Less than the preset value This means that the influence of actual external factors does not need to be considered at present, and the rebound strength can be guaranteed. Alternatively, the theoretical rebound strength can be used directly. Corresponding theoretical stable value of rebound strength This allows for the direct calculation of the optimal testing age, and the maintenance plan can be implemented using simple maintenance methods. When the difference value... Greater than the preset value When this occurs, it indicates the formation of a difference value. This is mainly due to the influence of various external factors. Therefore, further accurate identification of these external factors is needed to evaluate the maintenance plan and the optimal testing age.
[0052] Specifically, when the difference value Greater than the preset value In this case, all estimated external factors can be freely combined to obtain multiple different factor sets. Then, the historical influence of the rebound strength corresponding to each estimated external factor in the pre-calibrated factor set is used. Combined with the difference in rebound strength Corresponding formation time The comprehensive influence value of rebound strength can be calculated. The formula can be expressed as The comprehensive influence value of rebound strength was obtained. Then, the combined influence value of all rebound strengths is calculated. and difference value Compare to find the difference value The closest combined impact value of rebound strength That is, the difference value found The closest combined impact value of rebound strength It can be expressed by the formula as follows ,in, This represents the comprehensive impact value of the optimal rebound strength.
[0053] Next, step S40 is executed to perform a steady-state assessment based on actual external factors and measured rebound strength, and to obtain a stable value of rebound strength.
[0054] After screening out the actual external factors, the concrete rebound strength analysis system can further combine the measurement of rebound strength to preliminarily assess the current actual external factors and the possible stable value of rebound strength, thereby adjusting the curing plan in advance to reduce the interference of actual external factors on the stable value of rebound strength.
[0055] In step S40, a steady-state assessment is performed based on actual external factors and measured rebound strength to obtain a stable rebound strength value, which may further include: The rebound strength is determined based on the comprehensive influence value of actual external factors corresponding to the rebound strength. The theoretical stable value of the rebound strength was obtained. Actual impact reduction ; Reduce based on actual impact and the theoretical stable value of rebound strength The theoretical stable value of the remaining rebound strength is obtained. ; Based on actual external factors, the theoretical stable value of the residual rebound strength is obtained. The first predicted impact reduction ; Based on the theoretical stability value of residual rebound strength And the first predicted impact reduction The rebound strength stability value was obtained. .
[0056] After obtaining the measured rebound strength using a concrete rebound strength analysis system, and considering actual external factors, a comprehensive influence value of the rebound strength corresponding to the measured rebound strength can be formed. To calculate the theoretical stability value of rebound strength due to actual external factors. Actual impact reduction The overall influence value of the rebound strength For calculations, please refer to The conclusion is drawn. Further reduction is achieved by utilizing the actual impact. Theoretical stable value of rebound strength Optimization was performed to obtain the theoretical stable value of the remaining rebound strength. The formula can be expressed as For the theoretical stable value of residual rebound strength Based on actual external factors, a calibrated conservative impact reduction can be obtained through methods such as table lookup, and used as the theoretical stable value for the remaining rebound strength. The first predicted impact reduction Furthermore, this is combined with the theoretical stable value of residual rebound strength. And the first predicted impact reduction It can achieve a stable value for rebound strength. Calculations are performed. It is worth noting that this first prediction affects the reduction. To achieve a theoretically stable value for the remaining rebound strength without increasing maintenance methods. The resulting impact is reduced. Furthermore, the reduction in the first predicted impact is also reduced. The determination can also be made from the theoretical stable value of the residual rebound strength. Theoretical stable value of rebound strength The ratio determines this. In other words, when the theoretical stable value of the rebound strength is obtained from the table... The corresponding calibrated predicted impact reduction Then, the first predicted reduction in impact can be obtained. .
[0057] Next, proceed to step S50 and select the corresponding maintenance plan based on the rebound strength stability value.
[0058] After obtaining the stable rebound strength value through the concrete rebound strength analysis system, the appropriate curing plan can be selected by testing the stable rebound strength value. For example, when the stable rebound strength value reaches the stability threshold, the ideal rebound strength can be obtained directly without considering the implementation of a curing plan. Of course, to be on the safe side, some curing measures can be implemented. If the stable rebound strength value is less than the stability threshold, the strength of the curing plan and the adequacy of the curing measures can be adjusted based on the difference between the stable rebound strength value and the stability threshold, in order to improve the stability of the rebound strength value.
[0059] Next, step S60 is executed, and the optimal test age is predicted based on the feedback rebound strength corresponding to the maintenance plan, actual external factors, and measured rebound strength.
[0060] After allocating a curing plan using the concrete rebound strength analysis system, and based on the implementation of the curing plan, the rebound strength of the concrete surface is periodically measured again as feedback rebound strength. This feedback rebound strength is also the rebound strength after removing the surface error of the concrete before the rebound hammer test. Based on the feedback rebound strength, actual external factors, and measured rebound strength, the optimal testing age for the final stable rebound strength can be further analyzed. This optimal testing age can then be used as a time node to re-measure the corresponding rebound strength using a rebound hammer, achieving the final rebound strength acceptance. This effectively saves the time, manpower, and material costs of repeatedly measuring rebound strength during the concrete curing process to determine when it tends to stabilize, making the maintenance and management of the concrete curing process simple and efficient.
[0061] In step S60, based on the feedback rebound strength corresponding to the maintenance plan, actual external factors, and measured rebound strength, the optimal test age is predicted, which may further include: The rebound strength is determined based on the comprehensive influence value of actual external factors corresponding to the rebound strength. The theoretical stable value of the rebound strength was obtained. Actual impact reduction ; The strength difference between the current rebound strength and the previous rebound strength according to the maintenance plan. The actual impact reduction was obtained. The predicted impact on the increment ; Based on actual external factors, the reduction in actual impact is obtained. The second predicted impact reduction ; Reduce based on actual impact Predicting the incremental impact Second prediction impact reduction The rebound strength stability adjustment value was calculated. ; Based on the rebound strength stability adjustment value The optimal testing age was predicted.
[0062] When predicting the optimal test age using a concrete rebound strength analysis system, the comprehensive influence value of rebound strength can be used. To determine the theoretical stable value of the rebound strength Actual impact reduction Furthermore, based on the selected maintenance plan, the difference between the current feedback rebound strength and the previous feedback rebound strength is obtained. This allows us to determine the maintenance effect, that is, the reduction in actual impact resulting from the maintenance plan. The predicted impact on the increment In other words, it is possible to utilize the difference in strength. The theoretical stable value of rebound strength can be obtained by referring to the table. The corresponding theoretical prediction of the incremental impact Therefore, we can conclude that the reduction is excluding the actual impact. The predicted impact increment corresponding to the remaining rebound strength stability value, excluding Then, by considering actual external factors, a method corresponding to the first predicted reduction in impact can be used to obtain the second predicted reduction in impact. The formula is expressed as Furthermore, reductions can be made based on the actual impact. Predicting the incremental impact Second prediction impact reduction To calculate the rebound strength stability adjustment value Then, based on the rebound strength stability adjustment value The rebound strength limit at which stability is achieved is calculated. Then, through the rebound strength limit Further table lookup revealed that the rebound strength limit had been reached. Time required And reduce the amount based on the actual impact. Corresponding formation time The optimal testing age was calculated. This allows us to use the optimal testing age as a time node and then use the rebound hammer to measure the corresponding rebound strength again to achieve the final rebound strength acceptance. This effectively saves the time, manpower, and material costs of repeatedly measuring the rebound strength during the concrete curing process to determine when it tends to stabilize, making the maintenance and management of the concrete curing process simple and efficient.
[0063] Please see Figure 3 The present invention also provides a concrete rebound strength analysis system 11, comprising: an acquisition unit 111 for acquiring the measured rebound strength during the concrete curing process; a collection unit 112 for collecting all estimated external factors affecting the measured rebound strength corresponding to the external environment of the concrete; a screening unit 113 for evaluating the estimated external factors based on the measured rebound strength and the cured data of the concrete, and screening out the actual external factors affecting the formation of the measured rebound strength; an evaluation unit 114 for performing a steady-state evaluation based on the actual external factors and the measured rebound strength, and obtaining a stable value of the rebound strength; a selection unit 115 for selecting a corresponding curing scheme based on the stable value of the rebound strength; and a prediction unit 116 for predicting the optimal test age based on the feedback rebound strength corresponding to the curing scheme, the actual external factors, and the measured rebound strength.
[0064] It should be noted that the concrete rebound strength analysis system 11 provided in the above embodiments and the concrete rebound strength analysis method provided in the above embodiments belong to the same concept. The specific operation methods of each module and unit have been described in detail in the method embodiments and will not be repeated here. In practical applications, the concrete rebound strength analysis system 11 provided in the above embodiments can be assigned to different functional modules as needed, that is, the internal structure of the device can be divided into different functional modules to complete all or part of the functions described above. This is not a limitation here.
[0065] Please see Figure 4 The electronic device 1 may include a memory 12, a processor 13, and a bus, and may also include a computer program stored in the memory 12 and executable on the processor 13, such as a concrete rebound strength analysis program.
[0066] The memory 12 includes at least one type of readable storage medium, such as flash memory, portable hard drive, multimedia card, card-type memory (e.g., SD or DX memory), magnetic memory, magnetic disk, optical disk, etc. In some embodiments, the memory 12 can be an internal storage unit of the electronic device 1, such as a portable hard drive of the electronic device 1. In other embodiments, the memory 12 can be an external storage device of the electronic device 1, such as a plug-in portable hard drive, smart media card (SMC), secure digital (SD) card, flash card, etc., equipped on the electronic device 1. Furthermore, the memory 12 can include both internal and external storage units of the electronic device 1. The memory 12 can be used not only to store application software and various types of data installed on the electronic device 1, such as code for concrete rebound strength analysis, but also to temporarily store data that has been output or will be output.
[0067] In some embodiments, the processor 13 may be composed of integrated circuits, such as a single packaged integrated circuit or multiple integrated circuits with the same or different functions, including one or more central processing units (CPUs), microprocessors, digital processing chips, graphics processors, and combinations of various control chips. The processor 13 is the control unit of the electronic device 1, connecting various components of the electronic device 1 through various interfaces and lines. It executes programs or modules (such as concrete rebound strength analysis programs) stored in the memory 12, and calls data stored in the memory 12 to perform various functions and process data of the electronic device 1.
[0068] The processor 13 executes the operating system of the electronic device 1 and various installed applications. The processor 13 executes the applications to implement the steps in the above-described concrete rebound strength analysis method.
[0069] For example, the computer program may be divided into one or more modules, which are stored in the memory 12 and executed by the processor 13 to complete this application. The one or more modules may be a series of computer program instruction segments capable of performing specific functions, which describe the execution process of the computer program in the electronic device 1. For example, the computer program may be divided into units in a concrete rebound strength analysis system.
[0070] The integrated unit implemented as a software functional module described above can be stored in a computer-readable storage medium, which can be non-volatile or volatile. The software functional module, stored in the storage medium, includes several instructions to cause a computer device (which may be a personal computer, a computer device, or a network device, etc.) or a processor to execute some functions of the concrete rebound strength analysis method described in the various embodiments of this application.
[0071] In summary, the concrete rebound strength analysis method and system disclosed in this invention corrects the measured rebound strength by performing error analysis on the initial rebound strength during the concrete curing process, thus ensuring the accuracy of the concrete rebound strength analysis. Furthermore, when analyzing the rebound strength, by utilizing pre-calibrated estimated external factors of the external environment during the concrete curing process, the actual external factors affecting the formation of the measured rebound strength can be screened from the estimated external factors. This allows for a more accurate prediction of the stable rebound strength value using accurate actual external factors. Moreover, based on the predicted stable rebound strength value, the curing plan can be adjusted and optimized to achieve rational and continuous curing of the concrete, thereby adjusting the stable rebound strength value to meet the corresponding index requirements. Furthermore, during the curing process using the optimized curing scheme, the optimal testing age corresponding to the stable rebound strength can be predicted based on the measured rebound strength. This optimal testing age allows for better scheduling of the final stable rebound strength measurement, reducing the frequency of repeated concrete rebound strength measurements and saving time, manpower, and material costs. Therefore, this invention effectively overcomes the various shortcomings of existing technologies and has high industrial applicability.
[0072] The above embodiments are merely illustrative of the principles and effects of the present invention and are not intended to limit the invention. Any person skilled in the art can modify or alter the above embodiments without departing from the spirit and scope of the present invention. Therefore, all equivalent modifications or alterations made by those skilled in the art without departing from the spirit and technical concept disclosed in the present invention should still be covered by the claims of the present invention.
Claims
1. A method for analyzing the rebound strength of concrete, characterized in that, include: Obtain the measured rebound strength during the concrete curing process; Collect all estimated external factors that would affect the measured rebound strength of the concrete in its external environment. Based on the measured rebound strength and the cured data of the concrete, the estimated external factors are evaluated, and the actual external factors that affect the formation of the measured rebound strength are screened out. A steady-state assessment is performed based on the actual external factors and the measured rebound strength to obtain a stable value of the rebound strength. Select the corresponding maintenance plan based on the rebound strength stability value; Based on the feedback rebound strength corresponding to the maintenance plan, the actual external factors, and the measured rebound strength, the optimal testing age is predicted.
2. The concrete rebound strength analysis method according to claim 1, characterized in that, Obtaining the rebound strength of concrete during the curing process includes: Acquire preliminary measurement data during the concrete curing process. The preliminary measurement data includes preliminary rebound strength, first image data of the concrete surface before the preliminary rebound strength is measured, and second image data of the concrete surface after the preliminary rebound strength is measured. Based on the first image data and the second image data, the pit shape data corresponding to the pit formation during the rebound test is corrected and obtained. Based on the indentation shape data, a correction coefficient for the initial rebound strength is determined; The initial rebound strength is adjusted by the correction factor to obtain the measured rebound strength during the concrete curing process.
3. The concrete rebound strength analysis method according to claim 2, characterized in that, Based on the first image data and the second image data, the shape data of the pit formed during the rebound test is determined, including: Based on the second image data, the initial shape data of the pit in the second image data is obtained, and the initial shape data includes the coordinates of the second center point. and the second region forming the pit ; Based on the initial shape data of the pit in the second image data, the coordinates of the first center point of the pit in the first image data are obtained. and the first area range ; For the first area range Feature monitoring was performed to obtain abnormal features. The abnormal features include abnormal pits, abnormal protrusions, abnormal cracks, and abnormal surface roughness on the concrete surface. Based on the abnormal characteristics The feature values are used to obtain the offset influence data that forms the initial shape data. ; According to the offset influence data Generate adjustment matrix The initial shape data is corrected to determine the shape data of the pit that forms the pit during the rebound test.
4. The concrete rebound strength analysis method according to claim 3, characterized in that, The feature value includes the abnormal location and abnormal shape corresponding to the abnormal feature; Based on the abnormal characteristics The feature values are used to obtain the offset influence data that forms the initial shape data. ,include: Based on the abnormal characteristics Corresponding abnormal location and abnormal shapes The coordinates of the position relative to the first center point are obtained. Abnormal areas in different orientations and abnormal areas Corresponding multiple abnormal shapes Total anomaly volume ; For the abnormal region Anomaly center coordinates Compared to the coordinates of the first center point Calculate the abnormal offset distance at the corresponding offset azimuth to obtain the abnormal offset distance at the corresponding offset azimuth. ; According to the abnormal region Corresponding total anomaly volume and the abnormal offset distance The abnormal shape offset of the pit along the corresponding offset direction is obtained. and abnormal offset direction ; Based on the abnormal offset direction corresponding to all offset orientations of each of the aforementioned abnormal features and the shape anomaly offset The offset influence data that forms the initial shape data is obtained. .
5. The concrete rebound strength analysis method according to claim 2, characterized in that, Based on the indentation shape data, a correction coefficient for the initial rebound strength is determined, including: The indentation shape data is compared with standard indentation shape data to obtain the operational error of the rebound hammer in generating the indentation shape data during testing. ; Based on the corrected pit shape data, the corresponding offset influence data and corresponding influencing moderating factors To obtain the first degree of influence value ; Based on the first degree of influence value and the first correction factor The first correction factor was calculated. ; According to the operational error Second correction factor The second correction coefficient was calculated. ; According to the first correction coefficient and the second correction coefficient Determine the correction coefficient for the initial rebound strength. .
6. The concrete rebound strength analysis method according to claim 1, characterized in that, Based on the measured rebound strength and the cured data of the concrete, the estimated external factors are evaluated, and the actual external factors are screened out, including: The difference in rebound strength is obtained by comparing at least two consecutive measurements of the rebound strength. The two consecutive rebound strength measurements include the previous rebound strength measurement. And the next rebound strength measurement ; Based on the rebound strength difference Formation time And the previously measured rebound strength The theoretical rebound strength is converted to obtain the next theoretical rebound strength. ; Based on the aforementioned maintenance data The next theoretical rebound strength The next measurement of rebound strength and the formation time The estimated external factors are evaluated, and the actual external factors are selected.
7. The concrete rebound strength analysis method according to claim 6, characterized in that, Based on the aforementioned maintenance data The next theoretical rebound strength The next measurement of rebound strength and the formation time The estimated external factors are evaluated, and the actual external factors are screened to obtain the following: According to the formation time The maintenance data corresponding to the unit maintenance time and coefficient conversion factor The rebound strength for the next measurement is obtained. Corrected rebound strength correction factor ; According to the rebound strength correction coefficient For the next measurement of rebound strength Make corrections to obtain the next corrected rebound strength. ; For the next corrected rebound strength and the next theoretical rebound strength Compare and obtain the difference value ; When the difference value Greater than the preset value Then, all the predicted external factors are combined to obtain a factor set; Based on the historical impact of the rebound strength corresponding to each of the estimated external factors in the set of factors and the formation time The comprehensive influence value of rebound strength is obtained. ; The combined influence value of the rebound strength corresponding to the set of all the aforementioned factors The difference value Compare and find the difference value. The closest combined influence value of the rebound strength ; The difference value The closest combined influence value of the rebound strength The corresponding set of factors is taken as the actual external factors.
8. The concrete rebound strength analysis method according to claim 1, characterized in that, A steady-state assessment is performed based on the actual external factors and the measured rebound strength to obtain a stable rebound strength value, including: The rebound strength is determined based on the combined influence value of the actual external factors corresponding to the measured rebound strength. The theoretical stable value of the rebound strength was obtained. Actual impact reduction ; Based on the actual impact, the reduction was carried out. and the theoretical stable value of the rebound strength The theoretical stable value of the remaining rebound strength is obtained. ; Based on the actual external factors, the theoretical stable value of the remaining rebound strength is obtained. The first predicted impact reduction ; Based on the theoretical stable value of the residual rebound strength and the first predicted impact reduction The rebound strength stability value was obtained. .
9. The concrete rebound strength analysis method according to claim 1, characterized in that, Based on the feedback rebound strength corresponding to the maintenance plan, the actual external factors, and the measured rebound strength, the optimal testing age is predicted, including: The rebound strength is determined based on the combined influence value of the actual external factors corresponding to the measured rebound strength. The theoretical stable value of the rebound strength was obtained. Actual impact reduction ; The strength difference between the current feedback rebound strength and the previous feedback rebound strength corresponding to the maintenance plan. The reduction in the actual impact is obtained. The predicted impact increment ; Based on the actual external factors, the reduction in the actual impact is obtained. The second predicted impact reduction ; Based on the actual impact, the reduction was carried out. Predicting the incremental impact Second prediction impact reduction The rebound strength stability adjustment value was calculated. ; According to the rebound strength stability adjustment value The optimal testing age is predicted.
10. A concrete rebound strength analysis system, characterized in that, include: The acquisition unit is used to acquire the measured rebound strength during the concrete curing process; The collection unit is used to collect all estimated external factors that affect the measured rebound strength of the concrete in the external environment. The screening unit is used to evaluate the estimated external factors based on the measured rebound strength and the cured data of the concrete, and to screen out the actual external factors that affect the formation of the measured rebound strength. An evaluation unit is used to perform a steady-state evaluation based on the actual external factors and the measured rebound strength, and to obtain a stable value of rebound strength. The selection unit is used to select the corresponding maintenance scheme based on the rebound strength stability value; as well as The prediction unit is used to predict the optimal test age based on the feedback rebound strength corresponding to the maintenance plan, the actual external factors, and the measured rebound strength.