An intelligent recognition method, system, device and medium for the impermeability strength of concrete

Abstract

An intelligent identification method, system, device and medium for the impermeability strength of concrete, which relates to the technical field of data processing. The method includes: obtaining the pressure parameters of the concrete specimen to be tested and the pressure acquisition moments corresponding to the pressure parameters, and generating an osmotic pressure curve of the concrete specimen to be tested according to the pressure parameters and the pressure acquisition moments; determining the fluctuation stability determination result of the osmotic pressure curve based on the pressure change rate between two adjacent pressure acquisition moments in the osmotic pressure curve; obtaining the image of the seepage water spot on the surface of the concrete specimen to be tested, and calculating the water spot area growth rate of the seepage water spot image at two adjacent image acquisition moments; determining the expansion stability determination result of the seepage water spot based on the water spot area growth rate; combining the fluctuation stability determination result and the expansion stability determination result to determine the impermeability strength grade of the concrete specimen to be tested. Implementing the technical solution provided by this application achieves the effect of improving the accuracy of identifying the impermeability strength of concrete.

Description

Technical Field

[0001] This application relates to the technical field of data processing, and particularly relates to an intelligent identification method, system, device and medium for the anti-seepage strength of concrete. Background Technique

[0002] With the rapid development of urbanization construction, the application of concrete building structures in humid environments such as water conservancy projects and underground projects is becoming increasingly widespread. As an important indicator to measure the durability and safety of concrete, the anti-seepage performance of concrete has received more and more attention in the engineering field.

[0003] Currently, in engineering practice, the pressure penetration method is generally used to detect the anti-seepage performance of the concrete specimens to be tested. By applying water pressure to the specimens, the inspectors observe the penetration situation of the concrete specimens to be tested to evaluate the anti-seepage strength grade of the concrete. However, in actual applications, due to the subtle changes in the concrete specimens to be tested during the anti-seepage test, if only the inspectors conduct artificial identification and evaluation, it is often easy to miss test data, resulting in errors in the test results, thus reducing the accuracy of the identification of the anti-seepage strength of concrete. Summary of the Invention

[0004] This application provides an intelligent identification method, system, device and medium for the anti-seepage strength of concrete, which has the effect of improving the accuracy of the identification of the anti-seepage strength of concrete.

[0005] In the first aspect, this application provides an intelligent identification method for the anti-seepage strength of concrete, including:

[0006] Obtain the pressure parameters of the concrete specimen to be tested and the pressure acquisition time corresponding to the pressure parameters, and generate the seepage pressure curve of the concrete specimen to be tested according to the pressure parameters and the pressure acquisition time;

[0007] Based on the pressure change rate between two adjacent pressure acquisition times in the seepage pressure curve, determine the fluctuation stability determination result of the seepage pressure curve;

[0008] Obtain the seepage water spot image on the surface of the concrete specimen to be tested, and calculate the water spot area growth rate of the seepage water spot image at two adjacent image acquisition times;

[0009] Based on the water spot area growth rate, determine the expansion stability determination result of the seepage water spot;

[0010] Combine the fluctuation stability determination result and the expansion stability determination result to determine the anti-seepage strength grade of the concrete specimen to be tested.

[0011] In the second aspect of this application, an intelligent identification system for the anti-seepage strength of concrete is provided. The system includes:

[0012] A parameter acquisition module, configured to acquire the pressure parameter of the concrete specimen to be tested and the pressure acquisition moment corresponding to the pressure parameter, and generate an osmotic pressure curve of the concrete specimen to be tested according to the pressure parameter and the pressure acquisition moment;

[0013] A fluctuation stability determination result determination module, configured to determine the fluctuation stability determination result of the osmotic pressure curve based on the pressure change rate between two adjacent pressure acquisition moments in the osmotic pressure curve;

[0014] An expansion stability determination result determination module, configured to acquire an image of the osmotic water spot on the surface of the concrete specimen to be tested, and calculate the water spot area growth rate of the osmotic water spot image at two adjacent image acquisition moments; based on the water spot area growth rate, determine the expansion stability determination result of the osmotic water spot;

[0015] An impermeability strength identification module, configured to determine the impermeability strength grade of the concrete specimen to be tested by combining the fluctuation stability determination result and the expansion stability determination result.

[0016] In a third aspect of the present application, an electronic device is provided, including a memory, a processor, and a program stored on the memory and executable on the processor. When the program is loaded and executed by the processor, it can implement a method for intelligent identification of the impermeability strength of concrete.

[0017] In a fourth aspect of the present application, a computer-readable storage medium is provided. The computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the processor is enabled to implement a method for intelligent identification of the impermeability strength of concrete.

[0018] In summary, one or more technical solutions provided in the embodiments of the present application have at least the following technical effects or advantages:

[0019] By adopting the above technical solutions, during the test, the pressure parameters of the concrete specimen to be tested and the corresponding pressure acquisition moments are obtained and an osmotic pressure curve is generated, so that the trend of pressure change can be tracked and quantitatively analyzed more accurately. Furthermore, by comparing the pressure change rates at two adjacent pressure acquisition moments in the osmotic pressure curve, the determination result of its fluctuation stability can be judged. On this basis, the image of the osmotic water spot on the surface of the concrete specimen to be tested is obtained at the same time and the growth rate of the water spot area at two adjacent image acquisition moments is calculated to determine the determination result of the expansion stability of the osmotic water spot. Thus, the internal osmotic pressure fluctuation of the specimen under pressure and the expansion of the surface water spot can be evaluated doubly, avoiding omissions or misjudgments that may be caused by a single monitoring dimension, and making the determination of the concrete impermeability behavior more comprehensive and reliable. When the determination results of the fluctuation stability and the expansion stability confirm each other and both show stability, it can be determined that the concrete specimen has reached the corresponding impermeability state, and thus the impermeability strength grade of the concrete specimen to be tested can be determined quickly and accurately by combining the determination results of both, improving the accuracy of concrete impermeability strength identification. Description of the Drawings

[0020] Figure 1 is a schematic flow chart of a method for intelligent identification of concrete impermeability strength provided by an embodiment of the present application;

[0021] Figure 2 is a schematic structural diagram of a system for intelligent identification of concrete impermeability strength provided by an embodiment of the present application;

[0022] Figure 3 is a schematic structural diagram of an electronic device provided by an embodiment of the present application.

[0023] Description of the reference numerals: 300, electronic device; 301, processor; 302, communication bus; 303, user interface; 304, network interface; 305, memory. Detailed Embodiments

[0024] In order to enable those skilled in the art to better understand the technical solutions in this specification, the technical solutions in the embodiments of this specification will be clearly and completely described below in conjunction with the drawings in the embodiments of this specification. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all the embodiments.

[0025] In the description of the embodiments of the present application, words such as "for example" or "for illustration" are used to represent examples, illustrations or explanations. Any embodiment or design solution described as "for example" or "for illustration" in the embodiments of the present application should not be construed as being more preferred or having more advantages than other embodiments or design solutions. Exactly speaking, the use of words such as "for example" or "for illustration" is intended to present related concepts in a specific manner.

[0026] In the description of the embodiments of the present application, the term "plurality" means two or more. For example, a plurality of systems means two or more systems, and a plurality of screen terminals means two or more screen terminals. In addition, the terms "first" and "second" are only used for descriptive purposes and cannot be construed as indicating or implying relative importance or implicitly specifying the indicated technical features. Thus, the features defined with "first" and "second" may explicitly or implicitly include one or more of such features. The terms "comprise", "include", "have" and their variants all mean "including but not limited to", unless otherwise specifically emphasized in other ways.

[0027] The embodiments of the present application provide a method for intelligent identification of the impermeability strength of concrete. In one embodiment, please refer to Figure 1 , Figure 1 which is a schematic flow chart of the method for intelligent identification of the impermeability strength of concrete provided by the embodiments of the present application. This method can be implemented depending on a computer program, which can be integrated in an application or run as an independent tool-type application. This method can also be implemented depending on a single-chip microcomputer and can also run on an intelligent identification system for the impermeability strength of concrete based on the von Neumann architecture. Specifically, this method may include the following steps:

[0028] Step 101: Obtain the pressure parameters of the concrete specimen to be tested and the pressure acquisition moments corresponding to the pressure parameters, and generate an osmotic pressure curve of the concrete specimen to be tested according to the pressure parameters and the pressure acquisition moments.

[0029] Among them, the concrete specimen to be tested refers to a concrete sample made according to standard specifications for impermeability performance testing. This specimen is placed in an impermeability test device during testing and is subjected to water pressure to evaluate the impermeability performance of the concrete.

[0030] The pressure parameter refers to the real-time water pressure value acting on the surface of the specimen collected by a pressure sensor during the impermeability test of the concrete specimen to be tested. This value reflects the actual water pressure borne by the concrete specimen during the test.

[0031] The pressure acquisition moment refers to the specific time point corresponding to each pressure parameter collected by the pressure sensor, which is used to record the process of the pressure parameter changing with time, ensure that the pressure data has a time attribute, and facilitate subsequent analysis of the pressure change trend.

[0032] The osmotic pressure curve refers to a curve graph plotted with the pressure acquisition moment as the abscissa and the pressure parameter as the ordinate. This curve visually shows the trend of the pressure changing with time of the concrete specimen to be tested during the entire test process and is used to analyze the impermeability performance of the concrete specimen.

[0033] Specifically, first place the concrete specimen to be tested in the impermeability test device, and collect the pressure parameters acting on the surface of the specimen in real time through the pressure sensors set on the test device. In order to record the time characteristics of the pressure change, the system will automatically record the pressure acquisition moment corresponding to each pressure parameter, so as to obtain the pressure data containing time information. After obtaining the pressure parameters and the pressure acquisition moments, first obtain the initial pressure value of the concrete specimen to be tested, and subtract the initial pressure value from the pressure parameters to obtain the target pressure value to eliminate the influence of environmental pressure. Subsequently, arrange the target pressure values in time sequence according to the pressure acquisition moments to generate a pressure-time series reflecting the law of pressure change with time. Considering that the original data may have random fluctuations, the moving average method is used to smooth the pressure-time series. By selecting an appropriate time window to calculate the average value of the data points within the window, the smoothed pressure-time series is obtained as the window moves step by step. Finally, with the pressure acquisition moments as the abscissa and the smoothed pressure-time series as the ordinate, the seepage pressure curve of the concrete specimen to be tested is generated. This automated data acquisition and processing method avoids data omission easily caused by manual observation, and at the same time eliminates the influence of interference factors through data smoothing processing, so that the finally generated seepage pressure curve can accurately reflect the pressure change trend of the concrete specimen during the detection process, providing a reliable data basis for subsequent impermeability performance analysis.

[0034] Based on the above embodiments, as an optional embodiment, in step 101: generating the seepage pressure curve of the concrete specimen to be tested according to the pressure parameters and the pressure acquisition moments, this step may further include the following steps:

[0035] Step 201: Obtain the initial pressure value of the concrete specimen to be tested, and subtract the initial pressure value from the pressure parameters to obtain the target pressure value.

[0036] Specifically, first, before the impermeability test of the concrete specimen to be tested starts, obtain the initial pressure value of the concrete specimen to be tested through the pressure sensor. This initial pressure value reflects the environmental pressure state of the specimen when no water pressure is applied. Then subtract the initial pressure value from the pressure parameters collected during the test respectively to obtain the target pressure value after eliminating the influence of environmental pressure, so as to exclude the interference of environmental factors on the test results and make the subsequent analysis more accurately reflect the true impermeability performance of the concrete specimen.

[0037] Step 202: Arrange the target pressure values in time sequence according to the pressure acquisition moments to generate a pressure-time series.

[0038] Specifically, the obtained target pressure values are arranged in chronological order according to their corresponding pressure acquisition times to generate a pressure time series containing time information. Through chronological arrangement, the variation law of the target pressure value with time can be clearly presented, laying a foundation for subsequent data processing and analysis. Since the pressure sensor continuously collects a large amount of data during the detection process, chronological arrangement can ensure the continuity and integrity of the data, which is conducive to accurately grasping the pressure change trend.

[0039] Step 203: Smooth the pressure time series by using the moving average method, and generate an osmotic pressure curve of the concrete specimen to be tested with the pressure acquisition time as the abscissa and the smoothed pressure time series as the ordinate.

[0040] Specifically, the data in the pressure time series are smoothed by using the moving average method. The specific operation of the moving average method is to select an appropriate time window, calculate the average value of all data points within the window as the new value of the central point, and as the window moves step by step, a complete smoothed pressure time series is obtained. Smoothing can effectively reduce the influence of random fluctuations and noise in the pressure data, making the pressure change trend more obvious. Finally, with the pressure acquisition time as the abscissa and the smoothed pressure time series as the ordinate, the osmotic pressure curve of the concrete specimen to be tested is plotted. This processing method not only retains the main trend of the pressure change but also eliminates the influence of interference factors, enabling the osmotic pressure curve to more accurately reflect the change process of the impermeability performance of the concrete specimen.

[0041] Step 102: Determine the determination result of the fluctuation stability of the osmotic pressure curve based on the pressure change rate between two adjacent pressure acquisition times in the osmotic pressure curve.

[0042] Among them, the pressure change rate refers to the pressure change speed between two adjacent pressure acquisition times in the osmotic pressure curve, and its calculation result reflects the degree of pressure change per unit time. This parameter can be used to quantitatively evaluate the severity of the pressure change.

[0043] The determination result of the fluctuation stability refers to the stability evaluation result obtained by analyzing the distribution characteristics of the pressure change rate in the osmotic pressure curve. When this ratio is small, it indicates that the overall fluctuation of the osmotic pressure curve is stable; when this ratio is large, it indicates that the osmotic pressure curve fluctuates violently. This result can be used to judge the pressure stability degree of the concrete specimen during the detection process.

[0044] Specifically, in order to evaluate the stability of pressure change of the concrete specimen to be tested during the detection process, it is necessary to analyze the pressure change at adjacent moments based on the seepage pressure curve. First, the two adjacent pressure acquisition moments in the seepage pressure curve are traversed, and the pressure change rate between each pair of adjacent moments is calculated. Specifically, the pressure change rate in the time period can be obtained by calculating the pressure value of the next moment minus the pressure value of the previous moment, and then dividing it by the time interval between the two moments. By analyzing the magnitude of the pressure change rate, it can be judged whether the pressure change is drastic. When the absolute value of the pressure change rate is less than the preset threshold, it indicates that the pressure change is gentle in the time period; when the absolute value of the pressure change rate is greater than the preset threshold, it indicates that the pressure change is drastic in the time period. By counting the proportion of time periods in which the pressure change rate exceeds the threshold during the entire detection process, the fluctuation stability judgment result of the seepage pressure curve can be obtained. This fluctuation stability analysis method based on the pressure change rate can objectively evaluate the pressure stability of the concrete specimen during the detection process, avoid the subjectivity of manual judgment, and at the same time, by setting a reasonable threshold, it can accurately identify the time period of drastic pressure fluctuations, providing an important basis for evaluating the anti-seepage performance of concrete specimens.

[0045] Based on the above embodiment, as an optional embodiment, in step 102: determining the fluctuation stability determination result of the osmotic pressure curve based on the pressure change rate at two adjacent pressure acquisition moments in the osmotic pressure curve, this step may also include the following steps:

[0046] Step 301: Obtain the age of the concrete specimen to be tested; determine a correction coefficient of the pressure change rate based on the age, and determine a target pressure change rate based on the correction coefficient and the pressure change rate.

[0047] Specifically, first obtain the age of the concrete specimen to be tested, because the age of the concrete specimen will affect its internal structural characteristics and impermeability. Based on the differences in the pressure response characteristics of concrete specimens of different ages, the pressure change rate needs to be corrected accordingly. Specifically, the correction coefficient of the pressure change rate can be determined according to the pre-established age-correction coefficient correspondence. For example, the correction coefficient of the corresponding age can be obtained by looking up a table. Subsequently, the original pressure change rate is multiplied by the correction coefficient to obtain the target pressure change rate that takes into account the influence of age. This correction method can eliminate the influence of age differences on the judgment of the pressure change rate, making the subsequent stability judgment more universal.

[0048] Step 302: When the absolute value of the pressure change rate is less than a preset fluctuation threshold, the corresponding time point is marked as a stable point.

[0049] Specifically, by comparing the absolute value of the target pressure change rate with the preset fluctuation threshold, the stable points in the seepage pressure curve are identified. When the absolute value of the target pressure change rate corresponding to a certain time point is less than the preset fluctuation threshold, it indicates that the pressure change at this time point is relatively gentle. Therefore, this time point is marked as a stable point. This threshold-based judgment method can objectively identify the time period with stable pressure change and provide basic data for subsequent evaluation of the overall stability.

[0050] Step 303: Statistically analyze the duration of continuously marked stable points in the seepage pressure curve. When the duration is greater than or equal to the stable duration threshold, determine that the fluctuation stability determination result of the seepage pressure curve is stable; when the duration is less than the stable duration threshold, determine that the fluctuation stability determination result of the seepage pressure curve is abnormal.

[0051] Specifically, statistically analyze the time period of continuously marked stable points in the seepage pressure curve and calculate the duration of continuous stable points. When the duration of continuous stable points is greater than or equal to the preset stable duration threshold, it indicates that the test concrete specimen has maintained a stable pressure state for a sufficient long time. At this time, determine the fluctuation stability determination result of the seepage pressure curve as stable. On the contrary, when the duration of continuous stable points is less than the stable duration threshold, it indicates that the test concrete specimen has not maintained a stable state for a sufficient long time. At this time, determine the fluctuation stability determination result as abnormal. This judgment method based on the continuous stable duration not only considers the intensity of pressure change but also pays attention to the persistence of the stable state, and can more comprehensively evaluate the stability of the impermeability performance of the concrete specimen.

[0052] Step 103: Obtain the image of the seepage water spot on the surface of the test concrete specimen and calculate the growth rate of the water spot area of the seepage water spot image at two adjacent image acquisition times.

[0053] Among them, the seepage water spot image refers to the image of the water stain diffusion trace that appears on the surface of the test concrete specimen collected by the image acquisition device. Specifically, it is the digital image record of the dark area formed on the surface of the concrete specimen due to water penetration. These images can intuitively show the diffusion range and distribution state of water on the surface of the concrete specimen. By processing and analyzing the seepage water spot image, the water seepage situation of the concrete specimen can be quantitatively evaluated.

[0054] The growth rate of the water spot area refers to the change speed of the area of the seepage water spot on the surface of the concrete specimen between two adjacent image acquisition times. Its calculation result reflects the degree of expansion of the water spot area per unit time. This parameter can be used to quantitatively evaluate the water seepage diffusion speed of the concrete specimen and then judge the impermeability performance of the concrete.

[0055] Specifically, to comprehensively evaluate the impermeability performance of the concrete specimen to be tested, it is necessary to analyze the dynamic change characteristics of the permeated water spots on the specimen surface. First, during the detection process, the image acquisition device set on the test device continuously acquires the images of the permeated water spots on the surface of the concrete specimen to be tested at preset time intervals. For each acquired permeated water spot image, image processing technology is used to identify and segment the water spot area. By calculating the number of pixel points in the water spot area and combining with the image resolution, the actual area of the water spot at each image acquisition moment can be obtained. Subsequently, the water spot areas at two adjacent image acquisition moments are analyzed. By calculating the water spot area at the latter moment minus the water spot area at the former moment and then dividing by the time interval between the two moments, the growth rate of the water spot area during this time period is obtained. The growth rate of the water spot area reflects the speed of water seepage diffusion in the concrete specimen per unit time, and this parameter can intuitively reflect the impermeability performance of the concrete specimen. Through this automated image acquisition and analysis method, the expansion process of the permeated water spots can be accurately recorded and quantified, avoiding the subjectivity and errors of the traditional manual measurement method, and providing data support for evaluating the impermeability performance of the concrete specimen.

[0056] Based on the above embodiments, as an alternative embodiment, in step 103: calculating the growth rate of the water spot area of the permeated water spot image at two adjacent image acquisition moments, this step may further include the following steps:

[0057] Step 401: Obtain the gray value distribution of the permeated water spot image and determine the gray threshold of the water spot edge based on the gray value distribution.

[0058] Specifically, first, it is necessary to analyze the gray values of the acquired permeated water spot image, because the water spot area and the non-water spot area exhibit different gray value distribution characteristics in the image. By statistically analyzing the gray values of each pixel point in the image, the gray value distribution histogram of the entire image is obtained. Based on the bimodal characteristics of this histogram, the gray value distribution ranges of the water spot area and the non-water spot area can be identified, and the gray threshold of the water spot edge is determined at the valley position between the two peaks. This method of determining the threshold based on the gray characteristics of the image can adaptively process the permeated water spot images under different lighting conditions and improve the accuracy of subsequent water spot recognition.

[0059] Based on the above embodiments, as an alternative embodiment, in step 401: determining the gray threshold of the water spot edge based on the gray value distribution, this step may further include the following steps:

[0060] Step 411: Determine the standard gray reference plate placed at the test position where the concrete specimen to be tested is located. The standard gray reference plate includes a dry area reference strip and a wet area reference strip.

[0061] Specifically, to eliminate the influence of environmental light changes on water stain recognition, a standard gray reference plate needs to be placed at the test position of the concrete specimen to be tested. The standard gray reference plate includes two characteristic regions: a dry region reference strip and a wet region reference strip. The gray value of the dry region reference strip corresponds to the standard gray value of the non-seeping concrete surface, and the gray value of the wet region reference strip corresponds to the standard gray value of the fully wet concrete surface. By simultaneously recording the gray values of these two standard reference strips during the image acquisition process, a reference for subsequent gray value correction can be provided to ensure accurate recognition results for water stain images obtained under different lighting conditions.

[0062] Step 421: Obtain the gray values of the dry region reference strip and the wet region reference strip; calculate the average gray value of the non-seeping region on the concrete specimen to be tested to obtain the measured dry value.

[0063] Specifically, first extract the gray values of the dry region reference strip and the wet region reference strip on the standard gray reference plate from the seepage water stain image. At the same time, select the region without seepage phenomenon in the seepage water stain image of the concrete specimen to be tested, and calculate the average value of the gray values of all pixel points in this region to obtain the measured dry value. This measured dry value reflects the actual gray characteristics of the non-seeping region of the concrete specimen under the current lighting conditions. By comparing the measured dry value with the gray value of the standard reference strip, the influence degree of environmental light on the image gray value can be quantitatively evaluated.

[0064] Step 431: Use the ratio of the measured dry value to the gray value of the dry region reference strip as the gray correction coefficient; use the product of the gray value of the wet region reference strip and the gray correction coefficient as the water stain edge gray threshold.

[0065] Specifically, to correct the gray value deviation caused by environmental light, first calculate the ratio of the measured dry value to the gray value of the dry region reference strip to obtain the gray correction coefficient. This gray correction coefficient reflects the deviation degree of the current lighting conditions relative to the standard lighting conditions. Then multiply the gray value of the wet region reference strip by this gray correction coefficient to obtain the water stain edge gray threshold considering the actual lighting conditions. This correction method based on the standard reference can effectively eliminate the influence of environmental light changes on water stain recognition and improve the accuracy and reliability of water stain edge recognition.

[0066] Step 402: Perform binarization processing on the seepage water stain image according to the water stain edge gray threshold to obtain the water stain region.

[0067] Specifically, a determined gray - scale threshold of the water stain edge is used to perform binary processing on the infiltrated water stain image. Specifically, the pixel points in the image with gray - scale values less than the gray - scale threshold of the water stain edge are determined as the water stain area, and their gray - scale values are set to 0 (black). The pixel points with gray - scale values greater than or equal to the gray - scale threshold of the water stain edge are determined as the non - water stain area, and their gray - scale values are set to 255 (white). Through this binary processing, a continuous gray - scale image can be converted into a binary image containing only the water stain area and the non - water stain area, providing a clear area division for subsequent area calculation.

[0068] Step 403: Count the number of pixel points in the water stain area and convert the number of pixel points into the actual water stain area.

[0069] Specifically, pixel statistics of the water stain area are performed on the binary - processed image. By traversing all pixel points in the image and counting the number of pixel points with a gray - scale value of 0, the number of pixels in the water stain area can be obtained. Subsequently, based on the resolution parameters of the image acquisition device, the number of pixel points is converted into the actual water stain area. For example, if the actual area size corresponding to each pixel point is known, then multiplying the counted number of pixel points by the actual area corresponding to a single pixel point can obtain the actual area of the water stain. This method of calculating the area based on pixel statistics can accurately quantify the actual size of the water stain.

[0070] Step 404: Calculate the ratio between the difference in the actual water stain areas at two adjacent image acquisition times and the time interval to obtain the water stain area growth rate.

[0071] Specifically, the actual water stain areas at two adjacent image acquisition times are analyzed and calculated. First, calculate the actual water stain area at the later time minus the actual water stain area at the previous time to obtain the increment of the water stain area during this period. Then divide this increment by the time interval between the two image acquisition times to obtain the water stain area growth rate. This method of calculating the growth rate can accurately reflect the change speed of the water stain area over time and provide an important quantitative index for evaluating the anti - permeability performance of concrete specimens.

[0072] Step 104: Based on the water stain area growth rate, determine the evaluation result of the expansion stability of the infiltrated water stain.

[0073] Among them, the evaluation result of expansion stability refers to the evaluation conclusion of the expansion state of the infiltrated water stain on the surface of the concrete specimen to be tested, including two states: stable state and abnormal state. The stable state indicates that the water seepage process of the concrete specimen has reached a relative balance, and the abnormal state indicates that the water seepage process of the concrete specimen is still changing continuously or there are abnormal fluctuations. Through this binary evaluation result, it can be intuitively reflected whether the water seepage diffusion of the concrete specimen has reached a stable state, providing an important basis for evaluating the anti - permeability performance of concrete.

[0074] Specifically, to evaluate whether the expansion process of the seepage water stain has reached a stable state, it is necessary to analyze and judge the growth rate of the water stain area. First, obtain the growth rate data of the water stain area for multiple consecutive time periods, which reflect the changing trend of the water stain expansion speed. When the absolute value of the growth rate of the water stain area is less than the preset expansion fluctuation threshold, mark the corresponding time period as a stable interval. Subsequently, count the cumulative duration of the continuously marked stable intervals. When this duration is greater than or equal to the preset expansion stability duration threshold, determine that the expansion stability determination result of the seepage water stain is stable, indicating that the water seepage diffusion of the concrete specimen to be tested has reached a relatively stable state; when the cumulative duration is less than the preset expansion stability duration threshold, determine that the expansion stability determination result of the seepage water stain is abnormal, indicating that the water seepage diffusion process of the concrete specimen to be tested is still changing continuously. This stability determination method based on the growth rate of the water stain area not only considers the instantaneous change of the water stain expansion speed but also pays attention to the persistence of the stable state, and can comprehensively reflect the impermeability performance characteristics of the concrete specimen.

[0075] Based on the above embodiments, as an alternative embodiment, in step 104: determining the expansion stability determination result of the seepage water stain based on the growth rate of the water stain area, this step may further include the following steps:

[0076] Step 501: Uniformly divide the surface area of the concrete specimen to be tested into a preset number of detection areas, and calculate the growth rate of the water stain area in each detection area.

[0077] Specifically, to analyze in detail the water seepage characteristics of different areas on the surface of the concrete specimen to be tested, it is necessary to perform refined area division and analysis on the surface of the specimen. First, uniformly divide the entire surface area of the concrete specimen to be tested into several detection areas of equal size according to the preset grid division method. For example, the surface can be divided into different numbers of grid detection areas such as 3×3, 4×4, or 5×5. For each detection area, respectively obtain the water stain area data at two adjacent image acquisition moments in this area, calculate the difference in the water stain area within the area, and divide this difference by the time interval to obtain the local growth rate of the water stain area in this detection area. Through this regional growth rate calculation method, the water seepage diffusion speeds of each detection area on the surface of the concrete specimen to be tested can be obtained respectively, thereby reflecting the differences in the penetration characteristics of different positions on the surface of the concrete specimen, helping to discover local water seepage anomalies, and providing a more detailed and accurate basis for the impermeability performance evaluation of the concrete specimen.

[0078] Step 502: Determine the maximum and minimum values of the growth rate of the water stain area in each detection area.

[0079] Specifically, to evaluate the uniformity of water seepage diffusion between the detection areas on the surface of the concrete specimen to be tested, it is necessary to conduct a comparative analysis of the growth rates of the water stain areas in all detection areas. By traversing the data of the growth rates of the water stain areas in all detection areas, the maximum value and the minimum value are found. These two extreme values reflect the fluctuation range of the water seepage diffusion speed on the surface of the concrete specimen to be tested. The maximum value represents the area where the water seepage diffuses the fastest, and there may be local defects or weak points; the minimum value represents the area where the water seepage diffuses the slowest, reflecting better impermeability performance. By determining these two characteristic values, not only can the non-uniform degree of water seepage diffusion on the surface of the concrete specimen be quantitatively evaluated, but also an important reference basis can be provided for the subsequent identification of abnormal areas and the determination of seepage uniformity, which helps to comprehensively evaluate the overall impermeability performance of the concrete specimen.

[0080] Step 503: When each detection area meets the preset extended stability determination rule, determine that the extended stability determination result of the permeated water stain is stable; when each detection area does not meet the preset extended stability determination rule, determine that the extended stability determination result of the permeated water stain is abnormal. Among them, the preset extended stability determination rule is: in each detection area, the difference between the maximum value and the minimum value is less than the difference threshold, and the proportion of the number of detection areas where the growth rate of the water stain area is less than the stable rate threshold in the total number of detection areas is greater than the preset proportion.

[0081] Specifically, to comprehensively evaluate the overall stability of the expansion of the permeated water stain on the surface of the concrete specimen to be tested, it is necessary to analyze the growth rate of the water stain area in each detection area based on the preset extended stability determination rule. First, calculate the difference between the maximum value and the minimum value of the growth rates of the water stain areas in all detection areas. This difference reflects the degree of dispersion of the water seepage diffusion speed between different areas. When this difference is less than the preset difference threshold, it indicates that the water seepage diffusion speed in each detection area is relatively uniform. Second, count the number of detection areas where the growth rate of the water stain area is less than the stable rate threshold, and calculate the proportion of these areas in the total number of detection areas. This proportion reflects the distribution range of the areas that have reached the stable state on the entire surface of the specimen. When this proportion is greater than the preset proportion, it indicates that the water seepage diffusion in most areas has tended to be stable. When both of the above conditions are met, determine that the extended stability determination result of the permeated water stain is stable, indicating that the water seepage process of the concrete specimen has generally reached a relatively stable state; on the contrary, when any one of the conditions is not met, determine that the extended stability determination result is abnormal, indicating that there is non-uniform diffusion or continuous change in the water seepage process of the concrete specimen. This determination method based on comprehensive analysis of multiple detection areas not only considers the uniformity between local areas but also pays attention to the overall stability, and can more accurately reflect the impermeability performance characteristics of the concrete specimen.

[0082] Step 105: Combine the fluctuation stability determination result and the extended stability determination result to determine the impermeability strength grade of the concrete specimen to be tested.

[0083] Among them, the impermeability strength grade refers to the impermeability performance grade determined according to the penetration characteristics of the concrete specimen to be tested under the action of standard water pressure. The larger the value, the better the impermeability performance. This grade division is obtained by comparing the characteristic parameters (such as the final stable water spot area, diffusion rate, etc.) of the penetration water spot when it reaches the double stable state of time and space with the pre-established evaluation criteria. Through this grade division, the ability of the concrete specimen to prevent water penetration can be quantitatively characterized, providing an important basis for the waterproof design and quality control of concrete structures.

[0084] Specifically, to comprehensively evaluate the impermeability performance of the concrete specimen to be tested, two key characteristics, namely the fluctuation stability and expansion stability of the penetration water spot, need to be considered. First, obtain the determination results of fluctuation stability and expansion stability, which respectively reflect the change law of the water spot area in the time dimension and the diffusion characteristics in the space dimension. When both the determination result of fluctuation stability and the determination result of expansion stability are stable, it indicates that the water seepage process of the concrete specimen has reached a stable state in both the time and space dimensions. At this time, according to the pre-established impermeability strength grade evaluation criteria and combined with the final stable value of the water spot area, the impermeability strength grade of the concrete specimen to be tested can be determined; when there are abnormalities in either the determination result of fluctuation stability or the determination result of expansion stability, it indicates that the water seepage process of the concrete specimen has not reached a completely stable state. At this time, it is necessary to extend the test time or further analyze the reasons for the abnormalities. This method for evaluating the impermeability strength grade based on double stability determination can more accurately and reliably reflect the actual impermeability performance of the concrete specimen by comprehensively considering the time and space characteristics of the water seepage process.

[0085] Based on the above embodiments, as an optional embodiment, in step 105: combining the determination results of fluctuation stability and expansion stability to determine the impermeability strength grade of the concrete specimen to be tested, this step may further include the following steps:

[0086] Step 601: During the time period when both the determination result of fluctuation stability and the determination result of expansion stability are stable, count the stable duration.

[0087] Specifically, to ensure that the water seepage process of the concrete specimen to be tested reaches a sufficient stability, it is necessary to count the duration of the common stability of fluctuation stability and expansion stability. First, identify the time period during the entire test process when both the determination result of fluctuation stability and the determination result of expansion stability are stable, that is, the time period when the area change of the penetration water spot in the time dimension tends to be stable and the diffusion rate distribution in the space dimension tends to be uniform. Then, count the duration of this time period, which reflects the persistence of the stable state of the water seepage process of the concrete specimen and provides a time basis for reliably evaluating the impermeability strength grade subsequently.

[0088] Step 602: When the stable duration is greater than the preset grade determination duration, obtain the average seepage pressure value within the time period.

[0089] Specifically, to ensure the accuracy of the anti-seepage strength grade evaluation, representative seepage pressure data needs to be obtained based on a sufficiently long stable period. First, compare the statistically obtained stable duration with the preset grade determination duration. When the stable duration exceeds the preset duration, it indicates that the water seepage process of the concrete specimen has reached a sufficiently stable state. Then, within this stable time period, collect the seepage pressure values at multiple moments and calculate their arithmetic mean to obtain the average seepage pressure value. This method of calculating the mean based on a long-term stable state can effectively eliminate the influence of random fluctuations in the seepage pressure measurement process and obtain a more representative seepage pressure characteristic value.

[0090] Step 603: Based on the preset seepage pressure numerical interval mapping table, determine the numerical interval corresponding to the average seepage pressure value; according to the calibration result of the numerical interval, determine the anti-seepage strength grade of the concrete specimen to be tested.

[0091] Specifically, to convert the average seepage pressure value into a standard anti-seepage strength grade, the pre-established mapping relationship of seepage pressure numerical intervals needs to be used. First, compare the calculated average seepage pressure value with each interval in the seepage pressure numerical interval mapping table to determine the numerical interval to which the seepage pressure value belongs. Then, according to the calibration result corresponding to this numerical interval, determine the anti-seepage strength grade of the concrete specimen to be tested, such as P6, P8, P10, etc. This grade evaluation method based on a standardized mapping relationship not only ensures the standardization and comparability of the evaluation results, but also facilitates the mutual recognition of test results between different laboratories, providing a reliable technical basis for concrete quality control.

[0092] Referring to Figure 2 , a concrete anti-seepage strength intelligent identification system provided by an embodiment of the present application, the system includes: a parameter acquisition module, a fluctuation stability determination result determination module, an extended stability determination result determination module, and an anti-seepage strength identification module, where:

[0093] The parameter acquisition module is used to acquire the pressure parameters of the concrete specimen to be tested and the pressure acquisition moments corresponding to the pressure parameters, and generate a seepage pressure curve of the concrete specimen to be tested according to the pressure parameters and the pressure acquisition moments;

[0094] The fluctuation stability determination result determination module is used to determine the fluctuation stability determination result of the seepage pressure curve based on the pressure change rate between two adjacent pressure acquisition moments in the seepage pressure curve;

[0095] An extended stability determination result determination module is used to obtain the permeated water spot image on the surface of the concrete specimen to be tested, and calculate the growth rate of the water spot area in the permeated water spot image at two adjacent image acquisition times; based on the growth rate of the water spot area, determine the determination result of the extended stability of the permeated water spot.

[0096] An impermeability strength identification module is used to determine the impermeability strength grade of the concrete specimen to be tested by combining the fluctuation stability determination result and the extended stability determination result.

[0097] On the basis of the above embodiment, the parameter acquisition module is further used to obtain the initial pressure value of the concrete specimen to be tested, subtract the initial pressure value from the pressure parameter to obtain the target pressure value; arrange the target pressure values in time sequence according to the pressure acquisition time to generate a pressure time series; use the moving average method to smooth the pressure time series, and take the pressure acquisition time as the abscissa and the smoothed pressure time series as the ordinate to generate the seepage pressure curve of the concrete specimen to be tested.

[0098] On the basis of the above embodiment, the fluctuation stability determination result determination module is further used to obtain the age of the concrete specimen to be tested; based on the age, determine the correction coefficient of the pressure change rate, and based on the correction coefficient and the pressure change rate, determine the target pressure change rate; when the absolute value of the pressure change rate is less than the preset fluctuation threshold, mark the corresponding time point as a stable point; count the duration of consecutive stable points marked in the seepage pressure curve, and when the duration is greater than or equal to the stable duration threshold, determine that the fluctuation stability determination result of the seepage pressure curve is stable, and when the duration is less than the stable duration threshold, determine that the fluctuation stability determination result of the seepage pressure curve is abnormal.

[0099] On the basis of the above embodiment, the extended stability determination result determination module is further used to obtain the gray value distribution of the permeated water spot image, and determine the gray threshold of the water spot edge based on the gray value distribution; perform binary processing on the permeated water spot image according to the gray threshold of the water spot edge to obtain the water spot area; count the number of pixel points in the water spot area, and convert the number of pixel points into the actual water spot area; calculate the ratio of the difference between the actual water spot areas at two adjacent image acquisition times to the time interval to obtain the growth rate of the water spot area.

[0100] On the basis of the above embodiment, the extended stability determination result determination module is further used to determine a standard gray reference plate placed at the test position where the concrete specimen to be tested is located. The standard gray reference plate includes a dry area reference strip and a wet area reference strip; obtain the gray values of the dry area reference strip and the wet area reference strip; calculate the average gray value of the non-seepage area on the concrete specimen to be tested to obtain the measured dry value; take the ratio of the measured dry value to the gray value of the dry area reference strip as the gray correction coefficient; take the product of the gray value of the wet area reference strip and the gray correction coefficient as the gray threshold of the water spot edge.

[0101] Based on the above embodiments, the extended stability determination result determination module is further configured to evenly divide the surface area of the concrete specimen to be tested into a preset number of detection areas, and calculate the growth rate of the water stain area in each detection area; determine the maximum value and the minimum value of the growth rate of the water stain area in each detection area; when each detection area meets the preset extended stability determination rule, determine that the extended stability determination result of the permeated water stain is stable, and when each detection area does not meet the preset extended stability determination rule, determine that the extended stability determination result of the permeated water stain is abnormal; wherein, the preset extended stability determination rule is: in each detection area, the difference between the maximum value and the minimum value is less than the difference threshold, and the proportion of the number of detection areas where the growth rate of the water stain area is less than the stable rate threshold in the total number of detection areas is greater than the preset proportion.

[0102] Based on the above embodiments, the anti-seepage strength identification module is further configured to count the stable duration within a time period when both the fluctuation stability determination result and the extended stability determination result are stable; when the stable duration is greater than the preset grade determination duration, obtain the average seepage pressure value within the time period; based on the preset seepage pressure numerical interval mapping table, determine the numerical interval corresponding to the average seepage pressure value; and determine the anti-seepage strength grade of the concrete specimen to be tested according to the calibration result of the numerical interval.

[0103] It should be noted that when the device provided in the above embodiments implements its functions, only the above-mentioned division of each functional module is used for illustration. In actual applications, the above functions can be allocated to different functional modules according to needs, that is, the internal structure of the device is divided into different functional modules to complete all or part of the functions described above. In addition, the device and method embodiments provided in the above embodiments belong to the same concept, and the specific implementation process is detailed in the method embodiments, which will not be repeated here.

[0104] This application also discloses an electronic device. Refer to Figure 3 , Figure 3 which is a schematic structural diagram of an electronic device disclosed in an embodiment of the present application. The electronic device 300 may include: at least one processor 301, at least one network interface 304, a user interface 303, a memory 305, and at least one communication bus 302.

[0105] Among them, the communication bus 302 is used to realize the connection and communication between these components.

[0106] Among them, the user interface 303 may include a display (Display) interface and a camera (Camera) interface. Optionally, the user interface 303 may further include a standard wired interface and a wireless interface.

[0107] Among them, the network interface 304 may optionally include a standard wired interface, a wireless interface (such as a WI-FI interface).

[0108] Among them, the processor 301 may include one or more processing cores. The processor 301 connects various parts within the entire server using various interfaces and lines. By running or executing instructions, programs, code sets, or instruction sets stored in the memory 305, and by calling the data stored in the memory 305, it executes various functions of the server and processes data. Optionally, the processor 301 may be implemented in at least one of the following hardware forms: Digital Signal Processing (DSP), Field-Programmable Gate Array (FPGA), Programmable Logic Array (PLA). The processor 301 may integrate one or a combination of several of the Central Processing Unit (CPU), Graphics Processing Unit (GPU), and modem, etc. Among them, the CPU mainly processes the operating system, user interface graphics, and application programs, etc.; the GPU is responsible for rendering and drawing the content to be displayed on the display screen; the modem is used to process wireless communication. It can be understood that the above-mentioned modem may not be integrated into the processor 301 and may be implemented separately by a single chip.

[0109] Among them, the memory 305 may include Random Access Memory (RAM), and may also include Read-Only Memory. Optionally, the memory 305 includes a non-transitory computer-readable storage medium. The memory 305 can be used to store instructions, programs, code, code sets, or instruction sets. The memory 305 may include a program storage area and a data storage area. Among them, the program storage area may store instructions for implementing the operating system, instructions for at least one function (such as touch function, sound playback function, image playback function, etc.), instructions for implementing the above-mentioned various method embodiments, etc.; the data storage area may store the data involved in the above-mentioned various method embodiments. Optionally, the memory 305 may also be at least one storage device located far from the aforementioned processor 301. Referring to Figure 3 , as a computer storage medium, the memory 305 may include an operating system, a network communication module, a user interface module, and an application program for a method of intelligent identification of concrete impermeability strength.

[0110] In Figure 3 In the electronic device 300 shown, the user interface 303 is mainly used to provide an interface for the user to input and obtain the data input by the user; and the processor 301 can be used to call the application program stored in the memory 305 for an intelligent identification method of concrete impermeability strength. When executed by one or more processors 301, the electronic device 300 is caused to execute the method of one or more of the above embodiments. It should be noted that, for the foregoing method embodiments, for simplicity of description, they are all expressed as a series of action combinations. However, those skilled in the art should know that the present application is not limited by the described action sequence, because according to the present application, certain steps can be performed in other sequences or simultaneously. Secondly, those skilled in the art should also know that the embodiments described in the specification are all preferred embodiments, and the actions and modules involved are not necessarily essential to the present application.

[0111] In the above embodiments, the descriptions of the respective embodiments have their own emphases. For the parts not detailed in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0112] In several implementation manners provided by the present application, it should be understood that the disclosed device can be implemented in other ways. For example, the device embodiments described above are only illustrative. For example, the division of units is only a logical function division. In actual implementation, there may be other division methods. For example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the displayed or discussed coupling or direct coupling or communication connection to each other can be through some service interfaces. The indirect coupling or communication connection of the device or unit can be in an electrical or other form.

[0113] The units described as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units, that is, they can be located in one place, or can be distributed to multiple network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0114] In addition, the functional units in each embodiment of the present application can be integrated in a processing unit, or each unit can exist physically alone, or two or more units can be integrated in one unit. The above integrated units can be implemented in the form of hardware or in the form of software functional units.

[0115] When the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable memory. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or all or part of this technical solution, can be embodied in the form of a software product. This computer software product is stored in a memory and includes several instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the methods of various embodiments of this application. And the aforementioned memory includes: various media such as USB flash drives, mobile hard disks, magnetic disks, or optical discs that can store program codes.

[0116] The above are only exemplary embodiments of the present disclosure and should not be used to limit the scope of the present disclosure. That is, any equivalent changes and modifications made in accordance with the teachings of the present disclosure still fall within the scope covered by the present disclosure. Those skilled in the art will readily think of other implementation schemes of the present disclosure after considering the specification and the practice of the disclosure.

[0117] This application aims to cover any variations, uses, or adaptive changes of the present disclosure that follow the general principles of the present disclosure and include common general knowledge or conventional technical means in the technical field not recorded in the present disclosure. The specification and the embodiments are only regarded as exemplary.

Claims

1. An intelligent identification method for the impermeability strength of concrete, characterized in that, Including: Obtain the pressure parameter of the concrete specimen to be tested and the pressure acquisition moment corresponding to the pressure parameter, and generate the seepage pressure curve of the concrete specimen to be tested according to the pressure parameter and the pressure acquisition moment; Based on the pressure change rate between two adjacent pressure acquisition moments in the seepage pressure curve, determine the fluctuation stability determination result of the seepage pressure curve; Obtain the seepage water spot image on the surface of the concrete specimen to be tested, and calculate the water spot area growth rate of the seepage water spot image at two adjacent image acquisition moments; Based on the water spot area growth rate, determine the expansion stability determination result of the seepage water spot; Combine the fluctuation stability determination result and the expansion stability determination result to determine the impermeability strength grade of the concrete specimen to be tested; The determining the fluctuation stability determination result of the seepage pressure curve based on the pressure change rate between two adjacent pressure acquisition moments in the seepage pressure curve includes: Obtain the age of the concrete specimen to be tested; Based on the age, determine the correction coefficient of the pressure change rate, and based on the correction coefficient and the pressure change rate, determine the target pressure change rate; When the absolute value of the pressure change rate is less than the preset fluctuation threshold, mark the corresponding time point as a stable point; Count the duration of continuously marked stable points in the seepage pressure curve. When the duration is greater than or equal to the stable duration threshold, determine that the fluctuation stability determination result of the seepage pressure curve is stable. When the duration is less than the stable duration threshold, determine that the fluctuation stability determination result of the seepage pressure curve is abnormal; The determining the expansion stability determination result of the seepage water spot based on the water spot area growth rate includes: Evenly divide the surface area of the concrete specimen to be tested into a preset number of detection areas, and calculate the water spot area growth rate in each detection area; Determine the maximum value and the minimum value of the water spot area growth rate in each detection area; When each detection area meets the preset expansion stability determination rule, determine that the expansion stability determination result of the seepage water spot is stable. When each detection area does not meet the preset expansion stability determination rule, determine that the expansion stability determination result of the seepage water spot is abnormal; Wherein, the preset expansion stability determination rule is: In each detection area, the difference between the maximum value and the minimum value is less than the difference threshold, and the proportion of the number of detection areas where the water spot area growth rate is less than the stable rate threshold in the total number of detection areas is greater than the preset proportion.

2. The intelligent identification method for the impermeability strength of concrete according to claim 1, characterized in that The generating the seepage pressure curve of the concrete specimen to be tested according to the pressure parameter and the pressure acquisition moment includes: Obtain the initial pressure value of the concrete specimen to be tested, and subtract the initial pressure value from the pressure parameter to obtain the target pressure value; Arrange the target pressure values in time sequence according to the pressure acquisition moment to generate a pressure time series; Use the moving average method to smooth the pressure time series, and generate the seepage pressure curve of the concrete specimen to be tested with the pressure acquisition moment as the abscissa and the smoothed pressure time series as the ordinate.

3. The intelligent identification method for the impermeability strength of concrete according to claim 1, characterized in that Calculating the water spot area growth rate of the permeated water spot image at two adjacent image acquisition times includes: Obtaining the gray value distribution of the permeated water spot image and determining the gray threshold of the water spot edge based on the gray value distribution; Performing binarization processing on the permeated water spot image according to the gray threshold of the water spot edge to obtain a water spot area; Counting the number of pixel points in the water spot area and converting the number of pixel points into the actual water spot area; Calculating the ratio between the difference in the actual water spot areas at the two adjacent image acquisition times and the time interval to obtain the water spot area growth rate.

4. The intelligent identification method for the impermeability strength of concrete according to claim 3, wherein Determining the gray threshold of the water spot edge based on the gray value distribution includes: Determining a standard gray reference plate placed at the test position of the concrete specimen to be tested, where the standard gray reference plate includes a dry area reference strip and a wet area reference strip; Obtaining the gray values of the dry area reference strip and the wet area reference strip; Calculating the average gray value of the non-seepage area on the concrete specimen to be tested to obtain the measured dry value; Taking the ratio of the measured dry value to the gray value of the dry area reference strip as the gray correction coefficient; Taking the product of the gray value of the wet area reference strip and the gray correction coefficient as the gray threshold of the water spot edge.

5. The intelligent identification method for the anti-seepage strength of concrete according to claim 1, characterized in that Combining the fluctuation stability determination result and the expansion stability determination result to determine the impermeability strength grade of the concrete specimen to be tested includes: During the time period when both the fluctuation stability determination result and the expansion stability determination result are stable, counting the stable duration; When the stable duration is greater than the preset grade determination duration, obtaining the average seepage pressure value during this time period; Based on a preset seepage pressure numerical interval mapping table, determining the numerical interval corresponding to the average seepage pressure value; According to the calibration result of the numerical interval, determining the impermeability strength grade of the concrete specimen to be tested.

6. An intelligent identification system for the impermeability strength of concrete, characterized in that, The system includes: A parameter acquisition module for acquiring the pressure parameter of the concrete specimen to be tested and the pressure acquisition time corresponding to the pressure parameter, and generating a seepage pressure curve of the concrete specimen to be tested according to the pressure parameter and the pressure acquisition time; A fluctuation stability determination result determination module for determining the fluctuation stability determination result of the seepage pressure curve based on the pressure change rate between two adjacent pressure acquisition times in the seepage pressure curve; An expansion stability determination result determination module for obtaining the permeated water spot image on the surface of the concrete specimen to be tested and calculating the water spot area growth rate of the permeated water spot image at two adjacent image acquisition times; determining the expansion stability determination result of the permeated water spot based on the water spot area growth rate; An impermeability strength identification module for combining the fluctuation stability determination result and the expansion stability determination result to determine the impermeability strength grade of the concrete specimen to be tested; Determining the fluctuation stability determination result of the seepage pressure curve based on the pressure change rate between two adjacent pressure acquisition times in the seepage pressure curve includes: Obtaining the age of the concrete specimen to be tested; Based on the age, determine a correction coefficient for the rate of change of the pressure, and based on the correction coefficient and the rate of change of the pressure, determine a target rate of change of the pressure; When the absolute value of the rate of change of the pressure is less than a preset fluctuation threshold, mark the corresponding time point as a stable point; Statistically calculate the duration of continuously marked stable points in the seepage pressure curve. When the duration is greater than or equal to a stable duration threshold, determine that the fluctuation stability determination result of the seepage pressure curve is stable. When the duration is less than the stable duration threshold, determine that the fluctuation stability determination result of the seepage pressure curve is abnormal; The determining the expansion stability determination result of the permeation water spot based on the water spot area growth rate includes: Evenly divide the surface area of the concrete test piece to be measured into a preset number of detection areas, and calculate the water spot area growth rate in each detection area; Determine the maximum value and the minimum value of the water spot area growth rate in each detection area; When each detection area meets a preset expansion stability determination rule, determine that the expansion stability determination result of the permeation water spot is stable. When each detection area does not meet the preset expansion stability determination rule, determine that the expansion stability determination result of the permeation water spot is abnormal; Wherein, the preset expansion stability determination rule is: In each detection area, the difference between the maximum value and the minimum value is less than a difference threshold, and the proportion of the number of detection areas where the water spot area growth rate is less than a stable rate threshold in the total number of detection areas is greater than a preset ratio.

7. An electronic device, characterized in that, Comprising a processor, a memory, a user interface and a network interface, the memory is used for storing instructions, the user interface and the network interface are used for communicating with other devices, and the processor is used for executing the instructions stored in the memory so that the electronic device executes the concrete impermeability strength intelligent identification method according to any one of claims 1-5.

8. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores instructions, and when the instructions are executed, the concrete impermeability strength intelligent identification method according to any one of claims 1-5 is executed.

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