Intelligent identification method, system and equipment for concrete impermeability strength and medium

Abstract

The invention discloses an intelligent concrete impermeability strength identification method, system and device and a medium, and relates to the technical field of data processing. The method comprises the following steps: acquiring a pressure parameter of a to-be-tested concrete test piece and a pressure acquisition moment corresponding to the pressure parameter, and generating an osmotic pressure curve of the to-be-tested concrete test piece according to the pressure parameter and the pressure acquisition moment; determining a fluctuation stability judgment result of the osmotic pressure curve based on the pressure change rate of two adjacent pressure acquisition moments in the osmotic pressure curve; acquiring a seepage water spot image of the surface of the to-be-detected concrete test piece, and calculating 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, determining an expansion stability judgment result of the seepage water spots; and determining the anti-permeability strength grade of the to-be-tested concrete test piece by combining the fluctuation stability judgment result and the extension stability judgment result. By implementing the technical scheme provided by the invention, the effect of improving the recognition accuracy of the impervious strength of the concrete is achieved.

Description

Technical Field

[0001] The present application relates to the field of data processing technology, and in particular to a method, system, equipment and medium for intelligently identifying the anti-permeability strength of concrete. Background Art

[0002] With the rapid development of urbanization, concrete building structures are increasingly used in humid environments such as water conservancy projects and underground projects. The impermeability of concrete, as an important indicator to measure its durability and safety, is increasingly valued by the engineering community.

[0003] At present, the pressure penetration method is commonly used in engineering practice to test the impermeability of concrete specimens. By applying water pressure to the specimens, the testers observe the penetration of the concrete specimens to evaluate the concrete's impermeability strength grade. However, in actual applications, due to the subtle changes in the concrete specimens during the impermeability test, it is easy to miss the test data if the testers only conduct manual identification and evaluation, resulting in errors in the test results, thereby reducing the accuracy of concrete impermeability strength identification. Summary of the invention

[0004] The present application provides a method, system, device and medium for intelligently identifying the anti-permeability strength of concrete, which has the effect of improving the accuracy of identifying the anti-permeability strength of concrete.

[0005] In a first aspect, the present application provides a method for intelligently identifying the anti-permeability strength of concrete, comprising: Acquire pressure parameters of the concrete specimen to be tested and the pressure collection time corresponding to the pressure parameters, and generate a permeability pressure curve of the concrete specimen to be tested according to the pressure parameters and the pressure collection time; Determining a 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; Acquire the image of the seepage water spot 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, determining the expansion stability determination result of the infiltration water spot; The anti-permeability strength grade of the concrete specimen to be tested is determined by combining the fluctuation stability determination result and the extended stability determination result.

[0006] In a second aspect of the present application, a system for intelligently identifying the anti-permeability strength of concrete is provided, the system comprising: A parameter acquisition module, used to acquire pressure parameters of the concrete specimen to be tested and the pressure acquisition time corresponding to the pressure parameters, and generate a permeability pressure curve of the concrete specimen to be tested according to the pressure parameters and the pressure acquisition time; A fluctuation stability determination result determination module, used to determine the fluctuation stability determination result of the osmotic pressure curve based on the pressure change rate of two adjacent pressure collection moments in the osmotic pressure curve; The module for determining the result of the extended stability determination is used to obtain the image of the seepage water spot 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 extended stability determination result of the seepage water spot; The anti-permeability strength identification module is used to determine the anti-permeability strength grade of the concrete specimen to be tested by combining the fluctuation stability determination result and the extended stability determination result.

[0007] In a third aspect of the present application, an electronic device is provided, comprising a memory, a processor, and a program stored in the memory and executable on the processor, wherein the program can implement an intelligent identification method for the anti-permeability strength of concrete when loaded and executed by the processor.

[0008] In a fourth aspect of the present application, a computer-readable storage medium is provided, wherein the computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the processor implements a method for intelligently identifying the impermeability strength of concrete.

[0009] In summary, one or more technical solutions provided in the embodiments of the present application have at least the following technical effects or advantages: By adopting the above technical scheme, the pressure parameters of the concrete specimen to be tested and the corresponding pressure collection time are obtained during the test process and a seepage pressure curve is generated, so that the pressure change trend can be tracked and quantitatively analyzed more accurately, and then the fluctuation stability judgment result is judged by comparing the pressure change rate at two adjacent pressure collection times in the seepage pressure curve. On this basis, the image of the infiltration water spot on the surface of the concrete specimen to be tested is simultaneously obtained and the water spot area growth rate at two adjacent image collection times is calculated, so as to determine the extension stability judgment result of the infiltration water spot, so that the internal seepage pressure fluctuation of the specimen under pressure and the surface water spot expansion can be double-evaluated, avoiding omissions or misjudgments that may be caused by a single monitoring dimension, and making the judgment on the concrete anti-seepage behavior more comprehensive and reliable. When the fluctuation stability judgment result and the extension stability judgment result confirm each other and both show stability, it can be determined that the concrete specimen has reached the corresponding anti-seepage state, so as to combine the judgment results of the two to quickly and accurately determine the anti-seepage strength grade of the concrete specimen to be tested, thereby improving the accuracy of concrete anti-seepage strength identification. BRIEF DESCRIPTION OF THE DRAWINGS

[0010] Figure 1It is a flow chart of a method for intelligently identifying the anti-seepage strength of concrete provided in an embodiment of the present application; Figure 2 It is a structural schematic diagram of a concrete anti-seepage strength intelligent identification system provided in an embodiment of the present application; Figure 3 It is a structural schematic diagram of an electronic device provided in an embodiment of the present application.

[0011] Description of reference numerals: 300, electronic device; 301, processor; 302, communication bus; 303, user interface; 304, network interface; 305, memory. DETAILED DESCRIPTION

[0012] In order to enable technicians in this field 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 part of the embodiments of this application, not all of the embodiments.

[0013] In the description of the embodiments of the present application, words such as "for example" or "for example" are used to indicate examples, illustrations or explanations. Any embodiment or design described as "for example" or "for example" in the embodiments of the present application should not be interpreted as being more preferred or more advantageous than other embodiments or designs. Specifically, the use of words such as "for example" or "for example" is intended to present related concepts in a specific way.

[0014] In the description of the embodiments of the present application, the meaning of the term "multiple" refers to two or more. For example, multiple systems refer to two or more systems, and multiple screen terminals refer to two or more screen terminals. In addition, the terms "first" and "second" are used for descriptive purposes only and cannot be understood as indicating or implying relative importance or implicitly indicating the indicated technical features. Thus, the features defined as "first" and "second" may explicitly or implicitly include one or more of the features. The terms "include", "comprise", "have" and their variations all mean "including but not limited to", unless otherwise specifically emphasized.

[0015] The present application embodiment provides a method for intelligently identifying the anti-permeability strength of concrete. In one embodiment, please refer to Figure 1 , Figure 1 The flowchart of the method for intelligent identification of concrete impermeability strength provided by the embodiment of the present application can be implemented by a computer program, which can be integrated into an application or run as an independent tool application. The method can also be implemented by a single-chip microcomputer or run on a concrete impermeability strength intelligent identification system based on the von Neumann system. Specifically, the method can include the following steps: Step 101: obtaining pressure parameters of a concrete specimen to be tested and a pressure acquisition time corresponding to the pressure parameters, and generating a permeability pressure curve of the concrete specimen to be tested according to the pressure parameters and the pressure acquisition time.

[0016] Among them, the concrete specimen to be tested refers to a concrete sample made in accordance with standard specifications for testing the impermeability of the concrete. During the test, the specimen is placed in an impermeability test device and subjected to water pressure to evaluate the impermeability of the concrete.

[0017] The pressure parameter refers to the real-time water pressure value acting on the surface of the concrete specimen collected by the pressure sensor during the anti-permeability test of the concrete specimen. This value reflects the actual water pressure that the concrete specimen is subjected to during the test.

[0018] The pressure collection moment refers to the specific time point corresponding to when the pressure sensor collects each pressure parameter. It is used to record the process of pressure parameter changes over time, ensure that the pressure data has time attributes, and facilitate subsequent analysis of pressure change trends.

[0019] The seepage pressure curve refers to a curve graph drawn with the pressure collection time as the horizontal axis and the pressure parameter as the vertical axis. This curve intuitively shows the trend of pressure change over time of the concrete specimen to be tested during the entire testing process, and is used to analyze the anti-seepage performance of the concrete specimen.

[0020] Specifically, the concrete specimen to be tested is first placed in the anti-permeability test device, and the pressure parameters acting on the surface of the specimen are collected in real time by the pressure sensor set on the test device. In order to record the time characteristics of pressure changes, the system automatically records the pressure collection time corresponding to each pressure parameter, so as to obtain pressure data containing time information. After obtaining the pressure parameters and the pressure collection time, the initial pressure value of the concrete specimen to be tested is first obtained, and the target pressure value is obtained by subtracting the initial pressure value from the pressure parameter to eliminate the influence of the ambient pressure. Subsequently, the target pressure value is arranged in time sequence according to the pressure collection time to generate a pressure time series reflecting the law of pressure change over 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 in the window, the smoothed pressure time series is obtained as the window gradually moves. Finally, the seepage pressure curve of the concrete specimen to be tested is generated with the pressure collection time as the horizontal coordinate and the smoothed pressure time series as the vertical coordinate. This automated data collection and processing method avoids data omissions that are easily caused by manual observation. At the same time, it eliminates the influence of interference factors through data smoothing processing, so that the final permeability pressure curve can accurately reflect the pressure change trend of the concrete specimen during the detection process, providing a reliable data basis for subsequent anti-permeability performance analysis.

[0021] Based on the above embodiment, as an optional embodiment, in step 101: generating a permeability curve of the concrete specimen to be tested according to the pressure parameter and the pressure acquisition time, this step may also include the following steps: Step 201: Obtain an initial pressure value of the concrete specimen to be tested, and subtract the initial pressure value from the pressure parameter to obtain a target pressure value.

[0022] Specifically, before the concrete specimen to be tested begins the water-resistance test, the initial pressure value of the concrete specimen to be tested is obtained through the pressure sensor, and the initial pressure value reflects the environmental pressure state of the specimen when no water pressure is applied. Then, the pressure parameters collected during the test are subtracted from the initial pressure value to obtain the target pressure value after eliminating the influence of environmental pressure. This can eliminate the interference of environmental factors on the test results, so that the subsequent analysis can more accurately reflect the true water-resistance performance of the concrete specimen.

[0023] Step 202: Arrange the target pressure values ​​in time sequence according to the pressure collection time to generate a pressure time series.

[0024] Specifically, the target pressure values ​​obtained are arranged in chronological order according to their corresponding pressure collection moments to generate a pressure time series containing time information. Through time series arrangement, the change pattern of the target pressure value over time can be clearly displayed, laying the foundation for subsequent data processing and analysis. Since the pressure sensor continuously collects a large amount of data during the detection process, time series arrangement can ensure the continuity and integrity of the data, which is conducive to accurately grasping the pressure change trend.

[0025] Step 203: Smoothing the pressure time series by using the moving average method, and generating a seepage pressure curve of the concrete specimen to be tested by taking the pressure acquisition time as the abscissa and the smoothed pressure time series as the ordinate.

[0026] Specifically, the moving average method is used to smooth the data in the pressure time series. The specific operation of the moving average method is to select an appropriate time window, calculate the average value of all data points in the window as the new value of the center point, and obtain a complete smoothed pressure time series as the window moves gradually. Smoothing can effectively reduce the impact of random fluctuations and noise in the pressure data, making the pressure change trend more obvious. Finally, the seepage pressure curve of the concrete specimen to be tested is drawn with the pressure collection time as the horizontal coordinate and the smoothed pressure time series as the vertical coordinate. This processing method not only retains the main trend of pressure change, but also eliminates the influence of interference factors, so that the seepage pressure curve can more accurately reflect the change process of the concrete specimen's impermeability performance.

[0027] Step 102: Determine the fluctuation stability determination result of the osmotic pressure curve based on the pressure change rate at two adjacent pressure collection moments in the osmotic pressure curve.

[0028] Among them, the pressure change rate refers to the speed of pressure change between two adjacent pressure collection moments in the osmotic pressure curve. The calculated result reflects the degree of pressure change per unit time. This parameter can be used to quantitatively evaluate the severity of pressure changes.

[0029] The fluctuation stability judgment result refers to the stability assessment result obtained by analyzing the distribution characteristics of the pressure change rate in the seepage pressure curve. When this ratio is small, it indicates that the overall fluctuation of the seepage pressure curve is stable; when this ratio is large, it indicates that the seepage pressure curve fluctuates violently. This result can be used to judge the pressure stability of the concrete specimen during the test process.

[0030] 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.

[0031] 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: 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.

[0032] 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.

[0033] 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.

[0034] Specifically, by comparing the absolute value of the target pressure change rate with the preset fluctuation threshold, the stable point in the osmotic pressure curve is 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 that time point is relatively gentle, so the time point is marked as a stable point. This threshold-based judgment method can objectively identify the time period when the pressure changes steadily, providing basic data for the subsequent evaluation of overall stability.

[0035] Step 303: Count the duration of continuous marks as stable points in the osmotic pressure curve. When the duration is greater than or equal to the stable duration threshold, the fluctuation stability judgment result of the osmotic pressure curve is determined to be stable. When the duration is less than the stable duration threshold, the fluctuation stability judgment result of the osmotic pressure curve is determined to be abnormal.

[0036] Specifically, a statistical analysis is performed on the time periods in the seepage pressure curve that are continuously marked as stable points, and the duration of the continuous stable points is calculated. When the duration of the continuous stable points is greater than or equal to the preset stable duration threshold, it means that the concrete specimen to be tested has maintained a stable pressure state for a sufficiently long time, and the fluctuation stability judgment result of the seepage pressure curve is determined to be stable. On the contrary, when the duration of the continuous stable points is less than the stable duration threshold, it means that the concrete specimen to be tested has failed to maintain a stable state for a sufficiently long time, and the fluctuation stability judgment result is determined to be abnormal. This judgment method based on the continuous stable duration not only takes into account the severity of the pressure change, but also pays attention to the continuity of the stable state, and can more comprehensively evaluate the stability of the anti-permeability performance of the concrete specimen.

[0037] Step 103: obtaining an image of the water spot on the surface of the concrete specimen to be tested, and calculating the water spot area growth rate of the water spot at two adjacent image acquisition moments.

[0038] The water spot image refers to the image of the water stain diffusion traces on the surface of the concrete specimen to be tested, which is collected by the image acquisition device. It is specifically manifested as a 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 water spot image, the water seepage of the concrete specimen can be quantitatively evaluated.

[0039] The water spot area growth rate refers to the rate of change of the water spot area on the surface of the concrete specimen between two adjacent image acquisition moments. The calculation result reflects the expansion of the water spot area per unit time. This parameter can be used to quantitatively evaluate the water seepage diffusion rate of concrete specimens and then judge the anti-seepage performance of concrete.

[0040] Specifically, in order to comprehensively evaluate the anti-seepage performance of the concrete specimen to be tested, it is necessary to analyze the dynamic change characteristics of the infiltration water spots on the surface of the specimen. First, during the detection process, the image acquisition device set on the test device continuously acquires the infiltration water spot images on the surface of the concrete specimen to be tested at preset time intervals. For each collected infiltration water spot image, the water spot area is identified and segmented using image processing technology. By calculating the number of pixels in the water spot area and combining the image resolution, the actual area of ​​the water spot at each image acquisition moment can be obtained. Subsequently, the water spot area at two adjacent image acquisition moments is analyzed. The water spot area growth rate in the time period is obtained by calculating the water spot area at the next moment minus the water spot area at the previous moment, and then dividing it by the time interval between the two moments. The water spot area growth rate reflects the speed of water diffusion of the concrete specimen per unit time. This parameter can intuitively reflect the anti-seepage performance of the concrete specimen. Through this automated image acquisition and analysis method, the expansion process of the infiltration water spot can be accurately recorded and quantified, avoiding the subjectivity and errors of the traditional manual measurement method, and providing data support for evaluating the anti-seepage performance of the concrete specimen.

[0041] Based on the above embodiment, as an optional embodiment, in step 103: calculating the water spot area growth rate of the infiltration water spot image at two adjacent image acquisition moments, this step may also include the following steps: Step 401: Obtain the grayscale value distribution of the infiltrated water spot image, and determine the grayscale threshold of the water spot edge based on the grayscale value distribution.

[0042] Specifically, it is necessary to first analyze the grayscale value of the acquired water spot image, because the water spot area and the non-water spot area show different grayscale value distribution characteristics in the image. By counting the grayscale values ​​of each pixel in the image, the grayscale value distribution histogram of the entire image is obtained. Based on the bimodal characteristics of the histogram, the grayscale value distribution range of the water spot area and the non-water spot area can be identified, and the grayscale threshold of the water spot edge can be determined at the valley between the two peaks. This threshold determination method based on image grayscale features can adaptively process water spot images under different lighting conditions and improve the accuracy of subsequent water spot recognition.

[0043] Based on the above embodiment, as an optional embodiment, in step 401: determining the grayscale threshold of the water spot edge based on the grayscale value distribution, this step may also include the following steps: Step 411: Determine a standard grayscale reference plate placed at the test position of the concrete specimen to be tested, the standard grayscale reference plate comprising a dry area reference bar and a wet area reference bar.

[0044] Specifically, in order to eliminate the influence of ambient light changes on water spot recognition, a standard grayscale reference plate needs to be placed at the test position of the concrete specimen to be tested. The standard grayscale reference plate includes two characteristic areas: a dry area reference bar and a wet area reference bar, wherein the grayscale value of the dry area reference bar corresponds to the standard grayscale value of the surface of uninfiltrated concrete, and the grayscale value of the wet area reference bar corresponds to the standard grayscale value of the surface of fully infiltrated concrete. By simultaneously recording the grayscale values ​​of these two standard reference bars during the image acquisition process, a benchmark reference can be provided for subsequent grayscale value correction, ensuring that accurate recognition results can be obtained for water spot images obtained under different lighting conditions.

[0045] Step 421: Obtain the grayscale values ​​of the dry area reference bar and the wet area reference bar; calculate the average grayscale value of the non-water-seepage area on the concrete specimen to be tested to obtain the measured dry value.

[0046] Specifically, the grayscale values ​​of the dry area reference bar and the wet area reference bar on the standard grayscale reference plate are first extracted from the infiltration water spot image. At the same time, the area without water seepage is selected in the infiltration water spot image of the concrete specimen to be tested, and the average grayscale value of all pixels in the area is calculated to obtain the measured dry value. This measured dry value reflects the actual grayscale characteristics of the non-water seepage area of ​​the concrete specimen under the current lighting conditions. By comparing the measured dry value with the grayscale value of the standard reference bar, the influence of ambient light on the grayscale value of the image can be quantitatively evaluated.

[0047] Step 431: The ratio of the measured dry value to the grayscale value of the dry area reference bar is used as the grayscale correction coefficient; the product of the grayscale value of the wet area reference bar and the grayscale correction coefficient is used as the grayscale threshold of the water spot edge.

[0048] Specifically, in order to correct the grayscale value deviation caused by ambient light, the ratio of the measured dry value to the grayscale value of the reference bar in the dry area is first calculated to obtain the grayscale correction coefficient. The grayscale correction coefficient reflects the degree of deviation of the current lighting conditions relative to the standard lighting conditions. Then, the grayscale value of the reference bar in the wet area is multiplied by the grayscale correction coefficient to obtain the grayscale threshold of the water spot edge that takes into account the actual lighting conditions. This correction method based on standard reference can effectively eliminate the influence of ambient light changes on water spot recognition and improve the accuracy and reliability of water spot edge recognition.

[0049] Step 402: Binarize the infiltrated water spot image according to the grayscale threshold of the water spot edge to obtain the water spot area.

[0050] Specifically, the determined water spot edge grayscale threshold is used to perform binarization processing on the infiltration water spot image. Specifically, the pixel points in the image whose grayscale value is less than the water spot edge grayscale threshold are determined as the water spot area, and their grayscale value is set to 0 (black), and the pixel points whose grayscale value is greater than or equal to the water spot edge grayscale threshold are determined as the non-water spot area, and their grayscale value is set to 255 (white). Through this binarization process, the continuous grayscale image can be converted into a binary image containing only the water spot area and the non-water spot area, providing a clear area division for the subsequent area calculation.

[0051] Step 403: Count the number of pixels in the water spot area, and convert the number of pixels into the actual water spot area.

[0052] Specifically, the pixel count of the water spot area is performed on the binary image. By traversing all the pixels in the image and counting the number of pixels with a gray value of 0, the number of pixels in the water spot area can be obtained. Subsequently, based on the resolution parameter of the image acquisition device, the number of pixels is converted into the actual water spot area. For example, if the actual area size corresponding to each pixel is known, the actual area of ​​the water spot can be obtained by multiplying the number of pixels obtained by counting the actual area corresponding to a single pixel. This area calculation method based on pixel statistics can accurately quantify the actual size of the water spot.

[0053] Step 404: Calculate the ratio between the difference in actual water spot areas between two adjacent image acquisition moments and the time interval to obtain a water spot area growth rate.

[0054] Specifically, the actual water spot area at two adjacent image acquisition moments is analyzed and calculated. First, the actual water spot area at the latter moment is subtracted from the actual water spot area at the previous moment to obtain the increment of the water spot area during this period. Then, the increment is divided by the time interval between the two image acquisition moments to obtain the water spot area growth rate. This growth rate calculation method can accurately reflect the rate of change of the water spot area over time, and provide an important quantitative indicator for evaluating the anti-permeability performance of concrete specimens.

[0055] Step 104: Based on the water spot area growth rate, determine the expansion stability judgment result of the infiltration water spot.

[0056] Among them, the extension stability judgment result refers to the evaluation conclusion of the expansion state of the water spot on the surface of the concrete specimen to be tested, which includes 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 or there are abnormal fluctuations. Through this binary judgment 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-seepage performance of concrete.

[0057] Specifically, in order to evaluate whether the expansion process of the seepage water spot has reached a stable state, it is necessary to analyze and judge the water spot area growth rate. First, the water spot area growth rate data for multiple consecutive time periods are obtained, which reflect the changing trend of the water spot expansion speed. When the absolute value of the water spot area growth rate is less than the preset expansion fluctuation threshold, the corresponding time period is marked as a stable interval. Subsequently, the cumulative duration of the continuous marked stable interval is counted. When the duration is greater than or equal to the preset expansion stability time threshold, the expansion stability judgment result of the seepage water spot is determined to be stable, indicating that the 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 time threshold, the expansion stability judgment result of the seepage water spot is determined to be abnormal, indicating that the seepage diffusion process of the concrete specimen to be tested is still changing. This stability judgment method based on the water spot area growth rate not only takes into account the instantaneous change of the water spot expansion speed, but also pays attention to the continuity of the stable state, and can fully reflect the anti-seepage performance characteristics of the concrete specimen.

[0058] Based on the above embodiment, as an optional embodiment, in step 104: determining the expansion stability determination result of the infiltration water spot based on the water spot area growth rate, this step may also include the following steps: Step 501: 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.

[0059] Specifically, in order to analyze the water seepage characteristics of different areas on the surface of the concrete specimen to be tested in detail, it is necessary to perform refined regional division and analysis on the surface of the specimen. First, the entire surface area of ​​the concrete specimen to be tested is evenly divided into several equal-sized detection areas 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, the water spot area data of the area at two adjacent image acquisition moments are obtained respectively, the difference in the water spot area in the area is calculated, and the difference is divided by the time interval to obtain the local water spot area growth rate of the detection area. Through this regionalized growth rate calculation method, the water seepage diffusion rate of each detection area on the surface of the concrete specimen to be tested can be obtained respectively, thereby reflecting the difference in permeability characteristics at different positions on the surface of the concrete specimen, which is helpful to discover local water seepage abnormalities and provide a more detailed and accurate basis for the evaluation of the anti-permeability performance of concrete specimens.

[0060] Step 502: Determine the maximum and minimum values ​​of the water spot area growth rate in each detection area.

[0061] Specifically, in order to evaluate the uniformity of water seepage diffusion between the test areas on the surface of the concrete specimen to be tested, it is necessary to compare and analyze the water spot area growth rate of all test areas. By traversing the water spot area growth rate data of all test areas, the maximum and minimum values ​​are found. These two extreme values ​​reflect the fluctuation range of the water seepage diffusion rate on the surface of the concrete specimen to be tested. The maximum value represents the area with the fastest water seepage diffusion, which may have local defects or weak points; the minimum value represents the area with the slowest water seepage diffusion, reflecting better anti-seepage performance. By determining these two characteristic values, not only can the uneven 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 permeability uniformity, which is helpful to comprehensively evaluate the overall anti-seepage performance of the concrete specimen.

[0062] Step 503: When each detection area satisfies the preset expansion stability judgment rule, the expansion stability judgment result of the infiltration water spot is determined to be stable; when each detection area does not satisfy the preset expansion stability judgment rule, the expansion stability judgment result of the infiltration water spot is determined to be abnormal; wherein, the preset expansion stability judgment rule is: in each detection area, the difference between the maximum value and the minimum value is less than the difference threshold, and the number of detection areas with a water spot area growth rate less than the stability rate threshold accounts for a proportion greater than a preset proportion of the total number of detection areas.

[0063] Specifically, in order to comprehensively evaluate the overall stability of the expansion of the water spot on the surface of the concrete specimen to be tested, it is necessary to analyze the water spot area growth rate of each detection area based on the preset expansion stability judgment rule. First, the difference between the maximum and minimum values ​​of the water spot area growth rate in all detection areas is calculated, and the difference reflects the discrete degree of the water seepage diffusion rate between different areas. When the difference is less than the preset difference threshold, it indicates that the water seepage diffusion rate of each detection area is relatively uniform. Secondly, the number of detection areas whose water spot area growth rate is less than the stable rate threshold is counted, and the proportion of these areas to the total number of detection areas is calculated. The proportion reflects the distribution range of the areas that have reached a stable state on the entire specimen surface. When the proportion is greater than the preset proportion, it indicates that the water seepage diffusion in most areas has tended to be stable. When the above two conditions are met at the same time, the expansion stability judgment result of the infiltration water spot is determined to be stable, indicating that the water seepage process of the concrete specimen has reached a relatively stable state as a whole; on the contrary, when any condition is not met, the expansion stability judgment result is determined to be abnormal, indicating that there is uneven diffusion or continuous change in the water seepage process of the concrete specimen. This judgment method based on comprehensive analysis of multiple test areas not only takes into account the uniformity between local areas, but also pays attention to the overall stability, and can more accurately reflect the anti-permeability performance characteristics of concrete specimens.

[0064] Step 105: Determine the anti-permeability strength grade of the concrete specimen to be tested by combining the fluctuation stability determination result and the extended stability determination result.

[0065] Among them, the impermeability strength grade refers to the impermeability performance grade determined according to the permeability characteristics of the concrete specimen under the standard water pressure. The larger the value, the better the impermeability performance. This grading is based on the comparison of the characteristic parameters of the infiltration water spot when it reaches the dual-spatial and temporal stable state (such as the final stable water spot area, diffusion rate, etc.) with the pre-established evaluation standards. Through this grading, the ability of concrete specimens to prevent water penetration can be quantitatively characterized, providing an important basis for the waterproof design and quality control of concrete structures.

[0066] Specifically, in order to comprehensively evaluate the impermeability of the concrete specimen to be tested, it is necessary to comprehensively consider the two key characteristics of the fluctuation stability and extension stability of the infiltration water spot. First, obtain the fluctuation stability judgment results and the extension stability judgment results. These two results reflect the change law of the water spot area in the time dimension and the diffusion characteristics in the space dimension respectively. When the fluctuation stability judgment results and the extension stability judgment results are both stable, it means that the water seepage process of the concrete specimen has reached a stable state in both time and space dimensions. At this time, the impermeability strength grade of the concrete specimen to be tested can be determined according to the pre-established impermeability strength grade evaluation standard and the final stable value of the water spot area; when there is an abnormality in the fluctuation stability judgment result or the extension stability judgment result, it means 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 cause of the abnormality. This impermeability strength grade evaluation method based on dual stability judgment can more accurately and reliably reflect the actual impermeability performance of the concrete specimen by comprehensively considering the temporal and spatial characteristics of the water seepage process.

[0067] Based on the above embodiment, as an optional embodiment, in step 105: combining the fluctuation stability determination result and the extended stability determination result to determine the impermeability strength grade of the concrete specimen to be tested, this step may also include the following steps: Step 601: During the time period when both the fluctuation stability determination result and the extended stability determination result are stable, the duration of stability is counted.

[0068] Specifically, in order to ensure that the water seepage process of the concrete specimen to be tested is fully stable, it is necessary to count the duration of the stability of both the fluctuation stability and the extended stability. First, during the entire test process, identify the time period in which both the fluctuation stability determination results and the extended stability determination results are stable, that is, the period in which the area change of the seepage water spot in the time dimension tends to be stable, and the diffusion rate distribution in the spatial dimension tends to be uniform. Then, count the duration of this time period, which reflects the continuity of the stable state of the concrete specimen's water seepage process, and provides a time basis for the subsequent reliable evaluation of the anti-seepage strength grade.

[0069] Step 602: When the duration of the stability is longer than the preset level determination duration, the average osmotic pressure value in the time period is obtained.

[0070] Specifically, in order to ensure the accuracy of the anti-seepage strength grade assessment, it is necessary to obtain representative seepage pressure data based on a sufficiently long stable period. First, the statistically obtained stable duration is compared 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 the stable time period, the seepage pressure values ​​at multiple times are collected and their arithmetic mean is calculated to obtain the average seepage pressure value. This average value calculation method 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.

[0071] Step 603: Based on a preset seepage pressure value interval mapping table, determine the value 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 value interval.

[0072] Specifically, in order to convert the average osmotic pressure value into a standard impermeability strength grade, it is necessary to use the pre-established osmotic pressure numerical interval mapping relationship. First, compare the calculated average osmotic pressure value with the various intervals in the osmotic pressure numerical interval mapping table to determine the numerical interval to which the osmotic pressure value belongs. Then, based on the calibration results corresponding to the numerical interval, determine the impermeability strength grade of the concrete specimen to be tested, such as P6, P8, P10, etc. This grade assessment method based on standardized mapping relationships not only ensures the standardization and comparability of the assessment results, but also facilitates the mutual recognition of test results between different laboratories, providing a reliable technical basis for concrete quality control.

[0073] Reference Figure 2 , is a concrete impermeability strength intelligent identification system provided by an embodiment of the present application, the system comprises: a parameter acquisition module, a fluctuation stability determination result determination module, an extended stability determination result determination module, and an impermeability strength identification module, wherein: A parameter acquisition module is used to acquire the pressure parameters of the concrete specimen to be tested and the pressure acquisition time corresponding to the pressure parameters, and generate a permeability pressure curve of the concrete specimen to be tested according to the pressure parameters and the pressure acquisition time; A fluctuation stability determination result determination module is used to determine 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; The extended stability determination result determination module is used to obtain the infiltration water spot image on the surface of the concrete specimen to be tested, and calculate the water spot area growth rate of the infiltration water spot image at two adjacent image acquisition moments; based on the water spot area growth rate, determine the extended stability determination result of the infiltration water spot; The anti-permeability strength identification module is used to determine the anti-permeability strength grade of the concrete specimen to be tested by combining the fluctuation stability determination result and the extended stability determination result.

[0074] On the basis of the above embodiment, the parameter acquisition module is also used to 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; the target pressure value is arranged in time sequence according to the pressure collection time to generate a pressure time series; the pressure time series is smoothed using the moving average method, and the pressure collection time is used as the horizontal coordinate and the smoothed pressure time series is used as the vertical coordinate to generate a seepage pressure curve of the concrete specimen to be tested.

[0075] On the basis of the above embodiment, the fluctuation stability determination result determination module is also 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 a preset fluctuation threshold, mark the corresponding time point as a stable point; count the duration of continuous marking as a stable point 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, 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.

[0076] On the basis of the above-mentioned embodiment, the extended stability judgment result determination module is also used to obtain the grayscale value distribution of the infiltration water spot image, and determine the grayscale threshold of the water spot edge based on the grayscale value distribution; binarize the infiltration water spot image according to the grayscale threshold of the water spot edge to obtain the water spot area; count the number of pixels in the water spot area, and convert the number of pixels into the actual water spot area; calculate the ratio of the difference between the actual water spot areas at two adjacent image acquisition moments and the time interval to obtain the water spot area growth rate.

[0077] On the basis of the above-mentioned embodiment, the extended stability judgment result determination module is also used to determine a standard grayscale reference plate placed at the test position of the concrete specimen to be tested, the standard grayscale reference plate including a dry area reference bar and a wet area reference bar; obtain the grayscale values ​​of the dry area reference bar and the wet area reference bar; calculate the average grayscale value of the non-water-seepage area on the concrete specimen to be tested to obtain the measured dry value; use the ratio of the measured dry value to the grayscale value of the dry area reference bar as the grayscale correction coefficient; and use the product of the grayscale value of the wet area reference bar and the grayscale correction coefficient as the grayscale threshold of the water spot edge.

[0078] On the basis of the above-mentioned embodiment, the extended stability determination result determination module is also used to 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 and minimum values ​​of the water spot area growth rate in each detection area; when each detection area meets the preset extended stability determination rule, the extended stability determination result of the infiltration water spot is determined to be stable, and when each detection area does not meet the preset extended stability determination rule, the extended stability determination result of the infiltration water spot is determined to be abnormal; wherein the preset extended stability determination rule is: in each detection area, the difference between the maximum and minimum values ​​is less than the difference threshold, and the number of detection areas with a water spot area growth rate less than the stable rate threshold accounts for a proportion of the total number of detection areas that is greater than a preset proportion.

[0079] On the basis of the above embodiment, the anti-permeability strength identification module is also used to count the duration of stability in a time period when both the fluctuation stability determination results and the extended stability determination results are stable; when the duration of stability is greater than the preset grade determination time, the average permeability pressure value in the time period is obtained; based on a preset permeability pressure value interval mapping table, the numerical interval corresponding to the average permeability pressure value is determined; according to the calibration result of the numerical interval, the anti-permeability strength grade of the concrete specimen to be tested is determined.

[0080] It should be noted that: when the device provided in the above embodiment realizes its function, only the division of the above functional modules is used as an example. In actual application, the above functions can be assigned to different functional modules as needed, 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 embodiment belong to the same concept, and the specific implementation process is detailed in the method embodiment, which will not be repeated here.

[0081] The present application also discloses an electronic device. Figure 3 , Figure 3 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 .

[0082] The communication bus 302 is used to realize the connection and communication between these components.

[0083] The user interface 303 may include a display interface and a camera interface. Optionally, the user interface 303 may also include a standard wired interface and a wireless interface.

[0084] The network interface 304 may optionally include a standard wired interface or a wireless interface (such as a WI-FI interface).

[0085] Among them, the processor 301 may include one or more processing cores. The processor 301 uses various interfaces and lines to connect various parts in the entire server, and executes various functions of the server and processes data by running or executing instructions, programs, code sets or instruction sets stored in the memory 305, and calling data stored in the memory 305. Optionally, the processor 301 can be implemented in at least one hardware form of digital signal processing (Digital Signal Processing, DSP), field programmable gate array (Field-Programmable Gate Array, FPGA), and programmable logic array (Programmable Logic Array, PLA). The processor 301 can integrate one or a combination of a central processing unit (Central Processing Unit, CPU), a graphics processing unit (Graphics Processing Unit, GPU) and a modem. Among them, the CPU mainly processes the operating system, user interface diagrams and applications, 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 communications. It can be understood that the above-mentioned modem may not be integrated into the processor 301, and it can be implemented separately through a chip.

[0086] Among them, the memory 305 may include a random access memory (Random Access Memory, RAM) and may also include a read-only memory (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, codes, code sets or instruction sets. The memory 305 may include a program storage area and a data storage area, wherein the program storage area may store instructions for implementing an operating system, instructions for at least one function (such as a touch function, a sound playback function, an image playback function, etc.), instructions for implementing the above-mentioned various method embodiments, etc.; the data storage area may store data involved in the above-mentioned various method embodiments, etc. The memory 305 may optionally also be at least one storage device located away from the aforementioned processor 301. Refer to Figure 3 The memory 305 as a computer storage medium may include an operating system, a network communication module, a user interface module, and an application program for an intelligent identification method of concrete anti-permeability strength.

[0087] exist Figure 3In the electronic device 300 shown, the user interface 303 is mainly used to provide an input interface for the user 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 a method for intelligently identifying the impermeability strength of concrete. When executed by one or more processors 301, the electronic device 300 executes one or more methods in the above-mentioned embodiments. It should be noted that for the aforementioned method embodiments, for the sake of simple description, they are all expressed as a series of action combinations, but those skilled in the art should be aware that the present application is not limited by the described order of actions, because according to the present application, certain steps can be performed in other orders or simultaneously. Secondly, those skilled in the art should also be aware that the embodiments described in the specification are all preferred embodiments, and the actions and modules involved are not necessarily required for the present application.

[0088] In the above embodiments, the description of each embodiment has its own emphasis. For parts that are not described in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0089] In the several embodiments provided in this application, it should be understood that the disclosed devices can be implemented in other ways. For example, the device embodiments described above are only schematic, such as the division of units, which is only a logical function division. There may be other division methods in actual implementation, such as 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 mutual coupling or direct coupling or communication connection shown or discussed can be through some service interfaces, and the indirect coupling or communication connection of devices or units can be electrical or other forms.

[0090] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0091] In addition, each functional unit in each embodiment of the present application may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of software functional units.

[0092] If 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 the present application, or the part that contributes to the prior art, or all or part of the technical solution can be embodied in the form of a software product, which is stored in a memory and includes several instructions for a computer device (which can be a personal computer, server or network device, etc.) to execute all or part of the steps of the various embodiments of the present application. The aforementioned memory includes: various media that can store program codes, such as USB flash drives, mobile hard drives, magnetic disks or optical disks.

[0093] The above are only exemplary embodiments of the present disclosure and cannot be used to limit the scope of the present disclosure. That is, any equivalent changes and modifications made according to the teachings of the present disclosure are still within the scope of the present disclosure. After considering the disclosure of the specification and practice, those skilled in the art will easily think of other embodiments of the present disclosure.

[0094] This application is intended to cover any variation, use or adaptation of the present disclosure, which follows the general principles of the present disclosure and includes common knowledge or customary technical means in the art not recorded in the present disclosure. The description and examples are to be regarded as exemplary only.

Claims

1. A method for intelligently identifying the anti-seepage strength of concrete, characterized in that: include: Acquire pressure parameters of the concrete specimen to be tested and the pressure collection time corresponding to the pressure parameters, and generate a permeability pressure curve of the concrete specimen to be tested according to the pressure parameters and the pressure collection time; Determining a 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; Acquire the image of the seepage water spot 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, determining the expansion stability determination result of the infiltration water spot; The anti-permeability strength grade of the concrete specimen to be tested is determined by combining the fluctuation stability determination result and the extended stability determination result.

2. The intelligent identification method of concrete anti-seepage strength according to claim 1 is characterized in that: The step of generating a permeability curve of the concrete specimen to be tested according to the pressure parameter and the pressure acquisition time includes: Obtaining an initial pressure value of the concrete specimen to be tested, and subtracting the initial pressure value from the pressure parameter to obtain a target pressure value; Arranging the target pressure values ​​in time sequence according to the pressure collection moments to generate a pressure time series; The pressure time series is smoothed by using a moving average method, and the pressure collection time is used as the abscissa and the smoothed pressure time series is used as the ordinate to generate a permeability curve of the concrete specimen to be tested.

3. The intelligent identification method of concrete anti-seepage strength according to claim 1 is characterized in that: The step of 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 comprises: Obtaining the age of the concrete specimen to be tested; determining a correction coefficient of the pressure change rate based on the age, and determining a target pressure change rate based on the correction coefficient and the pressure change rate; 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; The duration of continuous marks as stable points in the osmotic pressure curve is counted. When the duration is greater than or equal to the stable duration threshold, the fluctuation stability judgment result of the osmotic pressure curve is determined to be stable. When the duration is less than the stable duration threshold, the fluctuation stability judgment result of the osmotic pressure curve is determined to be abnormal.

4. The intelligent identification method of concrete anti-seepage strength according to claim 1 is characterized in that: The calculating the water spot area growth rate of the infiltration water spot image at two adjacent image acquisition moments includes: Acquire the gray value distribution of the infiltrated water spot image, and determine the gray threshold of the water spot edge based on the gray value distribution; Binarize the infiltrated water spot image according to the water spot edge grayscale threshold to obtain a water spot area; Counting the number of pixels in the water spot area, and converting the number of pixels into an actual water spot area; The ratio between the difference between the actual water spot areas at the two adjacent image acquisition moments and the time interval is calculated to obtain the water spot area growth rate.

5. The intelligent identification method of concrete anti-seepage strength according to claim 4 is characterized in that: The step of determining the grayscale threshold of the water spot edge based on the grayscale value distribution comprises: Determine a standard grayscale reference plate placed at a test position of the concrete specimen to be tested, wherein the standard grayscale reference plate includes a dry area reference bar and a wet area reference bar; Acquiring grayscale values ​​of the dry region reference strip and the wet region reference strip; Calculating the average gray value of the non-water-seepage area on the concrete specimen to be tested to obtain a measured dry value; The ratio of the measured dryness value to the grayscale value of the dry area reference bar is used as a grayscale correction coefficient; The product of the grayscale value of the reference strip of the wetted area and the grayscale correction coefficient is used as the grayscale threshold of the water spot edge.

6. The intelligent identification method of concrete anti-seepage strength according to claim 1 is characterized in that: The step of determining the expansion stability determination result of the infiltration 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 of the detection areas; Determine the maximum and minimum values ​​of the water spot area growth rate in each of the detection areas; When each of the detection areas meets the preset expansion stability judgment rule, the expansion stability judgment result of the infiltration water spot is determined to be stable; when each of the detection areas does not meet the preset expansion stability judgment rule, the expansion stability judgment result of the infiltration water spot is determined to be abnormal; The preset extended stability determination rule is: In each of the detection areas, the difference between the maximum value and the minimum value is less than the difference threshold, and the number of detection areas where the water spot area growth rate is less than the stable rate threshold accounts for a greater than preset proportion of the total number of detection areas.

7. The intelligent identification method of concrete anti-seepage strength according to claim 1 is characterized in that: The step of combining the fluctuation stability determination result and the extended stability determination result to determine the anti-permeability strength grade of the concrete specimen to be tested comprises: In a time period when both the fluctuation stability determination result and the extended stability determination result are stable, counting the duration of stability; When the stability duration is longer than the preset level determination duration, obtaining the average osmotic pressure value in the time period; Based on a preset osmotic pressure value interval mapping table, determining the value interval corresponding to the average osmotic pressure value; According to the calibration result of the numerical range, the anti-permeability strength grade of the concrete specimen to be tested is determined.

8. An intelligent identification system for concrete impermeability strength, characterized in that: The system comprises: A parameter acquisition module, used to acquire pressure parameters of the concrete specimen to be tested and the pressure acquisition time corresponding to the pressure parameters, and generate a permeability pressure curve of the concrete specimen to be tested according to the pressure parameters and the pressure acquisition time; A fluctuation stability determination result determination module, used to determine the fluctuation stability determination result of the osmotic pressure curve based on the pressure change rate of two adjacent pressure collection moments in the osmotic pressure curve; The module for determining the result of the extended stability determination is used to obtain the image of the seepage water spot 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 extended stability determination result of the seepage water spot; The anti-permeability strength identification module is used to determine the anti-permeability strength grade of the concrete specimen to be tested by combining the fluctuation stability determination result and the extended stability determination result.

9. An electronic device, characterized in that: It includes a processor, a memory, a user interface and a network interface, the memory is used to store instructions, the user interface and the network interface are used to communicate with other devices, and the processor is used to execute the instructions stored in the memory so that the electronic device executes the intelligent identification method for the anti-permeability strength of concrete as described in any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores instructions, and when the instructions are executed, the method for intelligently identifying the anti-permeability strength of concrete according to any one of claims 1 to 7 is executed.

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