A seepage test system and method for continuously measuring the infiltration distance of special fluids

Abstract

The present invention belongs to the technical field of seepage testing and discloses a seepage test system and method for continuously measuring the infiltration distance of a special fluid. The system conducts a seepage test, records pore water pressure and seepage flow rate parameters, and captures a video of the seepage process. Python code is used to extract frames from the captured video at fixed time intervals, and the frames are sequentially processed to obtain a black and white image. The pixel values ​​of the white portion and their proportion of the total pixel values ​​in the image are calculated; the infiltration distance is estimated; and the relationship between the infiltration distance and time is derived based on the time interval set when extracting the frames. The seepage test results are analyzed by combining pore water pressure, seepage flow rate, and infiltration distance. The present invention uses a transparent organic glass tube device to conduct the test. Based on the phenomenon that the seepage of the special fluid causes the original soil to change color, Python code based on computer image processing technology is used to continuously and accurately measure the infiltration distance.

Description

Technical Field

[0001] The invention belongs to the technical field of seepage test, and in particular relates to a seepage test system and method for continuously measuring the infiltration distance of a special fluid. Background Art

[0002] In many current projects, soil modification often requires improvement to meet the strength and permeability requirements of existing soils during construction. For example, permeation grouting, a common foundation treatment technique, can repair problematic soils without disturbing their original structure, improving their mechanical properties. Furthermore, soil modification techniques are often used during shield tunneling to ensure the proper operation of the shield machine. Shield tunneling soil modification techniques often use high-pressure gas to inject soil conditioners such as bentonite slurry, foam, and polymers into the soil ahead of the shield machine. This modifies the permeability and mechanical properties of the soil, ensuring tunnel face stability. Therefore, in soil modification methods such as grouting, further understanding of the permeability and infiltration distance of specific fluids (slurries, foams, etc.) is crucial. Conventional methods typically analyze soil permeability using constant and variable head tests. The infiltration distance is often estimated using the seepage flow rate and the soil's inherent porosity. However, due to the complex properties and composition of the specialized fluids used in actual projects, and the inherent drainage of the fluids during seepage, traditional methods cannot accurately measure seepage distance, and thus cannot further analyze the permeability of specialized fluids. Furthermore, existing methods cannot continuously measure infiltration distance, and manual measurement is slow, resulting in insufficient data.

[0003] Through the above analysis, the problems and defects of the existing technology are as follows:

[0004] (1) The traditional constant head test method and variable head test method cannot accurately measure the seepage distance of special fluids such as mud and foam, which further affects the accurate analysis of the permeability of special fluids.

[0005] (2) Existing measurement methods are usually unable to continuously measure the infiltration distance and often need to rely on manual work, which not only leads to slow measurement speed but also may affect the measurement accuracy due to human factors.

[0006] (3) Traditional methods for estimating seepage distance usually only consider the seepage flow rate and the porosity of the soil itself. However, in actual situations, the rheological properties of special fluids such as mud and foam may affect the seepage distance. Existing technologies cannot fully utilize this information, which may cause the measurement results to deviate from the actual situation. Summary of the Invention

[0007] In view of the problems existing in the prior art, the present invention provides a seepage test system and method for continuously measuring the infiltration distance of a special fluid.

[0008] The present invention is implemented as follows: a seepage test method for continuously measuring the infiltration distance of a special fluid. This seepage test method uses a transparent cylinder device to perform real-time video shooting, and uses Python code to process the video frames to obtain infiltration distance data. The seepage test results are further analyzed in combination with pore water pressure, seepage flow rate and infiltration distance; and automated analysis of continuously measured infiltration distance is achieved.

[0009] Furthermore, the seepage test method for continuously measuring the infiltration distance of a special fluid specifically comprises the following steps:

[0010] Step 1: Use a transparent cylinder device to conduct a seepage test, record the pore water pressure and seepage flow parameters, and shoot a video of the seepage process;

[0011] Step 2: Use Python code to extract frames from the captured video at fixed time intervals, and then perform grayscale processing, Gaussian blur, binarization, dilation, and erosion on the frames to obtain black and white images;

[0012] Step 3: Calculate the pixel value of the infiltration area (white part) and its proportion to the total pixel value of the image;

[0013] Step 4: Estimate the infiltration distance based on the original size of the video shooting area and the above ratio;

[0014] Step 5: According to the time interval set when extracting frames, the relationship between the infiltration distance and time is obtained;

[0015] Step six: Analyze the seepage test results based on pore water pressure, seepage flow rate, and infiltration distance.

[0016] Furthermore, the second step uses Python code to extract frames from the captured video at fixed time intervals, specifically including:

[0017] Read the video file, extract a frame from the video file, and save the frame as a new image for subsequent processing;

[0018] Define the number of frames and the time interval for extracting frames. Taking a video with a frame rate of 25 frames per second (fps) as an example, the frame number at time 0 is defined as 1. After completing the processing of a certain frame, images are extracted one by one at intervals of 25 frames, and the number of frames is accumulated until the end of the video. The result of the extraction is that one frame is extracted as the image to be processed per second.

[0019] Furthermore, the step 2 sequentially performs grayscale processing, Gaussian blurring, binarization, dilation, and corrosion on the frame to obtain a black and white image, specifically including:

[0020] The extracted frames are converted into grayscale images. During the grayscale conversion process, the light intensity information is retained. When the digital image is converted into gray, there will be obvious differences in the grayscale values ​​of the infiltration area and the original sand layer.

[0021] Use Gaussian blur to process the image, remove noise caused by the texture of sand particles themselves, and smooth the image texture;

[0022] The grayscale image is converted into a binary image using the Otsu binarization algorithm. Due to the color difference between the infiltration area and the original sand layer, the image will show two distinct areas, black and white. The white area is the infiltration area, and the black area is the original soil area (the division of the area is related to the color of the soil and fluid itself, and the specific division can be determined according to the actual situation);

[0023] Morphological operations – dilation and erosion are used to further eliminate image noise and smooth the contours between black and white areas to obtain the processed black and white image.

[0024] Furthermore, the step three uses the black and white image to calculate the proportion of the infiltrated area, specifically including:

[0025] Calculate the pixel values ​​of the entire black and white image and the white and black areas. Based on the pixel values, calculate and output the ratio of the white area to the total image area.

[0026] Furthermore, the fourth step estimates the infiltration distance based on the original size of the video shooting area and the above ratio, specifically including:

[0027] Based on the phenomenon of sand layer discoloration caused by the infiltration of special fluids and the results of Python code image processing, the infiltration distance is approximately the product of the original size of the photographed area and the ratio output by the above Python code;

[0028] According to the time interval set when extracting frames in Python code, the relationship between infiltration distance and time is obtained.

[0029] Another object of the present invention is to provide a seepage test system for continuously measuring the seepage distance of a special fluid, which implements the seepage test method for continuously measuring the seepage distance of a special fluid. The system comprises:

[0030] The cylinder has threaded openings on the upper and lower sides corresponding to the cylinder sealing screw cover and the cylinder screw base, and a plurality of pressure measuring holes are opened on the side of the middle part of the cylinder wall;

[0031] The electronic pore water pressure gauge is sealed and connected to the cylinder body through the pressure measuring hole to measure the pore water pressure at the predetermined position;

[0032] Signal demodulator, used to analyze the collected signals of the electronic pore water pressure meter and read the data in real time and store it on the computer;

[0033] Electronic scales and water storage containers are used to record the seepage flow of the measurement system in real time and store the permeate;

[0034] The camera is placed horizontally with the transparent cylindrical device to record the infiltration process of the special fluid into the sand layer and save it as a video file.

[0035] Furthermore, an air pressure interface is provided on the side of the cylinder body, and the air pressure interface can be connected to an air pressure boosting device to provide the required air pressure for the inside of the cylinder body.

[0036] Furthermore, the cylindrical sealing screw cover includes a rubber ring, which is connected to the cylinder body in a threaded fixing manner;

[0037] The cylindrical spiral base includes a rubber ring, which is connected to the cylinder in a threaded fixing manner. The bottom includes a permeable stone for preventing the sand and gravel filled in the cylinder from flowing out; below the permeable stone is a water storage cavity, which includes an overflow port for collecting seepage flow.

[0038] In combination with the above technical solutions and the technical problems solved, the advantages and positive effects of the technical solutions to be protected by the present invention are as follows:

[0039] First, this invention uses a transparent organic glass tube device to conduct experiments. Based on the phenomenon that the seepage of special fluids (mud, foam, etc.) causes the original soil to change color, Python code based on computer image processing technology is used to continuously and accurately measure the infiltration distance. Furthermore, this method can be used to measure and analyze the permeability properties of special fluids (mud, foam, etc.) used in various engineering projects, enriching the technical means of seepage testing in geotechnical engineering.

[0040] The present invention uses Python code to perform digital image processing, can continuously and automatically collect data from digital images, and is less affected by external interference and human factors.

[0041] As a new measurement technology used in geotechnical engineering, this technical solution can be combined with instrument and equipment development to form a complete geotechnical engineering measurement system with commercial value.

[0042] In traditional seepage measurement technology, the drainage volume of the measurement system is often used to estimate fluid parameters such as the seepage flow rate. However, for complex special fluids (mud, foam, etc.), their inherent drainage properties can cause errors in the measurement results, that is, the different seepage flow rates of each component in the fluid lead to measurement errors. This scheme is based on the phenomenon that the seepage of special fluids (mud, foam, etc.) causes the color of the original soil to change, and can directly measure parameters such as the fluid penetration distance. At the same time, combined with data such as the overall drainage volume of the measurement system, the seepage properties of special fluids (mud, foam, etc.) can be analyzed in more detail.

[0043] Second, Step 1: The use of a transparent cylinder device makes the seepage process observable, a significant technological advancement because it enables real-time monitoring and recording of the infiltration of specific fluids. Furthermore, the measurement of pore water pressure and seepage flow rate provides the basis for subsequent data analysis.

[0044] Step 2: The use of Python code makes it possible to extract frames from the video and perform image processing, which includes grayscale processing, Gaussian blur, binarization, dilation, and erosion techniques. This is a significant technological advancement because these processing steps can significantly improve the accuracy of image analysis.

[0045] Step 3: By calculating the pixel value of the infiltration area (white part) and its ratio to the total pixel value of the image, the degree of infiltration of a specific fluid can be quantitatively evaluated. This is a significant technological advancement because it makes it possible to quantitatively analyze the degree of infiltration.

[0046] Step 4: Estimate the infiltration distance based on the original size of the video shooting area and the above ratio. This is a significant technical advancement because it makes it possible to accurately calculate the infiltration distance.

[0047] Step 5: Based on the time interval set when extracting frames, the relationship between the infiltration distance and time is obtained. This is a significant technical advancement because it makes it possible to analyze the impact of time on the infiltration distance.

[0048] Step 6: Finally, the seepage test results are analyzed by combining pore water pressure, seepage flow rate, and infiltration distance. This is a significant technological advancement because it makes it possible to comprehensively analyze the seepage test results, which is crucial for understanding and predicting the seepage behavior of special fluids.

[0049] In general, the significant technological advancement of this seepage test method for continuously measuring the infiltration distance of special fluids is reflected in its ability to achieve real-time monitoring of the special fluid seepage process, image processing and analysis, estimation of the infiltration distance, and comprehensive analysis of the seepage test results. BRIEF DESCRIPTION OF THE DRAWINGS

[0050] Figure 1 This is a flow chart of a seepage test method for continuously measuring the infiltration distance of a special fluid provided by an embodiment of the present invention;

[0051] Figure 2 This is a schematic diagram of the composition structure and connection of the test device provided in an embodiment of the present invention;

[0052] Figure 3 is a schematic diagram of an extracted original image provided by an embodiment of the present invention;

[0053] Figure 4 is a schematic diagram of a grayscale image provided by an embodiment of the present invention;

[0054] Figure 5 is a schematic diagram of an image after Gaussian blur processing provided by an embodiment of the present invention;

[0055] Figure 6 is a schematic diagram of a binary image provided by an embodiment of the present invention;

[0056] Figure 7 This is a schematic diagram of a picture after expansion and corrosion processing provided by an embodiment of the present invention;

[0057] Figure 8 This is a schematic diagram of the Python code output result provided by an embodiment of the present invention;

[0058] Figure 9 This is a comparison chart of measurement results between the technical solution provided by an embodiment of the present invention and the prior art solution, comparing the difference between the infiltration distance change curve obtained in the technical solution and the result obtained in the prior art solution.

[0059] In the figure: 1. Plexiglas cylinder; 2. Cylinder sealing screw cap; 3. Cylinder screw base; 4. First electronic pore water pressure gauge; 5. Second electronic pore water pressure gauge; 6. Third electronic pore water pressure gauge; 7. Cable; 8. Signal demodulator; 9. Electronic scale and water storage container; 10. Rubber water hose; 11. Computer; 12. Camera. DETAILED DESCRIPTION

[0060] In order to make the purpose, technical solutions and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with the embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the present invention.

[0061] like Figure 1 As shown, the seepage test method for continuously measuring the infiltration distance of a special fluid provided by an embodiment of the present invention includes:

[0062] S101, using a transparent cylinder device to conduct a seepage test, record pore water pressure and seepage flow parameters, and shoot a video of the seepage process;

[0063] S102, using Python code to extract frames from the captured video at fixed time intervals, and sequentially performing grayscale processing, Gaussian blur, binarization, dilation, and erosion on the frames to obtain black and white images;

[0064] S103, calculating the pixel value of the infiltration area (white part) and its ratio to the total pixel value of the image;

[0065] S104, estimating the infiltration distance based on the original size of the video shooting area and the above ratio;

[0066] S105, obtaining a relationship between the infiltration distance and time according to the time interval set when extracting the frame;

[0067] S106, analyze the seepage test results based on pore water pressure, seepage flow rate, and infiltration distance.

[0068] The present invention discloses a seepage test system and method. A transparent organic glass tube device is used for the test. Based on the phenomenon that the seepage of special fluids (mud, foam, etc.) causes the color of the original soil to change, Python code based on computer image processing technology is used to continuously and accurately measure the infiltration distance.

[0069] like Figure 2 As shown, the test device mainly includes: an organic glass cylinder 1, a cylinder sealing screw cover 2, a cylinder spiral base 3, a first electronic pore water pressure gauge 4, a second electronic pore water pressure gauge 5, a third electronic pore water pressure gauge 6, a cable 7, a signal demodulator 8, an electronic scale and a water storage container 9, a rubber water hose 10, a computer 11 and a camera 12.

[0070] The plexiglass cylinder 1 is made of high-strength resin plastic, capable of withstanding strong pressure with minimal deformation. It has threaded openings at the top and bottom, corresponding to the cylinder's screw cap 2 and screw base 3. The cylinder has an inner diameter of 80mm and an outer diameter of 100mm. A pressure port is located 30mm from the top of the cylinder. Three 8mm diameter pressure taps are located in the center of the cylinder wall. Tape 1 is 250mm from the bottom of the cylinder, and the remaining taps are 100mm apart.

[0071] The cylindrical sealing screw cover 2 includes a rubber ring and is connected to the cylinder body in a threaded fixing manner to achieve an air pressure sealing effect.

[0072] The cylindrical spiral base 3, including a rubber ring, is threadedly connected to the cylinder body to achieve an airtight seal. A permeable stone at the bottom prevents the sand and gravel filled in the plexiglass cylinder from flowing out. Below the permeable stone is a water storage cavity with an overflow port to collect seepage flow.

[0073] The first electronic pore water pressure gauge 4, the second electronic pore water pressure gauge 5, and the third electronic pore water pressure gauge 6 have a measuring range of 0-1000 kPa and an accuracy of 0.1 kPa.

[0074] Cable 7 connects the electronic pore water pressure gauge and the signal demodulator, and connects the signal demodulator and the computer.

[0075] The signal demodulator 8 converts the electrical signals transmitted by the pore water pressure gauges 4-6 into digital signals.

[0076] The electronic scale and water storage container 9 are used to collect and record the seepage flow rate.

[0077] The rubber water pipe 10 connects the overflow port at the bottom of the cylindrical base 3 with the electronic scale and the water storage container 9.

[0078] Computer 11 reads and records data.

[0079] The camera 12 is used to shoot and store the infiltration test video file.

[0080] The lower part of the body of the organic glass cylinder 1 is connected to the base containing permeable stone by means of a screw fixation. The air pressure hole can be connected to the air pressure boosting device to provide the required air pressure inside the cylinder body. The pressure measuring hole on the side of the cylinder body is connected to the electronic pressure gauge through an elastic locking mechanism. The electronic pore water pressure gauge is sealed with the cylinder body through the pressure measuring hole to measure the pore water pressure at a predetermined position. After the signal is collected, it is transmitted to the signal demodulator 8 through the cable 7 for analysis, and the data is read in real time and stored on the computer 11. The system drainage flows out from the overflow port at the bottom of the cylinder base 3, flows to the electronic scale and water storage container 9 through the rubber water pipe 10, and records the seepage flow of the measurement system in real time. The camera 12 is placed horizontally with the transparent cylinder device to record the infiltration process of the special fluid into the sand layer and save it as a video file.

[0081] Its Python code functions are as follows:

[0082] 1. Read frames from the video file;

[0083] 2. Convert the above frames into grayscale images and use Gaussian blur to smooth the images and reduce noise;

[0084] 3. Convert the above image into a black and white image through image binarization processing;

[0085] 4. Use dilation and erosion to remove noise and smooth the contour;

[0086] 5. Calculate the pixel value of the white area and its proportion;

[0087] 6. Output the processed image, frame number, pixel value, and ratio;

[0088] 7. Repeat the above steps until the video ends.

[0089] Table 1 Python code for image processing and calculation of infiltration distance of the present invention

[0090]

[0091] The present invention proposes a method for completing the test using the cylinder test device and Python code according to the following steps:

[0092] Step one, using the test device, close the bottom drain port and fill the device with water, fill the sand layer to a specified height as an infiltration medium, and use the sedimentation saturation method to saturate the sand layer. Open the drain port to drain excess water, close the drain port after the upper surface of the liquid is flush with the upper surface of the sand layer, and then inject a special fluid (mud or foam, etc.) into the top of the sand layer. After sealing, connect the air pressure at the air inlet, open the drain port after the air pressure stabilizes, and the special fluid seeps into the sand layer under pressure. The electronic pore water pressure gauges 4-6 are used to collect pore water pressure information at different positions of the sand layer, and the electronic scale and water storage container 9 are used to collect the seepage flow of the system. At the same time, a camera 12 is used to record the infiltration process of the special fluid and save it as a video file.

[0093] Step 2: Process the video file captured in Step 1 using the Python code to extract data related to infiltration distance. The Python code extracts frames at fixed intervals until the end of the video. The extracted frames are then processed sequentially through grayscale processing, Gaussian blur, binarization, dilation, and erosion to produce a black and white image. The processed image is ultimately output, along with its corresponding frame number, pixel value, white area pixel value, and its proportion of the total image.

[0094] Step three: Estimate the infiltration distance based on the original size of the video recording area and the proportion of the white area described in step three. Based on the phenomenon of sand layer discoloration caused by the infiltration of special fluids and the results of image processing using the Python code, the infiltration distance is approximately the product of the original size of the infiltration area and the proportion output by the Python code. Based on the time interval set when extracting frames in the Python code, the relationship between the infiltration distance and time can be calculated. Furthermore, the test results can be further analyzed by combining information such as pore water pressure and seepage flow rate.

[0095] The test system and method of the present invention will be further described below with reference to the accompanying drawings and specific embodiments. However, the following embodiments are by no means intended to limit the present invention in any way.

[0096] Step 1: Using the test device ( Figure 2), close the bottom drain port and fill the device with water. Place the sand layer in the cylindrical device, fill the base and the part below 250mm of the cylinder, so that the top surface of the sand layer is between the pore water pressure gauge 4. This process uses the precipitation saturation method to saturate the sand layer. Open the drain port to drain excess water, make the upper surface of the liquid flush with the upper surface of the sand layer, then close the drain port, and then inject the special fluid (mud or foam, etc.) into the top of the sand layer. After sealing, connect the air pressure (50kPa) at the air inlet, open the drain port after the air pressure stabilizes, and the special fluid seeps into the sand layer under pressure. The electronic pore water pressure gauges 4-6 are used to collect pore water pressure information at different positions of the sand layer, and the electronic scale and water storage container 9 are used to collect the seepage flow of the system. At the same time, a camera 12 is used to record the infiltration process of the special fluid and save it as a video file.

[0097] Step 2: Process the video file collected in step 1 using the Python code. The processing process is as follows:

[0098] 1. Read the video file and extract a frame from it. Save the frame as a new image ( Figure 3 ) for subsequent processing. Define the number of frames and the time interval for extracting frames. For a video with a frame rate of 25 frames per second (fps), define the frame number at time 0 as 1 (i.e., frame 1). After processing a frame, extract images one at a time interval of 25 frames, accumulating the number of frames until the video ends. When the video frame rate is 25 fps, the program extracts one frame per second as the image to be processed.

[0099] 2. Convert the above extracted frames into grayscale images ( Figure 4 ), in the grayscale conversion process, the light intensity information is retained and the digital image is converted into gray. There will be obvious differences in the grayscale values ​​of the infiltration area and the original sand layer. Use Gaussian blur to process the image ( Figure 5 ), removes noise caused by the texture of sand particles themselves and smoothes the image texture.

[0100] 3. Use Otsu binarization algorithm to convert the grayscale image into a binary image (black and white image, Figure 6 Due to the color difference between the infiltration area and the original sand layer, the image will show two distinct areas: black and white. The white area is the infiltration area, and the black area is the original soil area. (The division of the areas is related to the properties of the soil and fluid, and the specific division can be determined according to the actual situation.)

[0101] 4. Use morphological operations - dilation and erosion to further eliminate image noise and smooth the contours between black and white areas to obtain the processed black and white image ( Figure 7 ).

[0102] 5. Calculate the pixel size of the black and white image after step 4. Then calculate the pixel value of the area with non-zero pixel value (white area) and its proportion to the total pixel size.

[0103] 6. Display the processed image on the coordinate axis and output its corresponding frame number, pixel value, white area pixel value and its proportion of the total image ( Figure 8 ).

[0104] 7. Repeat the above steps until the video ends.

[0105] Step 3: Based on the phenomenon of sand layer discoloration caused by special fluid infiltration and the results of Python code image processing ( Figure 8 ), the infiltration distance is approximately the product of the original size of the infiltration area and the ratio output by the above Python code. Below, combined with the accompanying drawings, take the frame shown in the accompanying drawings as an example to calculate the infiltration distance. The original infiltration area size is 250mm, and the image pixel value, white pixel value and ratio output by the Python code are 2073600, 666558, and 32.145% respectively ( Figure 8 ), the infiltration distance is approximately 250 * 32.145% = 80.3625 mm. Furthermore, by using the time interval set when extracting frames in the Python code, we can derive the relationship between infiltration distance and time. Furthermore, by combining information such as pore water pressure and seepage flow rate, we can further analyze the test results.

[0106] Advantages of this technical solution over existing solutions: Existing solutions generally use seepage flow rate to estimate infiltration distance, which can be approximately equal to the seepage flow rate divided by the product of the cross-sectional area of ​​the infiltration region (i.e., the cross-sectional area of ​​the device) and the sample porosity. However, because special fluids often experience percolation and drainage during the seepage process, the infiltration distances measured by existing solutions are often overstated. In contrast, the visual analysis method used in this technical solution is more intuitive and accurate in measuring infiltration distance.

[0107] Combine Figure 9 (a) Comparing the time-varying infiltration distance curves obtained using the proposed solution with those obtained using the prior art solution reveals differences. The results show that, during the initial period of the experiment, the two solutions produced essentially identical results. However, over time, the infiltration distance measured using the prior art solution became significantly greater than that obtained using the proposed solution. Combined with theoretical analysis, it is clear that the infiltration distance measured using the prior art solution is too large, while the measurement results obtained using the proposed solution are more accurate.

[0108] The results obtained from this measurement method provide new insights into the seepage process of special fluids such as mud and foam. This measurement system addresses the shortcomings of traditional measurement systems and eliminates some misunderstandings in the understanding of seepage problems of fluids such as foam.

[0109] The six specific embodiments of the present invention are:

[0110] Example 1:

[0111] The test was conducted using mud. Sand was filled at the bottom of a transparent cylinder and saturated. Mud was poured above the sand layer and injected into the sand layer using compressed air. A water tank was connected to the bottom of the cylinder to monitor the drainage of the system in real time.

[0112] During the experiment, a camera was used to capture video of the seepage process, and a pressure sensor was used to record the pore water pressure.

[0113] Next, we use Python code to process the video. We extract one frame per second and perform grayscale processing, Gaussian blur, binarization, dilation, and erosion on this frame to produce a black and white image. In this image, white areas represent areas where mud has penetrated, and black areas represent sand that has not yet been penetrated by mud.

[0114] Next, we calculate the pixel value of the white portion and its ratio to the total pixel value of the image. Based on this ratio and the original size of the video area, we can calculate the distance the mud has penetrated. By calculating this distance at different time points, we can obtain a relationship between the infiltration distance and time.

[0115] Finally, the seepage test can be evaluated by analyzing the pore water pressure, seepage flow rate, and infiltration distance.

[0116] Example 2:

[0117] Step 1: First, prepare a transparent cylinder and fill the bottom with sand to saturate it. Install a pressure sensor on the cylinder wall to record the pore water pressure. At the same time, use a water tank connected to the bottom of the cylinder to monitor the system drainage in real time.

[0118] Step 2: Start the infiltration test, inject foam above the sand layer, use compressed air to inject the foam into the sand layer, and use video equipment (frame rate 25fps) to shoot the entire infiltration process.

[0119] Step 3: After the video is shot, use Python code to extract one frame every 50 frames, that is, one frame every 2 seconds. This can effectively reduce the complexity of processing while obtaining enough data.

[0120] Step 4: Next, the extracted frame is processed using grayscale, Gaussian blur, binarization, dilation, and erosion. This optimizes the image to improve clarity and contrast. In this step, you can choose more advanced image processing algorithms, such as deep learning image segmentation algorithms, to achieve more accurate results.

[0121] Step 5: Calculate the pixel values ​​of the white portion of the processed image (the area where the foam has penetrated) and its ratio to the total pixel values ​​in the image. Based on this ratio and the original size of the video area, we can calculate the distance the foam has penetrated. By calculating this distance at different time points, we can determine how the penetration distance changes over time.

[0122] Step 6: Finally, data analysis is performed based on the data of pore water pressure, seepage flow rate and infiltration distance to draw conclusions from the seepage test.

[0123] Combine Figure 9 (b) Comparing the time-varying infiltration distance curves obtained using the proposed solution with those obtained using the prior art solution reveals that, during the initial period of the experiment, the results obtained by the two solutions were essentially identical. However, over time, the infiltration distance measured by the prior art solution became significantly greater than that obtained using the proposed solution. Combined with theoretical analysis, it is clear that the infiltration distance measured by the prior art solution is too large, while the measurement results obtained by the proposed solution are more accurate.

[0124] Example 3:

[0125] 1. Conduct a seepage test using a transparent cylinder and a polymer solution as a special fluid, while simultaneously recording pore water pressure and seepage flow parameters, and taking a video of the entire seepage process.

[0126] 2. Use Python code to extract a frame from the video every 5 seconds, and then process these frames using grayscale processing, Gaussian blur, binarization, dilation and erosion techniques to obtain black and white images.

[0127] 3. Calculate the pixel value of the infiltration area (white part) and its ratio to the total pixel value of the image.

[0128] 4. Estimate the infiltration distance based on the original size of the video shooting area and the above ratio.

[0129] 5. According to the time interval (5 seconds) set when extracting frames, the relationship between infiltration distance and time is obtained.

[0130] 6. Analyze the seepage test results based on pore water pressure, seepage flow rate and infiltration distance.

[0131] Example 4:

[0132] 1. Use a transparent cylinder and oil as the special fluid to conduct a seepage test, while recording the pore water pressure and seepage flow parameters, and taking a video of the entire seepage process.

[0133] 2. Use Python code to extract a frame from the video every 10 seconds, and then process these frames using grayscale processing, Gaussian blur, binarization, dilation and erosion techniques to obtain black and white images.

[0134] 3. Calculate the pixel value of the infiltration area (white part) and its ratio to the total pixel value of the image.

[0135] 4. Estimate the infiltration distance based on the original size of the video shooting area and the above ratio.

[0136] 5. According to the time interval (10 seconds) set when extracting frames, the relationship between infiltration distance and time is obtained.

[0137] 6. Analyze the seepage test results based on pore water pressure, seepage flow rate and infiltration distance.

[0138] Embodiment 5:

[0139] 1. Use a transparent cylinder and honey as a special fluid to conduct a seepage test, while recording the pore water pressure and seepage flow parameters, and taking a video of the entire seepage process.

[0140] 2. Use Python code to extract a frame from the video every 30 seconds, and then process these frames using grayscale processing, Gaussian blur, binarization, dilation and erosion techniques to obtain black and white images.

[0141] 3. Calculate the pixel value of the infiltration area (white part) and its ratio to the total pixel value of the image.

[0142] 4. Estimate the infiltration distance based on the original size of the video shooting area and the above ratio.

[0143] 5. According to the time interval (30 seconds) set when extracting frames, the relationship between infiltration distance and time is obtained.

[0144] 6. Analyze the seepage test results based on pore water pressure, seepage flow rate and infiltration distance.

[0145] Example 6:

[0146] 1. Use a transparent cylinder and beer as the special fluid to conduct a seepage test, while recording the pore water pressure and seepage flow parameters, and taking a video of the entire seepage process.

[0147] 2. Use Python code to extract one frame from the video every 1 minute, and then process these frames using grayscale processing, Gaussian blur, binarization, dilation and erosion techniques to obtain black and white images.

[0148] 3. Calculate the pixel value of the penetration area (white part) and its proportion to the total pixel value of the image

[0149] 4. Estimate the infiltration distance based on the original size of the video shooting area and the above ratio.

[0150] 5. According to the time interval (1 minute) set when extracting frames, the relationship between infiltration distance and time is obtained.

[0151] 6. Analyze the seepage test results based on pore water pressure, seepage flow rate and infiltration distance.

[0152] In the above six examples, the specific fluids (mud, foam, polymer solution, oil, honey, beer) and the time intervals for extracting frames (1 second, 2 seconds, 5 seconds, 10 seconds, 30 seconds, 1 minute) are all different, demonstrating the wide applicability of this seepage test method.

[0153] It should be noted that the embodiments of the present invention can be implemented by hardware, software, or a combination of software and hardware. The hardware portion can be implemented using dedicated logic; the software portion can be stored in a memory and executed by an appropriate instruction execution system, such as a microprocessor or dedicated design hardware. Those skilled in the art will appreciate that the above-mentioned devices and methods can be implemented using computer-executable instructions and / or contained in processor control code, for example, such as a carrier medium such as a disk, CD or DVD-ROM, a programmable memory such as a read-only memory (firmware), or a data carrier such as an optical or electronic signal carrier. The devices and modules of the present invention can be implemented by hardware circuits such as very large-scale integrated circuits or gate arrays, semiconductors such as logic chips, transistors, or programmable hardware devices such as field programmable gate arrays, programmable logic devices, etc., can also be implemented by software executed by various types of processors, or can be implemented by a combination of the above-mentioned hardware circuits and software, such as firmware.

[0154] The above description is only a specific embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any modifications, equivalent substitutions and improvements made by any technician familiar with this technical field within the technical scope disclosed by the present invention and within the spirit and principles of the present invention should be covered by the scope of protection of the present invention.

Claims

1. A seepage test method for continuously measuring the infiltration distance of a special fluid, characterized in that: This seepage test method uses a transparent cylinder device to capture real-time video and processes the video frames using Python code to obtain infiltration distance data. The seepage test results are analyzed by combining pore water pressure, seepage flow rate and infiltration distance. The bottom drain port of the transparent cylindrical device is closed and the transparent cylindrical device is filled with water. A sand layer is filled to a specified height as an infiltration medium, and the sand layer is saturated using a sedimentation saturation method. The drain port is opened to drain excess water, and the upper surface of the liquid is flush with the upper surface of the sand layer, after which the drain port is closed. A special fluid is then injected above the sand layer, and after sealing, air pressure is applied at the air inlet. After the air pressure stabilizes, the drain port is opened, and the special fluid, which is mud, foam, or polymer, seeps into the sand layer under pressure. The seepage test method for continuously measuring the infiltration distance of a special fluid specifically comprises the following steps: Step 1: Use a transparent cylinder device to conduct a seepage test, record the pore water pressure and seepage flow parameters, and shoot a video of the seepage process; Step 2: Use Python code to extract frames from the captured video at fixed time intervals, and perform grayscale processing, Gaussian blur, binarization, dilation, and erosion on the frames to obtain black and white images; Step 3: Calculate the pixel value of the infiltration area and its proportion to the total pixel value of the image; Step 4: Estimate the infiltration distance based on the original size of the video shooting area and the above ratio; Step 5: According to the time interval set when extracting frames, the relationship between the infiltration distance and time is obtained; Step 6: Analyze the seepage test results by combining pore water pressure, seepage flow rate, and infiltration distance; 2. The seepage test method for continuously measuring the infiltration distance of a special fluid according to claim 1, characterized in that: The second step uses Python code to extract frames from the captured video at fixed time intervals, specifically including: Read the video file, extract a frame from the video file, and save the frame as a new image for subsequent processing; Define the number of frames and the time interval for extracting frames. Define the frame number of the frame at time 0 as 1. After completing the processing of a certain frame, extract images one by one at a time interval of 25 frames. The number of frames is accumulated until the end of the video. When the frame rate of the video is 25 frames per second, the extraction result is that one frame is extracted per second as the image to be processed.

3. The seepage test method for continuously measuring the infiltration distance of a special fluid according to claim 1, characterized in that: The second step sequentially performs grayscale processing, Gaussian blurring, binarization, dilation, and corrosion on the frame to obtain a black and white image, specifically including: The extracted frames are converted into grayscale images. During the grayscale conversion process, the light intensity information is retained. When the digital image is converted into gray, there will be obvious differences in the grayscale values ​​of the infiltration area and the original sand layer. Use Gaussian blur to process the image, remove noise caused by the texture of sand particles themselves, and smooth the image texture; The grayscale image is converted into a binary image using the Otsu binarization algorithm. Due to the color difference between the infiltration area and the original sand layer, the image will show two distinct areas, black and white. The white area is the infiltration area, and the black area is the original soil area. The division of the areas is related to the properties of the soil and fluid, and the specific division is determined according to the actual situation. Morphological operations – dilation and erosion are used to further eliminate image noise and smooth the contours between black and white areas to obtain the processed black and white image.

4. The seepage test method for continuously measuring the infiltration distance of a special fluid according to claim 1, characterized in that: The third step is to calculate the proportion of the infiltration area using the black and white image, which specifically includes: Calculate the pixel values ​​of the entire black and white image and the white and black areas. Based on the pixel values, calculate and output the ratio of the white area to the total image area.

5. The seepage test method for continuously measuring the infiltration distance of a special fluid according to claim 1, characterized in that: The fourth step is to estimate the infiltration distance based on the original size of the video shooting area and the above ratio, specifically including: Based on the phenomenon of sand layer discoloration caused by special fluid infiltration and the results of Python code image processing, the infiltration distance is approximately the product of the original size of the infiltration area and the ratio output by the above Python code; According to the time interval set when extracting frames in Python code, the relationship between infiltration distance and time is obtained.

6. A seepage test system for continuously measuring the seepage distance of a special fluid for implementing the seepage test method for continuously measuring the seepage distance of a special fluid according to any one of claims 1 to 5, characterized in that: The system comprises: The cylinder has threaded openings on the upper and lower sides corresponding to the cylinder sealing screw cover and the cylinder screw base, and a plurality of pressure measuring holes are opened on the side of the middle part of the cylinder wall; The electronic pore water pressure gauge is sealed and connected to the cylinder body through the pressure measuring hole to measure the pore water pressure at the predetermined position; Signal demodulator, used to analyze the collected signals of the electronic pore water pressure meter and read the data in real time and store it on the computer; Electronic scales and water storage containers are used to record the seepage flow of the measurement system in real time and store the permeate; The camera is placed horizontally with the transparent cylindrical device to record the infiltration process of the special fluid into the sand layer and save it as a video file.

7. The seepage test system for continuously measuring the infiltration distance of a special fluid according to claim 6, characterized in that: An air pressure interface is provided on the side of the cylinder body, and the air pressure interface can be connected to an air pressure boosting device to provide the required air pressure for the inside of the cylinder body.

8. The seepage test system for continuously measuring the infiltration distance of a special fluid according to claim 6, characterized in that: The cylindrical sealing screw cover includes a rubber ring and is connected to the cylinder body in a threaded fixing manner; The cylindrical spiral base includes a rubber ring, which is connected to the cylinder in a threaded fixing manner. The bottom includes a permeable stone for preventing the sand and gravel filled in the cylinder from flowing out; below the permeable stone is a water storage cavity, which includes an overflow port for collecting seepage flow.

9. An information data processing terminal, characterized in that: The information data processing terminal is used to implement the steps of the seepage test method for continuously measuring the infiltration distance of a special fluid as described in any one of claims 1 to 5.

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