Post-raining slope seepage characteristic testing method based on waveform inversion of nano-iron concentration distribution

Abstract

The invention discloses a post-raining side slope seepage characteristic testing method based on waveform inversion of nano-iron concentration distribution, and belongs to the field of seepage characteristic determination in foundation pit side slope stability monitoring, the method comprises the following steps: spraying a mixture of nano-iron particles and a surfactant into cumulonimbus to make nano-iron permeate into a side slope soil body along with rainfall; a radio frequency coil is arranged in the orthogonal direction of the selected section of the slope, an electromagnetic field is applied to excite nano iron resonance, and electromagnetic wave signals are collected; dividing the selected section of the slope into a plurality of grid units, and inverting the concentration distribution of the nano-iron in each grid unit by using an iterative optimization algorithm based on the electromagnetic wave signal to obtain an inversion result; and generating a seepage cloud picture based on the inversion result and calculating the seepage speed. According to the method, economic loss caused by large-area laying of nano-iron and interference to follow-up monitoring are avoided, the seepage position and size are determined, and complete and clear information is provided for monitoring seepage changes in slope engineering.

Description

Technical Field

[0001] The present invention belongs to the technical field of seepage characteristic determination in foundation pit slope stability monitoring, and in particular relates to a method for testing seepage characteristics of a slope after rain based on waveform inversion of nano-iron concentration distribution. Background Art

[0002] Under the influence of rainfall, water in the slope will seep along the voids in the soil. The dynamic water pressure generated by the seepage will increase the downward force of the soil and soften the soil, which will promote the formation of potential sliding surfaces and may cause the peeling of the surface soil. In addition, water will dissolve certain mineral components in the soil, destroy the original structure of the soil, and reduce the shear strength of the soil. These factors will jointly cause the instability of the foundation pit slope. Therefore, it is very important to determine the seepage path of water in the soil.

[0003] However, due to the uneven size, shape and distribution of voids in rock and soil, the fluidity in different locations is different, and water seepage is affected by surface tension, which makes the prediction of seepage path very complicated. Most current studies are based on random field simulation and numerical analysis to solve seepage problems, which are quite different from the actual seepage path. In actual engineering monitoring, existing methods include resistivity measurement, X-ray measurement, fluorescent material tracing, etc., but the soil has low electrical conductivity and a strong blocking effect on X-rays. Although fluorescent materials can track the seepage path, they are not easily soluble in water, making it difficult to determine externally, and fluorescent materials remaining on the slope surface will interfere with detection. Therefore, there is a need for a method to track the seepage path without destroying the original structure of the slope. The present invention proposes a method to track the seepage path using nano-iron and determine the seepage path and speed through the principle of electromagnetic induction. Summary of the Invention

[0004] In order to solve the above technical problems, the present invention proposes a method for testing the seepage characteristics of slopes after rain based on waveform inversion of nano-iron concentration distribution to solve the problems existing in the above-mentioned prior art.

[0005] To achieve the above objectives, the present invention provides a method for testing the seepage characteristics of slopes after rain based on waveform inversion of nano-iron concentration distribution, comprising:

[0006] Spraying a mixture of nano-iron particles and surfactants into cumulonimbus clouds, allowing the nano-iron to penetrate into the slope soil along with rainfall;

[0007] A radio frequency coil is set in the orthogonal direction of the selected slope section to apply an electromagnetic field to excite the nano-iron resonance and collect electromagnetic wave signals;

[0008] Dividing the selected cross section of the slope into a number of grid cells, and inverting the nano-iron concentration distribution in each grid cell using an iterative optimization algorithm based on the electromagnetic wave signal to obtain an inversion result;

[0009] A seepage cloud map is generated based on the inversion results and the seepage velocity is calculated.

[0010] Optionally, the process of spraying a mixture of nano-iron particles and a surfactant into a cumulonimbus cloud comprises:

[0011] A meteorological aircraft is used to mix nano-iron particles with a surfactant at a standard concentration of 20%-35% and then spray it into cumulonimbus clouds. The concentration of the surfactant is dynamically adjusted according to the ambient temperature. When the surface temperature is higher than 25°C, the concentration of the surfactant increases to 2-3 times the standard concentration.

[0012] Optionally, the process of applying an electromagnetic field by the radio frequency coil to excite the nano-iron resonance and collecting the electromagnetic wave signal includes:

[0013] A radio frequency coil is set in the orthogonal direction of the selected section of the slope, and a radio frequency source meter is arranged on the surface of the slope;

[0014] The radio frequency coil is connected to the radio frequency source meter to form a closed loop;

[0015] The radio frequency source generates an electromagnetic field to excite the nano-iron in the soil to resonate and generate electromagnetic wave signals;

[0016] The radio frequency coil receives the electromagnetic wave signal and outputs the electromagnetic wave signal to the oscilloscope for processing and display.

[0017] Optionally, based on the electromagnetic wave signal, an iterative optimization algorithm is used to invert the nano-iron concentration distribution in each grid unit to obtain an inversion result, comprising:

[0018] S1. Divide the selected slope section into a number of grid cells to obtain initial grid cells;

[0019] S2. constructing a boundary electromagnetic wave amplitude error based on the electromagnetic wave signal, and constructing an objective function based on the boundary electromagnetic wave amplitude error;

[0020] S3. Based on the initial grid cells, the objective function is iteratively calculated using a damped Newton iterative algorithm with a regularization factor introduced to obtain a current iterative calculation result;

[0021] S4. Based on the current iterative calculation result, identifying the monotonicity of the waveform function in the initial grid unit by a clustering algorithm, performing grid encryption on the non-monotonic area to obtain an encrypted grid unit;

[0022] S5. Use the encrypted grid unit as the initial grid unit and execute S3-S4 in a loop until the objective function is less than the set value, then stop the calculation and obtain the inversion result.

[0023] Optionally, the objective function constructed based on the boundary electromagnetic wave amplitude error is:

[0024]

[0025] Where f(R) is the target function, R is the electromagnetic wave amplitude, and p(R) is the potential waveform function at the boundary obtained by assuming concentration distribution. is the measured boundary potential waveform function, and x is the length of each side of the slope.

[0026] Optionally, a damped Newton iterative algorithm that introduces a regularization factor determines the convergence value of the objective function by adjusting a step size factor; wherein the step size factor is determined by backtracking line search.

[0027] Optionally, the process of generating a seepage cloud map and calculating the seepage velocity based on the inversion result includes:

[0028] Obtaining a nano-iron concentration value matrix based on the inversion result;

[0029] Converting the nano-iron concentration in the nano-iron concentration value matrix into a grayscale value for each grid cell;

[0030] Drawing a seepage cloud map based on the grayscale values ​​of a plurality of the grid cells;

[0031] Based on the seepage cloud map, the nano-iron concentrations at different positions at different times are extracted, and the nano-iron concentrations at different positions at different times are derivatized by taking a time element to calculate the concentration change rate to obtain the seepage velocity.

[0032] Optionally, the expression of the seepage velocity is:

[0033]

[0034] Where v represents the seepage velocity, P1 and P2 represent the nano-iron concentration at the first moment and the nano-iron concentration at the second moment, respectively, t1 and t2 represent the first moment and the second moment, respectively, ΔP represents the change in nano-iron concentration, and Δt is the time change.

[0035] Compared with the prior art, the present invention has the following advantages and technical effects:

[0036] The present invention provides a method for testing the seepage characteristics of slopes after rain based on waveform inversion of nano-iron concentration distribution. By spraying a mixture of nano-iron particles and surfactants into cumulonimbus clouds, the nano-iron is uniformly infiltrated into the slope soil with rainfall, effectively solving the problems of inaccurate prediction of seepage paths and difficulty in determining seepage velocity in traditional methods. A radio frequency coil is set in the orthogonal direction of the selected cross-section of the slope, and an electromagnetic field is applied to excite the resonance of the nano-iron and collect electromagnetic wave signals. This innovative design makes signal acquisition more accurate and provides reliable data support for subsequent concentration inversion. By dividing the selected cross-section of the slope into several grid units and using an iterative optimization algorithm to invert the nano-iron concentration distribution in each grid unit, the seepage path and seepage velocity can be accurately determined, providing a scientific basis for slope stability analysis. Finally, a seepage cloud map is generated based on the inversion results and the seepage velocity is calculated, which realizes the intuitive display and quantitative analysis of the seepage characteristics of the slope and improves the efficiency and accuracy of slope monitoring. BRIEF DESCRIPTION OF THE DRAWINGS

[0037] The accompanying drawings, which constitute part of this application, are intended to provide a further understanding of this application. The exemplary embodiments and descriptions of this application are intended to explain this application and do not constitute an improper limitation on this application. In the accompanying drawings:

[0038] Figure 1 Schematic diagram of the arrangement of instruments according to an embodiment of the present invention;

[0039] Figure 2 A soil unit resistance grid according to an embodiment of the present invention;

[0040] Figure 3 A schematic diagram of grid adjustment according to an embodiment of the present invention;

[0041] Figure 4 Schematic diagram of the algorithm structure of an embodiment of the present invention;

[0042] Figure 5 This is a seepage cloud diagram according to an embodiment of the present invention;

[0043] Figure 6 This is a flow chart of the seepage characteristics test according to an embodiment of the present invention;

[0044] Explanation of symbols: 1. Weather aircraft; 2. Surfactant; 3. Nano-iron particles; 4. Cumulonimbus cloud; 5. Rainwater containing nano-iron; 6. External power supply; 7. Radio frequency coil; 8. Radio frequency source meter; 9. Slope; 10. Conductor; 11. Nano-iron particles entering the soil with seepage; 12. Fixed filling materials such as wood chips and gravel; 13. Oscilloscope; 14. Concentration reconstruction; 15. Seepage cloud map. DETAILED DESCRIPTION

[0045] It should be noted that, in the absence of conflict, the embodiments and features of the embodiments in this application can be combined with each other. The present application will be described in detail below with reference to the accompanying drawings and in combination with the embodiments.

[0046] It should be noted that the steps shown in the flowcharts of the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions, and that, although a logical order is shown in the flowcharts, in some cases, the steps shown or described can be executed in an order different from that shown here.

[0047] Example 1

[0048] The present invention relates to a method for transporting nano-iron into a cumulonimbus cloud 4, which infiltrates into a slope along with rainwater during rainfall, and monitoring waveform signals through the resonance effect of the nano-iron excited by an electromagnetic field, inverting the concentration of the nano-iron at different positions, and determining the seepage path and seepage velocity.

[0049] The specific implementation principle is to use a meteorological aircraft 1 to transport relatively low-priced nano-iron into the cloud layer. The nano-iron is fully mixed with water vapor in the atmosphere. The rainwater 5 containing nano-iron penetrates into the slope soil with precipitation and naturally traces the seepage path. After that, it is necessary to determine the position of the nano-iron without damaging the slope structure on a large scale. Consider using the principle of electromagnetic induction, using the radio frequency source table 8 to generate a certain electromagnetic field to make the nano-iron protons vibrate, and the vibration generates electromagnetic waves. The electromagnetic waves are received by the radio frequency coil 7 and imported into the oscilloscope 13 to reconstruct the waveform function. The cross-section soil is divided into grids. According to the edge waveform distribution, the nano-iron concentration in each grid is iteratively solved to determine the position of the nano-iron in the soil, and the seepage path can be obtained. Finally, the seepage velocity is determined by measuring the change in nano-iron concentration over a period of time at a specific position and calculating its derivative.

[0050] like Figure 1 As shown, in view of the shortcomings of existing random field simulation technology and on-site monitoring technology in determining seepage, this embodiment provides a method for testing the seepage characteristics of slopes after rain based on waveform inversion of nano-iron concentration distribution, which solves the problems in the original technology of the path not matching the actual path, the difficulty in determining the seepage velocity, the large damage to the original slope, the difficulty in penetrating the soil, and the interference of tracking materials placed directly on the slope with monitoring, further reveals the law of water movement in the soil, and provides a basis for the stability analysis of foundation pit slopes affected by seepage.

[0051] The present invention first selects a slope 9 to be monitored. During the rainy season, nano-iron is introduced into cumulonimbus clouds 4 via a meteorological aircraft 1. After rainfall, rainwater 5 containing nano-iron infiltrates into the slope soil, forming seepage. Next, a slope section to be measured is selected. Utilizing the characteristic of nano-iron generating signals when resonating in a magnetic field, a specific radio frequency pulse is applied to the outside of the slope 9 to cause the nano-iron protons in the foundation pit slope to resonate. The resonant signal is received by a radio frequency coil 7 and transmitted to an oscilloscope 13. At this point, the signal waveforms on all sides of the slope 9 have been determined, and the nano-iron concentration at each position can be reconstructed using the Newton iteration method until the amplitude error between the edge signal waveform and the four boundary waveforms is less than 10. -6 Finally, a seepage cloud diagram 15 is drawn based on the concentration of nano-iron to show the seepage situation. The flow rate is determined based on the change of nano-iron concentration at the same position at the previous moment and the next moment. The flow rate at different positions is calculated by taking the derivative of the concentration difference and the time difference between the two moments. Figure 6 As shown, the specific steps include:

[0052] Step 1. Spray a mixture of surfactant 2 and nano-iron into cumulonimbus cloud 4 via meteorological aircraft 1, and wait for rainwater containing nano-iron to fully penetrate into the soil of slope 9.

[0053] Step 2. Select a trapezoidal seepage measurement section and dig two holes with a diameter of not less than 0.1m in directions orthogonal to each other in the sections. One hole is set at the top of the slope and the other is set on the slope surface. RF coils 7 are placed in each hole. RF source meter 8 is placed on the slope surface. The external power supply 6 is connected to the RF source meter 8 through a wire 10. The RF source meter 8 generates an electromagnetic field. The RF coil 7 is used to receive the electromagnetic wave signal generated by the resonance of nano-iron inside the soil. The obtained signal is transmitted to the oscilloscope 13 for processing and display.

[0054] Step 3. Divide the selected slope section into several grid cells. Based on the electromagnetic wave signal, use the iterative optimization algorithm to invert the nano-iron concentration distribution in each grid cell to obtain the inversion result. Divide the measurement area into grids and assign a nano-iron concentration value to each small grid area, such as Figure 2 As shown in the figure, due to the different amounts of nano-iron, its concentration content determines the amplitude of the electromagnetic wave in each area. Set an electromagnetic wave amplitude R = [R [1] ,R [2] ,....,R [j] ] is the objective function f(R) of the variable, reconstructs the nano-iron concentration value in each small area, and uses Newton's method to iterate continuously to find a concentration distribution that makes the edge waveform function and the real waveform distribution concentration value a certain value.

[0055]

[0056] Where x is the length of each side of the slope, and the lengths of the four sides of the trapezoid are respectively substituted into the calculation. p(R) is the potential waveform function at the boundary obtained by assuming the concentration distribution. is the measured boundary potential waveform function, and the difference between the two is taken. The closer the absolute value of the integral is to 0, the more reasonable the assumed concentration is. Therefore, it can be regarded as an optimization problem for f(R). Solve R0 when f(R) is close to 0. When R0 is less than 0, the nano-iron concentration value needs to be assigned to 0. When the density of the grid is too small, the f(R) function value will be too large, that is, the error is too large. In this case, it is necessary to increase the density of the grid and reduce the minimum grid density to 0.1 times the original grid side length to ensure that the function value within a single grid is monotonic. This process is performed using a clustering algorithm. The grids with non-monotonic function values ​​within the grid are marked as n, and the grids that meet the conditions are marked as y. For the grids marked as n, the minimum grid side length is reduced to 0.1 times the original side length. Then, according to the damped Newton method, the incremental size of each step of the concentration iteration is as shown in formula (2):

[0057]

[0058] The increment is written in matrix form as:

[0059]

[0060] Here is p,(R n ) Jacobian matrix, the element in row i and column j in the matrix is When it is a singular matrix, a regularization factor z can be introduced for correction, where the smaller the regularization factor z, the better, and the maximum value does not exceed 1. α is the step size factor determined by backtracking line search. Unlike the ordinary Newton iteration method, the damped Newton iteration method is easier to converge by adjusting the step size factor. At the same time, by limiting the gradient conditions, it avoids missing the convergence value due to excessive step size. Compared with previous solutions, by simultaneously limiting the function descent conditions and gradient conditions, the upper limit of convergence is determined while the lower limit of convergence is determined, making the step size value more scientific. During operation, it can be achieved by continuously adjusting the size of the step size factor. The limiting equation for the step size factor is:

[0061]

[0062] d n =-[p,(R n ) T p(R n )+zI] -1 p,(R n ) T f(R n ) (6)

[0063] In the formula, c1 and c2 are parameter values, where c1 ranges from 0 to 0.5 and c2 ranges from c1 to 1. In the process of nanopatch concentration inversion, since the objective function is the integral value of the participation function, the square difference of the residual f(R) can be combined with the Cauchy inequality to replace the gradient value in formulas 4 and 5, that is:

[0064]

[0065] When f(R) is less than the set value 10 -6 When , the iteration is stopped and the obtained concentration value distribution is regarded as the final soil nano-iron content distribution. During the operation, the concentration values ​​in each small grid are converted into grayscale values ​​and spliced ​​together. The algorithm structure is as follows Figure 4 As shown, in actual use, it is necessary to change the input of the edge electromagnetic field, the shape of the slope trapezoid, and the error threshold between the measured waveform and the calculated edge waveform to achieve the desired effect.

[0066] Furthermore, based on the electromagnetic wave signal, an iterative optimization algorithm is used to invert the nano-iron concentration distribution in each grid unit, and the process of obtaining the inversion result includes: S1, dividing the selected section of the slope into several grid units to obtain an initial grid unit; S2, constructing a boundary electromagnetic wave amplitude error based on the electromagnetic wave signal, and constructing a target function based on the boundary electromagnetic wave amplitude error; S3, based on the initial grid unit, using a damped Newton iterative algorithm with an introduced regularization factor to iteratively calculate the target function to obtain the current iterative calculation result; S4, based on the current iterative calculation result, using a clustering algorithm to identify the monotonicity of the waveform function in the initial grid unit, and performing grid encryption on the non-monotonic area to obtain an encrypted grid unit; S5, using the encrypted grid unit as the initial grid unit, and cyclically executing S3-S4. Until the target function is less than the set value, the calculation is stopped to obtain the inversion result.

[0067] Step 4. Based on the inversion results, perform concentration reconstruction 14 to generate a seepage cloud map 15 and calculate the seepage velocity, such as Figure 5 By plotting the nano-iron concentration value matrix into a seepage cloud map 15 according to the size, the seepage size and path of different soil positions can be obtained, forming a seepage cloud map 15 to monitor the seepage situation of the in-situ soil.

[0068] Step 5. Extract the concentrations at different positions at different times, and calculate the seepage velocity at different positions in the soil based on the concentration change rate of nano-iron, as shown in Formula 4, where P1 and P2 represent the nano-iron concentrations at different times, t1 and t2 represent different times, and judge the direction of seepage based on the dynamic changes of the cloud map, as well as the connection with the seepage in other sections.

[0069]

[0070] This invention effectively solves the problems of inaccurate seepage path prediction and difficulty determining seepage velocity in existing technologies. By directly delivering nano-iron into the soil through rainfall, this method is less susceptible to external factors such as wind and running water than directly coating the slope soil surface with nano-iron. It also offers targeted coverage, avoiding the economic losses of large-scale nano-iron deployment and interference with subsequent monitoring. It also determines the location and magnitude of seepage, providing complete and clear information for monitoring seepage changes in slope engineering.

[0071] Example 2

[0072] This embodiment provides a method for testing the seepage characteristics of a slope after rain based on waveform inversion of nano-iron concentration distribution, including the following steps:

[0073] S1. Using a meteorological aircraft 1, a mixture of a surfactant 2 and nano-iron is sprayed into a cumulonimbus cloud 4.

[0074] S2. Based on the research objectives and actual conditions, select the slope section where the seepage conditions need to be determined. Use drilling equipment to dig two holes in mutually orthogonal directions along the slope section, one located on the slope 9 and the other on the top of the slope 9. These two holes serve as the right-angled sides and bottom surface of the trapezoidal measuring section. The hole depth and diameter must meet the test requirements, i.e., be no less than 0.1 m, to ensure that the RF coil 7 can be smoothly inserted and in close contact with the soil. Fill the center with a fixed filler material 12, such as wood chips or gravel, to secure the coil. Connect the RF source meter 8 to the power supply and place it on the slope surface parallel to the voltage generator, ensuring full contact between the electrodes and the soil to reduce contact resistance. Then, apply an electromagnetic field. Use the distributed oscilloscope 13 of the RF source meter 8, which is located on the slope surface, to display the output electromagnetic wave waveform. Determine the edge waveform function of the four sides of the trapezoidal slope. This is equivalent to determining the boundary conditions of the subsequent resistance equation, i.e., the constraints of the conditional function, which are used for the subsequent internal resistance inversion. Since the divided unit interval is limited, that is, the resistance value on each micro segment is fixed, and the measured boundary waveform condition is a continuous function form, the grid density and division method at each position in S4 can be adjusted according to the size of the error at the boundary, such as Figure 3 As shown in the figure, if there is an increase or decrease in the waveform function within the length range of the grid, it will be divided more densely. When the density reaches approximately monotonicity in each grid interval, the fitted concentration value will be assigned to the grid at the corresponding boundary. This process automatically realizes the grid redivision through the clustering algorithm. When the function value in the grid is not monotonic, it is marked as "n" and the monotonic one is marked as "y". For the grid marked as n, its interval length is divided by 10 to refine the grid, and the error value at the boundary is approximately shared by the gradient of the grid along the height direction.

[0075] S3. Divide the measurement area into grids of approximately the same size. The side length of the grid cannot be greater than 1 / 10 of the side length of each side of the slope trapezoid. According to the received waveform, use the damped Newton method theoretical algorithm to invert the nano-iron distribution in the trapezoidal area. First, calculate the upper and lower limits of the step factor according to the formula, and calculate the iterative step size until the edge waveform is close to the mathematical fitting expression of the true waveform of the boundary. When the error is too large, the minimum size of the grid needs to be reduced by 10 times to encrypt the grid, refine the soil concentration distribution density, and increase the accuracy. After obtaining a relatively ideal grid concentration value, the grid concentration value is assigned to the horizontal, vertical, and inclined directions. Use the boundary conditions in S3 to verify that the concentration equation can be established in all directions and the error values ​​are less than the limit, which proves that the obtained results are good.

[0076] As a specific implementation of this embodiment, when the number of grids is 90 and the error threshold is 10 -6 , the cross-sectional area of ​​the slope was measured to be 2.25m 2 , the top input electromagnetic wave waveform function is The waveform function of the electromagnetic wave output at the bottom is V(x)=0.5sinx+0.5, and the waveform function of the input on the left is V(y)=e -y , the output waveform function on the right is V(y)=e y -1, it is calculated that when the regularization factor Z = 0.1 and α = 0.33, the optimal concentration distribution is: [[0.37480643 0.18846411 0.79057304 0.3133321 0.648698280.905370520.352768020.992095 0.86032617] [0.23527779 0.56526218 0.3775357 0.50965442 0.938911420.075751650.223281970.110595910.33484469] [0.12656331 0.88377779 0.6160869 0.10348833 0.869087540.172090160.014695990.445243260.82749165] [0.41919782 0.37052428 0.77496819 0.55017744 0.12531052 0.38341001 0.74520095 0.76333785 0.0823601] [0.98711998 0.17615357 0.8363884 0.57076552 0.63698004 0.96342184 0.33556759 0.99816882 0.24516863] [0.69253682 0.37272586 0.17806551 0.146126 0.306023140.609398460.488349490.060235530.34060398] [0.14050288 0.7287736 0.39024217 0.58415107 0.897329440.951992310.590324010.369959520.83239574] [0.06227053 0.79913329 0.55391302 0.44002161 0.540185830.467151910.1012593 0.8527722 0.03810903] [0.82946842 0.73874922 0.35894727 0.11688502 0.23330727 0.27390772 0.76051245 0.26133585 0.97004224] [0.46470672 0.68708728 0.57451511 0.33373329 0.254980610.142205210.78073912 0.40786705 0.03098886]]

[0087] S4. Use the algorithm to plot the final concentration values ​​into the form of a seepage cloud map 15 according to their size. The result is shown in the figure below. The darker part has a higher concentration of nano-iron, indicating that the seepage at this location in the slope is more serious. The lighter the color, the lower the concentration, and almost no seepage occurs.

[0088] Example 3

[0089] Step 1: Select the slope soil whose seepage conditions need to be measured. Before the rainy season arrives, use a meteorological aircraft 1 to spray nano-iron particles 3 into cumulonimbus clouds 4. At the same time, spray a surfactant 2 with a concentration of 20%-35% to activate the charge of the nano-iron. It should be noted that when the temperature is high, water vapor evaporates easily, and the concentration of the surfactant needs to be increased. Generally, the concentration is increased to 2-3 times to accelerate the condensation rate of water vapor.

[0090] Step 2: Select the cross section of the slope 9 to be measured, select two holes in two mutually perpendicular directions of the slope 9, and drill two holes with a diameter of not less than 0.1m to leave sufficient space for the placement of the RF coil 7. Place the RF coils 7 separately, and then fill the gaps with fixed filling materials 12 such as wood chips and gravel to fix the RF coils 7. Arrange the RF source surface 8 on the surface of the slope 9 to generate a certain changing electromagnetic field. After power is turned on, the RF coils 7 are used to capture the electromagnetic wave waveform excited by the nano-iron protons in the nano-iron particles 11 that enter the soil with seepage.

[0091] Step 3: Reconstruct the nano-iron concentration in each small interval using the received waveform function using the Newton iteration method. The location with the highest concentration is the percolation path.

[0092] Step 4: According to the size of the concentration value, the concentration calculated in each small interval is converted into a grayscale value, that is, a color variable, in each small interval, and drawn into a grayscale graph. The larger the grayscale value, that is, the darker the color, the higher the concentration of nano-iron, which proves that there are larger seepage pores here. The more serious the seepage, the smaller intervals are pieced together, and the seepage path diagram is reflected according to the darkness of the color.

[0093] Step 5: By taking the concentration difference captured at different times, take a time element derivative to calculate the concentration change rate and invert the seepage velocity.

[0094] The above are merely preferred embodiments of the present application, but the scope of protection of the present application is not limited thereto. Any changes or substitutions that can be easily conceived by a person skilled in the art within the technical scope disclosed in this application should be included in the scope of protection of the present application. Therefore, the scope of protection of the present application should be based on the scope of protection of the claims.

Claims

1. A method for testing the seepage characteristics of slopes after rain based on waveform inversion of nano-iron concentration distribution, characterized in that: The following steps are involved: spraying a mixture of nano-iron particles (3) and a surfactant (2) into a cumulonimbus cloud (4) so ​​that the nano-iron penetrates into the slope soil along with rainfall; A radio frequency coil (7) is arranged in an orthogonal direction of a selected cross section of the slope to apply an electromagnetic field to excite the nano-iron to resonate and collect electromagnetic wave signals; Dividing the selected cross section of the slope into a number of grid cells, and inverting the nano-iron concentration distribution in each grid cell using an iterative optimization algorithm based on the electromagnetic wave signal to obtain an inversion result; Based on the inversion results, a seepage cloud map (15) is generated and the seepage velocity is calculated.

2. The method for testing the seepage characteristics of slopes after rain based on waveform inversion of nano-iron concentration distribution according to claim 1, characterized in that: The process of spraying a mixture of nano iron particles (3) and a surfactant (2) into a cumulonimbus cloud (4) comprises: A meteorological aircraft (1) is used to mix nano-iron particles (3) with a surfactant (2) having a standard concentration of 20% to 35% and then spray the mixture into a cumulonimbus cloud (4). The concentration of the surfactant (2) is dynamically adjusted according to the ambient temperature. When the surface temperature is higher than 25°C, the concentration of the surfactant (2) is increased to 2 to 3 times the standard concentration.

3. The method for testing the seepage characteristics of slopes after rain based on waveform inversion of nano-iron concentration distribution according to claim 1, characterized in that: The process of applying an electromagnetic field by using the radio frequency coil (7) to excite the nano-iron resonance and collect electromagnetic wave signals includes: A radio frequency coil (7) is set in an orthogonal direction of a selected cross section of the slope, and a radio frequency source meter (8) is arranged on the surface of the slope; The radio frequency coil (7) is connected to the radio frequency source meter (8) to form a closed loop; The radio frequency source (8) generates an electromagnetic field to excite the nano-iron in the soil to resonate and generate electromagnetic wave signals; The radio frequency coil (7) receives the electromagnetic wave signal and outputs the electromagnetic wave signal to an oscilloscope (13) for processing and display.

4. The method for testing the seepage characteristics of slopes after rain based on waveform inversion of nano-iron concentration distribution according to claim 1, characterized in that: Based on the electromagnetic wave signal, the nano-iron concentration distribution in each grid cell is inverted using an iterative optimization algorithm to obtain the inversion result, including: S1. Divide the selected slope section into a number of grid cells to obtain initial grid cells; S2. constructing a boundary electromagnetic wave amplitude error based on the electromagnetic wave signal, and constructing an objective function based on the boundary electromagnetic wave amplitude error; S3. Based on the initial grid cells, the objective function is iteratively calculated using a damped Newton iterative algorithm with a regularization factor introduced to obtain a current iterative calculation result; S4. Based on the current iterative calculation result, identifying the monotonicity of the waveform function in the initial grid unit by a clustering algorithm, performing grid encryption on the non-monotonic area to obtain an encrypted grid unit; S5. Use the encrypted grid unit as the initial grid unit, and execute S3-S4 in a loop until the objective function is less than the set value, and then stop the calculation to obtain the inversion result.

5. The method for testing the seepage characteristics of slopes after rain based on waveform inversion of nano-iron concentration distribution according to claim 4, characterized in that: The objective function constructed based on the boundary electromagnetic wave amplitude error is: Where f(R) is the target function, R is the electromagnetic wave amplitude, and p(R) is the potential waveform function at the boundary obtained by assuming concentration distribution. is the measured boundary potential waveform function, and x is the length of each side of the slope.

6. The method for testing the seepage characteristics of slopes after rain based on waveform inversion of nano-iron concentration distribution according to claim 4, characterized in that: The damped Newton iterative algorithm with a regularization factor is used to determine the convergence value of the objective function by adjusting the step size factor, wherein the step size factor is determined by backtracking line search.

7. The method for testing the seepage characteristics of slopes after rain based on waveform inversion of nano-iron concentration distribution according to claim 1, characterized in that: The process of generating a seepage cloud map (15) based on the inversion result and calculating the seepage velocity includes: Obtaining a nano-iron concentration value matrix based on the inversion result; Converting the nano-iron concentration in the nano-iron concentration value matrix into a grayscale value for each grid cell; Drawing a seepage cloud map (15) based on the grayscale values ​​of a plurality of the grid cells; Based on the seepage cloud map (15), the nano-iron concentrations at different positions and at different times are extracted, and the nano-iron concentrations at different positions and at different times are derivatized by taking a time element to calculate the concentration change rate to obtain the seepage velocity.

8. The method for testing the seepage characteristics of slopes after rain based on waveform inversion of nano-iron concentration distribution according to claim 7, characterized in that: The expression of the seepage velocity is: Where v represents the seepage velocity, P1 and P2 represent the nano-iron concentration at the first moment and the nano-iron concentration at the second moment, respectively, t1 and t2 represent the first moment and the second moment, respectively, ΔP represents the change in nano-iron concentration, and Δt is the time change.

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