Permeation type reactive barrier material component characterization method and system based on complex resistivity method

Abstract

The invention belongs to the technical field of permeable reactive barrier structure detection, and discloses a permeable reactive barrier material component characterization method and system based on a complex resistivity method.The method comprises the steps that permeable reactive barrier filling materials with different component characteristics are prepared; respectively measuring structure parameters and complex resistivity parameters of the filling materials with different component characteristics; fitting analysis is conducted on the complex resistivity parameters of the filling material, and complex resistivity characteristic parameters are obtained; according to the structure parameters and the complex resistivity characteristic parameters of the filling material, establishing an electrical parameter quantitative model of the filling material components; and performing quantitative diagnosis and evaluation on the internal structure characteristics of the target PRB filling material by using the electrical parameter quantitative model. According to the method, fitting analysis is carried out by utilizing the complex resistivity and the filling material structure, and a mathematical relation is established, so that the problems of long-term monitoring of PRB material components and long-term stability of a maintenance system are solved, and the high efficiency and universality of a PRB technology are improved.

Description

Technical Field

[0001] This invention relates to the field of detection technology for permeable reactive wall structures, and in particular to a method and system for characterizing the composition of permeable reactive wall materials based on the complex resistivity method. Background Technology

[0002] The statements in this section are merely background information related to the present invention and do not necessarily constitute prior art.

[0003] Permeable reactive barriers (PRBs) are a passive environmental engineering technology for in-situ remediation of groundwater pollution. They involve placing a barrier containing a specific reactive medium along the groundwater flow path, utilizing the physical, chemical, or biological interactions between the medium and pollutants to remove, immobilize, or transform them. This method offers advantages such as high efficiency, low cost, and sustainability, and has become a crucial technology in groundwater remediation. However, it still faces technical bottlenecks in areas such as adapting to complex geological conditions, long-term operational stability, and handling complex pollutants, particularly in characterizing the PRB wall and quantifying the reactive medium components during long-term operation. These bottlenecks significantly limit the further development of PRB technology and pose substantial challenges to its effectiveness and efficiency in complex environments. Therefore, the intelligent upgrading of the long-term monitoring and maintenance system for PRB material components is an urgent problem to be solved. Summary of the Invention

[0004] To address the aforementioned issues, this invention proposes a method and system for characterizing the components of permeable reactive barrier (PRB) materials based on the complex resistivity method. By using complex resistivity and the structure of the filling material for fitting analysis and establishing a mathematical relationship, the long-term stability problem of the long-term monitoring and maintenance system for PRB material components is solved, thereby improving the efficiency and universality of PRB technology.

[0005] To achieve the above objectives, the present invention adopts the following technical solution: In a first aspect, the present invention provides a method for characterizing the composition of a permeable reactive wall material based on the complex resistivity method, comprising the following steps: Preparation of permeable reactive wall filling materials with different component characteristics; The structural parameters and complex resistivity parameters of filling materials with different component characteristics were measured respectively; By fitting and analyzing the complex resistivity parameters of the filling material, the characteristic parameters of the complex resistivity are obtained. Based on the structural parameters and complex resistivity characteristics of the filling material, a quantitative model of the electrical parameters of the filling material components is established. A quantitative model of electrical parameters is used to quantify and evaluate the internal structural characteristics of the target PRB filling material.

[0006] As an alternative implementation method, nonlinear fitting tests are used to improve the analytical efficiency and accuracy of the quantitative model of electrical parameters of filling material components.

[0007] As an alternative implementation method, the Debye decomposition model is: ; In the formula, N is the discrete value of the relaxation time. Quantity, Indicates the sampling relaxation time The corresponding polarization value.

[0008] As an alternative implementation method, the relaxation time is expressed as: ; In the formula, yes Peak frequency of the spectrum.

[0009] As an alternative implementation method, a quantitative model of the electrical parameters of the filling material components is established, specifically as follows: By combining the obtained structural parameters and complex resistivity characteristic parameters of the filling material, mathematical relationships and sensitivity analyses are performed using the Debye decomposition model and phase spectrum. The mathematical relationships between each complex resistivity characteristic parameter and key structural parameters are summarized through phase spectrum and relaxation time. The sensitivity of each complex resistivity characteristic parameter to different structural features is analyzed using the Debye decomposition model through power law relationship, revealing the intrinsic connection between the microstructural characteristics of the material and the macroscopic complex resistivity response.

[0010] As an alternative implementation, the polarizability of a filling material with low structural parameters can be fitted to that of a filling material with higher structural parameters. The formula for superimposing polarizability is: mc = 1-(1-m1)(1-m2). In the formula, m1 and m2 are both polarizabilities of the filling material with low structural parameters.

[0011] Secondly, the present invention provides a component characterization system for permeable reactive wall materials based on the complex resistivity method, comprising: The materials preparation module is configured to: prepare permeable reactive wall filling materials with different component characteristics; The parameter measurement module is configured to measure the structural parameters and complex resistivity parameters of filling materials with different component characteristics. The feature extraction module is configured to: perform fitting analysis on the complex resistivity parameters of the filling material to obtain the complex resistivity feature parameters; The model building module is configured to: establish a quantitative model of the electrical parameters of the filling material components based on the structural parameters and complex resistivity characteristic parameters of the filling material; The component characterization module is configured to: use an electrical parameter quantification model to quantitatively diagnose and evaluate the internal structural characteristics of the target PRB filling material.

[0012] Thirdly, the present invention provides an electronic device including a memory and a processor, and computer instructions stored in the memory and running on the processor, wherein the computer instructions, when executed by the processor, perform the method described in the first aspect.

[0013] Fourthly, the present invention provides a computer-readable storage medium for storing computer instructions, which, when executed by a processor, perform the method described in the first aspect.

[0014] Fifthly, the present invention provides a computer program product, including a computer program that, when executed by a processor, implements the method described in the first aspect.

[0015] Compared with the prior art, the beneficial effects of the present invention are as follows: This invention proposes a method for characterizing the composition of permeable reactive wall materials based on complex resistivity. First, permeable reactive wall filling materials with different component characteristics to be measured are prepared. Then, basic physical parameters such as specific surface area, particle density, and volume content of the filling materials are measured, along with the conductivity of pore water. Next, by setting the power supply current, signal acquisition points, and measurement voltage, a spectrum excitation instrument is used to scan within the effective frequency range to obtain complex resistivity spectrum data for different sand column devices. Then, a representative complex resistivity model (Debye decomposition model) is applied to fit the measured spectrum data, extracting the core complex resistivity parameters corresponding to each model. The mathematical relationships between each complex resistivity parameter and key structural parameters are summarized using the Debye decomposition model, phase spectrum, and relaxation time, and sensitivity analysis is performed. Finally, the intrinsic connection between the microstructural characteristics of the material and the macroscopic complex resistivity response is revealed, thereby diagnosing the structural characteristics of the filling material. This invention proposes a monitoring method that uses complex resistivity and filling material structure to fit and analyze the data and establish a mathematical relationship. This method is then applied to the intelligent upgrade of the long-term monitoring and maintenance system for PRB technology material components, which helps to improve the upper limit of PRB technology and ensure its efficiency and stability.

[0016] Advantages of additional aspects of the invention will be set forth in part in the description which follows, and in part will be obvious from the description, or may be learned by practice of the invention. Attached Figure Description

[0017] The accompanying drawings, which form part of this invention, are used to provide a further understanding of the invention. The illustrative embodiments of the invention and their descriptions are used to explain the invention and do not constitute an improper limitation of the invention.

[0018] Figure 1 This is a flowchart of the method for characterizing the composition of permeable reactive wall materials based on the complex resistivity method of the present invention; Figure 2 This is a schematic diagram of an optional method for constructing the sand column device in this invention; Figure 3 The resistivity spectrum curves of mixed fillings of zero-valent iron and activated carbon with different volume contents; Figure 4 Spectrum curves of complex resistivity of filling materials under different pore water conductivity conditions; Figure 5 Complex resistivity spectrum curves of zero-valent iron and activated carbon filling materials with different particle sizes; Figure 6 Fitted data graphs of filling materials under different pore water conductivity conditions; Figure 7 Fitted data graphs for different ratios of zero-valent iron and activated carbon; Figure 8 Figure showing the fitting results of the complex resistivity model for composite filling materials with different particle sizes; Figure 9 This is a graph showing the relationship between the relaxation time of the filling material and the radius of the reacting particles. Detailed Implementation

[0019] The present invention will be further described below with reference to the accompanying drawings and embodiments.

[0020] It should be noted that the following detailed description is exemplary and intended to provide further illustration of the invention. Unless otherwise specified, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention pertains.

[0021] It should be noted that the terminology used herein is for the purpose of describing particular embodiments only and is not intended to limit the exemplary embodiments of the invention. As used herein, unless the context clearly indicates otherwise, the singular form is intended to include the plural form as well. Furthermore, it should be understood that the terms "comprising" and "having," and any variations thereof, are intended to cover a non-exclusive inclusion, for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but includes other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0022] Where there is no conflict, the embodiments and features in the embodiments of the present invention can be combined with each other.

[0023] Example 1 like Figure 1As shown, this embodiment provides a method for characterizing the composition of a permeable reactive wall material based on the complex resistivity method, including the following steps: Preparation of permeable reactive wall filling materials with different component characteristics; The structural parameters and complex resistivity parameters of filling materials with different component characteristics were measured respectively; By fitting and analyzing the complex resistivity parameters of the filling material, the characteristic parameters of the complex resistivity are obtained. Based on the structural parameters and complex resistivity characteristics of the filling material, a quantitative model of the electrical parameters of the filling material components is established. A quantitative model of electrical parameters is used to quantify and evaluate the internal structural characteristics of the target PRB filling material.

[0024] The specific solution of the present invention is as follows: Preparation of typical permeable reactive wall filling materials with different component characteristics: The composition features include sand column experimental apparatuses with different filling schemes (reaction material ratios and volume contents, matrix particle size and specific surface area) and different simulated pore liquids (controlling different electrical conductivities). The specific construction method is as follows: The experimental materials are sieved to ensure a relatively concentrated particle size distribution. The quartz sand material is washed with deionized water until the conductivity of the washed water sample is less than 0.001 S / m, and finally dried in an oven at 100 °C for 24 hours. Activated carbon and zero-valent iron samples are washed with deionized water and freeze-dried under vacuum at -80 °C for 24 hours. The reaction particles and matrix are uniformly dry-mixed according to different VC values ​​to form different reaction material content ratios r (the ratio is set according to an equal gradient or bond threshold, i.e., r = ...). + k·Δr, The minimum content ratio is indicated by k, the proportionality coefficient is indicated by Δr, and the gradient value is indicated by Δr. Particle size d (to avoid clogging of the sand column while ensuring sufficient contact between the reactant and pore water, using linear intervals) and pore water conductivity EC (based on the sand column experimental setup with equal gradient intervals according to conventional mineralization (approximately 100 ~ 500 μS / cm), medium mineralization (approximately 500 ~ 5000 μS / cm), and high mineralization (≥ 5000 μS / cm)). The experimental setup has a column length of 9.5 cm and an inner diameter of 2.5 cm. Figure 2 As shown, a NaCl solution with a conductivity of 0.08 S / m was injected from the bottom of the sand column at a constant flow rate of 2 mL / min using a peristaltic pump until the conductivity of the solution flowing out from the top was close to that of the injected solution. Different reactant content ratios, particle sizes, and pore water conductivity were set.

[0025] Measurement of structural parameters of infill material for permeable reactive walls: Structural parameter measurements included: measuring the basic physical parameters of the PRB reactive material, including specific surface area, particle density, and volume content; measuring the electrical conductivity of pore water in the composite filling material; and testing the specific surface area of ​​quartz sand, zero-valent iron, and activated carbon using the nitrogen adsorption method (Micromeritics ASAP 2460) and Brunauer-Emmett-Teller (BET). S s The specific surface area of ​​the material is calculated according to the formula. Calculate the specific surface area per unit pore volume (specific surface area index). (μm -1 In the formula, ρ is the density of the reactant particles, and VC is the volume content of the reactant particles. This refers to the porosity of the composite filling material. The surface shape of the material (particle size and shape are obtained using a scanning electron microscope); the electrical conductivity of the pore water in the filling material is directly measured using a conductivity meter.

[0026] Measurement of complex resistivity parameters of infill material for permeable reactive walls: Complex resistivity parameter measurement: The mixed material is uniformly filled into the acrylic column; sodium chloride solution is injected from the bottom of the column at a constant flow rate using a peristaltic pump until the conductivity of the effluent is close to that of the injected solution; the power supply current, signal acquisition points, and measurement voltage are configured for each sand column device, utilizing the phase difference between the two ( The complex resistivity characteristics of porous media are characterized by using a spectrum exciter to scan within the effective frequency range and present the complete polarization process; the complex resistivity spectrum data of different sand column devices are measured and obtained.

[0027] Frequency domain complex resistivity measurements were performed using a PSIP spectrum induced polarization instrument, within the frequency range. Hz to Signal acquisition points were set between Hz to ensure a complete polarization process within the effective frequency range. Two spiral power supply electrodes were placed at the upper and lower ends of the sand column to provide a stable current field. Two measuring electrodes, spaced 3.5 cm apart, were placed on one side of the sand column. Both electrodes were Ag-AgCl non-polarizing electrodes. The above electrode setup was used for four-electrode complex resistivity measurement.

[0028] Fitting analysis of complex resistivity characteristic parameters of filling materials: A representative complex resistivity model (Debye decomposition model) is applied to fit the measured spectral data (fitting data such as...). Figure 6 , 7 8); Extract the core complex resistivity parameters corresponding to each model, including polarizability, conductivity amplitude, relaxation time, model constants, etc. (data such as...) Figure 3 , 4 5).

[0029] The Debye decomposition model used for fitting the characteristic parameters of the complex resistivity of the filling material is: ; In the formula, N is the discrete value of the relaxation time. Quantity, Indicates the sampling relaxation time The corresponding polarization value and relaxation time range must cover the measured frequency range. Indicates low-frequency resistivity. Represents the imaginary unit. Represents angular frequency. Based on relaxation time distribution. It can calculate various polarization parameters: total polarizability Mean log relaxation time Median relaxation time (Corresponding to the relaxation time when half of the total polarizability is reached), peak relaxation time (Corresponding to the i-th local maximum of the relaxation time distribution).

[0030] The relaxation time of the fitting analysis of the complex resistivity characteristic parameters of the filling material is expressed as: In the formula, yes The peak frequency of the spectrum. Specifically, the relaxation time of polarization in conductor minerals, in relation to particle size and pore water conductivity, can be expressed as: In the formula, ( ( ) is the specific volume capacitance. denoted by pore water conductivity, and r represents the radius of polarized particles.

[0031] Establish a quantitative model of the electrical parameters of the filling material components: combining the obtained material structure parameters and the extracted complex resistivity characteristic parameters ( Figure 3 , 4 5) Mathematical relationships and sensitivity analyses were performed using the Debye decomposition model and phase spectrum; the complex resistivity parameters and key structural parameters (especially the volume content of the reactant material VC and the specific surface area per unit pore volume) were summarized through phase spectrum and relaxation time. The mathematical relationship between particle size and relaxation time was investigated; the sensitivity of various complex resistivity parameters to different structural features was analyzed using the Debye decomposition model based on the power law relationship; the intrinsic connection between the microstructural features of the material (distribution of reactive particles, active interface) and the macroscopic complex resistivity response was revealed, as well as the specific surface area. There is a power-law relationship between it and polarizability. m = a × [ ] b The relaxation time is proportional to the square of the particle radius of the reaction. )(like Figure 9As shown). Relaxation time is inversely proportional to pore water conductivity (as shown). ).

[0032] A quantitative model of the electrical parameters of the filling material components is established. The polarizability (m1 and m2) of the filling material with low structural parameters can be used to fit the polarizability mc of the filling material with higher structural parameters (the sum of the structural parameters of the former). The formula for superimposing the polarizability is as follows: mc = 1-(1-m1)(1-m2); the real part conductivity at low frequencies characterizes the conductivity ( ) Subjected to electrolyte conduction ( ), surface conduction ( ) and conductor conduction ( Three-part control: + + .

[0033] By applying the established quantitative model of the electrical parameters of the filling material components, residual analysis (nonlinear fitting test) can be used to improve the efficiency and accuracy of the analysis; further calculations can be performed using a gradient boosting tree model. (x) = ( (x) represents the initial model (round 0 model). , To find the parameter that minimizes the sum of subsequent losses " Let N be the loss function and N be the number of samples. For the true value, (where the initial predicted value is used), then the model for the m-th round is: ( x ) = ( x ) + η • ( x ),in The learning rate (controls the contribution weight of each tree to prevent overfitting). ( x () represents the overall model of the previous round. ( x Let be the base learner trained in the m-th round. The final model is: ( x ) = ( x ) + η ( x ).in M This represents the total number of iterations (total number of trees). ( x ) represents the predicted value of the final model.

[0034] Structural Feature Diagnosis of Filling Materials Based on Complex Resistivity Method: This method applies a quantitative model of the electrical parameters of the filling material components, acquires complex resistivity spectrum data of actual or simulated PRB systems, and extracts the parameters; the unit pore volume reflects the specific surface area of ​​the material. There is a strong correlation between polarizability and polarizability; the two have a power-law relationship and the power exponent is close to 1. m = a×[ ] b The relaxation time of the filling medium is closely related to the size of the reactant particles and the pore water conductivity associated with ion mobility, and the relaxation time is proportional to the square of the radius of the reactant particles; and the relaxation time of the filling material containing the reactant medium is inversely proportional to the pore water conductivity; therefore, the internal structural characteristics of the target PRB composite filling material (such as the effective distribution of reactant materials and the degree of development of active interfaces) can be quantitatively diagnosed and evaluated through various complex resistivity parameters.

[0035] Example 2 This embodiment provides a component characterization system for permeable reactive wall materials based on the complex resistivity method, including: The materials preparation module is configured to: prepare permeable reactive wall filling materials with different component characteristics; The parameter measurement module is configured to measure the structural parameters and complex resistivity parameters of filling materials with different component characteristics. The feature extraction module is configured to: perform fitting analysis on the complex resistivity parameters of the filling material to obtain the complex resistivity feature parameters; The model building module is configured to: establish a quantitative model of the electrical parameters of the filling material components based on the structural parameters and complex resistivity characteristic parameters of the filling material; The component characterization module is configured to: use an electrical parameter quantification model to quantitatively diagnose and evaluate the internal structural characteristics of the target PRB filling material.

[0036] It should be noted that the above modules correspond to the steps in Embodiment 1, and the examples and application scenarios implemented by the above modules and their corresponding steps are the same, but are not limited to the content disclosed in Embodiment 1. It should also be noted that the above modules can be executed in a computer system as part of the system.

[0037] In further embodiments, the following is also provided: An electronic device includes a memory and a processor, as well as computer instructions stored in the memory and running on the processor, which, when executed by the processor, perform the method described in Embodiment 1. For brevity, further details are omitted here.

[0038] It should be understood that in this embodiment, the processor can be a central processing unit (CPU), or it can be other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. A general-purpose processor can be a microprocessor or any conventional processor.

[0039] A computer-readable storage medium for storing computer instructions that, when executed by a processor, perform the method of Embodiment 1.

[0040] The method in Example 1 can be directly executed by a hardware processor, or it can be executed by a combination of hardware and software modules within the processor. The software modules can reside in readily available storage media in the art, such as random access memory, flash memory, read-only memory, programmable read-only memory, electrically erasable programmable memory, or registers. This storage medium is located in memory; the processor reads information from the memory and, in conjunction with its hardware, completes the steps of the above method. To avoid repetition, a detailed description is not provided here.

[0041] A computer program product includes a computer program that, when executed by a processor, implements the method in Embodiment 1.

[0042] The present invention also provides at least one computer program product tangibly stored on a non-transitory computer-readable storage medium. The computer program product includes computer-executable instructions, such as instructions included in program modules, which execute in a device on a target real or virtual processor to perform the processes / methods described above. Typically, program modules include routines, programs, libraries, objects, classes, components, data structures, etc., that perform specific tasks or implement specific abstract data types. In various embodiments, the functionality of program modules can be combined or divided among program modules as needed. The machine-executable instructions for the program modules can execute within a local or distributed device. In a distributed device, the program modules can reside in both local and remote storage media.

[0043] The computer program code used to implement the methods of the present invention may be written in one or more programming languages. This computer program code may be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing device, such that when executed by the computer or other programmable data processing device, the program code causes the functions / operations specified in the flowcharts and / or block diagrams to be implemented. The program code may be executed entirely on a computer, partially on a computer, as a stand-alone software package, partially on a computer and partially on a remote computer, or entirely on a remote computer or server.

[0044] In the context of this invention, computer program code or related data may be carried by any suitable carrier to enable a device, apparatus, or processor to perform the various processes and operations described above. Examples of carriers include signals, computer-readable media, and the like. Examples of signals may include electrical, optical, radio, sound, or other forms of propagation signals, such as carrier waves, infrared signals, etc.

[0045] Those skilled in the art will recognize that the units and algorithm steps described in conjunction with the embodiments herein can be implemented in electronic hardware or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0046] While the specific embodiments of the present invention have been described above in conjunction with the accompanying drawings, this is not intended to limit the scope of protection of the present invention. Those skilled in the art should understand that various modifications or variations that can be made by those skilled in the art without creative effort based on the technical solutions of the present invention are still within the scope of protection of the present invention.

Claims

1. A method for characterizing the composition of permeable reactive wall materials based on the complex resistivity method, characterized in that, Includes the following steps: Preparation of permeable reactive wall filling materials with different component characteristics; The structural parameters and complex resistivity parameters of filling materials with different component characteristics were measured respectively; By fitting and analyzing the complex resistivity parameters of the filling material, the characteristic parameters of the complex resistivity are obtained. Based on the structural parameters and complex resistivity characteristics of the filling material, a quantitative model of the electrical parameters of the filling material components is established. A quantitative model of electrical parameters is used to quantify and evaluate the internal structural characteristics of the target PRB filling material.

2. The method for characterizing the composition of permeable reactive wall materials based on the complex resistivity method as described in claim 1, characterized in that, The analytical efficiency and accuracy of the quantitative model for the electrical parameters of filling material components are improved by using nonlinear fitting tests.

3. The method for characterizing the composition of permeable reactive wall materials based on the complex resistivity method as described in claim 1, characterized in that, The Debye decomposition model is: ； In the formula, N is the discrete value of the relaxation time. Quantity, Indicates the sampling relaxation time The corresponding polarization value.

4. The method for characterizing the composition of permeable reactive wall materials based on the complex resistivity method as described in claim 3, characterized in that, Relaxation time is expressed as: ； In the formula, yes Peak frequency of the spectrum.

5. The method for characterizing the composition of permeable reactive wall materials based on the complex resistivity method as described in claim 1, characterized in that, A quantitative model for the electrical parameters of the filling material components is established, specifically as follows: By combining the obtained structural parameters and complex resistivity characteristic parameters of the filling material, mathematical relationships and sensitivity analyses are performed using the Debye decomposition model and phase spectrum. The mathematical relationships between each complex resistivity characteristic parameter and key structural parameters are summarized through phase spectrum and relaxation time. The sensitivity of each complex resistivity characteristic parameter to different structural features is analyzed using the Debye decomposition model through power law relationship, revealing the intrinsic connection between the microstructural characteristics of the material and the macroscopic complex resistivity response.

6. The method for characterizing the composition of permeable reactive wall materials based on the complex resistivity method as described in claim 1, characterized in that, The polarizability of a filling material with low structural parameters can be fitted to the polarizability of a filling material with higher structural parameters. The formula for superimposing polarizability is: mc = 1-(1-m1)(1-m2). In the formula, m1 and m2 are both polarizabilities of the filling material with low structural parameters.

7. A component characterization system for permeable reactive wall materials based on the complex resistivity method, characterized in that, include: The materials preparation module is configured to: prepare permeable reactive wall filling materials with different component characteristics; The parameter measurement module is configured to measure the structural parameters and complex resistivity parameters of filling materials with different component characteristics. The feature extraction module is configured to: perform fitting analysis on the complex resistivity parameters of the filling material to obtain the complex resistivity feature parameters; The model building module is configured to: establish a quantitative model of the electrical parameters of the filling material components based on the structural parameters and complex resistivity characteristic parameters of the filling material; The component characterization module is configured to: use an electrical parameter quantification model to quantitatively diagnose and evaluate the internal structural characteristics of the target PRB filling material.

8. An electronic device, characterized in that, It includes a memory and a processor, as well as computer instructions stored in the memory and running on the processor, which, when executed by the processor, perform the method according to any one of claims 1-6.

9. A computer-readable storage medium, characterized in that, Used to store computer instructions, which, when executed by a processor, perform the method described in any one of claims 1-6.

10. A computer program product, characterized in that, Includes a computer program, which, when executed by a processor, implements the method described in any one of claims 1-6.

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