Slope measurement method and system based on high-density electrical method monitoring

Abstract

The invention discloses a slope measurement method and system based on high-density electrical method monitoring, and the method comprises the steps: arranging a plurality of electrode arrays in a to-be-measured slope region through employing a high-density electrical method monitoring technology; applying current to the side slope area through a power generation electrode in the electrode array, measuring voltage response by using a receiving electrode in the electrode array, performing inversion processing on acquired voltage data, obtaining resistivity data of the side slope area, and generating a resistivity distribution diagram of the side slope area; carrying out inversion processing again by changing the discharge position to obtain a changed resistivity distribution diagram; complementing the resistivity before and after the change to obtain a combined resistivity distribution diagram; and analyzing the combined resistivity distribution diagram to obtain a stability evaluation result of the slope. The method has higher adaptability and precision, can provide reliable slope stability evaluation under complex geological conditions, and provides a scientific basis for engineering construction and disaster early warning.

Description

Technical Field

[0001] The present invention relates to the technical field of slope measurement, and in particular to a slope measurement method and system based on high-density electrical monitoring. Background Art

[0002] Slope stability assessment is a key issue in geotechnical engineering, especially in infrastructure construction such as mountainous areas, roads, and railways. Traditional slope stability assessment methods usually rely on field surveys, laboratory tests, and mechanical models, but these methods are limited by time, space, and cost, and the accuracy of the assessment results is low under complex geological conditions. In order to overcome these problems, slope monitoring technology based on electrical exploration has gradually been widely used. Electrical exploration can obtain resistivity information of underground media by measuring changes in surface electric fields, thereby inferring the structure and stability of the soil. However, traditional electrical technology has certain limitations in the process of high-density electrode layout, data acquisition and processing, especially in the accurate inversion of resistivity distribution and stability assessment under complex geological environments. Therefore, the use of innovative high-density electrical monitoring technology combined with artificial intelligence algorithms for slope stability assessment has become a promising solution. Summary of the invention

[0003] In view of the above-mentioned problems, the present invention is proposed.

[0004] Therefore, the technical problem solved by the present invention is that the existing slope measurement method has optimization problems such as low accuracy and unreasonable analysis of slope stability.

[0005] In order to solve the above technical problems, the present invention provides the following technical solutions: a slope measurement method based on high-density electrical monitoring, comprising:

[0006] In the slope area to be tested, multiple electrode arrays are deployed using high-density electrical monitoring technology;

[0007] Applying current to the slope area through the generating electrodes in the electrode array, and measuring the voltage response using the receiving electrodes in the electrode array, inverting the collected voltage data to obtain the resistivity data of the slope area, and generating a resistivity distribution map of the slope area;

[0008] By changing the discharge position and re-performing the inversion process, the changed resistivity distribution map is obtained;

[0009] Complement the data before and after the change to obtain the combined resistivity distribution map;

[0010] The combined resistivity distribution map is analyzed to obtain the slope stability assessment result.

[0011] As a preferred solution of the slope measurement method based on high-density electrical monitoring described in the present invention, the electrode array includes arranging power generation electrodes and receiving electrodes respectively, configured according to the geological conditions of the slope and the measurement accuracy requirements, and the electrode density is the number of electrode points per unit area not less than the density threshold.

[0012] As a preferred solution of the slope measurement method based on high-density electrical monitoring described in the present invention, the inversion processing includes: establishing a forward model, dividing the underground medium into multiple discrete units, setting an initial resistivity value for each unit, and calculating the relationship between the resistivity and the observed voltage value, and the resistivity and the positions of the two receiving electrodes by a forward algorithm; using the forward model, inputting the observed voltage value and the positions of the two receiving electrodes, and outputting the resistivity for the positions of the two receiving electrodes;

[0013] The resistivity data of the slope area includes: generating electrodes that discharge alternately and generating electrodes that perform discharge randomly; when the electrodes discharge, obtaining potential data by using a receiving electrode between two discharge electrodes;

[0014] The slope profile is meshed using finite element technology, and the corresponding monitoring area is matched according to the position of every two receiving electrodes;

[0015] Between the two discharge electrodes, the potential data of two receiving electrodes are randomly selected, and the resistivity of the monitoring area corresponding to the selected receiving electrodes is calculated to obtain the resistivity of the monitoring area.

[0016] As a preferred solution of the slope measurement method based on high-density electrical monitoring described in the present invention, wherein: the resistivity distribution map of the slope area includes, after completing the resistivity calculation of any two receiving electrode monitoring areas between the two discharge electrodes, performing a detailed resistivity analysis;

[0017] The detailed analysis includes: if the resistivity of the monitoring area is equal to the resistivity of the slope soil, then the resistivity of the monitoring area is defined as the first monitoring result; if the resistivity of the monitoring area is other values, then the resistivity of the monitoring area is defined as the second monitoring result; assuming that the credibility of the first monitoring result is higher than that of the second monitoring result, and the resistivity in each grid is the same, if there are two or more monitoring results in the same grid, then the first monitoring result is preferentially selected as the final monitoring result of the grid; if there is only one monitoring result in the grid, then it is directly used as the final monitoring result of the grid; if there are two or more monitoring results in the same grid and the first monitoring result is not included, then the monitoring result is set as a pending grid; the pending grid also includes the grid in the profile that is not matched by the receiving electrode;

[0018] The data of the undetermined grid is supplemented by using an interpolation method to obtain the resistivity distribution map.

[0019] As a preferred solution of the slope measurement method based on high-density electrical monitoring described in the present invention, the changing of the electrode array position includes reselecting the power generation electrodes that perform discharge, and using the reselected power generation electrodes to perform inversion processing and detailed resistivity analysis.

[0020] As a preferred solution of the slope measurement method based on high-density electrical monitoring described in the present invention, the complementary data before and after the change include obtaining the final monitoring result of each grid before the change, and using the final monitoring result of each grid after the change as initial data, re-performing the process of refinement analysis and the process of supplementing data of the determined grid by interpolation method to obtain a combined resistivity distribution map.

[0021] As a preferred solution of the slope measurement method based on high-density electrical monitoring described in the present invention, wherein: the slope stability assessment result includes using a neural network to predict stability, input the slope angle and the combined resistivity distribution map, and output the probability of slope stability;

[0022] The neural network adds mechanical constraints to the loss function during the training process.

[0023] A slope measurement system based on high-density electrical monitoring using any of the methods described in the present invention, characterized in that:

[0024] The acquisition unit uses high-density electrical monitoring technology to deploy multiple electrode arrays in the slope area to be measured;

[0025] The monitoring unit applies current to the slope area through the generating electrodes in the electrode array, measures the voltage response using the receiving electrodes in the electrode array, performs inversion processing on the collected voltage data, obtains the resistivity data of the slope area, and generates a resistivity distribution map of the slope area; changes the discharge position and performs inversion processing again to obtain the changed resistivity distribution map; and complements the data before and after the change to obtain a combined resistivity distribution map;

[0026] The evaluation unit analyzes the combined resistivity distribution map to obtain the stability evaluation result of the slope.

[0027] A computer device comprises: a memory and a processor; the memory stores a computer program, wherein: the processor implements the steps of any one of the methods of the present invention when executing the computer program.

[0028] A computer-readable storage medium stores a computer program, wherein: when the computer program is executed by a processor, the steps of any one of the methods of the present invention are implemented.

[0029] Beneficial effects of the invention: The slope measurement method based on high-density electrical monitoring provided by the invention can effectively improve the accuracy and real-time performance of slope stability assessment by accurately inverting and analyzing resistivity distribution maps and combining neural networks to predict slope stability. This method breaks through the time and space limitations of traditional geological exploration, optimizes electrode layout and data processing, has stronger adaptability and accuracy, can provide reliable slope stability assessment under complex geological conditions, and provide a scientific basis for engineering construction and disaster warning. BRIEF DESCRIPTION OF THE DRAWINGS

[0030] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings required for use in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other accompanying drawings can be obtained based on these accompanying drawings without paying creative work.

[0031] Figure 1 An overall flow chart of a slope measurement method based on high-density electrical monitoring provided in the first embodiment of the present invention. DETAILED DESCRIPTION

[0032] In order to make the above-mentioned purposes, features and advantages of the present invention more obvious and easy to understand, the specific implementation methods of the present invention are described in detail below in conjunction with the drawings of the specification. Obviously, the described embodiments are part of the embodiments of the present invention, but not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary persons in the art without creative work should fall within the scope of protection of the present invention.

[0033] Example 1, reference Figure 1 , which is an embodiment of the present invention, provides a slope measurement method based on high-density electrical monitoring, comprising:

[0034] S1: In the slope area to be tested, multiple electrode arrays are deployed using high-density electrical monitoring technology.

[0035] Furthermore, the electrode array includes arranging power generation electrodes and receiving electrodes respectively, configured according to the geological conditions of the slope and the measurement accuracy requirements, and the electrode density is the number of electrode points per unit area not less than a density threshold.

[0036] The arrangement of the electrode array can reasonably configure the positions of the generating electrodes and the receiving electrodes according to the geological conditions of the slope and the measurement accuracy requirements, so that the application of current and the response measurement of voltage are more uniform and reliable. By ensuring that the electrode arrangement density is not lower than the density threshold, it can be ensured that there are enough electrodes per unit area, and the density and accuracy of the measurement data can be improved, thereby providing a high-quality data basis for subsequent resistivity inversion and slope stability analysis, and ensuring the accuracy and repeatability of the monitoring results.

[0037] S2: Apply current to the slope area through the generating electrodes in the electrode array, and measure the voltage response using the receiving electrodes in the electrode array, perform inversion processing on the collected voltage data, obtain the resistivity data of the slope area, and generate a resistivity distribution map of the slope area.

[0038] A forward model is established, the underground medium is divided into multiple discrete units, an initial resistivity value is set for each unit, and the relationship between the resistivity and the observed voltage value, as well as the resistivity and the positions of the two receiving electrodes are calculated by a forward algorithm; using the forward model, the observed voltage value and the positions of the two receiving electrodes are input, and the resistivity corresponding to the positions of the two receiving electrodes is output.

[0039] The resistivity data of the slope area includes randomly generating the generating electrodes for performing the discharge by alternating the generating electrodes; when the electrodes are discharged, the receiving electrodes between the two discharging electrodes are used to obtain the potential data. The profile of the slope is meshed by finite elements, and the corresponding monitoring area is matched according to the positions of every two receiving electrodes. The potential data of two receiving electrodes are randomly selected between the two discharging electrodes, and the resistivity of the monitoring area corresponding to the selected receiving electrodes is calculated to obtain the resistivity of the monitoring area.

[0040] It is important to say that by establishing a forward model, the resistivity distribution of the underground medium in the slope area is simulated, and the relationship between the resistivity and the observed voltage is analyzed through the forward algorithm. The slope area is divided into multiple discrete units, and the initial resistivity value is set for each unit. By inputting the voltage data and the electrode position, the resistivity distribution is reversed and calculated. This model can be used to match the observed voltage data with the electrode position, and then calculate the resistivity value of each monitoring area, ensuring that the obtained resistivity data is highly accurate and reasonable.

[0041] By randomly generating the discharge position of the generating electrode and selecting the receiving electrode between the two discharge electrodes to collect the potential data, the flexibility and coverage of the measurement can be enhanced, deviation can be avoided, and the spatial layout of the electrode array can be fully utilized. Through the finite element meshing slope planing map and electrode matching, the monitoring area can be accurately delineated and the resistivity of each area can be calculated. The final resistivity data provides the necessary input for the subsequent slope stability analysis, which helps to more accurately evaluate the stability of the slope.

[0042] After completing the resistivity calculation of any two receiving electrode monitoring areas between the two discharge electrodes, a detailed resistivity analysis is performed. The detailed analysis includes: if the resistivity of the monitoring area is equal to the resistivity of the slope soil, the resistivity of the monitoring area is defined as the first monitoring result; if the resistivity of the monitoring area is other values, the resistivity of the monitoring area is defined as the second monitoring result; assuming that the credibility of the first monitoring result is higher than the second monitoring result, and the resistivity in each grid is the same, if there are two or more monitoring results in the same grid, the first monitoring result is preferentially selected as the final monitoring result of the grid; if there is only one monitoring result in the grid, it is directly used as the final monitoring result of the grid; if there are two or more monitoring results in the same grid and the first monitoring result is not included, the monitoring result is set as a pending grid; the pending grid also includes the grids in the profile that are not matched by the receiving electrodes.

[0043] The calculated resistivity data is further refined and analyzed to improve the accuracy and credibility of the measurement results. By classifying and screening the resistivity of different monitoring areas, it is ensured that the final resistivity value can reflect the actual situation of the slope soil, thus providing a more reliable basis for the stability analysis of the slope.

[0044] Specifically, by comparing the resistivity of the monitored area with the known slope soil resistivity, if the resistivity is consistent with the soil resistivity, it is defined as the first monitoring result, indicating that the resistivity of the area is in line with expectations and has a high degree of credibility. If the resistivity deviates from the soil resistivity, it is defined as the second monitoring result, which has a low degree of credibility.

[0045] Furthermore, in the grid analysis process, if there are multiple resistivity monitoring results in the same grid, the first monitoring result with higher credibility is preferred, which can reduce errors and ensure the uniformity of the results. If the resistivity result in a grid is unclear or inconsistent with the first monitoring result, the grid is marked as a pending grid and data is supplemented for it. The pending grid also includes those areas that are not fully covered due to electrode layout reasons.

[0046] The data of the undetermined grid is supplemented by using an interpolation method to obtain the resistivity distribution map.

[0047] S3: By changing the discharge position, the inversion process is performed again to obtain a changed resistivity distribution map.

[0048] Reselect the power generation electrode that performs the discharge, and use the reselected power generation electrode to perform inversion processing and detailed resistivity analysis. By adjusting the discharge position of the electrode array, the accuracy and refinement of the resistivity distribution map are further optimized, thereby improving the accuracy and reliability of the inversion processing results. Specifically, by changing the discharge position and reselecting the power generation electrode that performs the discharge, the measurement error that may be caused by the fixed electrode layout position can be effectively avoided, ensuring that the current source monitors the slope area more comprehensively when it is in different positions, reducing possible blind spots.

[0049] It is important to know that the resistivity of some areas may be limited by the choice of discharge electrode location, and there may be uneven current propagation or unsatisfactory electrode array settings. By reselecting the location of the power generation electrode, it is possible to ensure that the current source covers more slope areas, especially those areas that were originally unmeasured or obstructed. After changing the discharge position, the inversion process will recalculate the resistivity data of the slope area based on the new discharge configuration. This can help compensate for the deviation caused by incomplete electrode layout or measurement errors in the previous time, and improve the accuracy of the data. By changing the electrode discharge position multiple times and performing inversion, a more detailed and comprehensive resistivity distribution map can be obtained, so that the geological characteristics of the entire area can better reflect the actual situation of the underground medium, and provide higher quality data support for subsequent slope stability analysis. Through multiple changes and inversions of the discharge position, the resistivity model can be gradually optimized to make it more in line with the actual geological conditions, reduce possible assumptions, and improve the credibility of the resistivity inversion results.

[0050] S4: Complement the data before and after the change to obtain a combined resistivity distribution map.

[0051] The final monitoring result of each grid before the change is obtained, and the final monitoring result of each grid after the change is used together as the initial data, and the process of refining analysis and the process of supplementing the data of the determined grid by the interpolation method are repeated to obtain the combined resistivity distribution map.

[0052] S5: Analyze the combined resistivity distribution map to obtain the slope stability assessment result.

[0053] Specifically, a neural network is used to predict stability, the angle of the slope and the combined resistivity distribution map are input, and the probability of slope stability is output; the neural network adds mechanical constraints to the loss function during the training process.

[0054] Slope stability is affected by multiple factors, such as soil quality, rock formation, slope, etc. The relationship between these factors is usually highly complex and nonlinear. Neural networks have strong nonlinear modeling capabilities and can capture complex relationships by learning a large amount of historical data to predict slope stability. By inputting the angle and resistivity distribution map of the slope, the neural network can output the probability of slope stability to help determine whether the slope has potential landslide risks.

[0055] Combining data such as resistivity distribution map and slope angle makes the slope stability assessment more comprehensive. The resistivity distribution map can reflect the physical properties of soil or rock formations, while the slope angle is one of the key factors affecting stability. By fusing data from these different sources through neural networks, the stability of the slope can be assessed more accurately.

[0056] Adding mechanical constraints (such as the conditions for landslide occurrence, mechanical models, etc.) when training neural networks can ensure that the prediction results of neural networks are more consistent with mechanical principles and avoid erroneous predictions that do not conform to actual mechanical laws. Mechanical constraints can help neural networks better learn the core laws of stability assessment, improve the credibility of the model, and avoid learning unrealistic results based on data alone. Neural networks can output the probability of slope stability through training. This probabilistic prediction result can provide greater flexibility for decision-making. For example, in actual projects, different emergency plans can be formulated or different protective measures can be taken based on the stability probability value. By combining neural networks with slope stability assessment, stability prediction can be performed automatically, avoiding the limitations of manual experience judgment and improving assessment efficiency and accuracy. In this way, slope changes can be responded to quickly, and timely warnings and treatment suggestions can be provided for actual projects.

[0057] The mechanical constraints include but are not limited to: Stability analysis constraints: Critical slip surface stability According to the geometric characteristics and physical properties of the slope, the following stability constraints can be designed to ensure that the stability results predicted by the neural network conform to the basic principles of critical slip surface analysis.

[0058] τ r =c+(σ n -ρh)tanφ

[0059] Where: τ r is the shear strength of the soil r ≤τ max ; c is the cohesion of soil; σ n is the normal stress of the soil, ρ is the density of the soil; h is the slope height; φ is the internal friction angle of the soil; τ max is the critical shear stress, which represents the maximum shear stress of the slope under stable conditions.

[0060] Slope and stability relationship constraints: The angle of the slope has a direct impact on its stability. In mechanics, a larger slope usually leads to a higher sliding tendency. The constraints can be designed as follows:

[0061] S=f(θ,τ)

[0062]

[0063] θ is the angle of the slope; S is the stability index, which is usually calculated by friction coefficient, soil cohesion, etc.; θ critical is the critical angle of the slope (beyond this angle, the slope stability is significantly reduced); S threshold is a given slope stability threshold, below which the slope is considered unstable.

[0064] Mechanical balance constraint: The stability of the slope is not only affected by a single factor, but also involves the balance of multiple forces. Balance constraints can be added to ensure the rationality of the slope stability prediction in a mechanical sense. For example, consider the balance between the total gravity and the anti-sliding force on the slope:

[0065] F gravity =W·sin ( θ )

[0066] F resisting ≥F gravity

[0067] Among them: F gravity is the gravity; W is the gravity of the soil; F resisting is the anti-sliding force; θ is the slope angle.

[0068] On the other hand, this embodiment also provides a slope measurement system based on high-density electrical monitoring, which includes:

[0069] The acquisition unit uses high-density electrical monitoring technology to deploy multiple electrode arrays in the slope area to be measured.

[0070] The monitoring unit applies current to the slope area through the generating electrodes in the electrode array, and measures the voltage response using the receiving electrodes in the electrode array, performs inversion processing on the collected voltage data, obtains the resistivity data of the slope area, and generates a resistivity distribution map of the slope area; by changing the discharge position, the inversion processing is performed again to obtain the resistivity distribution map after the change; and the resistivity distribution map after the change is obtained by complementing the data before and after the change.

[0071] The evaluation unit analyzes the combined resistivity distribution map to obtain the stability evaluation result of the slope.

[0072] If the above functions are implemented in the form of software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art or the part of the technical solution, can be embodied in the form of a software product. The computer software product is stored in a storage medium, including several instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present invention. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), disk or optical disk and other media that can store program codes.

[0073] The logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as an ordered list of executable instructions for implementing logical functions, and can be embodied in any computer-readable medium for use by an instruction execution system, device or apparatus (such as a computer-based system, a system including a processor, or other system that can fetch instructions from an instruction execution system, device or apparatus and execute instructions), or in conjunction with such instruction execution systems, devices or apparatuses. For the purposes of this specification, "computer-readable medium" can be any device that can contain, store, communicate, propagate or transmit a program for use by an instruction execution system, device or apparatus, or in conjunction with such instruction execution systems, devices or apparatuses.

[0074] More specific examples of computer-readable media (a non-exhaustive list) include the following: an electrical connection with one or more wires (electronic device), a portable computer disk case (magnetic device), a random access memory (RAM), a read-only memory (ROM), an erasable and programmable read-only memory (EPROM or flash memory), an optical fiber device, and a portable compact disk read-only memory (CDROM). In addition, the computer-readable medium may even be a paper or other suitable medium on which the program is printed, since the program may be obtained electronically, for example, by optically scanning the paper or other medium, followed by editing, deciphering or, if necessary, processing in another suitable manner, and then stored in a computer memory.

[0075] It should be understood that the various parts of the present invention can be implemented by hardware, software, firmware or a combination thereof. In the above-mentioned embodiments, a plurality of steps or methods can be implemented by software or firmware stored in a memory and executed by a suitable instruction execution system. For example, if implemented by hardware, as in another embodiment, it can be implemented by any one of the following technologies known in the art or their combination: a discrete logic circuit having a logic gate circuit for implementing a logic function for a data signal, a dedicated integrated circuit having a suitable combination of logic gate circuits, a programmable gate array (PGA), a field programmable gate array (FPGA), etc.

[0076] Example 2 is an embodiment of the present invention, which provides a slope measurement method based on high-density electrical monitoring. In order to verify the beneficial effects of the present invention, scientific demonstration is carried out through economic benefit calculation and simulation experiments.

[0077] The purpose of the experiment is to verify the effectiveness and innovation of slope resistivity monitoring and stability assessment by this method. The experiment selected a slope area with different soil layers and slopes, which has typical landslide risks.

[0078] After the electrode array is laid out, current is applied by alternating discharge. Each generating electrode is randomly selected and discharged alternately, with a discharge duration of 5 seconds and a discharge current intensity of 5A. When the current is applied, the receiving electrode between the two discharge electrodes is used to obtain the potential data. In order to obtain an accurate resistivity distribution map, the forward algorithm is used for data inversion to obtain the resistivity of each monitoring area. The specific forward modeling process is to perform finite element meshing according to the planing surface map of the slope, calculate the resistivity in each grid, and refine the resistivity distribution.

[0079] According to the inversion results, a detailed analysis was conducted for each resistivity monitoring area. If the resistivity of a grid is equal to the resistivity of the known soil, it is regarded as the first monitoring result (high confidence); if the resistivity deviates from the soil resistivity, it is regarded as the second monitoring result. If two or more monitoring results appear in a grid, the first monitoring result is preferred. If there is only one monitoring result, it is directly used.

[0080] For the resistivity distribution map before and after the change, the data of the undetermined grid is supplemented by interpolation method, and the final resistivity distribution map is obtained. This map is used as part of the neural network input and combined with the angle information of the slope to predict stability.

[0081] During the neural network training process, the input features include the angle of the slope and the combined resistivity distribution map. By adding mechanical constraints to the network loss function, the model's prediction results are consistent with the actual mechanical laws. The loss function takes into account the slope stability (such as critical slip surface analysis) and the relationship between resistivity and soil strength.

[0082] Table 1 Data record table

[0083]

[0084]

[0085] Through comparative analysis of the table data, we can see that the slope stability assessment results are jointly affected by factors such as resistivity distribution and slope. The specific analysis is as follows:

[0086] Relationship between slope and stability probability: As the slope increases (for example, from 30° to 38°), the stability probability of the slope gradually decreases, from the initial 98.5% to 85.3%. This shows that when the slope is larger, the trend of stability decreases significantly, which is consistent with the actual mechanical behavior of the slope, that is, large slopes are prone to landslides.

[0087] Relationship between resistivity and stability: An increase in resistivity usually reflects the density and strength of the soil. The resistivity of monitoring areas 1, 2, and 3 in the table is relatively low (1500Ω·m to 1800Ω·m), and the corresponding stability probability is high (more than 95%), indicating that the soil in these areas is relatively stable and can withstand greater external pressure. The resistivity of monitoring areas 4 and 5 is higher (2200Ω·m to 2500Ω·m), but their stability probability is lower (less than 90%), which shows that higher resistivity is not always proportional to stability, which may be due to changes in soil composition or insufficient moisture content.

[0088] Effectiveness of mechanical constraints: By introducing mechanical constraints in the training process of the neural network model, it is ensured that the prediction results are consistent with the actual physical laws. For example, the low stability probability of monitoring areas 4 and 5 can be reasonably explained by mechanical constraints. Although the resistivity of these areas is high, they still show unstable characteristics due to the limitation of soil strength.

[0089] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solutions of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical solutions of the present invention, which should all be included in the scope of the claims of the present invention.

Claims

1. A slope measurement method based on high-density electrical monitoring, characterized in that: include: In the slope area to be tested, multiple electrode arrays are deployed using high-density electrical monitoring technology; Applying current to the slope area through the generating electrodes in the electrode array, and measuring the voltage response using the receiving electrodes in the electrode array, inverting the collected voltage data to obtain the resistivity data of the slope area, and generating a resistivity distribution map of the slope area; By changing the discharge position and re-performing the inversion process, the changed resistivity distribution map is obtained; Complement the data before and after the change to obtain the combined resistivity distribution map; The combined resistivity distribution map is analyzed to obtain the slope stability assessment result.

2. The slope measurement method based on high-density electrical monitoring according to claim 1 is characterized in that: The electrode array includes arranging power generation electrodes and receiving electrodes respectively, and configuring them according to the geological conditions of the slope and the measurement accuracy requirements, and the electrode density is the number of electrode points per unit area that is not less than the density threshold.

3. The slope measurement method based on high-density electrical monitoring according to claim 2 is characterized in that: The inversion process includes: establishing a forward model, dividing the underground medium into a plurality of discrete units, setting an initial resistivity value for each unit, calculating the relationship between the resistivity and the observed voltage value, and the resistivity and the positions of the two receiving electrodes by a forward algorithm; using the forward model, inputting the observed voltage value and the positions of the two receiving electrodes, and outputting the resistivity for the positions of the two receiving electrodes; The resistivity data of the slope area includes: generating electrodes that discharge alternately and generating electrodes that perform discharge randomly; when the electrodes discharge, obtaining potential data by using a receiving electrode between two discharge electrodes; The slope profile is meshed using finite element technology, and the corresponding monitoring area is matched according to the position of every two receiving electrodes; Between the two discharge electrodes, the potential data of two receiving electrodes are randomly selected, and the resistivity of the monitoring area corresponding to the selected receiving electrodes is calculated to obtain the resistivity of the monitoring area.

4. The slope measurement method based on high-density electrical monitoring according to claim 3 is characterized in that: The resistivity distribution map of the slope area includes performing a detailed resistivity analysis after completing resistivity calculations of any two receiving electrode monitoring areas between the two discharge electrodes; The detailed analysis includes, if the resistivity of the monitoring area is equal to the resistivity of the slope soil, defining the resistivity of the monitoring area as the first monitoring result; If the resistivity of the monitoring area is other values, the resistivity of the monitoring area is defined as the second monitoring result; The credibility of the first monitoring result is higher than that of the second monitoring result. The resistivity in each grid is the same. If there are two or more monitoring results in the same grid, the first monitoring result is preferred as the final monitoring result of the grid; if there is only one monitoring result in the grid, it is directly used as the final monitoring result of the grid; If there are two or more monitoring results in the same grid and the first monitoring result is not included, the monitoring result is set as a pending grid; the pending grid also includes a grid in the cross-sectional view that is not matched by the receiving electrode; The data of the undetermined grid is supplemented by using an interpolation method to obtain the resistivity distribution map.

5. The slope measurement method based on high-density electrical monitoring according to claim 4 is characterized in that: The changing of the electrode array position includes reselecting the power generation electrodes for performing discharge, and performing inversion processing and detailed resistivity analysis using the reselected power generation electrodes.

6. The slope measurement method based on high-density electrical monitoring according to claim 5 is characterized in that: The complementary process before and after the change includes obtaining the final monitoring result of each grid before the change, taking the final monitoring result of each grid after the change as initial data, re-performing the process of detailed analysis and using the interpolation method to supplement the data of the determined grid, and obtaining a combined resistivity distribution map.

7. The slope measurement method based on high-density electrical monitoring according to claim 6 is characterized in that: The slope stability assessment result includes predicting the stability using a neural network, inputting the slope angle and the combined resistivity distribution map, and outputting the probability of slope stability; The neural network adds mechanical constraints to the loss function during the training process.

8. A slope measurement system based on high-density electrical monitoring using the method according to any one of claims 1 to 7, characterized in that: The acquisition unit deploys multiple electrode arrays in the slope area to be measured using high-density electrical monitoring technology; The monitoring unit applies current to the slope area through the generating electrodes in the electrode array, measures the voltage response using the receiving electrodes in the electrode array, performs inversion processing on the collected voltage data, obtains the resistivity data of the slope area, and generates a resistivity distribution map of the slope area; changes the discharge position and performs inversion processing again to obtain the changed resistivity distribution map; and complements the data before and after the change to obtain a combined resistivity distribution map; The evaluation unit analyzes the combined resistivity distribution map to obtain the stability evaluation result of the slope.

9. A computer device comprising: A memory and a processor; the memory stores a computer program, wherein the processor implements the steps of any method as claimed in claim 1 when executing the computer program.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 7 are implemented.

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