Stability analysis method based on displacement field-seepage field-chemical field coupling inversion

Abstract

The application discloses a stability analysis method based on displacement field-seepage field-chemical field coupling inversion, and relates to the technical field of tailing pond stability analysis. Historical test data of a tailing pond is collected, displacement field operation data of the tailing pond in a preset monitoring period is collected, baseline statistical characteristic parameters of the tailing pond are obtained through comprehensive analysis, and displacement deviation historical sequence of the tailing pond is obtained through deviation analysis on the baseline statistical characteristic parameters; displacement mutation analysis is performed on the displacement deviation historical sequence of the tailing pond, displacement mutation analysis results of the tailing pond are obtained, and a reference inversion safety coefficient of the tailing pond is obtained according to the displacement mutation analysis results of the tailing pond; seepage monitoring data and chemical characteristic data of the tailing pond are collected, real-time state safety coefficients of the tailing pond are obtained through stability analysis, stability analysis is performed on the real-time state safety coefficients, stability analysis results of the tailing pond are obtained, and the early warning capability of the tailing pond safety risk under the influence of chemical erosion and other factors is improved.

Description

Technical Field

[0001] This invention relates to the field of tailings dam stability analysis technology, specifically a stability analysis method based on displacement field-seepage field-chemical field coupling inversion. Background Technology

[0002] Stability analysis of tailings dams typically relies on displacement inversion methods. These methods derive the mechanical parameters of the dam body from monitored displacement data and determine the corresponding strength parameters through inversion, thereby assessing the stability of the tailings dam. However, traditional displacement inversion methods usually assume a stable mapping relationship between displacement and strength parameters, failing to consider the complex nonlinear changes within the tailings dam. This mapping relationship changes significantly, especially when chemical erosion or physicochemical damage occurs. Traditional methods cannot effectively address the nonlinear evolution of tailings dams caused by chemical and physical changes during long-term operation.

[0003] Existing inversion analysis methods typically seek the most suitable mechanical parameters by minimizing errors. However, these parameters obtained through error minimization may not match the actual physical state, leading to biased assessment results. Specifically, although the inverted parameters can minimize errors, they do not reflect the actual physical state of the tailings dam, resulting in an overestimated safety factor. Consequently, internal damage may not be identified in time, and potential risks may be overlooked. This bias may cause the actual condition of the tailings dam to continue to deteriorate. However, due to incorrect parameter estimation, the early warning system cannot accurately reflect the actual risks, and may ultimately miss the opportunity for timely intervention, increasing the risk of catastrophic damage to the tailings dam. Summary of the Invention

[0004] To address the shortcomings of existing technologies, this invention provides a stability analysis method based on displacement field-permeation field-chemical field coupling inversion, which can effectively solve the problems mentioned in the background technology.

[0005] To achieve the above objectives, the present invention is implemented through the following technical solution: a stability analysis method based on displacement field-seepage field-chemical field coupling inversion, including collecting historical test data of tailings dam, collecting displacement field operation data of tailings dam in a preset monitoring period, comprehensively analyzing to obtain baseline statistical characteristic parameters of tailings dam, and performing deviation analysis on baseline statistical characteristic parameters to obtain historical sequence of displacement deviation of tailings dam. Displacement abrupt change analysis was performed on the historical sequence of displacement deviation of the tailings dam to obtain the displacement abrupt change analysis results of the tailings dam. Based on the displacement abrupt change analysis results of the tailings dam, the displacement field operation data of the tailings dam was screened to obtain the benchmark displacement data of the tailings dam. The baseline displacement data of the tailings dam is used for inversion analysis to obtain the baseline inversion safety factor of the tailings dam. Seepage monitoring data and chemical characteristic data of the tailings dam are collected, and stability analysis is performed to obtain the real-time safety factor of the tailings dam. Stability analysis is then performed on the real-time safety factor to obtain the stability analysis results of the tailings dam.

[0006] Furthermore, the method for obtaining the baseline statistical characteristic parameters of the tailings dam through analysis is as follows: Based on historical test data of the tailings dam, a baseline constitutive model of the tailings dam was trained. Within the preset monitoring period, displacement field operation data of the tailings dam are collected. The displacement field operation data of the tailings dam includes geotechnical test data, in-situ test data and displacement monitoring data of each monitoring point of the tailings dam. Geotechnical test data and in-situ test data from each monitoring point of the tailings dam are input into the trained baseline constitutive model to obtain the baseline displacement prediction data for each monitoring point of the tailings dam. The baseline displacement prediction data of all monitoring points are statistically analyzed and stored as baseline statistical characteristic parameters.

[0007] Furthermore, the method for obtaining the historical sequence of tailings dam displacement deviation by performing deviation analysis on baseline statistical characteristic parameters is as follows: The displacement monitoring data of each monitoring point in the displacement field operation data of the tailings dam is compared with the baseline displacement prediction data of the corresponding monitoring point in the baseline statistical characteristic parameters to obtain the displacement residual corresponding to each monitoring point. The displacement residual includes horizontal displacement residual, vertical displacement residual and displacement rate residual. The displacement residuals of all monitoring points are summarized in chronological order to obtain the historical sequence of displacement deviations of the tailings dam.

[0008] Furthermore, the method for performing displacement abrupt change analysis on the historical sequence of displacement deviations in tailings ponds is as follows: From the historical sequence of displacement deviations of the tailings dam, the horizontal displacement residual, vertical displacement residual, and displacement rate residual of each monitoring point of the tailings dam in the current monitoring period are extracted. A comprehensive analysis is then performed to obtain the displacement deviation characterization value corresponding to each monitoring point of the tailings dam. The displacement deviation characterization value is used to comprehensively characterize the degree to which the displacement residual of the monitoring point deviates from the baseline statistical characteristic parameters.

[0009] Furthermore, the method for obtaining the displacement abrupt change analysis results of the tailings dam is as follows: The displacement deviation characterization value corresponding to each monitoring point of the tailings dam is compared with the preset displacement deviation characterization threshold. If the displacement deviation characterization value corresponding to a certain monitoring point of the tailings dam is higher than the preset displacement deviation characterization threshold, the displacement change analysis result corresponding to that monitoring point of the tailings dam is marked as having a displacement change. If the displacement deviation characterization value corresponding to a certain monitoring point of the tailings dam is lower than or equal to the preset displacement deviation characterization threshold, then the displacement mutation analysis result corresponding to that monitoring point of the tailings dam will be marked as having no displacement mutation.

[0010] Furthermore, the method for filtering the displacement field operation data of the tailings dam to obtain the reference displacement data of the tailings dam is as follows: When the displacement mutation analysis results of the tailings dam are marked as having a displacement mutation, the timestamp corresponding to the monitoring period when the displacement deviation characterization value of all monitoring points with displacement mutation in the displacement mutation analysis results first exceeds the preset displacement deviation characterization threshold is obtained, and the earliest timestamp among all timestamps is recorded as the displacement mutation start time. The reference displacement data is extracted from the displacement field operation data based on the start time of the displacement mutation.

[0011] Furthermore, the method for inverting and analyzing the baseline displacement data of the tailings dam is as follows: By comprehensively analyzing the geotechnical test data in the benchmark displacement data, the shear strength characterization value of the tailings dam is obtained. The seepage deformation coefficient of the tailings dam is obtained by comprehensively analyzing the in-situ test data in the benchmark displacement data. The baseline constitutive response coefficients of the tailings dam are obtained by comprehensively analyzing the displacement deviation values ​​corresponding to each monitoring point in each monitoring period. A weighted analysis was performed on the shear strength characterization value, seepage deformation coefficient, and benchmark constitutive response coefficient of the tailings dam to obtain the benchmark inversion safety factor of the tailings dam. The benchmark inversion safety factor of the tailings dam is used to quantify the overall stability of the tailings dam.

[0012] Furthermore, the method for collecting seepage monitoring data and chemical characteristic data of the tailings dam is as follows: Collect seepage monitoring data and chemical characteristic data of the tailings dam; Seepage monitoring data includes seepage flow rate, permeability, and seepage velocity; Chemical characteristic data include pH value, dissolved oxygen, and dissolved ion concentration.

[0013] Furthermore, the method for obtaining the real-time safety factor of the tailings dam through stability analysis is as follows: A comprehensive analysis of seepage monitoring data and chemical characteristic data of the tailings dam is conducted to obtain the chemical seepage anomaly assessment value of the tailings dam; Based on the chemical seepage anomaly assessment value of the tailings dam, the anomaly impact coefficient of the tailings dam is obtained. The product of the baseline inversion safety factor and the anomaly impact factor of the tailings dam is denoted as the real-time state safety factor of the tailings dam.

[0014] Furthermore, the method for obtaining the stability analysis results of the tailings dam is as follows: The real-time safety factor of the tailings dam is compared with the preset real-time safety factor threshold. If the real-time safety factor of the tailings dam is higher than the preset real-time safety factor threshold, the stability analysis result of the tailings dam is marked as stable. Otherwise, the stability analysis result of the tailings dam is marked as stable, and the instability warning information is sent to the staff's mobile terminal.

[0015] The present invention has the following beneficial effects: This invention employs a stability analysis method based on the coupled inversion of displacement field, seepage field, and chemical field. By comprehensively considering the combined effects of displacement field, seepage field, and chemical erosion on the tailings dam body, it can accurately predict the stability changes of the tailings dam under different physical conditions. This coupled analysis method overcomes the limitations of traditional single analysis models, more comprehensively reflecting the actual stability of the tailings dam under chemical erosion and external loads, and can provide a more accurate assessment basis for the long-term safety management of tailings dams.

[0016] The baseline constitutive model and dynamic adjustment mechanism proposed in this invention enhance the tailings dam's ability to cope with environmental changes such as chemical erosion during operation. By establishing a baseline constitutive model based on historical data of the tailings dam before chemical damage and performing deviation analysis based on displacement deviations during subsequent monitoring, structural changes caused by chemical damage can be detected in a timely manner. The safety factor can be automatically adjusted according to these changes, improving the adaptability and responsiveness of tailings dam monitoring data. In practical applications, this provides more accurate stability analysis, thereby ensuring the safety of the tailings dam.

[0017] The combined use of chemical seepage anomaly assessment value and anomaly influence coefficient in this invention optimizes the dynamic adjustment process of real-time state safety factor. By comprehensively analyzing seepage monitoring data and chemical characteristic data, it is possible to accurately assess the impact of chemical seepage on the strength degradation of dam materials, adjust the safety factor in a timely manner, and effectively reflect the potential risks of tailings dams. This safety factor calculation method based on real-time environmental changes enhances the real-time monitoring and early warning capabilities of tailings dams, effectively prevents structural instability caused by chemical erosion, and greatly improves the accuracy and reliability of tailings dam stability analysis. Attached Figure Description

[0018] Figure 1 This is a schematic diagram of the method flow of the present invention. Detailed Implementation

[0019] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0020] Please see Figure 1 As shown, this embodiment of the invention provides a technical solution: a stability analysis method based on displacement field-seepage field-chemical field coupling inversion, including collecting historical test data of tailings dam, collecting displacement field operation data of tailings dam in a preset monitoring period, comprehensively analyzing to obtain baseline statistical characteristic parameters of tailings dam, and performing deviation analysis on baseline statistical characteristic parameters to obtain historical sequence of displacement deviation of tailings dam.

[0021] Specifically, the method for analyzing and obtaining the baseline statistical characteristic parameters of the tailings dam is as follows: During the historical monitoring period in the early stage of tailings dam operation when it was not chemically damaged, historical test data of the tailings dam were collected. The historical test data of the tailings dam included historical geotechnical test data, historical in-situ test data and historical displacement monitoring data of each monitoring point of the tailings dam.

[0022] Historical geotechnical test data were obtained through standard geotechnical testing methods, including historical friction angle and historical cohesion of the soil. The friction angle of the soil is used to describe the anti-slip ability between soil particles, and the cohesion of the soil represents the cohesive force between soil particles.

[0023] Historical in-situ test data were obtained through on-site drilling and sampling, including historical void ratio and historical permeability coefficient. Void ratio represents the proportion of pores in the soil and affects soil permeability, while permeability coefficient reflects the soil's permeability capacity.

[0024] Historical displacement monitoring data is collected through surface displacement monitoring equipment and deep inclinometers, including historical horizontal displacement, historical vertical displacement, and historical displacement rate. Vertical displacement reflects the vertical settlement or uplift of the tailings dam, and displacement rate describes the displacement change per unit time, representing the rate of deformation. Based on the horizontal and vertical displacements, the historical horizontal displacement rate and historical vertical displacement rate are calculated respectively. The historical displacement rate is the single displacement rate value with the higher value among the historical horizontal displacement rate and historical vertical displacement rate at the same monitoring point.

[0025] Based on historical test data of the tailings dam, a baseline constitutive model of the tailings dam was trained.

[0026] The training method for the baseline constitutive model of the tailings dam is as follows: A dataset for training the baseline constitutive model is constructed. The dataset consists of multiple training samples. Each training sample uses historical geotechnical test data and historical in-situ test data collected in a historical monitoring cycle during the early stage of tailings dam operation when it was not chemically damaged as input features, and uses horizontal displacement, vertical displacement and displacement rate in the historical displacement monitoring data of the same historical monitoring cycle as output labels.

[0027] A multilayer perceptron (MLP) was selected as the baseline constitutive model architecture. The number of neurons in the input layer of the MLP is the same as the dimension of the input features, and the number of neurons in the output layer is the same as the dimension of the output labels. The MLP has three hidden layers with 128, 64, and 32 neurons respectively. The activation function is a modified linear unit function (MLU). The dataset was divided into a training set and a validation set according to a preset ratio. The MLP was trained under supervision using the training set. During training, the forward propagation of the MLP to the input features was used to calculate the predicted output baseline displacement data. The difference between the predicted output baseline displacement data and the output labels was calculated using the mean squared error loss function. The weight parameters and bias parameters of the MLP were iteratively updated using the backpropagation algorithm and the Adam optimizer to gradually reduce the value of the mean squared error loss function. During training, the prediction performance of the MLP was evaluated using the validation set at preset intervals. Training was terminated when the value of the mean squared error loss function on the validation set no longer decreased in consecutive preset rounds of evaluation, resulting in the trained baseline constitutive model.

[0028] Within the preset monitoring period, displacement field operation data of the tailings dam are collected. The displacement field operation data of the tailings dam includes geotechnical test data, in-situ test data and displacement monitoring data of each monitoring point of the tailings dam. The displacement monitoring data includes horizontal displacement, vertical displacement and displacement rate.

[0029] Geotechnical test data and in-situ test data from each monitoring point in the tailings dam were input into a trained baseline constitutive model to obtain baseline displacement prediction data for each monitoring point. The baseline displacement prediction data included predicted horizontal displacement, predicted vertical displacement, and predicted displacement rate. The baseline displacement prediction data from all monitoring points were statistically analyzed and stored as baseline statistical characteristic parameters. Geotechnical test data included soil friction angle and cohesion, while in-situ test data included void ratio and permeability coefficient.

[0030] It should be added that the cohesion in the geotechnical test data directly characterizes the bonding strength between tailings material particles, and the friction angle in the geotechnical test data directly characterizes the frictional resistance between tailings material particles. The higher the bonding strength and the greater the frictional resistance, the stronger the tailings material's ability to resist shear deformation, and the smaller the predicted horizontal and vertical displacement values ​​output under the same load conditions. The void ratio in the in-situ test data directly characterizes the density of the tailings material. The larger the void ratio, the stronger the compressibility of the tailings material under load, and the larger the predicted vertical displacement value output. The permeability coefficient in the in-situ test data directly characterizes the drainage capacity of the tailings material. The larger the permeability coefficient, the faster the excess pore water pressure dissipates, and the larger the predicted displacement rate value output. The multilayer perceptron establishes a nonlinear correlation from the mechanical parameters and physical state parameters of the tailings material to the displacement response through the physical mapping relationship between the above input features and output labels.

[0031] This invention establishes a baseline constitutive model during the initial, undamaged period of a tailings dam's operation. This model ensures that the mapping between displacement and strength parameters corresponds to the initial constitutive state of the dam material. Since the dam has not yet undergone chemical erosion during this period, geotechnical test data and in-situ testing data accurately reflect the original mechanical properties and physical state of the tailings material, and displacement monitoring data accurately reflect the load response of the tailings material in its original state. Therefore, the trained baseline constitutive model can serve as a physical reference for subsequent deviation analysis.

[0032] Specifically, the method for obtaining the historical sequence of tailings dam displacement deviation by performing deviation analysis on baseline statistical characteristic parameters is as follows: The displacement monitoring data of each monitoring point in the displacement field operation data of the tailings dam is compared with the baseline displacement prediction data of the corresponding monitoring point in the baseline statistical characteristic parameters to obtain the displacement residual corresponding to each monitoring point. The displacement residual includes horizontal displacement residual, vertical displacement residual and displacement rate residual.

[0033] The displacement residuals of all monitoring points are summarized in chronological order to obtain the historical sequence of displacement deviations of the tailings dam.

[0034] When the dam body is free from chemical damage, the displacement monitoring data closely matches the baseline displacement prediction data, with the displacement residuals fluctuating randomly around zero. However, when chemical erosion causes the constitutive relation of the dam body to deviate from its initial state, the same load will produce a larger deformation response, and the displacement residuals will systematically deviate from zero. Therefore, the statistical changes in the historical sequence of displacement deviations directly point to structural changes in the constitutive relation, providing the physical basis for subsequent displacement mutation analysis to effectively identify and confirm the timing of the deviation.

[0035] Displacement abrupt change analysis was performed on the historical sequence of displacement deviation of the tailings dam to obtain the displacement abrupt change analysis results. Based on the displacement abrupt change analysis results of the tailings dam, the displacement field operation data of the tailings dam was screened to obtain the benchmark displacement data of the tailings dam.

[0036] Specifically, the method for analyzing displacement abrupt changes in the historical sequence of tailings dam displacement deviations is as follows: From the historical sequence of displacement deviations of the tailings dam, the horizontal displacement residual, vertical displacement residual, and displacement rate residual of each monitoring point of the tailings dam in the current monitoring period are extracted. A comprehensive analysis is then performed to obtain the displacement deviation characterization value corresponding to each monitoring point of the tailings dam. The displacement deviation characterization value is used to comprehensively characterize the degree to which the displacement residual of the monitoring point deviates from the baseline statistical characteristic parameters.

[0037] In this embodiment, the displacement deviation values ​​corresponding to each monitoring point in the tailings dam can be obtained through the following analysis method, with the specific analysis conditions as follows: ; In the formula, This represents the displacement deviation value corresponding to the i-th monitoring point in the tailings dam. This represents the horizontal displacement residual at the i-th monitoring point of the tailings dam. This represents the deviation influence factor corresponding to the set unit horizontal displacement residual. This represents the vertical displacement residual at the i-th monitoring point of the tailings dam. This represents the deviation influence factor corresponding to the set unit vertical displacement residual. This represents the displacement rate residual at the i-th monitoring point of the tailings dam. This represents the deviation influence factor corresponding to the set unit displacement rate residual, i=1,2,3,…,n, where i represents the monitoring point number and n represents the total number of monitoring points.

[0038] It should be added that, in this embodiment, the deviation influence factors corresponding to the unit horizontal displacement residual, the unit vertical displacement residual, and the unit displacement rate residual are obtained from the stability analysis database.

[0039] It should be explained that the deviation influence factors corresponding to the unit horizontal displacement residual, unit vertical displacement residual, and unit displacement rate residual are used to characterize the importance of the horizontal displacement residual, vertical displacement residual, and displacement rate residual at each monitoring point of the tailings dam in the process of analyzing and obtaining the displacement deviation characterization value. In the stability analysis database, there is a pre-set mapping relationship between the displacement residual and the corresponding deviation influence factor. By matching the displacement residual of each monitoring point of the tailings dam with the pre-set mapping relationship, the deviation influence factors corresponding to the unit horizontal displacement residual, unit vertical displacement residual, and unit displacement rate residual can be obtained.

[0040] In this implementation plan, the horizontal displacement residuals, vertical displacement residuals, and displacement rate residuals at each monitoring point of the tailings dam are correlated and do not exist independently. For example, the horizontal displacement residual reflects the horizontal slippage trend of the tailings dam, the vertical displacement residual reflects the vertical subsidence state of the tailings dam, and the displacement rate residual reflects the degree of deformation of the tailings dam. When the material strength inside the tailings dam decreases due to chemical erosion, the increased vertical subsidence will increase the lateral extrusion trend in the horizontal direction, causing the vertical displacement residual and the horizontal displacement residual to increase simultaneously. At the same time, the accelerated deformation rate will further increase the displacement rate residual. All three indicate that the constitutive relationship of the tailings dam has deviated from the initial setting of the baseline constitutive model. By comprehensively analyzing the displacement deviation characterization values ​​corresponding to each monitoring point of the tailings dam, it is possible to assess whether the tailings dam in the area where the monitoring point is located is in a normal evolution state consistent with the prediction of the baseline constitutive model, thereby helping to improve the accuracy of the stability analysis of the tailings dam.

[0041] Specifically, the method for obtaining the displacement abrupt change analysis results of the tailings dam is as follows: The displacement deviation characterization value corresponding to each monitoring point of the tailings dam is compared with the preset displacement deviation characterization threshold. If the displacement deviation characterization value corresponding to a certain monitoring point of the tailings dam is higher than the preset displacement deviation characterization threshold, the displacement change analysis result corresponding to that monitoring point of the tailings dam is marked as having a displacement change. If the displacement deviation characterization value corresponding to a certain monitoring point of the tailings dam is lower than or equal to the preset displacement deviation characterization threshold, the displacement change analysis result corresponding to that monitoring point of the tailings dam is marked as not having a displacement change.

[0042] Specifically, the method for obtaining the baseline displacement data of the tailings dam by filtering the displacement field operation data is as follows: When the displacement mutation analysis results of the tailings dam are marked as having a displacement mutation, the displacement field operation data of the historical monitoring period that was collected earlier than the start time of the displacement mutation and belongs to the early stage of the tailings dam operation without chemical damage is extracted from the displacement field operation data of the tailings dam. The extracted displacement field operation data is stored as the reference displacement data.

[0043] The system obtains the timestamp corresponding to the monitoring period when the displacement deviation characterization value of all monitoring points with displacement mutations first exceeds the preset displacement deviation characterization threshold in the displacement mutation analysis results. The earliest timestamp among all timestamps is recorded as the displacement mutation start time. All displacement field operation data with acquisition time earlier than the displacement mutation start time are extracted from the displacement field operation data. From the extracted displacement field operation data, displacement field operation data within the historical monitoring period range where the acquisition time belongs to the early stage of tailings dam operation and has not been chemically damaged are further extracted. The displacement field operation data after the above two extraction steps are stored as the baseline displacement data. When the displacement mutation analysis results of the tailings dam are marked as having no displacement mutation, the displacement field operation data for the next preset monitoring period is collected.

[0044] Inversion analysis was performed on the baseline displacement data of the tailings dam to obtain the baseline inversion safety factor of the tailings dam.

[0045] The physical meaning of the benchmark inversion safety factor is: the safety factor corresponding to the dam material strength parameters inverted with reference to the constitutive relationship when the tailings dam is not chemically damaged in the early stage of operation. This safety factor does not decrease with the continuous development of subsequent chemical damage, but always remains at the reference level of the initial state of the dam.

[0046] Specifically, the method for inverting and analyzing the baseline displacement data of the tailings dam is as follows: By comprehensively analyzing the geotechnical test data of each monitoring point of the tailings dam in each monitoring period, the shear strength characterization value of the tailings dam is obtained. The shear strength characterization value represents the overall shear strength level of the tailings material in the current monitoring period.

[0047] By comprehensively analyzing the in-situ test data of each monitoring point in the tailings dam during each monitoring period, the seepage deformation coefficient of the tailings dam is obtained. The seepage deformation coefficient characterizes the overall seepage deformation characteristics of the tailings material under the coupled action of seepage and load.

[0048] By comprehensively analyzing the displacement deviation values ​​corresponding to each monitoring point of the tailings dam in each monitoring period, the reference constitutive response coefficient of the tailings dam is obtained. The reference constitutive response coefficient characterizes the overall response level of the tailings dam under the reference constitutive relationship under the current external load conditions.

[0049] A weighted analysis was performed on the shear strength characterization value, seepage deformation coefficient, and benchmark constitutive response coefficient of the tailings dam to obtain the benchmark inversion safety factor of the tailings dam. The benchmark inversion safety factor of the tailings dam is used to quantify the overall stability of the tailings dam.

[0050] In this embodiment, the baseline inversion safety factor of the tailings dam can be obtained through the following analysis method, with the specific analysis conditions as follows: ; In the formula, This represents the baseline inversion safety factor of the tailings dam. This represents the shear strength characterization value of the tailings dam. This represents the weighting factor corresponding to the set shear strength characterization value. This represents the seepage deformation coefficient of the tailings dam. This represents the weighting factor corresponding to the set seepage deformation coefficient. This represents the baseline constitutive response coefficient of the tailings dam. This represents the weighting factor corresponding to the set baseline constitutive response coefficients. This represents the friction angle at the i-th monitoring point of the tailings dam during the j-th monitoring period. This represents the weighting factor corresponding to the set unit friction angle. This represents the cohesion at the i-th monitoring point of the tailings dam during the j-th monitoring period. This represents the weighting factor corresponding to the set unit cohesion. This represents the porosity of the i-th monitoring point in the tailings dam during the j-th monitoring period. This represents the weighting factor corresponding to the set porosity. This represents the permeability coefficient at the i-th monitoring point of the tailings dam during the j-th monitoring period. This represents the reference permeability coefficient at the i-th monitoring point of the tailings dam during the j-th monitoring period. This represents the weighting factor corresponding to the set permeability coefficient. Let represent the displacement deviation characterization value corresponding to the i-th monitoring point of the tailings dam in the j-th monitoring period, i=1,2,3,…,n, where i represents the number of the monitoring point and n represents the total number of monitoring points, j=1,2,3,…,m, where j represents the number of the monitoring period and m represents the total number of monitoring periods.

[0051] It should be added that, in this embodiment, the weighting factors corresponding to the preset shear strength characterization value, the seepage deformation coefficient, the reference constitutive response coefficient, the unit friction angle, the unit cohesion, the porosity, and the permeability coefficient are obtained from the stability analysis database.

[0052] It should be explained that the weighting factors corresponding to the shear strength characterization value, seepage deformation coefficient, reference constitutive response coefficient, unit friction angle, unit cohesion, void ratio, and permeability coefficient are used to characterize the importance of the reference displacement data of the tailings dam in the process of analyzing and obtaining the reference inversion safety factor. In the stability analysis database, there is a pre-defined mapping relationship between the reference displacement data and the corresponding weighting factors. By matching the reference displacement data of the tailings dam with the pre-defined mapping relationship, the weighting factors corresponding to the shear strength characterization value, seepage deformation coefficient, reference constitutive response coefficient, unit friction angle, unit cohesion, void ratio, and permeability coefficient can be obtained.

[0053] In this implementation plan, the friction angle, cohesion, void ratio, permeability coefficient, and displacement deviation values ​​at various monitoring points of the tailings dam are correlated and not independent. For example, the friction angle and cohesion together constitute the shear strength of the tailings material. When chemical erosion causes the dissolution of interparticle cement within the tailings dam, the cohesion decreases first, followed by a decrease in interparticle frictional resistance, which in turn reduces the friction angle, resulting in a decrease in the shear strength value. The dissolution of cement also alters the pore structure of the tailings material, increasing the void ratio and permeability coefficient due to enhanced pore connectivity, thus increasing the seepage deformation coefficient. The decrease in shear strength and the deterioration of the pore structure together lead to a greater deformation response of the tailings dam under the same external load conditions. The deviation between the measured displacement value and the displacement prediction value output by the baseline constitutive model intensifies, and the displacement deviation value increases accordingly. Comprehensive analysis yields the benchmark inversion safety factor of the tailings dam, which can assess the overall stability of the tailings dam under a constitutive reference without chemical damage, thereby helping to identify the extent of deterioration caused by chemical erosion to the stability of the tailings dam.

[0054] Seepage monitoring data and chemical characteristic data of the tailings dam are collected, and stability analysis is performed to obtain the real-time safety factor of the tailings dam. Stability analysis is then performed on the real-time safety factor to obtain the stability analysis results of the tailings dam.

[0055] Specifically, the methods for collecting seepage monitoring data and chemical characteristic data of tailings ponds are as follows: Seepage monitoring equipment and chemical sensor equipment were used to collect seepage monitoring data and chemical characteristic data of the tailings dam. Seepage monitoring data included seepage flow rate, permeability, and seepage velocity; chemical characteristic data included pH value, dissolved oxygen, and dissolved ion concentration.

[0056] Seepage flow rate refers to the volume of seepage water passing through a monitoring section of the tailings dam per unit time, reflecting the scale of seepage water migration within the dam body. It is measured using a measuring weir in the seepage monitoring equipment deployed at the tailings dam monitoring section, obtaining the seepage flow rate values ​​at multiple monitoring time points within the current monitoring period. The arithmetic mean is taken as the seepage flow rate for that monitoring period. Permeability refers to the inherent ability of tailings materials to allow fluid passage, reflecting the degree of conductivity of the dam material for seepage water. It is measured through on-site borehole water injection tests at each monitoring point within the current monitoring period, and the arithmetic mean is taken as the permeability for that monitoring period. Seepage velocity refers to the speed at which seepage water migrates through the pores of the tailings dam, reflecting the speed of migration of corrosive solutions within the dam body. It is calculated by dividing the seepage flow rate by the cross-sectional area, obtaining the seepage velocity values ​​at multiple monitoring time points within the current monitoring period, and the arithmetic mean is taken as the seepage velocity for that monitoring period. pH reflects the acidity or alkalinity of the seepage water. The pH value is measured at multiple monitoring time points within the current monitoring period using a hydrogen ion concentration index electrode in an electrochemical sensor deployed at a pre-set monitoring section of the tailings dam. The arithmetic mean is taken as the pH value for that monitoring period. Dissolved oxygen refers to the oxygen content dissolved in the tailings pore water, reflecting the sufficiency of oxygen available for sulfide oxidation reactions in the seepage water. The dissolved oxygen concentration is measured at multiple monitoring time points within the current monitoring period using a dissolved oxygen electrode in an electrochemical sensor. The arithmetic mean is taken as the dissolved oxygen value for that monitoring period. Dissolved ion concentration refers to the total amount of ions dissolved in the tailings pore water, reflecting the accumulation of products from chemical dissolution reactions. The dissolved ion concentration is measured at multiple monitoring time points within the current monitoring period using an ion-selective electrode in an electrochemical sensor. The arithmetic mean is taken as the dissolved ion concentration for that monitoring period.

[0057] A comprehensive analysis of seepage monitoring data and chemical characteristic data of tailings dams yields an assessment value for chemical seepage anomalies. This assessment value characterizes the strength of chemically corrosive seepage driving the degradation of dam material strength under the coupling effect of the seepage field and chemical field within the tailings dam.

[0058] In this embodiment, the chemical seepage anomaly assessment value of the tailings dam can be obtained through the following analysis method, with the specific analysis conditions as follows: ; In the formula, This indicates the assessment value of chemical seepage anomalies in the tailings dam. This indicates the seepage flow rate of the tailings dam. This represents the anomaly assessment factor corresponding to the set unit seepage flow rate. This indicates the permeability of the tailings dam. This represents the anomaly assessment factor corresponding to the set unit penetration rate. This indicates the seepage velocity of the tailings dam. This represents the anomaly assessment factor corresponding to the set unit seepage velocity. This indicates the pH value of the tailings dam. This indicates the set reference pH value. This represents the anomaly assessment factor corresponding to the set unit pH value deviation. This indicates the dissolved oxygen level in the tailings dam. This indicates the anomaly assessment factor corresponding to the set unit of dissolved oxygen. This indicates the concentration of dissolved ions in the tailings dam. This indicates the anomaly assessment factor corresponding to the set unit dissolved ion concentration.

[0059] It should be added that, in this embodiment, the following pre-defined abnormal assessment factors are obtained from the stability analysis database: abnormal assessment factor corresponding to unit seepage flow rate, abnormal assessment factor corresponding to unit permeability, abnormal assessment factor corresponding to unit seepage velocity, abnormal assessment factor corresponding to unit pH value deviation, abnormal assessment factor corresponding to unit dissolved oxygen, and abnormal assessment factor corresponding to unit dissolved ion concentration.

[0060] It should be explained that the anomaly assessment factors corresponding to unit seepage flow rate, unit permeability, unit seepage velocity, unit pH deviation, unit dissolved oxygen, and unit dissolved ion concentration are used to characterize the importance of tailings dam seepage monitoring data and chemical characteristic data in the process of analyzing and obtaining chemical seepage anomaly assessment values. In the stability analysis database, there is a pre-defined mapping relationship between seepage monitoring data and chemical characteristic data and their corresponding anomaly assessment factors. By matching the tailings dam seepage monitoring data and chemical characteristic data with the pre-defined mapping relationship, the anomaly assessment factors corresponding to unit seepage flow rate, unit permeability, unit seepage velocity, unit pH deviation, unit dissolved oxygen, and unit dissolved ion concentration can be obtained.

[0061] In this implementation plan, the seepage flow rate, permeability, seepage velocity, pH value, dissolved oxygen, and dissolved ion concentration at various monitoring points in the tailings dam are correlated and not independent. For example, there is a close relationship between seepage flow rate and permeability; the higher the permeability, the higher the seepage flow rate, which in turn affects the movement mode and speed of water within the soil or dam body. Changes in seepage velocity and permeability can affect the distribution of water within the tailings dam, alter the concentrations of dissolved oxygen and dissolved ions, and influence chemical reactions and corrosion within the tailings dam. pH value is directly related to changes in dissolved oxygen; high dissolved oxygen concentrations usually promote certain chemical reactions, thereby exacerbating the corrosion of tailings dam materials. Dissolved ion concentration is directly related to the chemical stability of the soil or tailings materials; higher dissolved ion concentrations may lead to stronger chemical erosion, thus affecting the mechanical properties of the dam materials. Comprehensive analysis yields an assessment value for the chemical seepage anomalies in the tailings dam, which can evaluate the potential impact of the coupling effect of seepage and chemical fields on the tailings dam body, thus providing an important reference for the safety and stability of the tailings dam.

[0062] Specifically, the method for obtaining the real-time safety factor of a tailings dam through stability analysis is as follows: Based on the chemical seepage anomaly assessment value of the tailings dam, the anomaly impact coefficient of the tailings dam is obtained.

[0063] The abnormal chemical seepage assessment values ​​of the tailings dam are matched with the abnormal influence coefficients corresponding to each interval of abnormal chemical seepage assessment values ​​stored in the stability analysis database. The abnormal influence coefficients corresponding to the intervals in which the abnormal chemical seepage assessment values ​​are located are statistically calculated and recorded as the abnormal influence coefficients of the tailings dam.

[0064] The product of the baseline inversion safety factor and the anomaly impact factor of the tailings dam is denoted as the real-time state safety factor of the tailings dam.

[0065] The baseline inversion safety factor of the initial state is reduced according to the activity level of the current chemical erosion environment. The result after reduction is the current real-time safety factor of the dam body under the continuous action of chemical erosion. The higher the chemical seepage anomaly assessment value, the smaller the matched anomaly influence coefficient, and the greater the reduction of the real-time safety factor relative to the baseline inversion safety factor, reflecting the more significant the deterioration effect of chemical erosion on the stability of the dam body.

[0066] It should be noted that the analysis of seepage monitoring data and chemical characteristic data of tailings dams can reflect the interaction between seepage and chemical action within the tailings dam. Especially when water flow and chemical component infiltration affect the strength of tailings dam materials, if the degree of chemical seepage anomaly in the tailings dam is large, continuing to use the original baseline inversion safety factor for subsequent analysis without timely adjustment may lead to inaccurate safety assessments, thus failing to detect potential stability risks in a timely manner, and even affecting the actual stability of the tailings dam. Chemical seepage anomalies may accelerate the deterioration of tailings dam materials, reduce their shear strength and seepage stability, and make the dam body more susceptible to the influence of external loads and hydrological changes. Therefore, it is necessary to dynamically adjust the safety factor in conjunction with the chemical seepage anomaly assessment value of the tailings dam. The higher the chemical seepage anomaly assessment value of the tailings dam, the greater the chemical erosion and seepage impact on the dam body materials, the smaller the matched anomaly impact coefficient, and the smaller the real-time state safety factor obtained from the analysis, which can reflect the potential risks of the tailings dam in a timely manner.

[0067] Specifically, the method for obtaining the stability analysis results of tailings ponds is as follows: The real-time safety factor of the tailings dam is compared with the preset real-time safety factor threshold. If the real-time safety factor of the tailings dam is higher than the preset real-time safety factor threshold, the stability analysis result of the tailings dam is marked as stable. Otherwise, the stability analysis result of the tailings dam is marked as stable, and the instability warning information is sent to the staff's mobile terminal.

[0068] It should be noted that the stability analysis method based on displacement field-seepage field-chemical field coupling inversion also includes a stability analysis database. This database stores the following factors obtained through analysis of historical data: deviation influence factor corresponding to unit horizontal displacement residual, deviation influence factor corresponding to unit vertical displacement residual, deviation influence factor corresponding to unit displacement rate residual, displacement deviation characterization threshold, reference permeability coefficient of each monitoring point in the tailings dam during each monitoring period, weight factor corresponding to shear strength characterization value, weight factor corresponding to seepage deformation coefficient, weight factor corresponding to benchmark constitutive response coefficient, weight factor corresponding to unit friction angle, weight factor corresponding to unit cohesion, weight factor corresponding to porosity, weight factor corresponding to permeability coefficient, reference pH value, anomaly assessment factor corresponding to unit seepage flow rate, anomaly assessment factor corresponding to unit permeability, anomaly assessment factor corresponding to unit seepage velocity, anomaly assessment factor corresponding to unit pH value deviation, anomaly assessment factor corresponding to unit dissolved oxygen, anomaly assessment factor corresponding to unit dissolved ion concentration, anomaly influence coefficient corresponding to each chemical seepage anomaly assessment value interval, and real-time state safety factor threshold.

[0069] It should be noted that, in this document, relational terms such as "first" and "second" are used only to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such process, method, article, or apparatus.

[0070] The preferred embodiments of the present invention disclosed above are merely illustrative of the invention. These preferred embodiments do not exhaustively describe all details, nor do they limit the invention to the specific implementations described. Clearly, many modifications and variations can be made based on the content of this specification. This specification selects and specifically describes these embodiments to better explain the principles and practical applications of the invention, thereby enabling those skilled in the art to better understand and utilize the invention.

Claims

1. A stability analysis method based on displacement field-seepage field-chemical field coupled inversion, characterized in that, include: Historical test data of tailings dams are collected, displacement field operation data of tailings dams are collected during the preset monitoring period, and baseline statistical characteristic parameters of tailings dams are obtained through comprehensive analysis. Deviation analysis of baseline statistical characteristic parameters is then performed to obtain the historical sequence of displacement deviation of tailings dams. Displacement abrupt change analysis was performed on the historical sequence of displacement deviation of the tailings dam to obtain the displacement abrupt change analysis results of the tailings dam. Based on the displacement abrupt change analysis results of the tailings dam, the displacement field operation data of the tailings dam was screened to obtain the benchmark displacement data of the tailings dam. The baseline displacement data of the tailings dam is used for inversion analysis to obtain the baseline inversion safety factor of the tailings dam. Collect seepage monitoring data and chemical characteristic data of the tailings dam, conduct stability analysis to obtain the real-time safety factor of the tailings dam, and conduct stability analysis on the real-time safety factor to obtain the stability analysis results of the tailings dam. The method for obtaining the baseline statistical characteristic parameters of the tailings dam through analysis is as follows: Based on historical test data of the tailings dam, a baseline constitutive model of the tailings dam was trained. Within the preset monitoring period, displacement field operation data of the tailings dam are collected. The displacement field operation data of the tailings dam includes geotechnical test data, in-situ test data and displacement monitoring data of each monitoring point of the tailings dam. Geotechnical test data and in-situ test data from each monitoring point of the tailings dam are input into the trained baseline constitutive model to obtain the baseline displacement prediction data of each monitoring point of the tailings dam. The baseline displacement prediction data of all monitoring points are statistically analyzed and stored as baseline statistical feature parameters. The method for analyzing displacement abrupt changes in the historical sequence of tailings dam displacement deviations is as follows: From the historical sequence of displacement deviations of the tailings dam, the horizontal displacement residual, vertical displacement residual, and displacement rate residual of each monitoring point of the tailings dam in the current monitoring period are extracted. A comprehensive analysis is then performed to obtain the displacement deviation characterization value corresponding to each monitoring point of the tailings dam. The displacement deviation characterization value is used to comprehensively characterize the degree to which the displacement residual of the monitoring point deviates from the baseline statistical characteristic parameters.

2. The stability analysis method based on displacement field-seepage field-chemical field coupled inversion according to claim 1, characterized in that, The method for obtaining the historical sequence of tailings dam displacement deviation by performing deviation analysis on baseline statistical characteristic parameters is as follows: The displacement monitoring data of each monitoring point in the displacement field operation data of the tailings dam is compared with the baseline displacement prediction data of the corresponding monitoring point in the baseline statistical characteristic parameters to obtain the displacement residual corresponding to each monitoring point. The displacement residual includes horizontal displacement residual, vertical displacement residual and displacement rate residual. The displacement residuals of all monitoring points are summarized in chronological order to obtain the historical sequence of displacement deviations of the tailings dam.

3. The stability analysis method based on displacement field-seepage field-chemical field coupled inversion according to claim 1, characterized in that, The method for obtaining the displacement mutation analysis results of the tailings dam is as follows: The displacement deviation characterization value corresponding to each monitoring point of the tailings dam is compared with the preset displacement deviation characterization threshold. If the displacement deviation characterization value corresponding to a certain monitoring point of the tailings dam is higher than the preset displacement deviation characterization threshold, the displacement change analysis result corresponding to that monitoring point of the tailings dam is marked as having a displacement change. If the displacement deviation characterization value corresponding to a certain monitoring point of the tailings dam is lower than or equal to the preset displacement deviation characterization threshold, then the displacement mutation analysis result corresponding to that monitoring point of the tailings dam will be marked as having no displacement mutation.

4. The stability analysis method based on displacement field-seepage field-chemical field coupled inversion according to claim 3, characterized in that, The method for obtaining the baseline displacement data of the tailings dam by filtering the displacement field operation data of the tailings dam is as follows: When the displacement mutation analysis results of the tailings dam are marked as having a displacement mutation, the timestamp corresponding to the monitoring period when the displacement deviation characterization value of all monitoring points with displacement mutation in the displacement mutation analysis results first exceeds the preset displacement deviation characterization threshold is obtained, and the earliest timestamp among all timestamps is recorded as the displacement mutation start time. The reference displacement data is extracted from the displacement field operation data based on the start time of the displacement mutation.

5. The stability analysis method based on displacement field-seepage field-chemical field coupled inversion according to claim 4, characterized in that, The method for inverting and analyzing the baseline displacement data of the tailings dam is as follows: By comprehensively analyzing the geotechnical test data in the benchmark displacement data, the shear strength characterization value of the tailings dam is obtained. The seepage deformation coefficient of the tailings dam is obtained by comprehensively analyzing the in-situ test data in the benchmark displacement data. The baseline constitutive response coefficients of the tailings dam are obtained by comprehensively analyzing the displacement deviation values ​​corresponding to each monitoring point in each monitoring period. A weighted analysis was performed on the shear strength characterization value, seepage deformation coefficient, and benchmark constitutive response coefficient of the tailings dam to obtain the benchmark inversion safety factor of the tailings dam. The benchmark inversion safety factor of the tailings dam is used to quantify the overall stability of the tailings dam.

6. The stability analysis method based on displacement field-seepage field-chemical field coupled inversion according to claim 1, characterized in that, The method for collecting seepage monitoring data and chemical characteristic data of tailings ponds is as follows: Collect seepage monitoring data and chemical characteristic data of the tailings dam; Seepage monitoring data includes seepage flow rate, permeability, and seepage velocity; Chemical characteristic data include pH value, dissolved oxygen, and dissolved ion concentration.

7. The stability analysis method based on displacement field-seepage field-chemical field coupled inversion according to claim 6, characterized in that, The method for obtaining the real-time safety factor of the tailings dam through stability analysis is as follows: A comprehensive analysis of seepage monitoring data and chemical characteristic data of the tailings dam is conducted to obtain the chemical seepage anomaly assessment value of the tailings dam; Based on the chemical seepage anomaly assessment value of the tailings dam, the anomaly impact coefficient of the tailings dam is obtained. The product of the baseline inversion safety factor and the anomaly impact factor of the tailings dam is denoted as the real-time state safety factor of the tailings dam.

8. The stability analysis method based on displacement field-seepage field-chemical field coupled inversion according to claim 7, characterized in that, The method for obtaining the stability analysis results of the tailings dam is as follows: The real-time safety factor of the tailings dam is compared with the preset real-time safety factor threshold. If the real-time safety factor of the tailings dam is higher than the preset real-time safety factor threshold, the stability analysis result of the tailings dam is marked as stable. Otherwise, the stability analysis result of the tailings dam is marked as stable, and the instability warning information is sent to the staff's mobile terminal.

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