Potential response real-time detection system and method for leakage source of carbon dioxide storage in mine

Abstract

The application discloses a kind of real-time detection system and method of potential response of mine carbon dioxide storage leakage source, the system includes filling simulation pressure-bearing system, potential acquisition system, air charging exhaust system.The application simulates actual carbon dioxide storage stage, maintenance stage under laboratory conditions, electrode is arranged on the surface of filling body and the wall surface of rock inner cavity, real-time monitoring potential signal, extracts the time series of potential fluctuation amplitude at different potential measuring points, interpolates rock wall and filling body space using inverse distance weighted interpolation method, adds time window to the time series of potential fluctuation amplitude of each space position, and is processed using fuzzy C means clustering method, realizes the potential anomaly induction and accurate identification of hidden leakage source during carbon dioxide filling and maintenance.The application is simple to operate, and monitoring effect is good, can realize the effective monitoring of rock mass stress damage and the accurate positioning of gas leakage source position without affecting the effect of carbon dioxide storage.

Description

Technical Field

[0001] This invention relates to the field of roadway surrounding rock stabilization technology, specifically to a real-time potential response detection system and method for a carbon dioxide sequestration leakage source in a mine. Background Technology

[0002] With increasing carbon emissions, global warming, rising sea levels, and a series of other problems have had a severe and far-reaching impact on human survival. Therefore, many countries have adopted carbon dioxide sequestration measures to achieve the development goal of "carbon peaking and carbon neutrality." How to achieve long-term and stable carbon dioxide sequestration, as well as safe and efficient monitoring and early warning during the sequestration maintenance period, has become a hot research topic. In recent years, mining activities have generated many abandoned mines. These abandoned mines are generally located hundreds or even thousands of meters underground. Their collapsed goaf areas have a large number of pores and fractures, containing alkaline salt solutions that can adsorb and dissolve carbon dioxide, providing a good sealed space for carbon dioxide storage. Mine carbon dioxide sequestration technology is considered to have great potential and has been successfully applied in coal mines. However, the sequestration effect and monitoring of stable status are crucial during the sequestration maintenance phase. Previously, indicators such as temperature, pH value, and acoustic emission were commonly used as effective means of monitoring the carbon dioxide sequestration status. Although these monitoring methods can respond to anomalies in the sequestration status, they are easily affected by the environment and often cannot provide timely and effective predictive information. Therefore, there is an urgent need to research new monitoring methods to supplement the shortcomings of existing methods.

[0003] Spontaneous potential (SP) is a reliable monitoring method that can receive important information such as rock damage and fracture, and water content. At the source of carbon dioxide leakage, the flow of gas causes carbon dioxide to displace water in the surrounding coal and rock mass, changing the liquid-to-gas ratio in the pores and fractures of the coal and rock mass. SP can respond significantly to this change and can therefore be used for monitoring carbon dioxide sequestration. Currently, in terms of indoor experimental research, there are very few experimental systems available for simulating leakage conditions during carbon dioxide sequestration in coal mines, and these systems cannot realistically simulate the actual mining environment. Summary of the Invention

[0004] To address the aforementioned technical problems, this invention provides a real-time detection system and method for the potential response of leakage sources in mine carbon dioxide sequestration based on natural electrical signals.

[0005] To achieve the above-mentioned technical objectives, the present invention adopts the following technical solution: A real-time potential response detection system for a carbon dioxide sequestration leakage source in a mine includes a filling simulation pressure system, a potential acquisition system, and a filling and venting system. The filling simulation pressure system includes a pressure cylinder with an opening at the right end, a sealing cover at the right end of the pressure cylinder, a rock with a cavity inside the pressure cylinder, gravel inside the cavity, an opening at one end of the rock, a filler at the opening end of the rock, a notch on the filler for simulating a leakage channel, and a pressure plate at the top of the pressure cylinder that can apply stress to the rock. The potential acquisition system includes a potential acquisition instrument, a positive electrode, a negative electrode, and a shielded twisted pair cable. The positive electrodes are arranged in an array on the inner and outer surfaces of the filler and the wall of the rock cavity. The negative electrode is placed on the outer surface of the filler. Both the positive and negative electrodes are connected to the shielded twisted pair cable, which passes through a through hole in the sealing cover and is connected to the potential acquisition instrument. The inflation and deflation system includes a carbon dioxide cylinder, a waste gas recovery cylinder, a main pipeline, a first branch pipeline, a second branch pipeline, a third branch pipeline, and a fourth branch pipeline. A pressure gauge is installed on the carbon dioxide cylinder. One end of the main pipeline is connected to the waste gas recovery cylinder, and the other end is connected to the first branch pipeline. The first branch pipeline passes through a through-hole on the sealing cap and connects to a notch. One end of the second branch pipeline is connected to the main pipeline, and the other end passes through the left side wall of the pressure cylinder. One end of the third branch pipeline is connected to the main pipeline, and the other end passes through the left side wall of the pressure cylinder and the rock. One end of the fourth branch pipeline is connected to the carbon dioxide cylinder, and the other end is connected to the third branch pipeline. The second branch pipeline is equipped with a first suction pump and a third valve. The end of the main pipeline near the waste gas recovery cylinder is equipped with a second valve. The fourth branch pipeline is equipped with a first valve. The third branch pipeline is equipped with a second suction pump and a pressure sensor. The first branch pipeline is equipped with a micro-adjustment valve.

[0006] Preferably, the pressure cylinder and the sealing cover are bolted together to maintain the airtightness of the pressure cylinder.

[0007] Preferably, an insulating plate is provided at the bottom of the pressure plate.

[0008] Preferably, the gaps between the shielded twisted pair cable and the through hole, and the gaps between the first branch pipe and the through hole are sealed with glue to maintain the airtightness of the pressure cylinder.

[0009] This invention also provides a detection method for a real-time potential response detection system for carbon dioxide sequestration leakage sources in mines, comprising: S1: Immerse the rock, gravel, and filler in a salt solution with a concentration of 0.1 mol / L to 2 mol / L until completely saturated. Then, remove the rock and place it in a pressure cylinder, and place the gravel in the cavity. Arrange a positive electrode array on the inner and outer surfaces of the filler and the wall of the rock cavity. The positive electrode positions serve as potential measurement points. Arrange a negative electrode on the outer surface of the filler. Use polyurethane sealing agent to fill the gap between the filler and the rock. Connect the pressure cylinder and the sealing cover to maintain the airtightness of the pressure cylinder. S2: Background stress is applied to the rock through the pressure plate, and the potential acquisition instrument records the potential value at each potential measuring point as the potential value of the rock under natural deformation. S3: Apply a preset stress to the rock using a pressure plate, open the first valve, and close the second and third valves and the micro-adjustment valve to fill the cavity with carbon dioxide. The process of filling the cavity with carbon dioxide is the sealing stage. The gas pressure in the cavity is observed by a pressure sensor. When the carbon dioxide pressure in the cavity reaches 5MPa, the first valve is closed to stop filling the cavity with carbon dioxide and enter the maintenance stage. The potential acquisition instrument records the change response of the potential signal in real time during the sealing stage and the maintenance stage. S4: The potential acquisition instrument analyzes the intensity changes of the potential signal in real time during the sealing and maintenance stages, and draws a two-dimensional potential response cloud map. If the potential intensity value drops to less than the alarm threshold, it indicates that there is a risk of gas leakage. S5: Open the second valve and the micro-adjustment valve. The carbon dioxide gas in the cavity enters the waste gas recovery cylinder through the gap and the first branch pipe, simulating a natural leakage state. S6: Extract the characteristic parameters of the potential signals recorded in real time from all potential measurement points, and calculate the potential fluctuation amplitude A. V Potential fluctuation amplitude A V The calculation formula is as follows: In the formula, For the first f The potential intensity at time +1 For the first f The potential intensity at a given time; S7: The inverse distance weighted interpolation method is used to predict the unknown characteristic parameter values ​​of the two-dimensional space of the rock wall and the three-dimensional space of the filling body to obtain a two-dimensional or three-dimensional potential distribution map. The time series of potential fluctuation amplitude at each spatial location is divided into multiple sub-time series through time windows, and the spatial components are combined to obtain sub-spatiotemporal sequences. The fuzzy C-means clustering method is used to analyze the sub-spatiotemporal sequences in different time windows and obtain the cluster center and membership matrix of each time window. The anomaly value of each sub-spatiotemporal sequence is obtained by comparing it with the data of the previous normal operation state. Then, according to the membership matrix, each cluster in the time window is assigned a relative anomaly value. The magnitude of the relative anomaly value of the subordinate cluster in the time window to be measured at different spatial locations can be used to judge whether the filling rock mass is in a normal state. The average relative anomaly probability value of the time window cluster at any spatial location is calculated to draw a two-dimensional or three-dimensional potential spatial anomaly probability distribution map under real-time acquisition state. S8: Replace the rock or change the stress value applied to the rock by the pressure plate, and repeat steps S1-S7; S9: After the test, open the second valve, the third valve, the first air pump, and the second air pump, and close the micro-adjustment valve to extract all the gas in the simulated pressure system into the waste gas recovery cylinder to avoid environmental pollution. Then, remove the rock and the filling material, and compare the abnormal area identified in step S7 with the damage and leakage location on the rock and the filling material. Based on the two-dimensional or three-dimensional potential space anomaly probability distribution image drawn according to the potential fluctuation amplitude spatiotemporal sequence, the quality assessment of the sealed rock mass can be effectively monitored and warned.

[0010] Preferably, in step S5, the specific steps for calculating the sub-spatiotemporal sequence are as follows: Time series of potential fluctuation amplitude T A As the temporal component of the fuzzy C-means clustering method, it is combined with its spatial component to form a spatiotemporal sequence. Q A ={ q 1, q 2,……, q N}, for the first i Spatiotemporal data of potential signals q i Its expression is: in, q i ( s )and q i ( t These represent the spatial and temporal components of the data, respectively. q ia ( s ) is the first i The first data space component a Each component element a =2 represents a two-dimensional space. a =3 represents three-dimensional space. q ib ( t ) is the first i The first data time component b Each component element; spatiotemporal sequences Q A Adding a time window allows you to obtain the sub-time sequence; the time window length can be set to... L If we take the unit duration, then the first... m The time dimension in each time window is [(( m -1)* L +1),( m * L )], No. m The first time windowi Spatiotemporal data of potential signals q i sub-space sequence q im The expression is: .

[0011] Preferably, in step S5, the calculation process of the fuzzy C-means clustering method specifically includes: The Lagrange multiplier method is used to find the minimum value of the objective function for fuzzy C-means clustering, thus obtaining the cluster centers. The expression for the objective function, by introducing the Lagrange multiplier λ, is as follows: In the formula, e The number of clusters in the clustering. C The number of cluster centers. N For the sample size, c i For the first i Cluster centers, membership matrix u ij spatiotemporal data q j For the i Cluster centers c i membership degree To represent data similarity using Euclidean distance, , x For the proportion of time components, c i (s) is the first i Spatial components corresponding to each cluster center c i (t) is the th i The time component corresponding to each cluster center; The partial derivative of the objective function is used to obtain the first... i Cluster centers c i and membership matrix u ij The calculation formula is: In the formula, c r For the first r There are cluster centers, and 1 ≤ r ≤ C ; Set error threshold e The objective function is iterated until the termination condition is met, at which point the iteration stops. In the formula, For the first t The +1th iteration obtained i Cluster centers, c For the first t The first iteration obtained i Cluster centers; Using the obtained cluster centers and membership matrices to analyze the spatiotemporal data of the potential signal q i Reassigning values ​​yields reconstructed spatiotemporal data. : The clustering effect is evaluated using the recombination error E(ξ), and the value of ξ that minimizes this error is found: Define the spatiotemporal data of the i-th potential signal q i In the time window W m Sub-space sequence q im For the data to be detected, the sub-spatiotemporal sequence is calculated using the following formula. q im Relative anomaly value: In the formula, or im For the first m The relative anomaly value of the i-th potential signal sub-spatiotemporal sequence in a time window, 1≤ k ≤ m -1, W k Indicates time window W m A previous time window, an upcoming time window W m Sub-spatiotemporal sequences to be detected q im The sub-space-time sequence that was in a normal or working state before q ik Comparison, through relative anomaly values or im Determine whether the rock face and filling material are in normal condition during a certain period of the sealing and maintenance period; Further on the time window W m The relative outlier value corresponding to each cluster center in the data. f r (r=1,…, c j) Perform calculations and standardization, that is, process the time window W m The weighted average of the relative anomaly values ​​corresponding to each subsequence in the data is calculated using the following formula: when f r The larger the value, the larger the time window. W m subordinate number r A higher relative outlier in a subsequence of a class indicates a greater likelihood of potential hazards in the rock face and infill, and vice versa; setting an alarm threshold. F =0.8, when f r ≥ F An alarm will sound if the filling material is leaking abnormally.

[0012] Preferably, in step S5, the two-dimensional spatial components of the rock wall ( x p , y p ) or the three-dimensional spatial components of the infill ( x k , y k , z k The time window of the potential signal time series acquired at point ) W m The average relative outlier probability value of all cluster centers i m The calculation formula is: Assigning vectors of relative anomaly probability values ​​at any location in space The following formula can be used to plot the real-time two-dimensional or three-dimensional potential space anomaly probability distribution: Time window W m Sub-spatiotemporal sequence data to be detected q im This represents the latest spatiotemporal data collected in real time from the time series of potential fluctuation amplitude.

[0013] Compared with the prior art, the beneficial effects of the present invention are as follows: 1. The real-time potential response detection system and method for carbon dioxide sequestration leakage sources in mines of the present invention, by using a real-time leakage source detection system in the laboratory, can apply pressure to the rock mass and add air pressure to its interior, realistically simulating the environmental conditions for carbon dioxide sequestration in the goaf of a mine, overcoming the previous limitation that it was impossible to pressurize the rock cavity in the laboratory; by utilizing the natural potential characteristics of the leakage state during the carbon dioxide sequestration process and maintenance stage, contact-type natural potential monitoring can be performed, which can monitor the sequestration effect of coal and rock mass and filling body in real time, resist the interference of complex mining environment, and evaluate the sequestration effect and identify leakage in the goaf of a mine without affecting the carbon dioxide sequestration effect.

[0014] 2. This invention can be used to simulate the stability monitoring of sealing under different uniaxial loading schemes and prefabricated leakage gap conditions in the laboratory, and can also be directly applied to the sealing project of the goaf in the mine on site to monitor the stability of the sealing area in real time and identify the leakage channel.

[0015] 3. This invention uses natural potential signals to monitor leakage accidents in real time during the carbon dioxide sequestration process and maintenance phase, realizing monitoring and early warning of the entire carbon dioxide sequestration cycle in mines. The real-time recorded natural potential signals can accurately locate the carbon dioxide leakage location and leakage path, providing strong support for the quality assessment of carbon dioxide sequestration and early warning of leakage hazards.

[0016] 4. This invention adds a time window to the time series of potential fluctuation amplitudes and processes it using fuzzy C-means clustering to accurately identify and promptly warn of hidden leakage sources during carbon dioxide filling and maintenance. By characterizing and judging the evolution process of abnormal states through real-time two-dimensional or three-dimensional potential space anomaly probability distribution maps drawn based on membership matrices, the invention visualizes disaster state data and improves the accuracy of hazardous area identification. Attached Figure Description

[0017] To more clearly illustrate the technical solutions of the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.

[0018] Figure 1 This is a schematic diagram of a real-time potential response detection system for a mine carbon dioxide sequestration leakage source based on natural electrical signals.

[0019] Figure 2 This is a schematic diagram of the rock structure.

[0020] In the diagram: 1-Rock, 2-Filling material, 3-Cavity, 4-Notch, 5-Positive electrode, 6-Negative electrode, 7-Carbon dioxide cylinder, 8-Pressure gauge, 9-Crushed stone, 10-Waste gas recovery cylinder, 11-Micro-regulating valve, 12-Pressure cylinder, 13-Sealing cap, 14-Pressure sensor, 15-Pressure plate, 16-Main pipeline, 17-First branch pipeline, 18-Second branch pipeline, 19-Third branch pipeline, 20-Fourth branch pipeline, 21-Potential acquisition instrument, 23-First vacuum pump, 24-Second vacuum pump, 25-Shielded twisted pair cable, 26-Through hole, 27-Through pipe hole, 28-First valve, 29-Second valve, 30-Third valve. Detailed Implementation

[0021] The specific embodiments of the present invention will be further described below with reference to the accompanying drawings.

[0022] like Figure 1-2As shown, a real-time potential response detection system for a carbon dioxide sequestration leakage source in a mine includes a filling simulation pressure-bearing system, a potential acquisition system, and a filling and venting system. The filling simulation pressure-bearing system includes a pressure-bearing cylinder 12 with an opening at the right end. A sealing cover 13 is provided at the right end of the pressure-bearing cylinder 12. The pressure-bearing cylinder 12 and the sealing cover 13 are bolted together to maintain the airtightness of the pressure-bearing cylinder 12. The pressure-bearing cylinder 12 contains a rock 1 with a cavity 3, and the cavity 3 contains crushed stone 9. One end of the rock 1 is open, and a filler 2 is provided at the open end of the rock 1. The filler 2 is provided with a device for simulating leakage. The gap 4 in the channel, the upper part of the pressure cylinder 12 is provided with a pressure plate 15 that can apply stress to the rock 1 to simulate the geostress environment; the bottom of the pressure plate 15 is provided with an insulating plate; the potential acquisition system includes a potential acquisition instrument 21, a positive electrode 5, a negative electrode 6, and a shielded twisted pair cable 25. The positive electrode 5 is arranged in an array on the inner surface, outer surface of the filling body 2 and the wall of the inner cavity of the rock 1. The negative electrode 6 is set on the outer surface of the filling body 2. Both the positive electrode 5 and the negative electrode 6 are connected to the shielded twisted pair cable 25. The shielded twisted pair cable 25 passes through the through hole 26 provided on the sealing cover 13 and is connected to the electric current. The position acquisition device 21 is connected. The inflation and deflation system includes a carbon dioxide cylinder 7, a waste gas recovery cylinder 10, a main pipe 16, a first branch pipe 17, a second branch pipe 18, a third branch pipe 19, and a fourth branch pipe 20. A pressure gauge 8 is installed on the carbon dioxide cylinder 7. One end of the main pipe 16 is connected to the waste gas recovery cylinder 10, and the other end is connected to the first branch pipe 17. The first branch pipe 17 passes through the through hole 27 provided on the sealing cover 13 and connects to the notch 4. One end of the second branch pipe 18 is connected to the main pipe 16, and the other end passes through the left side wall of the pressure cylinder 12. One end of the third branch pipe 19 is connected to the main pipe 16, and the other end passes through the pressure cylinder 12 and the left side wall of the rock 1. One end of the fourth branch pipe 20 is connected to the carbon dioxide cylinder 7, and the other end is connected to the third branch pipe 19. The second branch pipe 18 is equipped with a first suction pump 23 and a third valve 30. The end of the main pipe 16 near the waste gas recovery cylinder 10 is equipped with a second valve 29. The fourth branch pipe 20 is equipped with a first valve 28. The third branch pipe 19 is equipped with a second suction pump 24 and a pressure sensor 14. The first branch pipe 17 is equipped with a micro-adjustment valve 11. The gaps between the shielded twisted pair cable 25 and the through hole 26, and between the first branch pipe 17 and the through hole 27, are sealed with glue to maintain the airtightness of the pressure cylinder 12.

[0023] This invention also provides a detection method for a real-time potential response detection system for carbon dioxide sequestration leakage sources in mines, comprising: S1: Immerse the rock 1, crushed stone 9 and filler 2 in a salt solution with a concentration of 0.1mol / L~2mol / L until completely saturated. Then, remove the rock 1 and place it in the pressure cylinder 12. Place the crushed stone 9 in the cavity 3. The crushed stone 9 simulates the environment of a real goaf. Arrange an array of positive electrodes 5 on the inner and outer surfaces of the filler 2 and the wall of the inner cavity of the rock 1. The positions of the positive electrodes 5 serve as potential measuring points. Arrange negative electrodes 6 on the outer surface of the filler 2. Use polyurethane sealing agent to fill the gap between the filler 2 and the rock 1. Connect the pressure cylinder 12 and the sealing cover 13 to maintain the airtightness of the pressure cylinder 12. S2: Background stress is applied to rock 1 through pressure plate 15, and potential acquisition instrument 21 records the potential value at each potential measuring point as the potential value of rock 1 bearing deformation under natural conditions. S3: Apply a preset stress to the rock 1 through the pressure plate 15, open the first valve 28, close the second valve 29, the third valve 30, and the micro-adjustment valve 11 to fill the cavity 3 with carbon dioxide. The process of filling the cavity 3 with carbon dioxide is the sealing stage. The pressure sensor 14 observes the gas pressure in the cavity 3. When the carbon dioxide pressure in the cavity 3 reaches 5MPa, close the first valve 28 to stop filling the carbon dioxide and enter the maintenance stage. The potential acquisition instrument 21 records the change response of the potential signal in real time during the sealing stage and the maintenance stage. S4: The potential acquisition instrument 21 analyzes the intensity changes of the potential signal in real time during the sealing and maintenance stages, and draws a two-dimensional potential response cloud map. The flow of air will replace the moisture in the surrounding rock mass and cause changes in the potential signal. If the potential intensity value drops to less than the alarm threshold, it indicates that there is a risk of gas leakage. S5: Open the second valve 29 and the micro-adjustment valve 11. The carbon dioxide gas in the cavity 3 enters the waste gas recovery cylinder 10 through the gap 4 and the first branch pipe 17, simulating a natural leakage state. S6: Extract the characteristic parameters of the potential signals recorded in real time from all potential measurement points, and calculate the potential fluctuation amplitude A. V Potential fluctuation amplitude A V The calculation formula is as follows: In the formula, Let be the potential intensity at time i+1. Let be the potential intensity at time i; S7: The inverse distance weighted interpolation method is used to predict the unknown characteristic parameter values ​​of the two-dimensional space of the rock wall and the three-dimensional space of the filling body to obtain a two-dimensional or three-dimensional potential distribution map. The time series of potential fluctuation amplitude at each spatial location is divided into multiple sub-time series through time windows, and the spatial components are combined to obtain sub-spatiotemporal sequences. The fuzzy C-means clustering method is used to analyze the sub-spatiotemporal sequences in different time windows and obtain the cluster center and membership matrix of each time window. The anomaly value of each sub-spatiotemporal sequence is obtained by comparing it with the data of the previous normal operation state. Then, according to the membership matrix, each cluster in the time window is assigned a relative anomaly value. The magnitude of the relative anomaly value of the subordinate cluster in the time window to be measured at different spatial locations can be used to judge whether the filling rock mass is in a normal state. The average relative anomaly probability value of the time window cluster at any spatial location is calculated to draw a two-dimensional or three-dimensional potential spatial anomaly probability distribution map under real-time acquisition state. S8: Replace rock 1 or change the stress value applied to rock 1 by pressure plate 15, and repeat steps S1-S7; S9: After the test, open the second valve 29, the third valve 30, the first air pump 23, and the second air pump 24, and close the micro-adjustment valve 11. All the gas in the simulated pressure system is pumped into the waste gas recovery cylinder 10 to avoid environmental pollution. Then, take out the rock 1 and the filling body 2, and compare the abnormal area identified in step S7 with the damage and leakage locations on the rock 1 and the filling body 2. Based on the two-dimensional or three-dimensional potential space anomaly probability distribution image drawn according to the potential fluctuation amplitude spatiotemporal sequence, the quality assessment of the sealed rock mass can be effectively monitored and warned.

[0024] The specific steps for calculating the sub-spatiotemporal sequence are as follows: Time series of potential fluctuation amplitude T A As the temporal component of the fuzzy C-means clustering method, it is combined with its spatial component to form a spatiotemporal sequence. Q A ={q1,q2,……,q N}, for the i-th potential signal spatiotemporal data q i Its expression is: Where, q i (s) and q i (t) represents the spatial and temporal components of the data, respectively, and q ia (s) represents the a-th component of the i-th data spatial component, where a=2 represents two-dimensional space, a=3 represents three-dimensional space, and q ib (t) is the b-th component of the i-th data time component; spatiotemporal sequences Q AAdding time windows yields sub-time sequences. Setting the time window length to L and taking a unit duration, the time dimension of the m-th time window is [(( m -1)* L +1),( m * L [)], the spatiotemporal data q of the i-th potential signal in the m-th time window i subspace sequence q im The expression is: .

[0025] The calculation process of the fuzzy C-means clustering method specifically includes: The Lagrange multiplier method is used to find the minimum value of the objective function for fuzzy C-means clustering, thus obtaining the cluster centers. The expression for the objective function, by introducing the Lagrange multiplier λ, is as follows: In the formula, e The number of clusters in the clustering. C The number of cluster centers. N For the sample size, c i For the first i Cluster centers, membership matrix u ij spatiotemporal data q j For the i Cluster centers c i membership degree To represent data similarity using Euclidean distance, , x For the proportion of time components, c i (s) is the first i Spatial components corresponding to each cluster center c i (t) is the th i The time component corresponding to each cluster center; The partial derivative of the objective function is used to obtain the first... i Cluster centers c i and membership matrix u ij The calculation formula is: In the formula, c r For the first r There are cluster centers, and 1 ≤ r ≤ C ; Set error threshold e The objective function is iterated until the termination condition is met, at which point the iteration stops. In the formula, For the first t The +1th iteration obtained i Cluster centers, c For the first t The first iteration obtained i Cluster centers; Using the obtained cluster centers and membership matrices to analyze the spatiotemporal data of the potential signal q i Reassigning values ​​yields reconstructed spatiotemporal data. : The clustering effect is evaluated using the recombination error E(ξ), and the value of ξ that minimizes this error is found: Define the spatiotemporal data of the i-th potential signal q i In the time window W m Sub-space sequence q im For the data to be detected, the sub-spatiotemporal sequence is calculated using the following formula. q im Relative anomaly value: In the formula, or im For the first m The relative anomaly value of the i-th potential signal sub-spatiotemporal sequence in a time window, 1≤ k ≤ m -1, W k Indicates time window W m A previous time window, an upcoming time window W m Sub-spatiotemporal sequences to be detected q im The sub-space-time sequence that was in a normal or working state before q ik Comparison, through relative anomaly values or im Determine whether the rock face and filling material are in normal condition during a certain period of the sealing and maintenance period; Further on the time window W mThe relative outlier value corresponding to each cluster center in the data. f r (r=1,…, c j ) Perform calculations and standardization, that is, process the time window W m The weighted average of the relative anomaly values ​​corresponding to each subsequence in the data is calculated using the following formula: when f r The larger the value, the larger the time window. W m subordinate number r A higher relative outlier in a subsequence of a class indicates a greater likelihood of potential hazards in the rock face and infill, and vice versa; setting an alarm threshold. F =0.8, when f r ≥ F An alarm will sound if the filling material is leaking abnormally.

[0026] Two-dimensional spatial components of the rock wall ( x p , y p ) or the three-dimensional spatial components of the infill ( x k , y k , z k The time window of the potential signal time series acquired at point ) W m The average relative outlier probability value of all cluster centers i m The calculation formula is: Assigning vectors of relative anomaly probability values ​​at any location in space The following formula can be used to plot the real-time two-dimensional or three-dimensional potential space anomaly probability distribution: Time window W m Sub-spatiotemporal sequence data to be detected q im This represents the latest spatiotemporal data collected in real time from the time series of potential fluctuation amplitude.

[0027] The above description is merely a specific embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the technical scope disclosed in the present invention should be included within the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be determined by the scope of the claims.

Claims

1. A real-time potential response detection system for a carbon dioxide sequestration leakage source in a mine, comprising a filling simulation pressure system, a potential acquisition system, and a filling and venting system, characterized in that: The filling simulation pressure system includes a pressure cylinder (12) with an opening at the right end. The pressure cylinder (12) has a sealing cover (13) at the right end. The pressure cylinder (12) has a rock (1) with a cavity (3) inside. The cavity (3) has gravel (9) inside. One end of the rock (1) is open. The open end of the rock (1) has a filler (2). The filler (2) has a notch (4) for simulating a leakage channel. The pressure cylinder (12) has a pressure plate (15) on the upper part that can apply stress to the rock (1). The potential acquisition system includes a potential acquisition device (21), a positive electrode (5), a negative electrode (6), and a shielded twisted pair cable (25). The positive electrode (5) is arranged in an array on the inner surface, outer surface, and inner wall of the rock (1) cavity of the filling body (2). The negative electrode (6) is set on the outer surface of the filling body (2). Both the positive electrode (5) and the negative electrode (6) are connected to the shielded twisted pair cable (25). The shielded twisted pair cable (25) passes through the through hole (26) provided on the sealing cover (13) and is connected to the potential acquisition device (21). The inflation and deflation system includes a carbon dioxide cylinder (7), a waste gas recovery cylinder (10), a main pipeline (16), a first branch pipeline (17), a second branch pipeline (18), a third branch pipeline (19), and a fourth branch pipeline (20). The carbon dioxide cylinder (7) is equipped with a pressure gauge (8). One end of the main pipeline (16) is connected to the waste gas recovery cylinder (10), and the other end is connected to the first branch pipeline (17). The first branch pipeline (17) passes through the through hole (27) provided on the sealing cap (13) and is connected to the notch (4). One end of the second branch pipeline (18) is connected to the main pipeline (16), and the other end passes through the left side wall of the pressure cylinder (12). The third branch pipeline... (19) One end is connected to the main pipeline (16), and the other end passes through the pressure cylinder (12) and the left side wall of the rock (1). One end of the fourth branch pipeline (20) is connected to the carbon dioxide cylinder (7), and the other end is connected to the third branch pipeline (19). The second branch pipeline (18) is equipped with a first air pump (23) and a third valve (30). The end of the main pipeline (16) near the waste gas recovery cylinder (10) is equipped with a second valve (29). The fourth branch pipeline (20) is equipped with a first valve (28). The third branch pipeline (19) is equipped with a second air pump (24) and a pressure sensor (14). The first branch pipeline (17) is equipped with a micro-adjustment valve (11).

2. The real-time potential response detection system for carbon dioxide sequestration leakage sources in mines according to claim 1, characterized in that, The pressure cylinder (12) and the sealing cover (13) are bolted together to maintain the airtightness of the pressure cylinder (12).

3. The real-time potential response detection system for carbon dioxide sequestration leakage sources in mines according to claim 1, characterized in that, An insulating plate is provided at the bottom of the pressure plate (15).

4. The real-time potential response detection system for carbon dioxide sequestration leakage sources in mines according to claim 1, characterized in that, The gaps between the shielded twisted pair cable (25) and the through hole (26), and between the first branch pipe (17) and the through hole (27) are sealed with glue to maintain the airtightness inside the pressure cylinder (12).

5. The detection method of the real-time potential response detection system for leakage sources in mine carbon dioxide sequestration as described in any one of claims 1-4, characterized in that, include: S1: Immerse the rock (1), gravel (9) and filler (2) with the cavity into a salt solution with a concentration of 0.1mol / L~2mol / L until completely saturated. Then take out the rock (1) and put it into the pressure cylinder (12). Place the gravel (9) in the cavity (3). Arrange a positive electrode (5) array on the inner and outer surfaces of the filler (2) and the wall of the inner cavity of the rock (1). The position of the positive electrode (5) is used as a potential measuring point. Arrange a negative electrode (6) on the outer surface of the filler (2). Use polyurethane sealing agent to fill the gap between the filler (2) and the rock (1). Connect the pressure cylinder (12) and the sealing cover (13) to maintain the airtightness of the pressure cylinder (12). S2: Background stress is applied to the rock (1) by the pressure plate (15), and the potential acquisition instrument (21) records the potential value at each potential measuring point as the potential value of the rock (1) under natural deformation. S3: Apply a preset stress to the rock (1) through the pressure plate (15), open the first valve (28), close the second valve (29), the third valve (30), and the micro-adjustment valve (11) to fill the cavity (3) with carbon dioxide. The process of filling the cavity (3) with carbon dioxide is the sealing stage. Observe the gas pressure in the cavity (3) through the pressure sensor (14). When the carbon dioxide gas pressure in the cavity (3) reaches 5MPa, close the first valve (28) to stop filling with carbon dioxide and enter the maintenance stage. The potential acquisition instrument (21) records the change response of the potential signal in the sealing stage and the maintenance stage in real time. S4: The potential acquisition instrument (21) analyzes the intensity change of the potential signal in the sealing and maintenance stages in real time and draws a two-dimensional potential response cloud map. If the potential intensity value drops to less than the alarm threshold, it indicates that there is a risk of gas leakage. S5: Open the second valve (29) and the micro-adjustment valve (11). The carbon dioxide gas in the cavity (3) enters the waste gas recovery cylinder (10) through the gap (4) and the first branch pipe (17) to simulate the natural leakage state. S6: Extract the characteristic parameters of the potential signals recorded in real time from all potential measurement points, and calculate the amplitude of potential fluctuations. A V Potential fluctuation amplitude A V The calculation formula is as follows: In the formula, For the first f The potential intensity at time +1 For the first f The potential intensity at a given time; S7: The inverse distance weighted interpolation method is used to predict the unknown characteristic parameter values ​​of the two-dimensional space of the rock wall and the three-dimensional space of the filling body to obtain two-dimensional or three-dimensional potential distribution maps. The time series of potential fluctuation amplitude at each spatial location is divided into multiple sub-time series through time windows, and the spatial components are combined to obtain sub-spatiotemporal sequences. The fuzzy C-means clustering method is used to analyze the sub-spatiotemporal sequences in different time windows and obtain the cluster center and membership matrix of each time window. The anomaly value of each sub-spatiotemporal sequence is obtained by comparing it with the data of the previous normal operation state. Then, according to the membership matrix, each cluster in the time window is assigned a relative anomaly value. The relative anomaly value of the subordinate clusters in the time window to be tested at different spatial locations can be used to determine whether the filling rock mass is in a normal state. Calculate the average relative anomaly probability value of time window clustering at any spatial location, and then draw a two-dimensional or three-dimensional potential spatial anomaly probability distribution map under real-time acquisition conditions; S8: Replace the rock (1) or change the stress value applied to the rock (1) by the pressure plate (15), and repeat steps S1-S7; S9: After the test, open the second valve (29), the third valve (30), the first air pump (23), and the second air pump (24), and close the micro-adjustment valve (11). All the gas in the simulated pressure system is drawn into the waste gas recovery cylinder (10) to avoid environmental pollution. Then, take out the rock (1) and the filling body (2) and compare the abnormal area identified in step S7 with the damage and leakage location on the rock (1) and the filling body (2). Based on the two-dimensional or three-dimensional potential space anomaly probability distribution image drawn according to the potential fluctuation amplitude spatiotemporal sequence, the quality assessment of the sealed rock mass can be effectively monitored and warned.

6. The detection method of the real-time potential response detection system for leakage sources in mine carbon dioxide sequestration as described in claim 5, characterized in that, In step S5, the specific steps for calculating the sub-spatiotemporal sequence are as follows: Time series of potential fluctuation amplitude T A As the temporal component of the fuzzy C-means clustering method, it is combined with its spatial component to form a spatiotemporal sequence. Q A ={q1,q2,……,q N }, for the first i Spatiotemporal data of potential signals q i Its expression is: in, q i ( s )and q i ( t ) represent the spatial and temporal components of the data, respectively, q ia (s) is the first i The first data space component a Each component element a =2 represents a two-dimensional space. a =3 represents three-dimensional space. q ib ( t ) is the first i The first data time component b Each component element; spatiotemporal sequences Q A Adding a time window allows you to obtain the sub-time sequence; the time window length can be set to... L If we take the unit duration, then the first... m The time dimension in each time window is [(( m -1)* L +1),···,( m * L )], No. m The first time window i Spatiotemporal data of potential signals q i sub-space sequence q im The expression is: 。 7. The detection method of the real-time potential response detection system for leakage sources in mine carbon dioxide sequestration as described in claim 5, characterized in that, In step S5, the calculation process of the fuzzy C-means clustering method specifically includes: The Lagrange multiplier method is used to find the minimum of the objective function for fuzzy C-means clustering, thereby obtaining the cluster centers. This is achieved by introducing Lagrange multipliers. λ The expression that constitutes the objective function is: In the formula, e The number of clusters in the clustering. C The number of cluster centers. N For the sample size, c i For the first i Cluster centers, membership matrix u ij spatiotemporal data q j For the i Cluster centers c i membership degree To represent data similarity using Euclidean distance, , ξ For the proportion of time components, c i (s) is the first i Spatial components corresponding to each cluster center c i (t) is the th i The time component corresponding to each cluster center; The partial derivative of the objective function is used to obtain the first... i Cluster centers c i and membership matrix u ij The calculation formula is: In the formula, c r For the first r There are cluster centers, and 1 ≤ r ≤ C ; Set error threshold ε The objective function is iterated until the termination condition is met, at which point the iteration stops. In the formula, For the first t The +1th iteration obtained i Cluster centers, c For the first t The first iteration obtained i Cluster centers; Using the obtained cluster centers and membership matrices to analyze the spatiotemporal data of the potential signal q i Reassigning values ​​yields reconstructed spatiotemporal data. : The clustering effect is evaluated using the recombination error E(ξ), and the value of ξ that minimizes this error is found: Define the spatiotemporal data of the i-th potential signal q i In the time window W m Sub-space sequence q im For the data to be detected, the sub-spatiotemporal sequence is calculated using the following formula. q im Relative anomaly value: In the formula, η im For the first m The relative anomaly value of the i-th potential signal sub-spatiotemporal sequence in a time window, 1≤ k ≤ m -1, W k Indicates time window W m A previous time window, an upcoming time window W m Sub-spatiotemporal sequences to be detected q im The sub-space-time sequence that was in a normal or working state before q ik Comparison, through relative anomaly values η im Determine whether the rock face and filling material are in normal condition during a certain period of the sealing and maintenance period; Further on the time window W m The relative outlier value corresponding to each cluster center in the data. φ r (r=1,…, c j ) Perform calculations and standardization, that is, process the time window W m The weighted average of the relative anomaly values ​​corresponding to each subsequence in the data is calculated using the following formula: when φ r The larger the value, the larger the time window. W m subordinate number r A higher relative outlier in a subsequence of a class indicates a greater likelihood of potential hazards in the rock face and infill, and vice versa; setting an alarm threshold. Φ =0.8, when φ r ≥ Φ An alarm will sound if the filling material is leaking abnormally.

8. The detection method of the real-time potential response detection system for a mine carbon dioxide sequestration leakage source as described in claim 5, characterized in that, In step S5, the two-dimensional spatial components of the rock wall ( x p , y p ) or the three-dimensional spatial components of the infill ( x k , y k , z k The time window of the potential signal time series acquired at point ) W m The average relative outlier probability value of all cluster centers θ m The calculation formula is: Assigning vectors of relative anomaly probability values ​​at any location in space The following formula can be used to plot the real-time two-dimensional or three-dimensional potential space anomaly probability distribution: Time window W m Sub-spatiotemporal sequence data to be detected q im This represents the latest spatiotemporal data collected in real time from the time series of potential fluctuation amplitude.

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