CN114718653A - Mine dynamic disaster real-time monitoring and early warning method based on three comprehensive parameters - Google Patents
Mine dynamic disaster real-time monitoring and early warning method based on three comprehensive parameters Download PDFInfo
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Abstract
A mine dynamic disaster real-time monitoring and early warning method based on three comprehensive parameters divides a monitoring area into a plurality of monitoring units with regular sizes; selecting and installing an intelligent seismic source and a seismic sensor in a monitoring area; determining a monitored sampling interval; micro-seismic generated by irregular rock stratum change is used as an auxiliary seismic source, and a velocity model of a monitoring area is inverted by combining a three-dimensional seismic full-wave imaging technology; determining mechanical parameters, resistivity and temperature values; calculating three comprehensive indexes of time and moment in each monitoring unit; calculating a long-term average value; calculating a short-term average value; comparing the short-term average value with the long-term average value to determine the type of the dynamic disaster; determining a final alarm level according to the distance between the three comprehensive parameter early warning units and the mining project; and displaying the final alarm level and the type of the potential disaster, and giving an optimal processing scheme and basis. The method can accurately early warn the mine dynamic disaster and provide sufficient processing time and an effective solution for processing the disaster.
Description
Technical Field
The invention belongs to the technical field of coal mine safety production, and particularly relates to a mine dynamic disaster real-time monitoring and early warning method based on three comprehensive parameters.
Background
In recent years, with the increase of coal mining depth and the high modernization of mining equipment, coal resource development faces a series of problems and difficulties which are not met by shallow mining, and meanwhile, new and higher requirements are provided for detection and early warning of factors causing coal mine dynamic disasters. Along with the increase of the mining depth and the mining intensity, the number of mines with dynamic disasters, the accident frequency and the damage intensity are increased, wherein water burst, coal and gas outburst and rock burst are the main coal mine dynamic disasters, and the method has the characteristics of sudden, rapid and violent property, large harm degree, wide influence range and the like, and is easy to induce other major accidents. The coal mine dynamic disaster is a nonlinear complex problem, and relates to the problems of a disaster-causing action mechanism of geological occurrence conditions, a coal and rock mass deformation and damage rule, engineering dynamic response characteristics, mining stress distribution and the like, and the disaster risk identification and monitoring early warning technology still lags behind the requirements of safe, efficient and green mining on dynamic disaster early warning under the current deep mining conditions. Therefore, the existing detection and early warning technology for coal mine dynamic disaster factors is not mature and perfect, the detection precision and early warning technology cannot completely meet the requirement of safe and efficient production of coal mines, and the method is a passive monitoring means and cannot really achieve the aim of early warning.
More than 90% of coal mines in China adopt underground mining, however, the geological conditions of the coal mines in China are quite complex on the whole. Anhui is an important coal base in China, the mining center of gravity of a main mining area is below-700 m at present, the main mining area rapidly extends downwards at the speed of 10-15 m each year, the mining depth of part of mine working faces is nearly kilometer, and the mining depth tends to increase continuously. Along with the increase of the mining depth of a mine, the gas content and the pressure of a coal seam sharply increase, the pressure of underground water is continuously increased, the pressure of the top floor and the bottom floor of the coal seam is proportionally increased, the risk of dynamic disasters is increased, and necessary measures need to be taken before the disasters occur to master the initiative of mine dynamic disaster prevention and control. Therefore, the research on the dynamic instability destruction triggering mechanism of the coal rock mass under deep high ground stress and strong mining conditions needs to be deeply developed from the correlation between the gas field, stress field and hydrology field change mechanism and the seismic wave propagation characteristics, the influence rule of coal rock fracture and evolution on seismic wave propagation is explored, advanced mine geophysical information acquisition equipment is developed, a three-dimensional seismic wave imaging platform is developed, and a disaster monitoring and early warning system is established to meet the important requirements of coal mine typical dynamic disaster risk identification and monitoring and early warning.
Disclosure of Invention
Aiming at the problems in the prior art, the invention provides a mine dynamic disaster real-time monitoring and early warning method based on three comprehensive parameters, which can accurately early warn the mine dynamic disaster, provide sufficient processing time and effective solutions for processing different types of disasters and overcome the defects of the traditional earthquake method for monitoring the mine dynamic disaster.
In order to achieve the aim, the invention provides a mine dynamic disaster real-time monitoring and early warning method based on three comprehensive parameters, which comprises the following steps:
the method comprises the following steps: after the range of the monitoring area is defined, dividing the monitoring area into a plurality of monitoring units with regular sizes;
selecting an intelligent seismic source and a seismic sensor, wherein the intelligent seismic source selects a controllable seismic source so as to be convenient for periodically exciting seismic signals with enough energy and ensure that the seismic excitation is sent to a seismic signal acquisition system according to accurate time; the seismic sensor is a sensor coupled with an electrode and a thermometer, so that the seismic sensor has the functions of receiving a vibration signal, transmitting current and measuring temperature;
step three: arranging an intelligent seismic source and seismic sensors along the edge of a monitoring area, and arranging the seismic sensors at corresponding points of the monitoring area of the intelligent seismic source to ensure that a seismic monitoring network formed by the intelligent seismic source and the seismic sensors can uniformly cover the full monitoring area;
step four: determining a sampling interval of monitoring according to the computing capacity of the monitoring system;
step five: in a monitoring area, firstly applying high-strength manual hammering to provide an accurate initial velocity model for inversion calculation and microseismic positioning; then, an intelligent seismic source is controlled to send a specific vibration signal to a seismic sensor at regular time, meanwhile, microseisms generated by irregular rock stratum changes are used as auxiliary seismic sources, a speed model of a monitoring area is inverted by combining a three-dimensional seismic full-wave imaging technology, a microseismic positioning calculation process in the monitoring area is corrected and optimized by using a real-time speed model, and microseismic positioning precision is improved;
step six: taking a seismic monitoring network as a reference, and simultaneously, combining an auxiliary seismic source to invert the mechanical parameters Lt of each rock stratum in the monitoring area;
seventhly, reflecting the resistivity Dt of each monitoring unit by using the measurement result of the electrode;
step eight: calculating the temperature value Wt of each monitoring unit by using the temperature value measured by the temperature sensor;
step nine: calculating three-field comprehensive indexes Ct of the time T moment in each monitoring unit;
s91: firstly, respectively determining the proportion Pl of a mechanical parameter Lt in a comprehensive index, determining the proportion Pd of resistivity Dt in the comprehensive index and determining the proportion Pw of temperature Wt in the comprehensive index according to the reliability of corresponding monitoring equipment and an acquisition method, and then calculating a three-field comprehensive index Ct by a formula (1);
Ct＝Lt×Pl+Dt×Pd+Wt×Pw t (1)；
s92: according to the determined sampling interval, calculating Ct1 and Ct2 … … Ctn in sequence, continuously moving the time window from 1 to n forwards along with the lapse of time and the update of Ct, removing the old data from the left window, and adding the new data from the right window;
step ten: calculating a long-term average value Ac according to formula (2);
Ac＝(Ct1+Ct2+…+Ctn)/W (2)；
wherein, W is the total number of samples;
step eleven: calculating a short-term average Ad according to formula (3);
Ad＝(Ctn-2+Ctn-1+Ctn)/M (3)；
in the formula, M takes the value of 3;
step twelve: comparing the short-term average Ad with the long-term average Ac, and determining the type of the dynamic disaster;
when Ad > Ac is adopted, if Lt > Dt > Wt is established, the rock stress concentration condition occurs, and the risk of rock burst disaster exists; if Dt > Lt > Wt is satisfied, gas analysis pores are increased, and the risk of gas outburst disasters exists; if Wt > Dt > Lt is satisfied, deep groundwater enters, and the risk of water inrush disaster is caused;
when Ac > Ad, if Lt > Dt > Wt is established, pressure relief and rock destruction are started, and risks of rock burst and water burst disasters are caused; if Dt > Lt > Wt is established, the condition of groundwater infiltration occurs, and risks of water inrush and water penetration disasters exist; if Wt > Dt > Lt is true, the risks of gas analysis heat absorption and surface water disasters occur, and the risks of water inrush and gas outburst disasters occur;
step thirteen: firstly, determining early warning limit values of changes of a short-term average value Ad and a long-term average value Ac; secondly, determining the original alarm level of the current monitoring area according to the ratio of the short-term average value Ad to the long-term average value Ac in combination with the determined initial early warning limit value, wherein the original alarm level is a low-level early warning state and a high-level alarm state from low to high; finally, determining the final alarm level according to the distance between the three comprehensive parameter early warning units and the mining project, and reducing the alarm level if the distance between the three comprehensive parameter early warning units and the mining project exceeds the distance of coal safety regulations by more than one time;
fourteen steps: and displaying the final alarm level and the potential disaster type through a display module, simultaneously giving an optimal processing scheme and basis for processing and preventing the type of dynamic disaster, and sending the original alarm level, the final alarm level, the processing scheme and the basis information to monitoring personnel.
Preferably, in step one, the size of the monitoring unit is determined according to the monitoring precision requirement.
Preferably, in the first step, the monitoring unit is a square with a side of 20 meters.
As a preference, in step nine, Pl is 0.4, Pd is 0.15 and Pw is 0.45.
As a preference, in step nine, the sampling interval ranges from 10 minutes to 30 minutes.
Further, in order to obtain accurate microseismic positioning accuracy, in the manual hammering process of the step five, the interval between adjacent hammering points is 5 meters.
Compared with the traditional early warning method, the method has the following advantages:
1. in the traditional dynamic disaster monitoring method, the frequency and the intensity of micro-earthquakes are mostly monitored as main basis for the occurrence of the dynamic disaster. Although the slight shock is a main index monitored by the conventional mine dynamic disaster early warning system, the slight shock is a result of rock damage, not a process, the frequency and the intensity of the slight shock are related to various factors, and a large amount of research and practice prove that the monitoring of the slight shock cannot effectively predict and forecast the mine dynamic disaster. In fact, the dynamic disaster of the mine is the result of mutual influence of a stress field, a gas field and a hydrological field in the rock, and finally the dynamic characteristics of the rock are reflected. The method comprehensively judges the possibility of the occurrence of the mine dynamic disaster by adopting the change of the mechanical characteristics, resistivity and temperature comprehensive index of the rock stratum in the monitoring area, thereby changing the monitored index from point to area or field. The method discards the frequency and the intensity of micro-earthquakes monitored by the traditional dynamic disaster monitoring method as the basis for the occurrence of the dynamic disaster, overcomes the defects of the earthquake method in monitoring the mine dynamic disaster, starts from the mechanism of the mine dynamic disaster, and provides a more effective mine dynamic disaster monitoring method. Therefore, the system fundamentally overcomes the defects of the conventional mine dynamic disaster monitoring system based on micro-seismic.
2. The mechanical parameters of the rock can be obtained by direct measurement or other methods. The direct measurement method is expensive and is limited to the use of the operator near the installation site, so the use site has certain limitations. In the method, a seismic network formed by the controllable seismic source and the sensor is adopted, as shown in fig. 3, the whole monitoring area can be completely covered in space, and no monitoring dead angle is reserved. The bearing state of the rock is determined by combining the stress-strain curve in the figure 1, so that the time and the place of the mine dynamic disaster can be accurately pre-warned, and sufficient time is provided for personnel evacuation and construction. The limitation of the existing dynamic disaster monitoring system based on micro-earthquake mainly shows in three aspects: firstly, calculating an average seismic wave propagation velocity model which is designed in advance in a basic monitoring area at a micro-seismic site, wherein the actual propagation velocity of seismic waves is related to the types, the damage degree and the stress state of rocks, the distribution of the types of rocks is regular in the mining process of a mine, and the damage degree and the stress state of the rocks are continuously changed along with time; secondly, the distribution of the microseisms is generally concentrated and cannot cover the calculation requirement of the whole monitoring area; finally, the most important point is that the time distribution of the occurrence of the micro-quake is random, and when the micro-quake occurs in a large quantity, the rock is probably close to the rock damage limit, and the time required by early warning cannot be provided. Therefore, the micro-vibration force disaster monitoring system is a passive monitoring system, has great hysteresis, and cannot really achieve the purpose of early warning, and the three-dimensional seismic inversion network formed by the controllable seismic source and the sensor effectively solves the problems of the conventional dynamic disaster monitoring system.
3. The Young modulus of the rock can be reduced due to the increase of the rock pore, the gas desorption and the water content, and the resistivity can be greatly reduced due to the invasion of underground water, so that the situation of water invasion or gas analysis can be judged by combining the inversion of the resistivity, and the problem of mechanical multiresolution of dynamic disasters is solved by measuring the resistivity, so that the mine dynamic disasters can be more accurately pre-warned, and sufficient processing time and an effective solution can be provided for processing different types of disasters.
4. In the method, the urgent degree of dynamic disaster of the mine can be accurately predicted by adding the temperature parameter components, which is the capability that a dynamic disaster monitoring system based on micro-earthquake does not have. In a fixed monitoring zone, temperature is a relatively stable parameter. Its sudden changes are typically precursors to dynamic disasters. The process of fast analyzing the gas from the surface of the coal rock is the most important characteristic of the gas outburst, but the process is a heat absorption process, and when the process occurs, a large amount of heat can be absorbed from the periphery, so that the temperature can be rapidly reduced; when the temperature rises, the temperature is usually related to the invasion of deep underground water, so that the three-field comprehensive index formed by the temperature parameters can provide more sufficient early warning time, and meanwhile, the reliability of early warning is improved.
5. In the method, the temperature sensor, the seismic sensor and the electrode are combined together to form the multifunctional sensor, so that the multifunctional sensor is convenient to install and manage, and meanwhile, as shown in figure 2, the position of the seismic sensor is fixed, so that the real-time performance and the accuracy of the speed model and the mechanical parameter calculation can be guaranteed.
6. The method uses the ratio of the short-term average value to the long-term average value to quantitatively calculate the parameter change of any monitoring unit, and directly links the change of the mechanical characteristics, resistivity and temperature of the unit rock along with time with the inoculation process of the dynamic disaster, thereby solving the defect of early warning of the dynamic disaster of the mine at the current stage. The three-field comprehensive parameter has the characteristics of convenience, practicability and reliability, has obvious advantages compared with other mine dynamic disaster monitoring methods, and provides a reliable solution for solving the problem of safe production of mines.
Drawings
FIG. 1 is a graph of stress-strain curves versus cumulative acoustic emissions;
FIG. 2 is a schematic diagram comparing intelligent seismic source monitoring and microseismic monitoring processes;
FIG. 3 is a schematic diagram of an intelligent seismic source and seismic sensor arrangement according to the present invention;
FIG. 4 is a schematic block diagram of a mine dynamic disaster real-time monitoring and early warning system based on three comprehensive parameters.
Detailed Description
The invention will be further explained with reference to the drawings.
As shown in fig. 2, 3 and 4, the invention provides a real-time monitoring and early warning method for mine dynamic disasters based on three comprehensive parameters, which comprises a real-time monitoring and early warning system for mine dynamic disasters based on three comprehensive parameters, wherein the real-time monitoring and early warning system comprises a monitoring area, an intelligent seismic source, a seismic sensor, an electrode, a thermometer, a display module and a controller; the monitoring area is divided into a plurality of monitoring units with regular sizes; the intelligent seismic sources are controllable seismic sources, the number of the intelligent seismic sources is multiple, every four intelligent seismic sources are arranged on the ground in the same monitoring unit and distributed at four corners of the same monitoring unit, and the intelligent seismic sources are used for periodically emitting seismic waves after receiving seismic wave excitation signals; the system comprises a plurality of seismic sensors, a controller and a monitoring area, wherein the plurality of seismic sensors are embedded in an underground space of the monitoring area and used for acquiring seismic wave signals emitted by an intelligent seismic source and microseismic signals generated by irregular rock stratum changes in real time and transmitting the acquired seismic wave signals and the microseismic signals to the controller in real time; the number of the electrodes is multiple, the electrodes are arranged in one-to-one correspondence with the seismic sensors and correspondingly buried nearby the seismic sensors, and the electrodes are used for acquiring resistivity signals in real time and sending the acquired resistivity signals to the controller in real time; the thermometer is correspondingly buried near the seismic sensors and used for acquiring temperature signals in real time and sending the acquired temperature signals to the controller in real time; the input end of the controller is connected with the plurality of seismic sensors, the plurality of electrodes and the plurality of thermometers through signal transmission cables, the output end of the controller is connected with the display module, the controller is used for sending seismic wave excitation signals to the intelligent seismic source, judging the type of the mine dynamic disaster according to the received vibration signals, micro-vibration signals, resistivity signals and temperature signals, and sending the judgment result to the display module. Preferably, the seismic sensor, the electrodes and the thermometer are coupled into an integrated device. Furthermore, in order to give an effective warning, the alarm device also comprises an alarm module, wherein the alarm module is used for giving an alarm action according to the control of the controller. Preferably, the controller is an industrial computer with a signal collector and a digital-to-analog conversion device.
The mine dynamic disaster real-time monitoring and early warning method based on the three comprehensive parameters comprises the following steps:
the method comprises the following steps: after the range of the monitoring area is defined, dividing the monitoring area into a plurality of monitoring units with regular sizes; preferably, the monitoring unit is a square with a side length of 20 meters.
Selecting an intelligent seismic source and a seismic sensor, wherein the intelligent seismic source selects a controllable seismic source so as to be convenient for periodically exciting seismic signals with enough energy and ensure that the seismic excitation is sent to a seismic signal acquisition system according to accurate time; the seismic sensor is a sensor coupled with an electrode and a thermometer, so that the seismic sensor has the functions of receiving a vibration signal, transmitting current and measuring temperature;
step three: arranging an intelligent seismic source and seismic sensors along the edge of a monitoring area, arranging the seismic sensors at corresponding points of the monitoring area of the intelligent seismic source, embedding the seismic sensors in an underground space of the monitoring area, and simultaneously ensuring that a seismic monitoring network formed by the intelligent seismic source and the seismic sensors can uniformly cover the whole monitoring area;
as a technical solution, the intelligent seismic source may be arranged on the ground of the monitoring unit; as another technical scheme, the intelligent seismic source can be arranged at the position of the coal seam roof;
preferably, the monitoring units are rectangular, wherein four intelligent seismic sources are arranged on the ground at four corners of each monitoring unit, and eight seismic sensors are buried in the underground space of each monitoring unit;
as a technical scheme, the seismic sensor can be buried near the top plate of the coal seam, and certainly, can also be buried at the position of the coal seam, or can be buried at the position of the bottom plate of the coal seam;
step four: determining a sampling interval of monitoring according to the computing capacity of the monitoring system; the smaller the interval, the higher the precision, the better the real-time performance of the system early warning, generally 5 minutes to 1 hour, as a preference, the sampling interval is set to be between 10 minutes and 30 minutes;
step five: in a monitoring area, firstly applying high-strength manual hammering, and providing an accurate initial velocity model for inversion calculation and microseismic positioning through the hammering position in combination with the installation position of a seismic sensor; then, an intelligent seismic source is controlled to send a specific vibration signal to a seismic sensor at regular time, meanwhile, microseisms generated by irregular rock stratum changes are used as auxiliary seismic sources, a speed model of a monitoring area is inverted by combining a three-dimensional seismic full-wave imaging technology, a microseismic positioning calculation process in the monitoring area is corrected and optimized by using a real-time speed model, and microseismic positioning precision is improved;
in order to obtain accurate microseismic positioning accuracy, in the manual hammering process of the step five, the interval between adjacent hammering points is 5 meters.
Step six: taking a seismic monitoring network as a reference, and simultaneously, combining an auxiliary seismic source to invert the mechanical parameters Lt of each rock stratum in the monitoring area;
seventhly, reflecting the resistivity Dt of each monitoring unit by using the measurement result of the electrode;
step eight: calculating the temperature value Wt of each monitoring unit by using the temperature value measured by the temperature sensor;
step nine: calculating three-field comprehensive indexes Ct of the time T moment in each monitoring unit;
s91: firstly, respectively determining the proportion Pl of a mechanical parameter Lt in a comprehensive index, determining the proportion Pd of resistivity Dt in the comprehensive index and determining the proportion Pw of temperature Wt in the comprehensive index according to the reliability of corresponding monitoring equipment and an acquisition method, and then calculating a three-field comprehensive index Ct by a formula (1);
Ct＝Lt×Pl+Dt×Pd+Wt×Pw t (1)；
as a preference, Pl is 0.4, Pd is 0.15, Pw is 0.45;
s92: according to the determined sampling interval, calculating to obtain Ct1 and Ct2 … … Ctn in sequence, moving the time window from 1 to n forward continuously along with the time lapse and the update of Ct, removing the old data from the left window, and adding the new data from the right window; the size n of the time window is related to 2 sampling intervals, typically around 50;
step ten: calculating a long-term average value Ac according to formula (2);
Ac＝(Ct1+Ct2+…+Ctn)/W (2)；
wherein, W is the total number of samples;
preferably, W is 50;
step eleven: calculating a short-term average Ad according to formula (3);
Ad＝(Ctn-2+Ctn-1+Ctn)/M (3)；
the short-term time window is mainly set for avoiding monitoring or calculation errors, generally, M is 3, and then the latest three values can be taken from the time window to calculate the average value;
step twelve: comparing the short-term average Ad with the long-term average Ac, and determining the type of the dynamic disaster, as shown in Table 1;
table 1: dynamic disaster types under different conditions of short-term average Ad and long-term average Ac
| Ad/Ac | Major contributing components | Possible reasons for | Type of disaster |
| Ad>Ac | Lt>Dt>Wt | Stress concentration of rock | Rock burst |
| Dt>Lt>Wt | Increase of gas desorption pore | Gas outburst | |
| Wt>Dt>Lt | Deep ground water ingress | Water inrush | |
| Ac>Ad | Lt>Dt>Wt | Pressure relief and rock openingInitial destruction | Rock burst and water inrush |
| Dt>Lt>Wt | Infiltration of ground water | Water inrush and permeation | |
| Wt>Dt>Lt | Gas desorption heat absorption, surface water | Water burst, gas burst |
When Ad > Ac, if Lt > Dt > Wt is established, the situation of rock stress concentration occurs, and the risk of rock burst disaster exists; if Dt > Lt > Wt is established, the gas analysis pore is increased, and the risk of gas outburst disaster is caused; if Wt > Dt > Lt is satisfied, deep groundwater enters, and the risk of water inrush disaster is caused;
when Ac > Ad, if Lt > Dt > Wt is established, pressure relief and rock destruction are started, and risks of rock burst and water burst disasters are caused; if Dt > Lt > Wt is established, the condition of groundwater infiltration occurs, and risks of water inrush and water penetration disasters exist; if Wt > Dt > Lt is satisfied, the risk of gas analysis heat absorption and surface water disaster occurs, and the risk of water burst and gas outburst disaster occurs;
step thirteen: firstly, determining early warning limit values of short-term average values and long-term average value changes: the change of the early warning limit value can be positive or negative, and the absolute value of the change is used; the early warning limit value is related to the coal and rock stratum characteristics of the mine, different mining areas have larger difference and are continuously adjusted according to monitoring historical data, and the initial early warning limit value can be set to be 10%.
Secondly, determining the original alarm level of the current monitoring area according to the ratio of the short-term average value Ad to the long-term average value Ac in combination with the determined initial early warning limit value, wherein the original alarm level is a low-level early warning state and a high-level alarm state from low to high;
when the initial early warning value is reached, the early warning state is a low-level early warning state, and when the initial early warning value is reached, the early warning state is a high-level warning state, namely:
Ad/Ac 10%, low-level early warning status;
Ad/Ac 20%, advanced alarm status;
finally, determining a final alarm level according to the distance between the three comprehensive parameter early warning units and the mining project, if the distance between the three comprehensive parameter early warning units and the mining project exceeds the distance of coal safety regulations by more than one time, reducing the alarm level, and if the original alarm level is in a high-level alarm state, reducing the alarm level to a low-level alarm state;
fourteen steps: and displaying the final alarm level and the potential disaster type through a display module, simultaneously giving an optimal processing scheme and basis for processing and preventing the type of dynamic disaster, and sending the original alarm level, the final alarm level, the processing scheme and the basis information to monitoring personnel.
Preferably, in step one, the size of the monitoring unit is determined according to the monitoring precision requirement.
As shown in fig. 1, the acoustic emission and microseismic monitoring system primarily relies on monitoring the frequency and intensity of fractures of coal rocks to predict the occurrence of a dynamic disaster. Compared with a three-dimensional earthquake, the system does not depend on a reflection interface and has continuous real-time monitoring performance; meanwhile, the anti-interference performance is high, the propagation of sound waves and seismic waves is stable, and even the interference of some mechanical noises is easy to eliminate, so that the development is rapid in recent years, and the early warning method has primary application in mine dynamic disaster early warning. But in engineering applications, it is limited in use because it monitors only the frequency and intensity of rock fractures. Firstly, a large amount of cracks are not generated before all dynamic disasters occur, for example, a large amount of rock fractures are not generated when high-pressure water or gas passes through a coal rock stratum fracture zone and protrudes into a working face; secondly, the strength and density of the rock fracture are related to various factors such as occurrence state of the rock mass and rock stratum structure, and a proper early warning limit value is difficult to find; finally, the occurrence time of the rock fracture is very close to the occurrence time of the dynamic disaster, and the reaction time after early warning is not enough. FIG. 1 is a relationship between stress-strain curves and cumulative acoustic emissions in a rock pressure test, and it can be seen that acoustic emissions occur during the whole rock pressure test, and that high acoustic emissions occur at a density near the failure, accompanied by a quiet period of 5 seconds, but such a short time hardly meets the requirements of safe production. From the perspective of space analysis, the state of a certain point is monitored, the judgment on the whole mining space is insufficient, and the acoustic emission and micro-seismic monitoring system is an urgent problem to be solved.
The method starts from the formation mechanism of the mine dynamic disaster and the actual production needs, and an effective mine dynamic disaster early warning system needs to have three main characteristics: (1) time continuity, namely the system needs to be continuously monitored for 24 hours, dynamic characteristics of the inoculation stage of the dynamic disaster are found, the possibility of forming the dynamic disaster is identified, and sufficient time guarantee is provided for early warning; (2) the reliability of monitoring and early warning is realized, the dynamic disaster early warning depending on the frequency and the strength of limited breaking points has blindness and uncertainty, and a reliable early warning system needs to accurately identify the premonition information of the dynamic disaster from monitoring the dynamic changes of a gas field, a stress field and a hydrology field and provide reliable dynamic disaster early warning and forecast; (3) the method is suitable for severe underground conditions, has strong anti-interference capability and fully ensures data reliability. The system utilizes the comprehensive index formed by the seismic wave propagation characteristics, the electric field characteristics and the temperature characteristics to monitor the states and changes of a stress field, a gas field and a hydrological field in a region, has all-weather uninterrupted monitoring capability and provides a reliable monitoring means for early warning of mine dynamic disasters.
Claims (6)
1. A mine dynamic disaster real-time monitoring and early warning method based on three comprehensive parameters is characterized by comprising the following steps:
the method comprises the following steps: after the range of the monitoring area is defined, dividing the monitoring area into a plurality of monitoring units with regular sizes;
selecting an intelligent seismic source and a seismic sensor, wherein the intelligent seismic source selects a controllable seismic source so as to be convenient for periodically exciting seismic signals with enough energy and ensure that the seismic excitation is sent to a seismic signal acquisition system according to accurate time; the seismic sensor is a sensor coupled with an electrode and a thermometer, so that the seismic sensor has the functions of receiving a vibration signal, transmitting current and measuring temperature;
step three: arranging an intelligent seismic source and seismic sensors along the edge of a monitoring area, and arranging the seismic sensors at corresponding points of the monitoring area of the intelligent seismic source to ensure that a seismic monitoring network formed by the intelligent seismic source and the seismic sensors can uniformly cover the full monitoring area;
step four: determining a sampling interval of monitoring according to the computing capacity of the monitoring system;
step five: in a monitoring area, firstly applying high-strength manual hammering to provide an accurate initial velocity model for inversion calculation and microseismic positioning; then, an intelligent seismic source is controlled to send a specific vibration signal to a seismic sensor at regular time, meanwhile, microseisms generated by irregular rock stratum changes are used as auxiliary seismic sources, a speed model of a monitoring area is inverted by combining a three-dimensional seismic full-wave imaging technology, a microseismic positioning calculation process in the monitoring area is corrected and optimized by using a real-time speed model, and microseismic positioning precision is improved;
step six: taking a seismic monitoring network as a reference, and simultaneously, combining an auxiliary seismic source to invert the mechanical parameters Lt of each rock stratum in the monitoring area;
seventhly, reflecting the resistivity Dt of each monitoring unit by using the measurement result of the electrode;
step eight: calculating the temperature value Wt of each monitoring unit by using the temperature value measured by the temperature sensor;
step nine: calculating three-field comprehensive indexes Ct of the time T moment in each monitoring unit;
s91: firstly, respectively determining the proportion Pl of a mechanical parameter Lt in a comprehensive index, determining the proportion Pd of resistivity Dt in the comprehensive index and determining the proportion Pw of temperature Wt in the comprehensive index according to the reliability of corresponding monitoring equipment and an acquisition method, and then calculating the three-field comprehensive index Ct through a formula (1);
Ct＝Lt×Pl+Dt×Pd+Wt×Pw t (1)；
s92: according to the determined sampling interval, calculating Ct1 and Ct2 … … Ctn in sequence, continuously moving the time window from 1 to n forwards along with the lapse of time and the update of Ct, removing the old data from the left window, and adding the new data from the right window;
step ten: calculating a long-term average value Ac according to formula (2);
Ac＝(Ct1+Ct2+…+Ctn)/W (2)；
wherein, W is the total number of samples;
step eleven: calculating a short-term average Ad according to formula (3);
Ad＝(Ctn-2+Ctn-1+Ctn)/M (3)；
in the formula, M takes the value of 3;
step twelve: comparing the short-term average Ad with the long-term average Ac, and determining the type of the dynamic disaster;
when Ad > Ac is adopted, if Lt > Dt > Wt is established, the rock stress concentration condition occurs, and the risk of rock burst disaster exists; if Dt > Lt > Wt is satisfied, gas analysis pores are increased, and the risk of gas outburst disasters exists; if Wt > Dt > Lt is satisfied, deep groundwater enters, and the risk of water inrush disaster is caused;
when Ac > Ad, if Lt > Dt > Wt is established, pressure relief and rock destruction are started, and risks of rock burst and water burst disasters are caused; if Dt > Lt > Wt is established, the condition of groundwater infiltration occurs, and risks of water inrush and water penetration disasters are caused; if Wt > Dt > Lt is satisfied, the risk of gas analysis heat absorption and surface water disaster occurs, and the risk of water burst and gas outburst disaster occurs;
step thirteen: firstly, determining early warning limit values of changes of a short-term average value Ad and a long-term average value Ac; secondly, determining the original alarm level of the current monitoring area according to the ratio of the short-term average value Ad to the long-term average value Ac in combination with the determined initial early warning limit value, wherein the original alarm level is a low-level early warning state and a high-level alarm state from low to high; finally, determining a final alarm level according to the distance between the three comprehensive parameter early warning units and the mining project, and reducing the alarm level if the distance between the three comprehensive parameter early warning units and the mining project exceeds the distance of the coal safety regulation by more than one time;
fourteen steps: and displaying the final alarm level and the potential disaster type through a display module, simultaneously giving an optimal processing scheme and basis for processing and preventing the type of dynamic disaster, and sending the original alarm level, the final alarm level, the processing scheme and the basis information to monitoring personnel.
2. The mine dynamic disaster real-time monitoring and early warning method based on the three comprehensive parameters as claimed in claim 1, wherein in the step one, the size of the monitoring unit is determined according to the monitoring precision requirement.
3. The mine dynamic disaster real-time monitoring and early warning method based on the three-field comprehensive parameters as claimed in claim 2, wherein in the step one, the monitoring unit is a square with a side length of 20 meters.
4. The method for real-time monitoring and early warning of mine dynamic disasters based on three comprehensive parameters is characterized in that in the ninth step, Pl is 0.4, Pd is 0.15, and Pw is 0.45.
5. The mine dynamic disaster real-time monitoring and early warning method based on the three comprehensive parameters is characterized in that in the ninth step, the sampling interval ranges from 10 minutes to 30 minutes.
6. The mine dynamic disaster real-time monitoring and early warning method based on the three comprehensive parameters as recited in claim 5, wherein in the manual hammering process of the fifth step, the interval between adjacent hammering points is 5 meters.
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN115346325A (en) * | 2022-08-12 | 2022-11-15 | 骄鹏科技(北京)有限公司 | Method and system for realizing cloud platform distributed underground space multi-parameter monitoring |
| CN117037456A (en) * | 2023-10-10 | 2023-11-10 | 山东科技大学 | Mine disaster prediction and early warning method and system for on-site monitoring |
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN115346325A (en) * | 2022-08-12 | 2022-11-15 | 骄鹏科技(北京)有限公司 | Method and system for realizing cloud platform distributed underground space multi-parameter monitoring |
| CN115346325B (en) * | 2022-08-12 | 2023-09-05 | 骄鹏科技(北京)有限公司 | Method and system for realizing cloud platform distributed underground space multi-parameter monitoring |
| CN117037456A (en) * | 2023-10-10 | 2023-11-10 | 山东科技大学 | Mine disaster prediction and early warning method and system for on-site monitoring |
| CN117037456B (en) * | 2023-10-10 | 2024-01-30 | 山东科技大学 | Mine disaster prediction and early warning method and system for on-site monitoring |
| CN117113519A (en) * | 2023-10-24 | 2023-11-24 | 安徽省交通勘察设计院有限公司 | Cable tower anchoring area damage model construction and earthquake vulnerability assessment method and system |
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