CN116564065A - Mine disaster prediction and early warning method combining on-site monitoring and numerical simulation - Google Patents
Mine disaster prediction and early warning method combining on-site monitoring and numerical simulation Download PDFInfo
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Abstract
The invention discloses a mine disaster prediction and early warning method combining on-site monitoring and numerical simulation in the disaster monitoring field, which comprises the following steps: step a, a monitoring pile is buried in a distributed mode and is connected with an early warning center through signals; step b, acquiring historical geological data of a region to be monitored, and constructing a functional relation between the soil fracture change rate and the vibration quantity and the deformation quantity based on a gray prediction algorithm to obtain a mine disaster prediction model; step c, obtaining the vibration quantity, the deformation quantity and the soil crack change rate of the monitoring node; step d, the data processing module performs data preprocessing and optimization; step e, obtaining a risk degree through a mine disaster prediction model, and predicting the mine disaster according to the risk degree; and f, determining a risk area according to the node position of the abnormal monitoring data, and sending an early warning signal to perform early warning. The scheme solves the problem that the change rate of the soil cracks is difficult to monitor in the prior art, so that mine disasters cannot be prevented and controlled earlier.
Description
Technical Field
The invention belongs to the field of disaster monitoring, and particularly relates to a mine disaster prediction and early warning method combining on-site monitoring and numerical simulation.
Background
The original stable mineral condition is changed in the mineral exploitation process, the local geological environment is changed, and the disaster caused or induced by the change of the geological environment due to the artificial mining activity is called mine geological disaster. Common mine geological disasters mainly comprise rock-soil ring layer deformation disasters and underground water level variation disasters, and are specifically expressed as induced earthquakes, landslide, pit water burst and water leakage. The occurrence of the mine geological disaster can cause immeasurable harm and damage to the ecological environment, natural resources and the economic society, so that the mine geological disaster is scientifically and accurately predicted and early-warned, and the loss caused by the mine geological disaster can be reduced.
The patent with the publication number of CN110307038B discloses an all-digital mine dynamic disaster comprehensive monitoring and early warning system and method, wherein the system comprises: the digital microseismic sensor is used for acquiring microseismic signals; the digital ground sound sensor is used for acquiring a ground sound signal; the intelligent disaster source analyzer analyzes and processes the received microseismic signals and the received ground sound signals in real time; and the data processing monitoring center performs signal data post-analysis based on the analyzed and processed signal data, and performs auxiliary decision making and real-time intelligent early warning based on the signal data after-analysis.
The system and the method combine the microseismic monitoring technology and the ground sound monitoring technology, integrate the sensing technology, the microelectronic technology, the digital signal processing technology and the computer communication technology and the like to develop a full-digital mine dynamic disaster comprehensive monitoring and early warning system, and realize real-time comprehensive monitoring and early warning of mine dynamic disasters.
Compared with the mine disaster caused by earthquake, the system has the characteristics of burst and abrupt, has obvious time effect due to rainfall infiltration, has multiple dry and wet circulation effects, causes tiny cracks near the slope shoulder, increases the gap water pressure of the cracks when rainfall is performed next time, causes water absorption softening of soil, increases the soil cracks through multiple dry and wet circulation, reduces the shear strength of the mine, and is easy to induce disasters such as earthquake or landslide.
Disclosure of Invention
In order to solve the problems, the invention aims to provide a mine disaster prediction and early warning method combining field monitoring and numerical simulation, which constructs a functional relation between the crack change rate and mine deformation and vibration according to the influence of time effect of soil crack change on mine disasters such as induced earthquake, landslide and the like, monitors the soil crack change rate of a region to be monitored through a monitoring pile, and predicts the possibility of occurrence of the mine disasters in the region by combining the deformation and vibration data of the mine, thereby solving the problem that the soil crack change rate is difficult to monitor in the prior art, and thus the mine disasters cannot be prevented and controlled earlier.
In order to achieve the above object, the technical scheme of the present invention is as follows: a mine disaster prediction and early warning method combining field monitoring and numerical simulation comprises the following steps:
step a, monitoring piles are buried in a distributed mode in a region to be monitored, and the monitoring piles are connected with an early warning center through signals;
step b, acquiring historical geological data of a region to be monitored, and constructing a functional relation between the soil crack change rate and the vibration quantity and the deformation quantity by an early warning analysis module based on a gray prediction algorithm to obtain a mine disaster prediction model;
step c, the micro-seismic monitoring module acquires the vibration quantity in the mine and marks the vibration quantity as a first signal, the InSAR image monitoring module acquires the deformation quantity of a monitoring node and marks the deformation quantity as a second signal, and the monitoring pile acquires the soil crack change rate of a region to be monitored and marks the soil crack change rate as a third signal;
step d, the data processing module performs data preprocessing and optimization on the first signal, the second signal and the third signal;
step e, inputting the optimized first signal, the optimized second signal and the optimized third signal into a mine disaster prediction model to obtain risk degrees, and predicting the mine disaster according to the risk degrees;
and f, determining a risk area by the data acquisition module according to the node position of the abnormal monitoring data, and sending an early warning signal to perform early warning by the early warning analysis module according to the risk area and the risk degree.
The principle of the scheme is as follows:
according to the scheme, according to the influence of the soil crack change on the mine disasters such as induced earthquake, landslide and the like, the function relation between the crack change rate, the mine deformation and vibration is constructed, the soil crack change rate of the area to be monitored is monitored through the monitoring piles, and the risk of the mine disasters in the area is predicted by combining the deformation and vibration data of the mine.
After the scheme is adopted, the following beneficial effects are realized:
compared with the prior art, the method and the device have the advantages that the risk degree of the mine disaster is subjected to numerical simulation according to the function relation of the crack change rate, the mine disaster deformation and the vibration quantity, the early warning can be carried out before the soil crack change rate reaches the threshold value for inducing the mine disaster, the early warning can be carried out on the mine disaster, residents in the area where the mine disaster is to occur can have more transfer time, and the safety of people and property is further protected.
Further, the mine disaster prediction and early warning method is based on a mine disaster early warning system for prediction and early warning, and the mine disaster early warning system comprises an early warning center and a plurality of monitoring piles which are arranged in a region to be monitored and used for monitoring the change rate of underground soil cracks of the mine:
the early warning center is used for inputting a mine disaster prediction model to calculate the risk degree according to the monitoring data of the area to be monitored, predicting and early warning the mine disaster based on the risk degree and the risk area, and comprises the following steps:
the data acquisition module is used for receiving the monitoring data of the monitoring pile, acquiring the position of the monitoring pile based on the RSSI ranging technology and the TOF ranging technology, wherein the monitoring pile is used as an independent monitoring node, the independent monitoring node forms a monitoring grid, and a risk area is determined according to the node position of the abnormal monitoring data;
the InSAR image monitoring module is used for acquiring image data of an area to be monitored in a preset time period and calculating deformation of a mine in a monitoring node range of an adjacent preset time period;
the microseism monitoring module is used for acquiring the vibration quantity generated by the fracture of the rock mass in the mine;
the data processing module is used for removing abnormal monitoring data and optimizing the data based on a particle swarm algorithm;
the storage module is used for storing the data monitored by the monitoring pile, the InSAR image monitoring module and the microseismic monitoring module;
the early warning analysis module is used for constructing a functional relation between the soil fracture change rate and the vibration quantity and the deformation quantity based on a gray prediction algorithm, obtaining a mine disaster prediction model, inputting the mine disaster prediction model to obtain a risk degree according to the monitoring data obtained by the monitoring pile, the deformation quantity obtained by the InSAR image monitoring module and the vibration quantity obtained by the micro-vibration monitoring module, and predicting the mine disaster according to the risk degree and sending early warning signals;
the monitoring pile comprises a pile body, a power supply module is arranged at the top of the pile body, a containing cavity is formed in the pile body and penetrates through the top of the pile body, a communication module, a pretreatment module and a supporting component are arranged in the containing cavity, a plurality of first sliding grooves and sliding holes are formed in the lower portion of the side wall of the pile body, a first elastic piece, a first strain gauge and a sliding block are sequentially connected in the first sliding grooves along the direction of the side wall of the pile body, a second sliding groove is communicated below the containing cavity, the supporting component comprises a compression bar longitudinally sliding along the containing cavity and the second sliding groove, a second strain gauge and a second elastic piece are sequentially connected at the bottom of the compression bar in a vertical direction, one end, far away from the second strain gauge, of the second elastic piece is fixedly connected with the bottom of the second sliding groove, a plurality of supporting bars are hinged in the middle of the compression bar, a limiting rod is hinged between the middle of each supporting bar and the containing cavity, a soil moisture sensor is arranged at the movable end of each supporting bar, the supporting bar can penetrate through the sliding holes to be inserted into underground soil, the monitoring pile is reinforced, the moisture content of soil around the pile body is monitored through the soil moisture sensor, and a locking component is arranged at the top of the compression bar;
the soil crack change rate is calculated by the pretreatment module according to the data of the soil moisture content sensor and the first strain gauge, constructing a functional relation between the soil moisture content and the soil cracks, and calculating the soil crack change rate.
The beneficial effects are that: when the monitoring pile is in an initial state, the first elastic piece and the second elastic piece enable the first strain piece and the second strain piece to keep a stress balance state under the condition that the soil pressure and the gravity of the compression bar are overcome, when rainwater permeates into the soil around a mine, the soil water content is increased, the soil is softened, the soil pressure received by the first strain piece is reduced, the soil crack is increased, the first strain piece extends outwards along with the sliding block, the moisture in the rain-stop soil volatilizes, the soil water content is reduced, the soil hardens, the soil pressure received by the first strain piece is increased, the soil crack is reduced, the first strain piece retracts inwards along with the sliding block, the functional relation between the soil water content and the soil crack is constructed through the displacement change of the soil water content and the first strain piece, and the soil crack change rate is calculated; according to the influence of the soil crack change on the induced earthquake, landslide and other mine disasters, the risk degree of the mine disasters is calculated, and compared with the prior art, the risk degree of the mine disasters is subjected to numerical simulation, early warning can be carried out before the soil crack change rate reaches the threshold value for inducing the mine disasters, early warning can be carried out on the mine disasters, residents in the area where the mine disasters are to occur can have more transfer time, and safety of people and property is further protected.
Further, the locking subassembly includes along the vertical locking piece and the third elastic component that sets gradually of depression bar, and the locking piece is articulated with depression bar lateral wall upper portion, and the third elastic component cover is established on depression bar upper portion, and holding chamber lateral wall upper portion has opened first locking groove and second locking groove in proper order, and second locking groove intercommunication has the release groove, and wherein, during initial state, locking piece joint is in first locking groove, and during the locking state, locking piece joint is in second locking groove.
The beneficial effects are that: the pile body inserts mine soil, the elasticity joint in the second locking groove of third elastic component is overcome to the locking piece to locking supporting component, pile body skew influences the accuracy of first strain gauge monitoring when avoiding soil softening, when need demolish the monitoring stake, get arbitrary support piece extrusion locking piece that can pass through the release groove, the locking piece breaks away from the spacing of second locking groove, upward movement under the elastic force effect of third elastic component, drive the bracing piece and withdraw to the holding chamber, the locking piece removes to first locking groove, can take out the monitoring stake, the monitoring stake is dismantled in the setting of this scheme, and has consolidated the stability of monitoring stake, make the measured data more have the accuracy.
Further, the top of the compression bar is fixedly connected with a sealing ring.
The beneficial effects are that: when in a locking state, the sealing ring seals the accommodating cavity, so that the electronic component is prevented from being damaged by rainwater leaking into the accommodating cavity in the monitoring process.
Further, the number of the first sliding groove, the first elastic piece, the first strain gauge and the sliding block is 4.
The beneficial effects are that: the first strain gauge can sense the soil pressure change of four directions at least, and the monitoring accuracy is improved.
Further, the data acquisition module is used for acquiring the position of the monitoring node: when the distance between the monitoring nodes is 0-4m, measuring the distance between the monitoring nodes by adopting an RSSI ranging method; and when the monitoring node spacing exceeds 4m, measuring the monitoring node spacing by adopting a TOF method.
The beneficial effects are that: because the close-range RSSI ranging method has small error, the middle-distance TOF ranging method has small error, and the corresponding ranging method is selected to range according to the approximate distance of the monitoring node, when the same-frequency measurement is satisfied, the ranging error is reduced, and the accuracy of subsequent prediction is convenient to improve.
Further, the data processing module processes the monitoring data in the following steps: and adopting a Gaussian regression model to perform mean value processing on the data of the node positions.
The beneficial effects are that: and the data of the node positions are subjected to mean value processing, so that a larger error value generated in the ranging process is eliminated, and the measuring precision is improved.
Further, the data processing module is used for processing the monitoring data, and peak value filtering is carried out on the node position data after mean value processing by adopting a Kalman filtering algorithm.
The beneficial effects are that: further eliminating larger error value generated in the ranging process and improving the measuring precision.
Drawings
Fig. 1 is a flow chart of a mine disaster prediction and early warning method according to an embodiment of the invention.
Fig. 2 is a schematic diagram of a module of a mine disaster prediction and early warning system according to an embodiment of the invention.
Fig. 3 is a cross-sectional view of a monitor post according to an embodiment of the present invention.
Fig. 4 is an enlarged view at a in fig. 3.
Fig. 5 is a cross-sectional view of the bottom of the pile body of the monitoring pile according to the embodiment of the present invention.
Detailed Description
The following is a further detailed description of the embodiments:
reference numerals in the drawings of the specification include: pile body 1, holding chamber 2, depression bar 3, bracing piece 4, gag lever post 5, slider 6, first elastic component 7, first foil gage 8, first spout 9, slide hole 10, power module 11, sealing washer 12, second foil gage 13, second elastic component 14, locking piece 15, third elastic component 16, first locking groove 17, second locking groove 18, release groove 19.
Example 1:
an example is substantially as shown in figures 1 to 5 of the accompanying drawings: the mine disaster prediction and early warning method combining on-site monitoring and numerical simulation is based on a mine disaster early warning system for prediction and early warning, wherein the mine disaster early warning system comprises an early warning center and a plurality of monitoring piles which are arranged in a region to be monitored and used for monitoring the change rate of underground soil cracks of a mine:
the early warning center is used for inputting a mine disaster prediction model to calculate the risk degree according to the monitoring data of the area to be monitored, predicting and early warning the mine disaster based on the risk degree and the risk area, and comprises the following steps:
the data acquisition module is used for receiving the monitoring data of the monitoring pile, acquiring the position of the monitoring pile based on the RSSI ranging technology and the TOF ranging technology, wherein the monitoring pile is used as an independent monitoring node, the independent monitoring node forms a monitoring grid, and a risk area is determined according to the node position of the abnormal monitoring data;
the InSAR image monitoring module is used for acquiring image data of an area to be monitored in a preset time period and calculating deformation of a mine in a monitoring node range of an adjacent preset time period;
the microseism monitoring module is used for acquiring the vibration quantity generated by the fracture of the rock mass in the mine;
the data processing module is used for removing abnormal monitoring data and optimizing the data based on a particle swarm algorithm;
the storage module is used for storing the data monitored by the monitoring pile, the InSAR image monitoring module and the microseismic monitoring module;
the early warning analysis module is used for constructing a functional relation between the soil fracture change rate and the vibration quantity and the deformation quantity based on a gray prediction algorithm, obtaining a mine disaster prediction model, inputting the mine disaster prediction model to obtain a risk degree according to the monitoring data obtained by the monitoring pile, the deformation quantity obtained by the InSAR image monitoring module and the vibration quantity obtained by the micro-vibration monitoring module, and predicting the mine disaster according to the risk degree and sending early warning signals;
the monitoring pile comprises a pile body 1, the bottom of the pile body 1 is conical, a power supply module 11 is arranged at the top of the pile body 1, a containing cavity 2 is formed in the pile body 1 and penetrates through the top of the pile body 1, a communication module, a pretreatment module and a supporting component are arranged in the containing cavity 2, a plurality of first sliding grooves 9 and sliding holes 10 are formed in the lower portion of the side wall of the pile body 1, a first elastic piece 7, a first strain gauge 8 and a sliding block 6 are sequentially connected in the first sliding grooves 9 along the direction of the side wall of the pile body 1, a second sliding groove is communicated below the containing cavity 2, the supporting component comprises a pressure rod 3 longitudinally sliding along the containing cavity 2 and the second sliding groove, a second strain gauge 13 and a second elastic piece 14 are sequentially connected at the bottom of the pressure rod 3 along the vertical direction, one end, far away from the second strain gauge 13, of the second elastic piece 14 is fixedly connected with the bottom of the second sliding groove, a plurality of supporting rods 4 are hinged at the middle of the pressure rod 3, a limiting rod 5 is hinged between the middle of each supporting rod 4 and the containing cavity 2, a soil moisture content sensor is arranged at the movable end of each supporting rod 4, the supporting rod 4 can penetrate through the soil content sensor in the direction of the pile body 10, and the soil sensor is inserted into the soil through the underground pile body to be reinforced, and the soil moisture content sensor is arranged around the soil sensor 1, and the monitoring pile body is monitored by the monitoring pressure rod 1;
the first strain gauge 8, the second strain gauge 13, the soil moisture sensor, the communication module and the power supply module 11 are all in signal connection with the preprocessing module, and the preprocessing module is used for constructing a functional relation between the soil moisture and the soil cracks according to the data of the soil moisture sensor and the first strain gauge 8 and calculating the change rate of the soil cracks.
The mine disaster prediction and early warning method specifically comprises the following steps:
step a, the monitoring piles are buried in a distributed mode in the area to be monitored, the pressure rods 3 are pressed downwards, the supporting rods 4 penetrate through the sliding holes 10 and are inserted into mine underground soil, the supporting rods 4 are locked through the locking assemblies, the first elastic pieces 7 and the second elastic pieces 14 are enabled to be in a stress balance state under the condition that soil pressure and the gravity of the pressure rods 3 are overcome, the first strain gauge 8 and the second strain gauge 13 are kept in a stress balance state, and then the monitoring piles are connected with an early warning center through the communication module in a signal mode.
And b, acquiring historical geological data of the area to be monitored, and constructing a functional relation between the soil crack change rate and the vibration quantity and the deformation quantity based on a gray prediction algorithm by the early warning analysis module to obtain a mine disaster prediction model.
Step c, the micro-seismic monitoring module acquires the vibration quantity in the mine and marks the vibration quantity as a first signal, the InSAR image monitoring module acquires the deformation quantity of a monitoring node and marks the deformation quantity as a second signal, and the monitoring pile acquires the soil crack change rate of a region to be monitored and marks the soil crack change rate as a third signal; the calculation of the soil crack change rate is specifically as follows: when the monitoring pile is in an initial state, the first elastic piece 7 and the second elastic piece 14 enable the first strain gauge 8 and the second strain gauge 13 to keep a stress balance state under the condition that the soil pressure and the gravity of the compression rod 3 are overcome, when rainwater infiltrates into the soil around a mine, the water content of the soil is increased, the soil is softened, the soil pressure received by the first strain gauge 8 is reduced, the soil cracks are increased, the first strain gauge 8 extends outwards along with the sliding block 6, the moisture in the rain-stop soil volatilizes, the soil water content is reduced, the soil hardens, the soil pressure received by the first strain gauge 8 is increased, the soil cracks are reduced, the first strain gauge 8 retracts inwards along with the sliding block 6, and the functional relation between the soil water content and the soil cracks is constructed through the displacement change of the soil water content and the first strain gauge 8, so that the soil crack change rate is calculated.
And d, the data processing module performs data preprocessing on the first signal, the second signal and the third signal, and performs data optimization based on a particle swarm algorithm.
And e, inputting the optimized first signal, the optimized second signal and the optimized third signal into a mine disaster prediction model to obtain risk degrees, and predicting the mine disaster according to the risk degrees.
And f, determining a risk area by the data acquisition module according to the node position of the abnormal monitoring data, and sending an early warning signal to perform early warning by the early warning analysis module according to the risk area and the risk degree.
Example 2:
the difference with the above embodiment is that the locking assembly includes a locking block 15 and a third elastic member 16 which are vertically and sequentially arranged along the compression bar 3, the locking block 15 is hinged to the upper portion of the side wall of the compression bar 3, the third elastic member 16 is sleeved on the upper portion of the compression bar 3, a first locking groove 17 and a second locking groove 18 are sequentially formed in the upper portion of the side wall of the accommodating cavity 2, the second locking groove 18 is communicated with a release groove 19, wherein in an initial state, the locking block 15 is clamped in the first locking groove 17, and in a locking state, the locking block 15 is clamped in the second locking groove 18.
The specific implementation process is as follows:
pile body 1 inserts mine soil, the elasticity joint of third elastic component 16 is overcome in second locking groove 18 to locking support assembly, pile body 1 skew influences the accuracy of first strain gauge 8 monitoring when avoiding soil softening, when need demolish the monitoring stake, get arbitrary support piece extrusion locking piece 15 that can pass through release groove 19, locking piece 15 breaks away from the spacing of second locking groove 18, upward movement under the elasticity effect of third elastic component 16, drive bracing piece 4 retract to holding chamber 2, locking piece 15 moves to first locking groove 17, can take out the monitoring stake, the setting of this scheme is convenient for install and dismantle the monitoring stake, and the stability of monitoring stake has been consolidated, make the measured data more have accuracy.
Example 3:
the difference with the above embodiment is that the top of the compression bar 3 is fixedly connected with a sealing ring 12.
The specific implementation process is as follows:
in the locking state, the sealing ring 12 seals the accommodating cavity 2, so that the electronic element is prevented from being damaged by rainwater leaking into the accommodating cavity 2 in the monitoring process, and discomfort of the palm during pressing is avoided when an operator applies force to the pressing rod 3.
Example 4:
the difference from the above embodiment is that the number of the first sliding groove 9, the first elastic member 7, the first strain gage 8 and the slider 6 is 4.
The specific implementation process is as follows:
it is ensured that the first strain gauge 8 can sense at least the change of the soil pressure in four directions, and the monitoring accuracy is improved.
Example 5:
the difference from the above embodiment is that the data acquisition module acquires the position of the monitoring node in that: when the distance between the monitoring nodes is 0-4m, measuring the distance between the monitoring nodes by adopting an RSSI ranging method; and when the monitoring node spacing exceeds 4m, measuring the monitoring node spacing by adopting a TOF method.
The specific implementation process is as follows:
because the close-range RSSI ranging method has small error, the middle-distance TOF ranging method has small error, and the corresponding ranging method is selected to range according to the approximate distance of the monitoring node, when the same-frequency measurement is satisfied, the ranging error is reduced, and the accuracy of subsequent prediction is convenient to improve.
Example 6:
the difference from the above embodiment is that the processing of the monitoring data by the data processing module is that: and adopting a Gaussian regression model to perform mean value processing on the data of the node positions.
The specific implementation process is as follows:
and the data of the node positions are subjected to mean value processing, so that a larger error value generated in the ranging process is eliminated, and the measuring precision is improved.
Example 7:
the difference from the above embodiment is that the data processing module processes the monitoring data, and also uses a kalman filtering algorithm to perform peak filtering on the node position data after the mean processing.
The specific implementation process is as follows:
further eliminating larger error value generated in the ranging process and improving the measuring precision.
It is noted that relational terms such as first and second, and the like are used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Moreover, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus.
The foregoing is merely an embodiment of the present invention, and a specific structure and characteristics of common knowledge in the art, which are well known in the scheme, are not described herein, so that a person of ordinary skill in the art knows all the prior art in the application day or before the priority date of the present invention, and can know all the prior art in the field, and have the capability of applying the conventional experimental means before the date, so that a person of ordinary skill in the art can complete and implement the present embodiment in combination with his own capability in the light of the present application, and some typical known structures or known methods should not be an obstacle for a person of ordinary skill in the art to implement the present application. It should be noted that modifications and improvements can be made by those skilled in the art without departing from the structure of the present invention, and these should also be considered as the scope of the present invention, which does not affect the effect of the implementation of the present invention and the utility of the patent. The protection scope of the present application shall be subject to the content of the claims, and the description of the specific embodiments and the like in the specification can be used for explaining the content of the claims.
Claims (8)
1. A mine disaster prediction and early warning method combining on-site monitoring and numerical simulation is characterized in that: the method comprises the following steps:
step a, monitoring piles are buried in a distributed mode in a region to be monitored, and the monitoring piles are connected with an early warning center through signals;
step b, acquiring historical geological data of a region to be monitored, and constructing a functional relation between the soil crack change rate and the vibration quantity and the deformation quantity by an early warning analysis module based on a gray prediction algorithm to obtain a mine disaster prediction model;
step c, the micro-seismic monitoring module acquires the vibration quantity in the mine and marks the vibration quantity as a first signal, the InSAR image monitoring module acquires the deformation quantity of a monitoring node and marks the deformation quantity as a second signal, and the monitoring pile acquires the soil crack change rate of a region to be monitored and marks the soil crack change rate as a third signal;
step d, the data processing module performs data preprocessing and optimization on the first signal, the second signal and the third signal;
step e, inputting the optimized first signal, the optimized second signal and the optimized third signal into a mine disaster prediction model to obtain risk degrees, and predicting the mine disaster according to the risk degrees;
and f, determining a risk area by the data acquisition module according to the node position of the abnormal monitoring data, and sending an early warning signal to perform early warning by the early warning analysis module according to the risk area and the risk degree.
2. The mine disaster prediction and early warning method combining on-site monitoring and numerical simulation according to claim 1, wherein the method comprises the following steps of: the mine disaster prediction and early warning method is based on a mine disaster early warning system for prediction and early warning, wherein the mine disaster early warning system comprises an early warning center and a plurality of monitoring piles which are arranged in a region to be monitored and used for monitoring the change rate of underground soil cracks of a mine:
the early warning center is used for inputting a mine disaster prediction model to calculate the risk degree according to the monitoring data of the area to be monitored, predicting and early warning the mine disaster based on the risk degree and the risk area, and comprises the following steps:
the data acquisition module is used for receiving the monitoring data of the monitoring pile, acquiring the position of the monitoring pile based on the RSSI ranging technology and the TOF ranging technology, wherein the monitoring pile is used as an independent monitoring node, the independent monitoring node forms a monitoring grid, and a risk area is determined according to the node position of the abnormal monitoring data;
the InSAR image monitoring module is used for acquiring image data of an area to be monitored in a preset time period and calculating deformation of a mine in a monitoring node range of an adjacent preset time period;
the microseism monitoring module is used for acquiring the vibration quantity generated by the fracture of the rock mass in the mine;
the data processing module is used for removing abnormal monitoring data and optimizing the data based on a particle swarm algorithm;
the storage module is used for storing the data monitored by the monitoring pile, the InSAR image monitoring module and the microseismic monitoring module;
the early warning analysis module is used for constructing a functional relation between the soil fracture change rate and the vibration quantity and the deformation quantity based on a gray prediction algorithm, obtaining a mine disaster prediction model, inputting the mine disaster prediction model to obtain a risk degree according to the monitoring data obtained by the monitoring pile, the deformation quantity obtained by the InSAR image monitoring module and the vibration quantity obtained by the micro-vibration monitoring module, and predicting the mine disaster according to the risk degree and sending early warning signals;
the monitoring pile comprises a pile body, a power supply module is arranged at the top of the pile body, a containing cavity is formed in the pile body and penetrates through the top of the pile body, a communication module, a pretreatment module and a supporting component are arranged in the containing cavity, a plurality of first sliding grooves and sliding holes are formed in the lower portion of the side wall of the pile body, a first elastic piece, a first strain gauge and a sliding block are sequentially connected in the first sliding grooves along the direction of the side wall of the pile body, a second sliding groove is communicated below the containing cavity, the supporting component comprises a compression bar longitudinally sliding along the containing cavity and the second sliding groove, a second strain gauge and a second elastic piece are sequentially connected at the bottom of the compression bar in a vertical direction, one end, far away from the second strain gauge, of the second elastic piece is fixedly connected with the bottom of the second sliding groove, a plurality of supporting bars are hinged in the middle of the compression bar, a limiting rod is hinged between the middle of each supporting bar and the containing cavity, a soil moisture sensor is arranged at the movable end of each supporting bar, the supporting bar can penetrate through the sliding holes to be inserted into underground soil, the monitoring pile is reinforced, the moisture content of soil around the pile body is monitored through the soil moisture sensor, and a locking component is arranged at the top of the compression bar;
the soil crack change rate is calculated by the pretreatment module according to the data of the soil moisture content sensor and the first strain gauge, constructing a functional relation between the soil moisture content and the soil cracks, and calculating the soil crack change rate.
3. The mine disaster prediction and early warning method combining on-site monitoring and numerical simulation according to claim 2, wherein the method comprises the following steps of: the locking assembly comprises a locking block and a third elastic piece which are vertically and sequentially arranged along the compression bar, the locking block is hinged to the upper portion of the side wall of the compression bar, the third elastic piece is sleeved on the upper portion of the compression bar, a first locking groove and a second locking groove are sequentially formed in the upper portion of the side wall of the accommodating cavity, the second locking groove is communicated with a release groove, the locking block is clamped in the first locking groove in an initial state, and the locking block is clamped in the second locking groove in a locking state.
4. The mine disaster prediction and early warning method combining on-site monitoring and numerical simulation according to claim 2, wherein the method comprises the following steps of: the top of the compression bar is fixedly connected with a sealing ring.
5. The mine disaster prediction and early warning method combining on-site monitoring and numerical simulation according to claim 2, wherein the method comprises the following steps of: the number of the first sliding grooves, the first elastic pieces, the first strain gages and the sliding blocks is 4.
6. The mine disaster prediction and early warning method combining on-site monitoring and numerical simulation according to claim 2, wherein the method comprises the following steps of: the data acquisition module is used for acquiring the positions of the monitoring nodes and comprises the following steps: when the distance between the monitoring nodes is 0-4m, measuring the distance between the monitoring nodes by adopting an RSSI ranging method; and when the monitoring node spacing exceeds 4m, measuring the monitoring node spacing by adopting a TOF method.
7. The mine disaster prediction and early warning method combining on-site monitoring and numerical simulation according to claim 2, wherein the method comprises the following steps of: the data processing module processes the monitoring data in the following steps: and adopting a Gaussian regression model to perform mean value processing on the data of the node positions.
8. The mine disaster prediction and early warning method combining on-site monitoring and numerical simulation according to claim 2, wherein the method comprises the following steps of: the data processing module is used for processing the monitoring data, and peak value filtering is carried out on the node position data after mean value processing by adopting a Kalman filtering algorithm.
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN117109427A (en) * | 2023-09-07 | 2023-11-24 | 陕西中岩物联信息科技有限公司 | Ground deformation monitoring system and method based on GNSS satellite positioning |
| CN117782226A (en) * | 2024-02-23 | 2024-03-29 | 四川省能源地质调查研究所 | Mine safety early warning system |
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Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN117109427A (en) * | 2023-09-07 | 2023-11-24 | 陕西中岩物联信息科技有限公司 | Ground deformation monitoring system and method based on GNSS satellite positioning |
| CN117782226A (en) * | 2024-02-23 | 2024-03-29 | 四川省能源地质调查研究所 | Mine safety early warning system |
| CN117782226B (en) * | 2024-02-23 | 2024-05-14 | 四川省能源地质调查研究所 | Mine safety early warning system |
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