CN117250670B - Detection capability assessment method, system and equipment of mine earthquake integrated monitoring station network - Google Patents
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Abstract
The invention discloses a detection capability assessment method, a detection capability assessment system and detection capability assessment equipment for an ore-earthquake integrated monitoring platform network, and relates to the field of seismic exploration. The method determines a confidence space based on the historical mine earthquake event catalogue; then calculating the maximum and minimum distances from each station to the confidence space according to the position information of each station in the station information catalog, and further calculating the single station detection capability of each station; according to the single station detection capability of each station, the detection probability of specific energy of the station network to the preselected layer of the communication space is calculated, and the minimum complete energy of the station network is calculated; and evaluating the detection capability of the station network according to the detection probability of the station network for the specific energy of the opposite space preselected layer and the minimum complete energy of the station network. According to the invention, objective historical mine earthquake event catalog data is used as calculation materials, and the mine earthquake detection capability is evaluated by counting whether each station participates in real mine earthquake event positioning, so that the method has stronger objectivity and can accurately evaluate the detection capability of the mine earthquake integrated monitoring station network.
Description
Technical Field
The invention relates to the technical field of seismic exploration in geophysical disciplines, in particular to a detection capability assessment method, a detection capability assessment system and detection capability assessment equipment for an integrated mining and earthquake monitoring table network.
Background
Rock burst is a dynamic phenomenon of sudden and severe damage of coal and rock mass around a roadway or a working surface due to instantaneous release of elastic strain energy, and is often accompanied by phenomena such as coal and rock mass throwing, ringing, air waves and the like. The underground engineering is the root cause of rock burst, and the underground engineering is excavated to lead to stress redistribution of surrounding rock, so that the surrounding rock is slowly deformed to accumulate elastic strain energy. The mining and earthquake integrated monitoring theory and the product are newer technologies which are introduced into mines from the field of seismic exploration of geophysical disciplines and developed, and the technologies perform rock burst early warning by collecting the fracture information (precursor information of accident occurrence) of rock mass, so that casualties are avoided and property loss is reduced. A common characteristic of the integrated monitoring product for mine and earthquake is that a mine and earthquake event catalog is generated, and the catalog is basic data for derivative researches such as rock burst trend early warning, vibration wave CT inversion, earthquake focus mechanism solution and the like. And the data quality of the mine earthquake event catalogue depends on the detection capability of the mine earthquake integrated monitoring station network to a great extent. Therefore, a method for objectively evaluating the detection capability of a platform network is needed in the art to meet the requirement of effectively laying an integrated monitoring system for mine and earthquake on site.
Disclosure of Invention
Aiming at the problems in the background art, the invention provides a detection capability assessment method, a detection capability assessment system and detection capability assessment equipment for an ore-earthquake integrated monitoring station network, so as to objectively and accurately assess the detection capability of the ore-earthquake integrated monitoring station network based on a historical ore-earthquake event catalog.
In order to achieve the above object, the present invention provides the following.
On one hand, the invention provides a detection capability assessment method of an ore-earthquake integrated monitoring station network, which comprises the following steps: determining a confidence space based on the historical mine earthquake event catalogue; the historical mine earthquake event catalogue comprises XYZ coordinate data representing the location of the mine earthquake event, energy of the mine earthquake event, average maximum amplitude of the mine earthquake event and a station used for positioning the mine earthquake event; calculating the maximum and minimum distances from each station to the confidence space according to the position information of each station in the station information catalog; calculating the single station detection capability of each station according to the maximum and minimum distances from each station to the confidence space; according to the single station detection capability of each station, the detection probability of specific energy of the station network to the communication space preselected layer is calculated in a dimension-reducing mode; calculating the minimum complete energy of the station network according to the detection probability of the station network for the specific energy of the pre-selected horizon in the opposite space; and evaluating the detection capability of the station network according to the detection probability of the station network for the specific energy of the opposite space preselected layer and the minimum complete energy of the station network.
Optionally, the determining the confidence space based on the historical mine earthquake event catalogue specifically includes: calculating the average value and standard deviation of X, Y and Z-column coordinate data representing the position of the mine earthquake event in the historical mine earthquake event catalogue; the upper and lower confidence interval limits for the three dimensions X, Y and Z are calculated from the average and standard of the X, Y and Z column coordinate data, respectively, to define the required confidence space.
Optionally, the calculating the single station detection capability of each station according to the maximum and minimum distances from each station to the confidence space specifically includes: for the first of the various stationsA station according to->Maximum and minimum distance of the individual station to the confidence space, screening out +.>The individual stations are used to calculate each +_ in the energy-distance space>A mine earthquake event set of the mine earthquake detection probability at the point; wherein->Represents energy, +.>Representing the distance; counting the +.f in the ore seismic event collection>The individual station detects and is not +.>The number of the mine earthquake events detected by each station is respectively recorded as N + And N _ The method comprises the steps of carrying out a first treatment on the surface of the Using the formula->Calculate->Personal station pair->Probability of mineral shock detection of a spot->As->Single station detection capability of individual stations.
Optionally, the method for calculating the detection probability of the specific energy of the station network to the communication space preselect horizon according to the detection capability dimension reduction of the single station of each station specifically comprises the following steps: using the formulaCalculating the detection probability of specific energy of the station network to the opposite space preselection layer; wherein->Represents->Single station detection capability of individual stations; />Represents->Probability of undetected by the individual stations; />Representing a station in the network; />Representing the probability that no station is able to detect; />Representative is only +.>Probability of detection by the individual stations; />Is->Station set detected simultaneously in seed arrangement combination mode, < >>For the number of detected stations; />Is the firstA set of other stations in a permutation and combination mode, < >>For an undetected number of stations; />Is a cumulative sign;preselecting coordinates in horizons for confidence space as +.>Is +.>Is simultaneously +.>Probability of detection by the individual station, +.>。
Optionally, the calculating the minimum complete energy of the station network according to the detection probability of the station network to the specific energy of the communication space pre-selected horizon specifically includes: using the formulaCalculating the minimum integrity energy of the network>The method comprises the steps of carrying out a first treatment on the surface of the Wherein->Representing a possible energy interval; />Representing the allowable energy error; />Representing taking the minimum value.
Optionally, the estimating the detection capability of the network according to the detection probability of the specific energy of the pre-selected horizon of the communication space of the network and the minimum complete energy of the network specifically includes: probability of detection of specific energy of station network versus communication space preselection horizonThe greater and minimum complete energy +.>The smaller the table network is, the stronger the detection capability of the table network to the mine earthquake event is。
On the other hand, the invention also provides a detection capability evaluation system of the mine earthquake integrated monitoring station network, which comprises the following components: the confidence space determining module is used for determining a confidence space based on the historical mine earthquake event catalogue; the historical mine earthquake event catalogue comprises XYZ coordinate data representing the location of the mine earthquake event, energy of the mine earthquake event, average maximum amplitude of the mine earthquake event and a station used for positioning the mine earthquake event; the maximum and minimum distance calculation module is used for calculating the maximum and minimum distances from each station to the confidence space according to the position information of each station in the station information catalog; the single station detection capability calculation module is used for calculating the single station detection capability of each station according to the maximum and minimum distances from each station to the confidence space; the station network detection probability calculation module is used for calculating the detection probability of specific energy of the station network relative to the pre-selected layer of the space according to the single station detection capability of each station; the station network minimum complete energy calculation module is used for calculating the station network minimum complete energy according to the detection probability of the station network to the communication space preselection horizon specific energy; and the station network detection capability evaluation module is used for evaluating the detection capability of the station network according to the detection probability of the station network for the specific energy of the opposite space preselected horizon and the minimum complete energy of the station network.
In still another aspect, the invention further provides an electronic device, which comprises a memory, a processor and a computer program stored in the memory and capable of running on the processor, wherein the detection capability evaluation method of the mine earthquake integrated monitoring station network is realized when the processor executes the computer program.
Optionally, the memory is a non-transitory computer readable storage medium.
According to the specific embodiments provided by the invention, the following technical effects are disclosed.
The invention provides a detection capability assessment method, a detection capability assessment system and detection capability assessment equipment for an ore-earthquake integrated monitoring platform network, which are characterized in that firstly, a confidence space is determined based on a historical ore-earthquake event catalogue; then, according to the position information of each station in the station information catalog, calculating the maximum and minimum distances from each station to the confidence space; calculating the single station detection capability of each station according to the maximum and minimum distances from each station to the confidence space; according to the single station detection capability of each station, the detection probability of specific energy of the station network to the communication space preselected layer is calculated in a dimension-reducing mode; calculating the minimum complete energy of the station network according to the detection probability of the station network for the specific energy of the pre-selected horizon in the opposite space; and evaluating the detection capability of the station network according to the detection probability of the station network for the specific energy of the opposite space preselected layer and the minimum complete energy of the station network. According to the invention, objective historical data is used as calculation materials, and the detection capability of the mine earthquake is evaluated by counting whether each station participates in real mine earthquake event positioning.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings that are needed in the embodiments will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
Fig. 1 is a flowchart of a detection capability evaluation method of an integrated mining-earthquake monitoring station network.
Fig. 2 is a schematic diagram of a detection capability of a BDS station in a coal mine according to an embodiment of the present invention.
FIG. 3 is a schematic diagram of the detection capabilities of an HDS station in a coal mine according to an embodiment of the present invention.
Fig. 4 is a schematic diagram of a detection capability of a certain coal mine XFJ station according to an embodiment of the present invention.
Fig. 5 is a probability diagram of detection of 5000J energy mine earthquake events at a-650 m horizon by a mine earthquake integrated monitoring station network pair provided by the embodiment of the invention.
Fig. 6 is a probability diagram of detection of a 2000J energy mine earthquake event at a-650 m horizon by a mine earthquake integrated monitoring station network pair provided by an embodiment of the invention.
Fig. 7 is a schematic diagram of minimum complete energy of a mine earthquake integrated monitoring station network pair-650 m horizon according to an embodiment of the invention.
Fig. 8 is a schematic diagram of minimum complete energy of a-630 m horizon of a mine earthquake integrated monitoring station network provided by an embodiment of the invention.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
The invention aims to provide a detection capability assessment method, a detection capability assessment system and detection capability assessment equipment for an ore-earthquake integrated monitoring platform network, so as to objectively and accurately evaluate the detection capability of the ore-earthquake integrated monitoring platform network based on a historical ore-earthquake event catalogue.
In order that the above-recited objects, features and advantages of the present invention will become more readily apparent, a more particular description of the invention will be rendered by reference to the appended drawings and appended detailed description.
Fig. 1 is a flowchart of a detection capability evaluation method of an integrated mining-earthquake monitoring station network. Referring to fig. 1, the detection capability assessment method of the mine earthquake integrated monitoring station network comprises steps 1 to 6.
Step 1: confidence spaces are determined based on the historical mine earthquake event catalogue.
The method of the invention evaluates the detection capability of the platform network based on statistical theory, and can calculate the minimum complete energy of the integrated monitoring platform network (platform network for short) for the mine earthquake at any position of the confidence space and the detection probability of the mine earthquake event at any position of the opposite confidence space according to the historical mine earthquake event catalogue. By the method, the corresponding index can be calculated and extracted so as to accurately evaluate the detection capability of the mine earthquake table network. Because the core of the method is data statistics, only the calculation result in the confidence space range is effective, and simultaneously, the required calculation force can be reduced by estimating the confidence space. The step 1 specifically includes:
step 1.1: the mean and standard deviation of X, Y and Z column coordinate data representing the location of the mine earthquake event in the historical mine earthquake event catalog are calculated.
Table 1 shows some of the mine earthquake data in the historical mine earthquake event catalog collected by the integrated mine earthquake monitoring system during the period of 1 day from 4 months of 2023 to 15 days of 4 months, and only some of the data are listed here for illustration due to the huge data volume.
As shown in table 1, the historical mine earthquake event catalog includes XYZ coordinate data representing the location of the mine earthquake event, energy of the mine earthquake event, average maximum amplitude of the mine earthquake event, and stations for locating the mine earthquake event.
Step 1.2: the upper and lower confidence interval limits for the three dimensions X, Y and Z are calculated from the average and standard of the X, Y and Z column coordinate data, respectively, to define the required confidence space.
Here, the space in the confidence space is a narrow space, that is, the XYZ three-dimensional space, and the required confidence space can be defined by calculating the upper and lower limits (6 numerical values) of the interval in three dimensions of X, Y, Z, respectively. Specifically, the upper and lower confidence interval limits for each direction are determined X, Y, Z according to a certain confidence interval coefficient, thereby determining the confidence space. For example, the confidence interval coefficients in the X and Y directions may be set to 1.96, and the confidence interval coefficient in the Z direction may be set to 1.6. Specifically, for a certain column of data in X, Y and Z-column coordinate data, the upper limit of the confidence interval thereof=the average value of the column coordinate data+the confidence interval coefficient×the standard deviation of the column coordinate data; confidence interval lower limit = mean value of the column of coordinate data-confidence interval coefficient x standard deviation of the column of coordinate data.
Step 2: and calculating the maximum distance and the minimum distance from each station to the confidence space according to the position information of each station in the station information catalogue.
The station information directory used in the present invention is shown in table 2, and the station information directory includes station names and corresponding position information of each station, and is represented by XYZ coordinate data.
The general idea of the step 2 is dicing and traversing, and the specific steps are as follows: step 2.1: dividing the confidence space into grids according to a fixed length (such as 1 m), and acquiring coordinate information of all grid nodes; step 2.2: traversing all grid nodes in the confidence space, and calculating the distance between the grid nodes and the selected station; step 2.3: storing each distance to obtain a distance list; step 2.4: finding the maximum and minimum distances from the distance list, namely the maximum distance and the minimum distance from the selected station to the confidence space; step 2.5: repeating the steps 2.2-2.4 to obtain the maximum and minimum distances from all the stations to the confidence space.
Step 3: and calculating the single station detection capability of each station according to the maximum and minimum distances from each station to the confidence space.
According to the historical mine earthquake event catalogue, an appropriate screening method is adopted, the detection probability of each station to mine earthquake events with different distances and different energies is counted to be used as the single station detection capability of each station, and the specific process comprises steps 3.1 to 3.4.
Step 3.1: partitioningAnd (5) a grid. Determining the distance scales of grids according to a certain grid distance according to the maximum and minimum distances from different stations to the confidence space calculated in the step 2; likewise, according to the confidence interval of the energy of the mine earthquake event, determining an energy scale according to a certain energy interval; thereby dividing +.>And (5) a grid.
The detection capability of a single station may be indicative ofIs a triplet (energy, distance, probability of detection) which is visually represented as shown in fig. 2 to 4. The relationship of the three quantities of the triplet may be understood as: probability =(energy, distance). Step 2 obtains the upper limit and the lower limit of the distance from each station to the confidence space, and the calculation can be simplified by dividing the upper limit and the lower limit into grids. The distance grid spacing is comprehensively determined according to the confidence space scale, the data size, the precision requirement and the computer computing power, and the numerical values of 10, 20, 50, 100 and the like can be generally selected. The maximum and minimum distances from a single station to the confidence space are the upper and lower limits of the coordinate values in the distance grid, and the value interval can be divided into (upper limit-lower limit)/interval values according to the grid interval, and the values are distance scales.
The energy confidence interval is the upper and lower limits of the energy scale. The certain energy interval is determined according to the magnitude of the energy confidence interval, and is generally determined in a segmented manner or determined by adopting log as a base. Taking segmentation determination as an example, the interval between the regional energy grids of 0-1000 joules can be selected to be 10 joules, the interval between the regional energy grids of 1000-10000 joules can be selected to be 50 joules, and the interval between the regional energy grids of more than 10000 joules can be selected to be 500 joules.
The distance scale and the energy scale are used for generating an empty table, the column coordinates of the table are distance scale values, the abscissa of the table is the energy scale value, and the generated empty table isAnd (5) a grid. />The grid (table) acts as a template and the corresponding detection probability values are subsequently calculated to fill the grid.
Step 3.2: and (5) screening data. The purpose is to screen out the stations for calculating distanceKilometers, energy of +.>The actual ore shock event used in the detection probability of the ore shock event of joules is shown in a screening formula (1).
（1）。
In the formula (1),is the average maximum amplitude; />To assume the distance of the mine earthquake event from the station; />The distance between the real mine earthquake event and the station is the distance between the real mine earthquake event and the station; />To hypothesize the energy of the mine earthquake event; />Is the energy of a real mine earthquake event; />To assume the energy difference between the mine earthquake event and the real mine earthquake event; />In order to assume that the maximum amplitude of the mine earthquake event is the same as that of the real mine earthquake event, the energy difference caused by different earthquake source distances is caused; />Is an allowable error. />And->Fitting values for magnitude-energy; />Parameters that are gauge functions; />For the station correction values, these 4 parameters need to be measured according to the mine practice. Taking a certain mine as an example, the values of the four parameters are 11.13, 1.4, 0.61 and 0.05 respectively.
When more than 10 ore earthquake events exist in the ore earthquake event list, the method satisfiesWhen the system is used, the station pair distance can be calculated according to the mine earthquake event catalogue>Kilometers, energy of +.>Probability of detection of a joule mine seismic event.
Step 3.3: a single station detection capability is calculated. TraversingEach discrete point of the grid acquires energy and distance information thereof; substituting the energy information and the distance coordinates into a data screening formula (1) to determine a mine earthquake event set which can be used for calculating the detection probability.
In particular for selected stationsEach blank point in the grid will acquire an energy +.>Sum distanceSubstituting them into +.>And->. Traversing the mine earthquake event list, substituting the distance from each mine earthquake event to the selected station into +.>Substituting the average maximum amplitude into +.>Substituting energy into +.>. Thus, each mine earthquake event calculates one，/>Satisfy condition->The mine earthquake event sets used for calculating the probability of a certain blank grid point of the selected station can be formed.
Screening out selected stations (e.g. the first of the stations)Individual station) for calculating each +.>After the mineral earthquake event set with the point detection probability, counting the number of the mineral earthquake events detected by the selected station and the mineral earthquake events detected by the unselected station in the mineral earthquake event set, and respectively marking the number as N + And N _ . Then single station pair->The calculation of the mining vibration detection probability of the point is shown in a formula (2).
（2）。
Wherein the method comprises the steps ofIndicating that the selected station pair occurs at a distance of +.>Is +.>And the detection probability of the mine earthquake event is taken as the single station detection capability of the selected station. The invention will be at->Personal station pair->Probability of mineral shock detection of a spot->Marked as->。
Step 3.4: the results are rationalized. The closer to the station, the more energetic the mine earthquake event should be detected, the greater the probability of the propagation and attenuation law of the vibration wave should be taken into account.
In the case of 50m mesh distance interval and 1000J energy interval, taking a certain coal mine BDS, HDS and XFJ station as examples, the probability map of detection of the station can be plotted as shown in fig. 2, 3 and 4, respectively. The detection probability map is a visual display of a (energy, distance and detection probability) table, and the detection capability of the station network where the station is located can be calculated by extracting a certain index through the visual display.
Step 4: and (3) calculating the detection probability of specific energy of the station network to the communication space preselected layer according to the single station detection capability of each station.
The final calculation result in step 3 is a set of five-dimensional dataRespectively including spatial three-dimensional coordinate information representing a position +.>Energy representing +.>And +.>，/>Is->Is a shorthand for (2).The three-dimensional coordinates of the space grid nodes are divided according to the confidence space. />Is the energy node (energy scale) that the energy confidence interval demarcates. />Indicating that the station is located +.>The energy of the dot is +.>Is a detection probability of a mine earthquake event. Wherein (1)>Is the value that the traversal is required to be, is the input quantity (or called the hypothesis quantity). In order to facilitate the display of results, the extraction of indexes and the saving of calculation power, the method of the invention selects to fix the energy or the detection probability on the basis of reducing one dimension (fixed height z) in space so as to obtain a group of three-dimensional data, such as->Or->. In step 4, the space is reduced from three dimensions to two dimensions, and the continuous two-dimensional plane is divided into discrete points by using a grid division method, and the specific steps comprise steps 4.1 to 4.4.
Step 4.1: determining a horizon in which the calculation result needs to be acquired. To facilitate result display and index extraction, a certain horizon in space is selected for calculation, e.g. a certain mine is taken as an example to determine that the calculated horizon is-650 m, i.e. the horizon is as followsPlane slices with coordinates (elevations) in confidence space.
Step 4.2: the grid spacing is determined. The continuous calculation area in the confidence space is divided into discrete grid points according to specific grid intervals, and the larger the grid interval is, the lower the calculation complexity is, for example, the grid interval is determined to be 50m by taking a certain mine as an example.
Since a certain elevation has been selected in step 4.1, i.e. fixedIs->. Thus, the plane space coordinates can be used +.>Expressed, for example, a square with a side length of 10 ranging from (0, 0) to (10, 10) will +.>And->The plane is divided into 10×10 meshes according to the interval thereof divided by the mesh pitch of 1.
Specifically, assume that the confidence space range isTo->Assuming that the preselected horizon is，/>Between->And->After the confidence space is reduced in dimension, let +.>After that, the confidence space becomes a two-dimensional planar space +.>To->. The two-dimensional plane space is defined as +.>By dividing, a distance table as shown in table 3 can be obtained.
The invention uses the idea of fixed variable to fix spaceCoordinates and one of energy and detection probability so that a planar thermodynamic diagram can be used to represent the detection capabilities of the table network.
Step 4.3: calculating a distance table of confidence space preselected horizon grid points and different stations. Obtaining coordinates of all grid points, i.e. a set of +.>Data. Calculating each station to the group based on the position information of the different stations in Table 2>Distance L of data points, generating for each station a corresponding +.>A table.
Step 4.4: the probability of detection of specific energy of the station network to the opposing spatially preselected layer is calculated as shown in equation (3).
（3）。
Wherein the method comprises the steps ofRepresents->Single-station detection capability of individual stations, abbreviated as +.>；/>Represents->The probability of undetectable by the individual station, abbreviated +.>；/>Representing the number of stations in a networkAn amount of; />Representing the probability that no station is able to detect; />Representative is only +.>The probability of detection by an individual station, abbreviated +.>；Is->Station set detected simultaneously in seed arrangement combination mode, < >>For the number of detected stations; />Is->A set of other stations in a permutation and combination mode, < >>For an undetected number of stations; />Is a cumulative sign; />Preselecting coordinates in horizons for confidence space as +.>Is +.>Is simultaneously +.>Probability of detection by the individual station, +.>。
The specific calculation process is as follows: first, according to、/>And the calculation result of step 4.3, generating +.>The coordinate scale is a column label, in order of +>The coordinate scale is a line label, and the numerical value in the table is +.>And->Is a grid of (c) a plurality of grids. Then, all points in the grid are calculated to be simultaneously 0 to +.>The probabilities detected by the individual stations are combined into a corresponding grid. Finally, the coordinates in the confidence space preselection horizon are calculated as +.>Is +.>Is also +.>Probability of detection by an individual station +.>And generates a corresponding grid.
For ease of understanding, the following description is given by way of example: 1) Assume that=5 i.e. 5 stations in the network, let +.>=3, i.e. calculate the probability of being detected simultaneously by 3 stations +.>. 2) Is all->Combinations 123, 124, 125, 134, 135, 145, 234, 235, 245, 345. 3) Here, taking the example of detection by station No. 123 only, the probability thereof is calculated as +.>. 4) Repeating step 3), in this example a total of 10 such probabilities can be calculated, which are added to obtain the probability that only 3 stations are simultaneously detecting +.>. 5) Similarly, the probability of being detected by 1 and 2 stations simultaneously can also be obtained>And->。
Taking a certain mine as an example, under the condition that the pre-selected horizon-650 m horizons and the grid spacing are 50m, the detection probability of the table network to 5000J and 2000J mine earthquake events is calculated respectively, and then the figures 5 and 6 can be obtained. The abscissa of FIGS. 5 and 6 isThe value in the figure is the calculated detection probability +.>。
Step 5: and calculating the minimum complete energy of the station network according to the detection probability of the station network for the specific energy of the opposite space preselected horizon.
The method is characterized in that the detection capability of the station network is calculated, the probability that the mine earthquake time is at least detected by a fixed number of stations is calculated by using the single station detection capability calculated in the prior art by using a permutation and combination method, so that the detection probability of the station network on specific energy is obtained, and then the energy with the detection probability larger than the specific probability at each grid point can be extracted as the minimum integral energy of the grid point. This particular probability may be set to 0.1 or 0.01.
The calculation of the minimum complete energy of the station network is shown in formula (4).
（4）。
Wherein the method comprises the steps ofPreselecting the coordinates in the horizon for the station network relative to the space>Minimum energy of grid point positions under the condition of meeting a neglected-recording threshold level, namely minimum complete energy of a station network; />Representing a possible energy interval; />Representing the allowable energy error; />Representing taking the minimum value.
The invention uses the mode of combining accumulation and multiplication, firstly calculates that the specific mining earthquake event is covered and only covered by 0,1 and 2 … in the table networkThe probability of detection by the individual stations then calculates that the specific mine earthquake event is at least +.>The probability of detection by each station is further determined, an energy confidence interval is further determined, a traversing energy list is generated according to fixed intervals, and the minimum complete energy of the station network for each position of the preselected horizon is obtained through traversing the energy list. The specific calculation steps are as follows: first, the energy error (i.e. the distance over which energy needs to be traversed) is determined>And the upper and lower limits of the energy interval, and generates an energy list for traversal. Then, the detection probability of the traversing energy of different grid points is calculated according to the step 4 according to the order of the energy from small to large. Finally, each grid point is selected to have the detection probability of more than 1-/or less>Is the minimum full energy of the grid point. Taking a certain mine as an example, under the condition that the grid spacing is 50m, calculating the minimum complete energy of the table network to the-650 m horizon and the-630 m horizon respectively, and obtaining the figures 7 and 8. The abscissa of FIGS. 7 and 8 is +.>The values in the figure are calculated minimum complete energy +.>。
Step 6: and evaluating the detection capability of the station network according to the detection probability of the station network for the specific energy of the opposite space preselected layer and the minimum complete energy of the station network.
The invention adopts a selection method of quantitative indexes of comparison evaluation, can analyze whether the key monitoring area coincides with the area with strong detection capability of the station network, whether the layout mode of the station network is reasonable, and can evaluate the detection capability of different mine station networks, and is specifically expressed as follows: on the premise of determining a key monitoring area, the average value of the detection probability and the minimum integral energy of the specific energy of the key monitoring area of the station network is extracted as an index, and the detection capability is stronger when the detection probability of the specific energy mine earthquake event is larger and the minimum integral energy is smaller.
The calculation result of the method can be used for evaluating the detection capability of the platform network to different areas, the detection capability of different platform network layout schemes and the detection capability of different mine platform networks, and specifically comprises the steps 6.1 to 6.3.
Step 6.1: the detection capability of the network for different areas is evaluated. Probability of detection of specific energy in a region of a preselected horizon in a phase space by a networkGreater, minimum full energy +.>The smaller the representative network is, the more capable the network is to detect a mine seismic event occurring in the area.
Step 6.2: the detection capabilities of the different station network layout schemes are evaluated. Firstly, determining an important monitoring area, and calculating the detection probability and the minimum complete energy of the important monitoring area on specific energy under different station network design schemes by changing the position of a station. Likewise, the greater the probability of detection of a mine earthquake event occurring in a key area and the smaller the minimum complete energy, the better the table mesh design scheme.
Step 6.3: the detection capabilities of the different mine desks were evaluated. Firstly, key monitoring areas of all mines are required to be determined, and the detection probability and the minimum complete energy of the key monitoring areas of all the mines for specific energy are calculated respectively. The detection capability of the tables of different mines can be ranked by comparing the two indexes.
The invention provides a complete set of methods from confidence space determination, single station detection capability calculation, dimension reduction calculation space, station network detection capability calculation to station network detection capability evaluation. According to the method, according to the existing mine earthquake event catalogue data, a probability statistical method is adopted to objectively evaluate the historical detection capability of different areas, different layout schemes and different mine tables, and a reliable numerical basis is provided for equipment investigation and table optimization. The specific advantages include: (1) the objectivity is strong, and the accuracy is high; according to the method, objective historical data are used as calculation materials, and the detection capability of each station is evaluated by counting whether each station participates in real mine earthquake event positioning; (2) the guidance on the table mesh is strong; the detection capability of different table mesh layout schemes on key monitoring areas is compared, so that the table mesh layout schemes can be compared and optimized; (3) the use is simple, and the application range is wide; the necessary basic data used by the method are common mine earthquake event catalogues and station information catalogues, and the data acquisition is extremely simple; because of the easy acquisition of the data, the method can be integrated into most of the existing mining-earthquake integrated monitoring systems to evaluate the detection capability of the mining-earthquake integrated monitoring station network.
Based on the method provided by the invention, the invention also provides a detection capability assessment system of the mine earthquake integrated monitoring station network, which comprises the following modules.
The confidence space determining module is used for determining a confidence space based on the historical mine earthquake event catalogue; the historical mine earthquake event catalogue comprises XYZ coordinate data representing the location of the mine earthquake event, energy of the mine earthquake event, average maximum amplitude of the mine earthquake event and a station used for locating the mine earthquake event.
And the maximum and minimum distance calculation module is used for calculating the maximum and minimum distances from each station to the confidence space according to the position information of each station in the station information catalog.
And the single station detection capability calculation module is used for calculating the single station detection capability of each station according to the maximum and minimum distances from each station to the confidence space.
And the station network detection probability calculation module is used for calculating the detection probability of specific energy of the station network relative to the pre-selected layer in the space according to the single station detection capability of each station.
And the station network minimum complete energy calculating module is used for calculating the station network minimum complete energy according to the detection probability of the station network to the specific energy of the pre-selected horizon of the communication space.
And the station network detection capability evaluation module is used for evaluating the detection capability of the station network according to the detection probability of the station network for the specific energy of the opposite space preselected horizon and the minimum complete energy of the station network.
Further, the present invention also provides an electronic device, which may include: a processor, a communication interface, a memory, and a communication bus. The processor, the communication interface and the memory complete communication with each other through a communication bus. The processor may call a computer program in the memory to perform the method of detection capability assessment of the mine earthquake integrated monitoring station network.
Furthermore, the computer program in the above-described memory may be stored in a non-transitory computer readable storage medium when it is implemented in the form of a software functional unit and sold or used as a separate product. Based on this understanding, the technical solution of the present invention may be embodied essentially or in a part contributing to the prior art or in the form of a software product stored in a storage medium, comprising several instructions for causing a computer device (which may be a personal computer, a server or a network device, etc.) to perform all or part of the steps of the method according to the embodiments of the present invention. And the aforementioned storage medium includes: various media capable of storing program codes, such as a U disk, a mobile hard disk, a read-only memory, a random access memory, a magnetic disk or an optical disk.
In the present specification, each embodiment is described in a progressive manner, and each embodiment is mainly described in a different point from other embodiments, and identical and similar parts between the embodiments are all enough to refer to each other. For the system disclosed in the embodiment, since it corresponds to the method disclosed in the embodiment, the description is relatively simple, and the relevant points refer to the description of the method section.
The principles and embodiments of the present invention have been described herein with reference to specific examples, the description of which is intended only to assist in understanding the methods of the present invention and the core ideas thereof; also, it is within the scope of the present invention to be modified by those of ordinary skill in the art in light of the present teachings. In view of the foregoing, this description should not be construed as limiting the invention.
Claims (8)
1. The method for evaluating the detection capability of the mine earthquake integrated monitoring station network is characterized by comprising the following steps of:
determining a confidence space based on the historical mine earthquake event catalogue; the historical mine earthquake event catalogue comprises XYZ coordinate data representing the location of the mine earthquake event, energy of the mine earthquake event, average maximum amplitude of the mine earthquake event and a station used for positioning the mine earthquake event;
calculating the maximum and minimum distances from each station to the confidence space according to the position information of each station in the station information catalog;
calculating the single station detection capability of each station according to the maximum and minimum distances from each station to the confidence space;
the calculating the single station detection capability of each station according to the maximum and minimum distances from each station to the confidence space specifically comprises the following steps:
for the first of the various stationsA station according to->Maximum and minimum distance of the individual station to the confidence space, screening out +.>The individual stations are used to calculate each +_ in the energy-distance space>A mine earthquake event set of the mine earthquake detection probability at the point; the screening formula is +.>The method comprises the steps of carrying out a first treatment on the surface of the Wherein (1)>Is the average maximum amplitude; />To assume the distance of the mine earthquake event from the station; />The distance between the real mine earthquake event and the station is the distance between the real mine earthquake event and the station; />To hypothesize the energy of the mine earthquake event; />Is the energy of a real mine earthquake event; />To assume the energy difference between the mine earthquake event and the real mine earthquake event; />In order to assume that the maximum amplitude of the mine earthquake event is the same as that of the real mine earthquake event, the energy difference caused by different earthquake source distances is caused; />Is an allowable error; />And->Fitting values for magnitude-energy; />Parameters that are gauge functions; />Correcting values for the station;
counting the quilt in the ore vibration event collectionThe individual station detects and is not +.>The number of mine earthquake events detected by each station is respectively marked as +.>And->；
Using the formulaCalculate->Personal station pair->Probability of mineral shock detection of pointsAs->Single station detection capability of individual stations;
according to the single station detection capability of each station, the detection probability of specific energy of the station network to the communication space preselected layer is calculated in a dimension-reducing mode;
calculating the minimum complete energy of the station network according to the detection probability of the station network for the specific energy of the pre-selected horizon in the opposite space;
and evaluating the detection capability of the station network according to the detection probability of the station network for the specific energy of the opposite space preselected layer and the minimum complete energy of the station network.
2. The method for evaluating the detection capability of the mine earthquake integrated monitoring station network according to claim 1, wherein the determining the confidence space based on the historical mine earthquake event catalogue specifically comprises:
calculating the average value and standard deviation of X, Y and Z-column coordinate data representing the position of the mine earthquake event in the historical mine earthquake event catalogue;
the upper and lower confidence interval limits for the three dimensions X, Y and Z are calculated from the average and standard of the X, Y and Z column coordinate data, respectively, to define the required confidence space.
3. The method for evaluating the detection capability of the mine earthquake integrated monitoring station network according to claim 2, wherein the step of calculating the detection probability of the station network to the specific energy of the opposite space preselected horizon according to the detection capability of the single station of each station is specifically comprised of:
using the formulaCalculating the detection probability of specific energy of the station network to the opposite space preselection layer; wherein->Represents->Single station detection capability of individual stations; />Represents->Probability of undetected by the individual stations; />Representing the number of stations in the network; />Representing the probability that no station is able to detect; />Representative is only +.>Probability of detection by the individual stations; />Is->Station set detected simultaneously in seed arrangement combination mode, < >>For the number of detected stations; />Is->A set of other stations in a permutation and combination mode, < >>For an undetected number of stations; />Is a cumulative sign; />Preselecting coordinates in horizons for confidence space as +.>Is +.>Is simultaneously +.>Probability of detection by the individual station, +.>。
4. The method for evaluating the detection capability of the mine earthquake integrated monitoring station network according to claim 3, wherein the calculating the minimum complete energy of the station network according to the detection probability of the station network to the specific energy of the opposite space preselected horizon specifically comprises the following steps:
using the formulaCalculating minimum complete energy of table networkThe method comprises the steps of carrying out a first treatment on the surface of the Wherein->Representing a possible energy interval; />Representing the allowable energy error; />Representing taking the minimum value.
5. The method for evaluating the detection capability of the mine earthquake integrated monitoring station network according to claim 4, wherein the method for evaluating the detection capability of the station network according to the detection probability of the station network for the specific energy of the opposite space preselected horizon and the minimum complete energy of the station network specifically comprises the following steps:
probability of detection of specific energy of station network versus communication space preselection horizonLarger and minimum full energyThe smaller the table network is, the stronger the detection capability of the table network to the mine earthquake event is.
6. The utility model provides a detection ability evaluation system of integration monitoring platform net is shaken to ore deposit which characterized in that includes:
the confidence space determining module is used for determining a confidence space based on the historical mine earthquake event catalogue; the historical mine earthquake event catalogue comprises XYZ coordinate data representing the location of the mine earthquake event, energy of the mine earthquake event, average maximum amplitude of the mine earthquake event and a station used for positioning the mine earthquake event;
the maximum and minimum distance calculation module is used for calculating the maximum and minimum distances from each station to the confidence space according to the position information of each station in the station information catalog;
the single station detection capability calculation module is used for calculating the single station detection capability of each station according to the maximum and minimum distances from each station to the confidence space;
the calculating the single station detection capability of each station according to the maximum and minimum distances from each station to the confidence space specifically comprises the following steps:
for the first of the various stationsA station according to->Maximum and minimum distance of the individual station to the confidence space, screening out +.>The individual stations are used to calculate each +_ in the energy-distance space>A mine earthquake event set of the mine earthquake detection probability at the point; the screening formula is +.>The method comprises the steps of carrying out a first treatment on the surface of the Wherein (1)>Is the average maximum amplitude; />To assume the distance of the mine earthquake event from the station; />The distance between the real mine earthquake event and the station is the distance between the real mine earthquake event and the station; />To hypothesize the energy of the mine earthquake event; />Is the energy of a real mine earthquake event; />To assume the energy difference between the mine earthquake event and the real mine earthquake event; />In order to assume that the maximum amplitude of the mine earthquake event is the same as that of the real mine earthquake event, the energy difference caused by different earthquake source distances is caused; />Is an allowable error; />And->Fitting values for magnitude-energy; />Parameters that are gauge functions; />Correcting values for the station;
counting the quilt in the ore vibration event collectionThe individual station detects and is not +.>The number of mine earthquake events detected by each station is respectively marked as +.>And->；
Using the formulaCalculate->Personal station pair->Probability of mineral shock detection of pointsAs->Single station detection capability of individual stations;
the station network detection probability calculation module is used for calculating the detection probability of specific energy of the station network relative to the pre-selected layer of the space according to the single station detection capability of each station;
the station network minimum complete energy calculation module is used for calculating the station network minimum complete energy according to the detection probability of the station network to the communication space preselection horizon specific energy;
and the station network detection capability evaluation module is used for evaluating the detection capability of the station network according to the detection probability of the station network for the specific energy of the opposite space preselected horizon and the minimum complete energy of the station network.
7. An electronic device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, wherein the processor, when executing the computer program, implements the method for evaluating the detection capability of the mine earthquake integrated monitoring station network according to any one of claims 1-5.
8. The electronic device of claim 7, wherein the memory is a non-transitory computer readable storage medium.
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