CN114264788B - Method for judging degree of correlation between different areas of working face and spontaneous combustion of coal - Google Patents
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Abstract
The invention discloses a judging method for the degree of correlation between different areas of a working surface and spontaneous combustion of coal, and relates to the field of prevention and control of spontaneous combustion of coal in goafs. The method continuously collects CO and O in different areas of the working surface 2 Concentration and then CO and O are converted using wavelet 2 Performing multi-scale evolution characteristic analysis on the concentration to obtain main periods and wavelet coefficients of the concentration of CO and O2 under different characteristic time scales; next, a sine wave is selected to fit CO and O 2 Wavelet coefficients at the first main period to obtain CO and O 2 Wave equation of wavelet coefficients; finally, obtaining CO and O according to wave equation 2 The phase difference and the initial amplitude are compared to obtain the relation between different areas and the coal spontaneous combustion relativity. The method is convenient to operate, can be used for guiding the emphasis point of gas monitoring at different stages of the working surface by judging the correlation degree between different regions of the working surface and the spontaneous combustion of coal, avoids the occurrence of redundant information, improves the spontaneous combustion control efficiency of the coal, and is more beneficial to preventing the occurrence of fire.
Description
Technical Field
The invention relates to a method for judging the degree of correlation between areas and coal spontaneous combustion, which is particularly suitable for judging the degree of correlation between different areas of a working face and coal spontaneous combustion, and belongs to the technical field of monitoring of working face gas concentration.
Background
Under the coal mine, spontaneous combustion of coal is one of disasters affecting safe stoping of a working face, and different areas of the working face all contain residual coal, so that due to the influences of ventilation, mining, pressure and the like, the oxidation degree of the residual coal in different areas is different, if fire prevention measures are taken indiscriminately, resource waste can be caused, and the spontaneous combustion prevention and control efficiency of the coal is low.
Oxygen is consumed by the residual coal to produce CO and the like, thus O 2 And the CO concentration can reflect the degree of spontaneous combustion of the coal. At present, the industrial site is mainly used for analyzing O 2 And the absolute concentration of CO and the change rate of the absolute concentration of CO determine whether spontaneous combustion of coal occurs in the monitoring area, but the reliability of the monitoring area or the correlation degree of the spontaneous combustion of the coal is not determined, so that the traditional method has blindness and limitation. For controlling gas, high-pumping channels are arranged on some working surfaces, and CO and O in the high-pumping channels are analyzed simultaneously 2 Concentration, and the spontaneous combustion degree of the coal was analyzed. In fact, whether the association between the gas in the high-suction roadway and the spontaneous combustion of the coal is tight or not and whether the association degree is strong or weak or not are not verified. Second, existing relying on O 2 The concentration division goaf coal spontaneous combustion three-zone method only can obtain a fuzzy dangerous area range, is a dangerous area distributed along the inclined direction of the working face, and can obtain a more accurate dangerous area if the dangerous area along the trend is obtained and overlapped. Therefore, the gas concentration after different brackets can be analyzed to obtain the correlation degree sequence of the gas concentration and the spontaneous combustion of the coal, and the final spontaneous combustion dangerous area of the coal can be obtained by combining three-zone division.
Therefore, in view of the above problems, it is necessary to provide a more reasonable and effective method to quickly and accurately determine the correlation degree between different areas of the working surface and spontaneous combustion of coal, so as to provide a basis for dividing spontaneous combustion areas of coal of the working surface and managing disasters, and ensure safe production of coal mines.
Disclosure of Invention
Aiming at the defects of the prior art, a more reasonable and effective method is provided to quickly and accurately determine the correlation degree between different areas of the working face and the spontaneous combustion of coal, provide basis for the division of the spontaneous combustion areas of the coal of the working face and disaster management, and ensure the safety production of the coal mine.
In order to achieve the above purpose, the method for judging the degree of correlation between different areas of the working surface and the spontaneous combustion of coal according to the invention is characterized in that: by continuously collecting workersCO and O in different areas of the working surface 2 Concentration information of (2) and then using wavelet transform to collect CO and O 2 Performing multiscale evolution feature analysis on the concentration information to obtain CO and O in each region under different feature time scales 2 A main period of the concentration and a wavelet coefficient; then selecting sine wave to fit CO and O 2 Wavelet coefficients at the first main period to obtain CO and O 2 Wave equation of wavelet coefficients; finally deriving CO and O from wave equation 2 The phase difference and the initial amplitude are compared to obtain the relation between different areas and the coal spontaneous combustion relativity.
Further, CO and O in the working surface are continuously collected 2 Different areas of concentration information include: inside the upper corner pocket wall, outside the upper corner pocket wall, high-level drainage lane and goaf, and CO and O inside the goaf and the upper corner pocket wall are monitored with emphasis 2 Is a gas concentration of (a).
The method specifically comprises the following steps:
step one, collecting O in different areas of underground stope face 2 And CO, and analyzing the collected different areas O 2 The different areas comprise an upper corner bag sub-wall, a high pumping lane and a goaf;
step two, based on wavelet transformation, pair O 2 And CO concentration to obtain O in different areas of the stope 2 Wavelet variance curve and wavelet coefficient cloud graph of CO concentration;
step three, according to different areas O of the stope face 2 Wavelet variance curve of CO concentration to obtain each region O 2 A characteristic time scale corresponding to a main period of CO;
step four, according to different areas O of the stope face 2 The wavelet coefficient cloud graph of the CO concentration comprises a plurality of main periods, a characteristic scale corresponding to the maximum wavelet variance is extracted as a first main period, and the wavelet coefficients of O2 and CO and corresponding sampling time are obtained under the first main period;
step five, utilizing sine function to make O 2 Fitting with wavelet coefficient under first main period of CO to obtain twoWave equation of the person;
step six, according to O 2 And the wave equation of the CO wavelet coefficient to obtain corresponding primary amplitude and primary phase difference;
step seven, judging the degree of correlation between different areas and the spontaneous combustion of the coal according to the change conditions of the initial amplitude and the initial phase difference, if CO and O 2 The larger the primary amplitude difference, the more significant the change in the two gases, and the higher the correlation between the region and spontaneous combustion of the coal is judged.
Further, in step one O 2 And a gas sampling period of CO of at least 1 month.
Further, in the second step, the basis function of the wavelet transform is a Morlet wavelet function.
Further, in the fifth step, the equation of the sine function is y=y 0 +Asin((x-x c ) Pi/omega), where y 0 The primary vibration of the wave, A is amplitude, omega is angular velocity, x c Is a known quantity.
Further, the goafs behind the hydraulic supports are divided according to the positions of the hydraulic supports, and the coal spontaneous combustion dangerous areas can be accurately divided by analyzing the correlation degree of the goafs corresponding to the different hydraulic supports and coal spontaneous combustion and combining the three coal spontaneous combustion zones, and the concrete steps are as follows:
s1, arranging a beam tube in a goaf behind a working face hydraulic support;
s2, collecting goaf gas by using the existing beam tube automatic sampling device and monitoring system, and carrying out O 2 And CO concentration analysis;
s3, dividing three spontaneous combustion zones of coal by using oxygen concentration, wherein the dividing indexes are 15% and 5%, more than 15% of the zones are heat dissipation zones, less than 5% of the zones are choking zones, and an oxidation zone is arranged between the zones;
s4, determining the correlation degree between the area behind each bracket and the spontaneous combustion of coal by fitting to obtain initial amplitude parameters and initial phase difference parameters in the wave equation, and sequencing; specifically, hydraulic supports arranged in the oxidation zone range are screened, and the probability ranking of coal spontaneous combustion is represented by ranking of the correlation degree of each support region and coal spontaneous combustion.
A hydraulic support is provided with A,The cross areas of the B and C groups and the oxidation zone are respectively an area 1, an area 2 and an area 3, if the relevance degree of the area corresponding to the three groups of hydraulic supports and the spontaneous combustion of coal is ranked as R A >R C >R B It is explained that the probability of spontaneous combustion of coal is greatest in zone 1, and secondly, zone 3 is smallest in zone 2.
The beneficial effects are that: the invention provides the concept of the correlation degree between different areas of the working surface and the spontaneous combustion of coal for the first time. The method is convenient to operate, not only can detect the gas concentration and the change condition of different areas of the working surface, but also can sort the correlation degree between different areas of the working surface and the spontaneous combustion of coal according to the multi-scale evolution characteristics of the gas concentration, and is used for guiding the precise control of the spontaneous combustion of the coal of the working surface, and can accurately divide the spontaneous combustion danger area of the coal according to the correlation degree and the three-band distribution of the spontaneous combustion of the coal, thereby being beneficial to preventing the spontaneous combustion disaster of the coal and taking targeted treatment measures after the disaster occurs.
Drawings
Fig. 1 is a cloud of CO wavelet coefficients within a bag sub-wall in an embodiment of the invention.
FIG. 2 shows O in a pocket wall according to an embodiment of the invention 2 Wavelet coefficient cloud.
Fig. 3 is a graph of CO wavelet variance within a bag sub-wall in an embodiment of the invention.
FIG. 4 shows O in a pocket wall according to an embodiment of the invention 2 Wavelet variance diagram.
FIG. 5 shows CO and O in the pouch wall according to an embodiment of the present invention 2 A schematic of a wavelet coefficient fluctuation curve at a first main period.
Fig. 6 is a cloud of CO wavelet coefficients outside the bag wall in an embodiment of the invention.
FIG. 7 shows the outside O of the pocket wall in an embodiment of the invention 2 Wavelet coefficient cloud.
Fig. 8 is a graph of CO wavelet variance outside the bag wall in an embodiment of the invention.
FIG. 9 shows the outside O of the pocket wall in an embodiment of the invention 2 Wavelet variance diagram.
FIG. 10 shows a specific embodiment of the present inventionExample bag wall exterior CO and O 2 A wavelet coefficient fluctuation curve at a first main period.
Fig. 11 is a cloud graph of CO wavelet coefficients for a high-pumping lane in an embodiment of the present invention.
FIG. 12 shows a high-pumping roadway O in an embodiment of the invention 2 Wavelet coefficient cloud.
Fig. 13 is a graph of CO wavelet variance for a high-pumping lane in an embodiment of the invention.
FIG. 14 shows a high-pumping roadway O in an embodiment of the invention 2 Wavelet variance diagram.
Fig. 15 is a schematic view of wavelet coefficient fluctuation curves under the first main period of the high-pumping roadway CO according to an embodiment of the present invention.
FIG. 16 shows a high-pumping roadway O in an embodiment of the invention 2 A schematic of a wavelet coefficient fluctuation curve at a first main period.
Fig. 17 is a cloud graph of goaf CO wavelet coefficients in an embodiment of the present invention.
FIG. 18 shows goaf O in an embodiment of the invention 2 Wavelet coefficient cloud diagram.
Fig. 19 is a graph of CO wavelet variance in goaf in an embodiment of the invention.
FIG. 20 shows goaf O in an embodiment of the invention 2 Wavelet variance diagram.
Fig. 21 is a schematic view of wavelet coefficient fluctuation curves under the first main cycle of the goaf CO according to an embodiment of the present invention.
FIG. 22 shows goaf O in an embodiment of the invention 2 A schematic of a wavelet coefficient fluctuation curve at a first main period.
FIG. 23 shows CO and O according to an embodiment of the present invention 2 The absolute value of the primary phase difference of the wavelet coefficients is shown.
FIG. 24 is a diagram of CO and O in an embodiment of the invention 2 Initial amplitude of concentration wavelet coefficient fitting equation.
FIG. 25 shows CO and O after the shelf according to an embodiment of the present invention 2 Is combined with three-zone accurate division of coal spontaneous combustion dangerous area schematic diagram.
FIG. 26 is a schematic diagram of a three-zone division of spontaneous combustion of coal in an embodiment of the invention.
FIG. 27 is a schematic illustration of the invention for precisely dividing the coal spontaneous combustion dangerous area according to the correlation of different stent areas and the coal spontaneous combustion in combination with three zones.
Detailed Description
The invention will be described in further detail with reference to the drawings and the specific examples.
As shown in fig. 1, the method for determining the degree of correlation between different areas of a working surface and spontaneous combustion of coal according to the present invention is characterized in that: by continuously capturing CO and O in different areas of the working surface 2 Concentration information of (2) and then using wavelet transform to collect CO and O 2 Performing multiscale evolution feature analysis on the concentration information to obtain CO and O in each region under different feature time scales 2 A main period of the concentration and a wavelet coefficient; then selecting sine wave to fit CO and O 2 Wavelet coefficients at the first main period to obtain CO and O 2 Wave equation of wavelet coefficients; finally deriving CO and O from wave equation 2 The phase difference and the initial amplitude are compared to obtain the relation between different areas and the coal spontaneous combustion relativity. Continuous collection of CO and O in a working surface 2 Different areas of concentration information include: inside the upper corner pocket wall, outside the upper corner pocket wall, high-level drainage lane and goaf, and CO and O inside the goaf and the upper corner pocket wall are monitored with emphasis 2 Is a gas concentration of (a).
The method specifically comprises the following steps:
step one, collecting O in different areas of underground stope face 2 And CO, and analyzing the collected different areas O 2 The different areas comprise an upper corner bag sub-wall, a high pumping lane and a goaf; o (O) 2 And a gas sampling period of CO of at least 1 month;
step two, based on wavelet transformation, pair O 2 And CO concentration to obtain O in different areas of the stope 2 A wavelet variance curve and a wavelet coefficient cloud chart of the concentration of CO, wherein the basis function of wavelet transformation is Morlet wavelet function;
step three, according to different areas O of the stope face 2 Wavelet variance curve of CO concentration to obtain each region O 2 A characteristic time scale corresponding to a main period of CO;
step four, according to different areas O of the stope face 2 The wavelet coefficient cloud graph of the CO concentration comprises a plurality of main periods, a characteristic scale corresponding to the maximum wavelet variance is extracted as a first main period, and the wavelet coefficients of O2 and CO and corresponding sampling time are obtained under the first main period;
step five, utilizing sine function to make O 2 Fitting with wavelet coefficients of the first main period of CO to obtain wave equations of the first main period and the second main period, wherein the equation of the sine function is y=y 0 +Asin((x-x c ) Pi/omega), where y 0 The primary vibration of the wave, A is amplitude, omega is angular velocity, x c Is a known quantity.
Step six, according to O 2 And the wave equation of the CO wavelet coefficient to obtain corresponding primary amplitude and primary phase difference;
step seven, judging the degree of correlation between different areas and the spontaneous combustion of the coal according to the change conditions of the initial amplitude and the initial phase difference, if CO and O 2 The larger the primary amplitude difference, the more significant the change in the two gases, and the higher the correlation between the region and spontaneous combustion of the coal is judged.
Dividing goafs behind the hydraulic supports according to the positions of the hydraulic supports, analyzing the correlation degree between goafs corresponding to different hydraulic supports and spontaneous combustion of coal, and then combining three spontaneous combustion zones of the coal to accurately divide a spontaneous combustion danger area of the coal, wherein the method comprises the following specific steps:
s1, arranging a beam tube in a goaf behind a working face hydraulic support;
s2, collecting goaf gas by using the existing beam tube automatic sampling device and monitoring system, and carrying out O 2 And CO concentration analysis;
s3, dividing three spontaneous combustion zones of coal by using oxygen concentration, wherein the dividing indexes are 15% and 5%, more than 15% of the zones are heat dissipation zones, less than 5% of the zones are choking zones, and an oxidation zone is arranged between the zones;
s4, determining the correlation degree between the area behind each bracket and the spontaneous combustion of coal by fitting to obtain initial amplitude parameters and initial phase difference parameters in the wave equation, and sequencing; specifically, hydraulic supports arranged in the oxidation zone range are screened, and the probability ranking of coal spontaneous combustion is represented by ranking of the correlation degree of each support region and coal spontaneous combustion.
The hydraulic supports arranged on the working surface are provided with three groups A, B and C, the crossing areas with the oxidation zone are respectively provided with an area 1, an area 2 and an area 3, if the correlation degree between the areas corresponding to the three groups of hydraulic supports and the spontaneous combustion of coal is ranked as R A >R C >R B It is explained that the probability of spontaneous combustion of coal is greatest in zone 1, and secondly, zone 3 is smallest in zone 2.
Embodiment one:
the invention relates to a judging method for the degree of correlation between different areas of a working surface and coal spontaneous combustion, which takes a working surface of a coal mine 401103 with a shanxi fir length Hu Guhe as an example for describing in detail:
o of the four areas including the inner side of the corner pocket wall, the outer side of the upper corner pocket wall, the high-suction roadway and the goaf 2 As with the CO concentration, for example, it was analyzed in detail.
Step one, collecting O in different areas of underground stope face 2 CO and its concentration was analyzed.
Step two, based on wavelet transformation, utilizing Matlab and Surfer software to perform O 2 And CO concentration to obtain O 2 The wavelet coefficient cloud and wavelet variance curves for CO concentration are shown in fig. 1-4 (in the upper corner pocket wall), fig. 6-9 (in the upper corner pocket wall), fig. 11-14 (high-extraction roadway), and fig. 17-20 (goaf).
Step three, according to the wavelet variance curve, O is obtained 2 A characteristic time scale corresponding to a main period of CO;
step four, extracting wavelet coefficients under the first main period according to the wavelet coefficient cloud picture to obtain O 2 And the wavelet coefficients of CO and the corresponding sampling times.
Step five, utilizing sine function to make O 2 Fitting to the wavelet coefficients at the first main period of CO yields wave equations for both, as shown in FIG. 5 (upper corner bagInside the wall), fig. 10 (outside the upper corner pocket wall), fig. 15 and 16 (high-head roadway), fig. 21 and 22 (goaf).
Step six, according to O 2 And the wave equation of the CO wavelet coefficient to obtain corresponding primary amplitude and primary phase difference, as shown in fig. 23 and 24.
Step seven, judging the degree of correlation between different areas and the spontaneous combustion degree of the coal according to the change conditions of the initial amplitude and the initial phase difference, as shown in figure 24, and determining the degree of correlation between CO and O 2 The larger the initial amplitude phase difference, the more significant the change in both gases, further indicating that the region has a higher correlation with spontaneous combustion of the coal.
According to the present case, the correlation with spontaneous combustion of coal is as follows: goaf, upper corner bag inside, upper corner bag outside, and high-suction roadway. Therefore, the gas concentration in the goaf and the upper corner bag sub-wall is monitored with emphasis, and the high-pumping roadway can be free from monitoring or reducing the monitoring frequency, so that the working efficiency is improved.
The study area is subdivided into goafs corresponding to all supports of the working face, and the coal spontaneous combustion dangerous area can be accurately divided by analyzing the relativity of the goafs corresponding to different supports and coal spontaneous combustion and combining the three coal spontaneous combustion zones, and the concrete steps are as follows:
and in the expansion step one, beam tubes are arranged behind the working face frame, and the arrangement mode is shown in fig. 25.
Expanding step two, collecting goaf gas by using beam tube automatic sampling device and monitoring system, and carrying out O 2 And CO concentration analysis.
Expanding step three, dividing coal spontaneous combustion three zones by using oxygen concentration, wherein the dividing index is 15% and 5%, more than 15% is a heat dissipation zone, less than 5% is a choking zone, and an oxidation zone is arranged between the heat dissipation zone and the choking zone, as shown in fig. 26.
Expanding step four, judging the correlation degree between the areas after different brackets and the spontaneous combustion of coal, and sequencing. Assuming that the three groups of A, B and C hydraulic supports are arranged, the crossing areas of the hydraulic supports and the oxidation zone are respectively an area 1, an area 2 and an area 3, if the relevance degree between the areas corresponding to the three groups of hydraulic supports and the spontaneous combustion of coal is ranked as R A >R C >R B Then the probability of spontaneous combustion of coal in zone 1 is the greatest, zone3 next, zone 2 is minimal, as shown in fig. 27.
It will be apparent to those skilled in the art that various modifications and variations can be made to the present invention without departing from the spirit or scope of the invention. Thus, it is intended that the present invention also include such modifications and alterations insofar as they come within the scope of the appended claims or the equivalents thereof.
Wavelet coefficients were calculated using Matlab:
selecting Morlet complex wavelet function in Matlab wavelet toolbox to make wavelet transformation to data sequence: clicking the submenu under "Wavelet1-D" Complex Continuous Wavelet-D ", opening the one-dimensional complex continuous Wavelet interface, clicking the" Load Signal "button under the" File "menu, and loading the time sequence runoff. In the invention, a CMor (1-1.5) is selected, the sampling period is 1, the maximum scale is 64, and a 'analysis' operation button is clicked to calculate the wavelet coefficient. The wavelet coefficients are saved as a crunoff.
Calculating complex wavelet coefficients and variances using Matlab
The crunoff. Mat file is imported in a workbench under Matlab interface. The calculation of the real part and variance of Morlet complex wavelet coefficient is started, and the specific operation is as follows: direct input function "shibu=real (coefs) in" Command Windows "; ", click the" enter "key to calculate the real part; input function "fangcha=sum (abs (coefs) & lt 2, 2); ", click" enter "key, calculate variance.
The method for drawing the wavelet coefficient real part contour map comprises the following steps:
first, the real part data of the wavelet coefficient is copied into Excel, wherein the column A is time, the column B is scale, and the column C is real part value of the corresponding wavelet coefficient under different time and scale. And secondly, converting the data into a data format identified by buffer 12.0, and finally, drawing a real part contour map of the wavelet coefficient.
Role of wavelet coefficient real part contour plot in multi-time scale analysis:
the wavelet coefficient real part contour map can reflect periodic changes of different time scales of the runoff sequence and distribution of the periodic changes in a time domain, so that future change trend of the runoff on the different time scales can be judged. In order to clearly illustrate the effect of the real part contour map of the wavelet coefficient in runoff multi-time scale analysis, when the real part value of the wavelet coefficient is positive, the real part contour map of the wavelet coefficient represents a runoff water-enlarging period, and 'H' represents a positive center; when negative, the run-off period is indicated, and the "L" represents the negative center, drawn by the dotted line.
In general, there is a 3-class scale periodic variation law of 18-32 years, 8-17 years and 3-7 years in the basin runoff evolution process. Wherein, quasi-twice oscillation of withered-abundant alternation occurs on the scale of 18-32 years; there are quasi 5 oscillations on the 8-17 year time scale. Meanwhile, the periodic variation of the two scales can be seen to be very stable in performance in the whole analysis period, and has universe; and the periodic variation of the scale of 3-10 years is more stable after 1980 s.
Drawing a wavelet coefficient contour map and a variance map by using Surfer:
and (3) exporting the data in the step (3), and then directly drawing a wavelet coefficient contour map by utilizing Surfer software. The variogram was directly drawn using Origin software. No additional calculations are required.
Claims (7)
1. A judging method for the degree of correlation between different areas of a working surface and spontaneous combustion of coal is characterized by comprising the following steps: by continuously capturing CO and O in different areas of the working surface 2 Concentration information of (2) and then using wavelet transform to collect CO and O 2 Performing multiscale evolution feature analysis on the concentration information to obtain CO and O in each region under different feature time scales 2 A main period of the concentration and a wavelet coefficient; according to different areas O of the stope face 2 The wavelet coefficient cloud image corresponding to the concentration of CO comprises a plurality of main periods, the characteristic scale corresponding to the maximum wavelet variance is extracted as the first main period, and then sine waves are selected to fit CO and O 2 Wavelet coefficients at the first main period to obtain CO and O 2 Wave equation of wavelet coefficients; finally deriving CO and O from wave equation 2 The phase difference and the initial amplitude can be compared to obtain the relation between different areas and the coal spontaneous combustion relativityCO and O in 2 The larger the area is, the larger the difference between CO and O2 is; if CO and O 2 The larger the primary amplitude difference, the more significant the change in the two gases, and the higher the correlation between the region and spontaneous combustion of the coal is judged.
2. The method for determining the degree of correlation between different areas of a working surface and spontaneous combustion of coal according to claim 1, wherein the CO and O in the working surface are continuously collected 2 Different areas of concentration information include: inside the upper corner pocket wall, outside the upper corner pocket wall, high-level drainage lane and goaf, and CO and O inside the goaf and the upper corner pocket wall are monitored with emphasis 2 Is a gas concentration of (a).
3. The method for determining the degree of correlation between different areas of a working surface and spontaneous combustion of coal according to claim 1, comprising the following steps:
step one, collecting O in different areas of underground stope face 2 And CO, and analyzing the collected different areas O 2 The different areas comprise an upper corner bag sub-wall, a high pumping lane and a goaf;
step two, based on wavelet transformation, pair O 2 And CO concentration to obtain O in different areas of the stope 2 Wavelet variance curve and wavelet coefficient cloud graph of CO concentration;
step three, according to different areas O of the stope face 2 Wavelet variance curve of CO concentration to obtain each region O 2 A characteristic time scale corresponding to a main period of CO;
step four, according to different areas O of the stope face 2 The wavelet coefficient cloud graph of the CO concentration comprises a plurality of main periods, a characteristic scale corresponding to the maximum wavelet variance is extracted as a first main period, and the wavelet coefficients of O2 and CO and corresponding sampling time are obtained under the first main period;
step five, utilizing sine function to make O 2 Fitting with wavelet coefficient of first main period of CO to obtain twoIs a wave equation of (2);
step six, according to O 2 And the wave equation of the CO wavelet coefficient to obtain corresponding primary amplitude and primary phase difference;
step seven, judging the degree of correlation between different areas and the spontaneous combustion of the coal according to the change conditions of the initial amplitude and the initial phase difference, if CO and O 2 The larger the primary amplitude difference, the more significant the change in the two gases, and the higher the correlation between the region and spontaneous combustion of the coal is judged.
4. The method for determining the degree of correlation between different areas of a working surface and spontaneous combustion of coal according to claim 2, wherein the method comprises the following steps of: o in step one 2 And a gas sampling period of CO of at least 1 month.
5. The method for determining the degree of correlation between different areas of a working surface and spontaneous combustion of coal according to claim 1, wherein the method comprises the following steps of: in the second step, the basis function of the wavelet transformation is Morlet wavelet function.
6. The method for determining the degree of correlation between different areas of a working surface and spontaneous combustion of coal according to claim 1, wherein in the fifth step, the equation of the sine function isWherein y is 0 The primary vibration of the wave, A is amplitude, omega is angular velocity, x c Is a known quantity.
7. The method for determining the degree of correlation between different areas of a working surface and spontaneous combustion of coal according to claim 1, wherein the method comprises the following steps of: dividing goafs behind the hydraulic supports according to the positions of the hydraulic supports, analyzing the correlation degree between goafs corresponding to different hydraulic supports and spontaneous combustion of coal, and then combining three spontaneous combustion zones of the coal to accurately divide a spontaneous combustion danger area of the coal, wherein the method comprises the following specific steps:
s1, arranging a beam tube in a goaf behind a working face hydraulic support;
s2, collecting goaf gas by using the existing beam tube automatic sampling device and monitoring system, and carrying out O 2 And CO concentration analysis;
s3, dividing three spontaneous combustion zones of coal by using oxygen concentration, wherein the dividing indexes are 15% and 5%, more than 15% of the zones are heat dissipation zones, less than 5% of the zones are choking zones, and an oxidation zone is arranged between the zones;
s4, determining the correlation degree between the area behind each bracket and the spontaneous combustion of coal by fitting to obtain initial amplitude parameters and initial phase difference parameters in the wave equation, and sequencing; specifically, hydraulic supports arranged in the oxidation zone range are screened out, and the probability ranking of coal spontaneous combustion is represented by ranking of the correlation degree of each support area and coal spontaneous combustion;
the hydraulic supports arranged on the working surface are provided with three groups A, B and C, the crossing areas with the oxidation zone are respectively provided with an area 1, an area 2 and an area 3, if the correlation degree between the areas corresponding to the three groups of hydraulic supports and the spontaneous combustion of coal is ranked as R A >R C >R B It is explained that the probability of spontaneous combustion of coal is greatest in zone 1, and secondly, zone 3 is smallest in zone 2.
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