CN114233386A - Coal mine disaster early warning method based on multi-parameter risk identification database - Google Patents
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Abstract
A coal mine disaster early warning method based on a multi-parameter risk identification database aims to provide a mine dynamic disaster multi-system collaborative comprehensive monitoring early warning method, which comprises the following steps: step 1, collecting foundation data of rock burst, wherein the foundation data comprises geological condition data, mining condition data and monitoring data; step 2, extracting effective analysis methods and building an analysis method library; and 3, selecting an analysis method under specific geological and mining conditions, selecting an effective analysis method in the analysis method library in the step 2 for monitoring areas under different conditions, taking the effective analysis method as an early warning factor of the monitoring area participating in monitoring and early warning, and grading according to the importance of each factor. Step 4, an early warning parameter calculation method discrimination mechanism sets early warning values for the danger discrimination mechanisms of the analysis methods selected in the step 3; and 5, comprehensively judging the danger level, and judging the early warning level of the monitoring area according to the number and the importance level of the early warning triggered by the analysis method selected in the step 3.
Description
Technical Field
The invention relates to the field of mine dynamic disaster monitoring and early warning, in particular to a coal mine disaster early warning method based on a multi-parameter risk identification database.
Background
The mine dynamic disaster is one of main factors influencing the safe and healthy development of mining industry in the world, has the characteristics of strong burst property, multiple influencing factors, strong contingency and the like, has extremely strong destructiveness, and once the disaster happens, the disaster can cause great loss of life and property of underground mine operators. Therefore, early monitoring and early warning of the mine dynamic disaster are important measures for preventing major mine dynamic disaster accidents. The mine dynamic disasters comprise rock burst, coal and gas outburst, roof caving, water inrush and the like caused by mine mining and underground engineering activities, the occurrence mechanism of the dynamic disasters such as the rock burst is complex, and the stress field is greatly influenced by factors such as roof drainage, surface subsidence and the like, so that the complexity of the occurrence mechanism of the dynamic disasters and the treatment difficulty are increased.
The rock burst is one of the common dynamic disaster damage phenomena in the construction process of deep-buried underground engineering, and at present, for monitoring and early warning of the rock burst disaster, various methods such as a drilling cutting monitoring method, a coal body stress monitoring method, an electromagnetic radiation monitoring method, a ground sound and microseismic monitoring method and the like have been proposed at home and abroad.
1) And (3) a drilling cutting monitoring method: the coal body stress state is known by monitoring the change rule of the coal bed drilling powder discharge amount and the related dynamic effect, so that the rock burst risk is predicted, and the method is the most commonly used monitoring method at present. However, this method has the disadvantages of individual operational errors and the inability to monitor continuously.
2) A coal body stress monitoring method: by continuously monitoring the mining stress in the coal body and predicting and evaluating the impact risk of the coal-rock body from the stress field, the method realizes the continuous monitoring of the mining stress variation of the coal body. However, the method is small in monitoring range, and the monitoring result is good in monitoring effect on spontaneous rock burst and poor in monitoring effect on induced rock burst.
3) Electromagnetic radiation monitoring method: and monitoring the electromagnetic intensity and the pulse number radiated outwards in the coal-rock body cracking process so as to judge the loading degree and the cracking strength of the coal-rock body and obtain the impact risk degree. However, the method is affected by various electrical signals underground, and the obtained result has uncertainty.
4) The method for monitoring the earthquake sound and the microseisms comprises the following steps: the vibration signals released in the coal rock mass cracking process are monitored, different cracking stages of the coal rock mass can be obtained through analysis, the overall damage condition and the energy release condition of the coal rock mass are known, and the prediction and early warning of impact are realized. However, the method only monitors the vibration signal generated by the fracture, and has a good monitoring effect on the induced rock burst and a poor monitoring effect on the spontaneous rock burst.
In conclusion, aiming at the complexity of mine disaster influencing factors, a plurality of monitoring systems are installed in a mine, but the outstanding problems that the early warning methods of the monitoring systems are relatively independent, the joint early warning efficiency is low and the like generally exist, and the method is especially outstanding in the aspect of judgment and identification of a multi-parameter dynamic danger area. In the aspect of a multi-parameter monitoring and early warning method, application with chinese patent No. CN201510786271 discloses a multi-parameter comprehensive monitoring and early warning method for a tunneling working face, which mainly realizes multi-parameter combined early warning for the tunneling working face in different regions by specifying an arrangement scheme of multi-parameter monitoring points for rock burst in different regions of the tunneling working face, but the method is only limited to the tunneling working face, only obtains multi-parameter early warning indexes for static partitions of the tunneling working face, and does not realize processing and analyzing the position and the risk degree of a disaster in a dangerous region. The application with the application number of CN 201910051 discloses a mine disaster multi-parameter local dangerous area judgment and early warning method, which realizes the identification of the local dangerous area of a mine disaster through the space positioning of monitoring points, and judges and identifies the local dangerous degree through multi-parameter monitoring results in a local range.
The invention discloses a coal mine disaster early warning method based on a multi-parameter risk judgment database, and provides a comprehensive early warning algorithm which selects a more targeted analysis method from a method library to participate in early warning through establishing a risk analysis method library and selecting the analysis method from the method library according to different geological and mining conditions in each monitoring area. The selected early warning method can be graded according to the importance degree, and the early warning grade of the monitoring area is judged according to the number and the importance grade of the early warning triggered by the selected analysis method.
Disclosure of Invention
The invention aims to provide a coal mine disaster early warning method based on a multi-parameter risk identification database, which has the advantages of simple structure, low cost and simple and convenient operation.
In order to solve the technical problem, the application provides the following technical scheme:
the coal mine disaster early warning method based on the multi-parameter risk identification database is a comprehensive monitoring early warning method applied to multi-system collaboration of mine dynamic disasters, can be widely applied to mine danger early warning threatened by mine dynamic disasters, is wide in application range and strong in pertinence, and can meet field requirements of various mines. The early warning method comprises the following steps: step 1, collecting foundation data of rock burst, wherein the foundation data can comprise geological condition data, mining condition data and monitoring data; step 2, extracting effective analysis methods and building an analysis method library; and 3, selecting an analysis method under specific geological and mining conditions, selecting an effective analysis method in the analysis method library in the step 2 for monitoring areas under different conditions, and taking the effective analysis method as an early warning factor for the monitoring areas to participate in monitoring and early warning, grading according to the importance of each factor, wherein the effective analysis method can be divided into a first grade and a second grade according to the importance from high to low. Step 4, an early warning parameter calculation method discrimination mechanism sets early warning values for the danger discrimination mechanisms of the analysis methods selected in the step 3; and 5, comprehensively judging the danger level, and judging the early warning level of the monitoring area according to the number and the importance level of the early warning triggered by the analysis method selected in the step 3.
The coal mine disaster early warning method based on the multi-parameter risk identification database is characterized in that the early warning parameters are used for distinguishing two grades of 'overrun and normal' by adopting a mode of delimiting an overrun early warning line, the early warning line is adjustable, and each user can determine a reasonable early warning line by adopting modes of field data analysis, numerical simulation, expert argument and the like according to the actual situation of the user.
Compared with the prior art, the coal mine disaster early warning method based on the multi-parameter risk identification database at least has the following beneficial effects:
the coal mine disaster early warning method based on the multi-parameter risk identification database solves the problems that the prior coal mine disaster early warning method is commonly used in the industry: the field data statistical method is mostly statistical analysis among multiple indexes in a single system, and combination of monitoring data of multiple systems is difficult to achieve; each index evaluation process of the AHP hierarchical analysis early warning method has certain subjective factors, and the requirement of 'one-side-one-strategy' of anti-scour is difficult to achieve; the master control factor weight method brings about the problems that special abnormal data is submerged and the like. The invention has stronger wide applicability and better pertinence of monitoring and early warning of specific conditions.
The early warning method has the advantages that the problem that the common field data statistical method in the industry at present is statistical analysis among multiple indexes in a single system is solved, and the combination of monitoring data of the multiple systems is difficult to realize; each index evaluation process of the AHP hierarchical analysis early warning method has certain subjective factors, and the requirement of 'one-side-one-strategy' of anti-scour is difficult to achieve; the main control factor weight identification method brings about the problems that special abnormal data are submerged and the like, the wide applicability is stronger, and the monitoring and early warning pertinence of specific conditions is better.
The coal mine disaster early warning method based on the multi-parameter risk identification database is further explained with reference to the attached drawings.
Drawings
Fig. 1 is a schematic flow diagram of a coal mine disaster early warning method based on a multi-parameter risk identification database according to the present invention.
Detailed Description
In order to make the technical problems, technical solutions and advantages to be solved by the present invention clearer, the following detailed description is provided with reference to the accompanying drawings, and the specific method is as follows:
as shown in fig. 1, the coal mine disaster early warning method based on the multi-parameter risk identification database of the present invention includes:
step 1, collecting basic data
Acquiring basic data of each area related to coal mine rock burst disaster early warning, wherein the basic data comprises monitoring data, geological condition data and mining condition data of a monitoring area;
step 2, extraction of effective analysis method and construction of analysis method library
And refining an analysis method for representing direct danger of the impact ground pressure disaster according to the acquired basic data. For example: in the microseismic monitoring data acquired in the step 1, according to basic research, the energy value of the maximum energy event of the microseismic in unit time is a factor related to the occurrence of the disaster, and the larger the energy of the maximum energy event in unit time is, the higher the risk degree of the disaster is. Thus, the energy value of the maximum energy event monitored by the microseisms per unit time is incorporated into the analysis method database.
For example, based on the research foundation already in the industry, the library of analytical methods is shown in Table 1-1, and the analytical methods in the following table can be expanded according to the depth of the research.
TABLE 1-1 data analysis methods library summary
Step 3, selecting analysis method under specific geological and mining conditions
And (3) selecting a more effective analysis method in the analysis method library in the step (2) as an early warning factor for the monitoring area to participate in monitoring and early warning aiming at monitoring areas with different geology and mining conditions, grading according to the importance degree of each factor, and dividing into a first grade and a second grade according to the importance degree from high to low.
For example: aiming at the special geological condition of a 'roof multi-hardness thick sandstone layer' in an inner Mongolia Wuqi area, the dynamic display of the area is mainly characterized by 'high dynamic load and low static load', analytical methods for reflecting 'high dynamic load' such as 'energy of maximum energy event in unit time', 'total energy in unit time' and the like in a monitoring system can be selected as a primary factor in a pertinence manner, and only stress indexes for reflecting 'low static load' such as 'stress value reaching the number of red early warning measuring points' and the like in stress monitoring are selected as secondary factors to participate in the comprehensive early warning of the local area. According to the method, early warning factors suitable for geological mining conditions of the area are selected, and the early warning factors are shown in tables 1-2.
TABLE 1-2 analysis of selected and ranked geological conditions
Step 4, setting early warning indexes of early warning factors;
and (3) setting an early warning value for the danger judging mechanism of each analysis method selected in the step (3). The early warning parameters adopt a mode of marking out an overrun early warning line, two grades of overrun and normal are judged, and the early warning line is adjustable.
For example, the warning indicators of the factors are set as follows:
1. monitoring data analysis index (microseismic monitoring part)
(1) Energy (EL) of maximum energy event per unit time
And (3) index definition: the index calculates the energy index of the maximum microseismic energy event within a certain time range before the moment.
Available parameters are as follows: interval time t1, warning line E1.
TABLE 2-1 method for determining energy (E1) of maximum energy event per unit time
(2) Total energy per unit time (ES)
And (3) index definition: the total energy index of the microseismic event within a certain time range before the index calculation time.
Available parameters are as follows: interval time t2, warning line E2.
TABLE 2-2 method for determining total energy (E2) per unit time
(3) Frequency of unit microseismic events (FS)
And (3) index definition: the index calculates the total number of microseismic events index within a certain time range before the moment.
Available parameters are as follows: interval time t3, warning line F1.
TABLE 2-3 discrimination method for unit microseismic event Frequency (FS)
(4) Energy release unit footage (EF)
And (3) index definition: the index calculates the ratio of total microseismic energy to total footage of the day before the moment (natural day). If the production is not carried out or the footage is not recorded in the previous day, the index does not participate in the calculation.
Available parameters are as follows: warning line E3.
TABLE 2-4 METHOD FOR DETERMINING ENTRAVELY ENERGY RELEASE (EF)
2. Monitoring data analysis index (stress monitoring part)
(1) The stress value reaches the number (Q) of red (or yellow) early warning measuring points
And (3) index definition: and (3) calculating the number of the measuring points when the stress value reaches red (or yellow) early warning at the moment by using the indexes.
Available parameters are as follows: the early warning values P1 and P2, and the number of early warning measuring points k1 and k 2.
TABLE 2-5 METHOD FOR DETERMINING THE QUALITY (Q) OF PRE-ALARM MEASURING POINTS WHICH STRESS VALUES reach RED (OR YELLOW) COLOUR
(2) Number of overrun points (PL, PB) for long and short stress acceleration
And (3) index definition: and (4) calculating the number of the measuring points of which the equal growth speed value of the stress reaches the early warning value within a certain time t at the moment by the index.
Available parameters are as follows: interval time t4 and t5, stress increase values P3 and P4, early warning lines PG1, PG2, PG3 and PG4, and the number of early warning measuring points k3, k4, k5 and k 6.
TABLE 2-6 method for judging number of overrun points (PL, PB) of stress length and stress speed increase
Note that: 1) in order to avoid stress surge caused by special conditions such as pressure supplement, the index participates in calculation only when the stress value is greater than P3 (default 6MPa, adjustable) within the time t4 and the time t 5.
2) In order to avoid abnormal increase of data caused by equipment failure, when the stress value is increased by more than P4 (default 10MPa, adjustable) within the time t4 and t5, the index does not participate in calculation.
(3) Mean value of stress (PA)
And (3) index definition: and calculating the average value of the stress values of the stress measuring points at the moment by the indexes.
Available parameters are as follows: the number of the measuring points K7 of the early warning value P5.
TABLE 2-4 stress mean (PA) discrimination method
Note that: statistics show that when all stress measuring points participate in the calculation of the average value, the index has almost no change. However, when the first few measuring points with larger statistical stress values are counted, the index has statistical significance. Therefore, stress measurement points involved in calculation are k7 (default 10, configurable) stress values.
3. Monitoring data analysis index (drill chip monitoring part)
And (3) index definition: and whether the drilling detection exceeds the standard in the monitoring area within the time t6 of index calculation.
Available parameters are as follows: at time t 6.
TABLE 2-4 methods for determining the drilling inspection index calculation method (z)
4. Geological condition analysis index
Evaluation results (a) index determination:
and (3) index definition: and (4) calculating whether the working surface is in the danger area to be evaluated at the moment according to the indexes. When the system is in a strong impact dangerous area, the first-level index is judged to be over-limit, when the system is in a medium impact dangerous area, the second-level index is judged to be over-limit, and the weak and the following dangerous areas do not participate in calculation.
Available parameters are as follows: none.
5. Mining condition analysis index
The index calculates the push mining or tunneling speed one day (natural day) before the moment. If the production is not carried out or the footage is not recorded in the previous day, the index does not participate in the calculation.
Available parameters are as follows: warning line S1.
TABLE 2-4 mining speed (S) discrimination method
Step 5, comprehensive danger grade discrimination
And (4) comprehensively judging the early warning level of the monitoring area according to the number and the importance level of the early warning triggered by the analysis method selected in the step (3).
The following discrimination mechanism is set to follow the principle:
(1) if only one primary index in the monitoring area exceeds the limit, orange early warning is achieved at least;
(2) if a plurality of secondary indexes exceed the limit, red early warning is possibly triggered;
(3) if any index exceeds the limit, early warning of the level above yellow is triggered;
(4) the number k of the first-stage parameter and the number k of the second-stage parameter of different early warning levels can be configured, and different monitoring areas can be independently configured.
TABLE 3-1 method for discriminating risk equal degree (risk grade) of monitoring area
For example: and 3, when the early warning condition of the early warning parameters determined in the step 3 is shown in the table 3-2, 1 primary index and 2 secondary indexes are out of limit in total, and the condition can be obtained by comparing the table 3-1, and the monitoring area is judged to meet the medium impact risk (orange).
TABLE 3-2 index trigger case for certain monitoring area
The above-mentioned embodiments are merely illustrative of the preferred embodiments of the present invention, and do not limit the scope of the present invention, and various modifications and improvements of the technical solution of the present invention by those skilled in the art should fall within the protection scope defined by the claims of the present invention without departing from the spirit of the present invention.
Claims (7)
1. A coal mine disaster early warning method based on a multi-parameter risk identification database is characterized by comprising the following steps:
step 1, collecting the foundation data of rock burst,
acquiring basic data of each region related to coal mine rock burst disaster early warning;
step 2, extraction of effective analysis method and construction of analysis method library,
according to the collected basic data, an analysis method for representing direct danger of the impact ground pressure disaster is extracted;
step 3, selecting an analysis method under specific geological and mining conditions,
selecting an effective analysis method in the analysis method library in the step 2 according to the condition of the monitoring area, taking the effective analysis method as an early warning factor of the monitoring area participating in monitoring and early warning, and grading according to the importance of each factor;
step 4, a discrimination mechanism of the early warning parameter calculation method,
setting early warning values for the danger judging mechanisms of the analysis methods selected in the step 3;
step 5, the judgment of the comprehensive danger level,
and (4) judging the early warning level of the monitoring area according to the number and the importance level of the early warning triggered by the analysis method selected in the step (3).
2. The multi-parameter risk assessment database-based coal mine disaster early warning method according to claim 1, wherein the rock burst foundation data comprises geological condition data, mining condition data and monitoring data.
3. The coal mine disaster early warning method based on the multi-parameter risk judgment database as claimed in claim 1, wherein the early warning parameters in step 4 are used for judging two levels of 'overrun and normal' by defining an overrun early warning line, and the early warning line is adjusted according to the preset rules of users.
4. A coal mine disaster early warning method based on a multi-parameter risk judgment database as claimed in claim 3, wherein step 3 is divided into a first level and a second level according to importance.
5. The coal mine disaster early warning method based on the multi-parameter risk judgment and identification database as claimed in claim 1, wherein the analysis method library comprises a monitoring data analysis method, a geological information data analysis method and a mining information data analysis method.
6. The coal mine disaster early warning method based on the multi-parameter risk judgment database as claimed in claim 5,
in the setting of the early warning value, the analysis indexes of the monitoring data of the microseismic monitoring comprise:
(1) energy EL of maximum energy event per unit time
(2) Total energy ES per unit time
(3) Frequency of events per microseismic unit FS
(4) Energy release EF per unit footage
The monitoring data analysis indexes of the stress monitoring comprise:
(1) the stress value reaches the quantity Q of red or yellow early warning measuring points
(2) Number of overrun points PL and PB of stress length and stress speed increase
(3) Stress average PA.
7. A coal mine disaster early warning method based on a multi-parameter risk judgment database as claimed in claim 4, wherein the judgment mechanism of the step 5 follows the following principle:
(1) if only one primary index in the monitoring area exceeds the limit, orange early warning is achieved at least;
(2) if a plurality of secondary indexes exceed the limit, red early warning is possibly triggered;
(3) if any index exceeds the limit, early warning of the level above yellow is triggered;
(4) the quantity of parameters of different early warning levels can be configured, and different monitoring areas can be independently configured.
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