CN110533887A - A kind of discrete mode method for early warning of coal and gas prominent disaster based on Real-time Monitoring Data, device and storage medium - Google Patents
A kind of discrete mode method for early warning of coal and gas prominent disaster based on Real-time Monitoring Data, device and storage medium Download PDFInfo
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- CN110533887A CN110533887A CN201910725777.7A CN201910725777A CN110533887A CN 110533887 A CN110533887 A CN 110533887A CN 201910725777 A CN201910725777 A CN 201910725777A CN 110533887 A CN110533887 A CN 110533887A
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- E—FIXED CONSTRUCTIONS
- E21—EARTH DRILLING; MINING
- E21F—SAFETY DEVICES, TRANSPORT, FILLING-UP, RESCUE, VENTILATION, OR DRAINING IN OR OF MINES OR TUNNELS
- E21F17/00—Methods or devices for use in mines or tunnels, not covered elsewhere
- E21F17/18—Special adaptations of signalling or alarm devices
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- G—PHYSICS
- G08—SIGNALLING
- G08B—SIGNALLING OR CALLING SYSTEMS; ORDER TELEGRAPHS; ALARM SYSTEMS
- G08B21/00—Alarms responsive to a single specified undesired or abnormal condition and not otherwise provided for
- G08B21/02—Alarms for ensuring the safety of persons
- G08B21/12—Alarms for ensuring the safety of persons responsive to undesired emission of substances, e.g. pollution alarms
- G08B21/14—Toxic gas alarms
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- G—PHYSICS
- G08—SIGNALLING
- G08B—SIGNALLING OR CALLING SYSTEMS; ORDER TELEGRAPHS; ALARM SYSTEMS
- G08B21/00—Alarms responsive to a single specified undesired or abnormal condition and not otherwise provided for
- G08B21/02—Alarms for ensuring the safety of persons
- G08B21/12—Alarms for ensuring the safety of persons responsive to undesired emission of substances, e.g. pollution alarms
- G08B21/16—Combustible gas alarms
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- G—PHYSICS
- G08—SIGNALLING
- G08B—SIGNALLING OR CALLING SYSTEMS; ORDER TELEGRAPHS; ALARM SYSTEMS
- G08B21/00—Alarms responsive to a single specified undesired or abnormal condition and not otherwise provided for
- G08B21/18—Status alarms
- G08B21/182—Level alarms, e.g. alarms responsive to variables exceeding a threshold
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- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02A—TECHNOLOGIES FOR ADAPTATION TO CLIMATE CHANGE
- Y02A90/00—Technologies having an indirect contribution to adaptation to climate change
- Y02A90/10—Information and communication technologies [ICT] supporting adaptation to climate change, e.g. for weather forecasting or climate simulation
Abstract
The present invention provides a kind of discrete mode method for early warning of the coal and gas prominent disaster based on Real-time Monitoring Data, device and storage medium, elapse several periods forward on the basis of current time, utilize coal-mine gas monitoring system comprising, the variation tendency and oscillation variance of the relative gas burst quantity of each getting working face day part are calculated in real time, form discrete mode early warning sequence, pass through the historical record of coal and gas prominent precursor information, in conjunction with the genesis mechanism of coal and gas prominent accident, implicit coalbed gas geology and mining technology information, early warning modal parameter and trending early warning classification thresholds are determined using big data analysis method, realize the online real-time dynamic classification early warning reconciliation police of coal and gas prominent disaster.
Description
Technical field
The present invention relates to safety in production field more particularly to a kind of coal and gas prominent disasters based on Real-time Monitoring Data
Discrete mode method for early warning, device and storage medium.
Background technique
For coal mine, coal and gas prominent disaster is one of disaster, and coal and gas prominent accident occurs every time
Great casualties and economic loss will be caused to coal mine, it is bigger to coal mine also further to induce gas explosion sometimes
Loss, greatly affected the industrial competition of highly gassy mine.
In the prior art, the sensing mode for capableing of omnidirectional detection coal and gas prominent disaster precursor information is complete not enough
Kind, most of coal mine is only mounted with gas concentration sensor and air velocity transducer, how effective using these sensing datas
The prediction and early warning for carrying out Gas Outburst disaster are always a stubborn problem.Although such as published patent document
CN108506041A provides a kind of dynamic disaster mode method for early warning based on Real-time Monitoring Data, embodies Gas timing
Online embodiment of the sequence to the precursor information of Gas Outburst disaster, but need to construct mode function, it is increased to the realization of method
Certain difficulty, and due to not considering that (hole) gap is split with exploitation disturbance and gas in gas pressure and coal seam during Gas
Variation tendency and oscillatory condition when gushing out cannot achieve the on-line early warning reconciliation police of the prominent disaster of coal mine gas.
Summary of the invention
In order to overcome the deficiencies in the prior art described above, the present invention provide it is a kind of using relative gas burst quantity it is discrete when
Sequence sequence realizes the alert coal and gas prominent disaster based on Real-time Monitoring Data of the prominent disaster on-line early warning reconciliation of coal mine gas
Discrete mode method for early warning, method include:
Step 1 demarcates gas flow according to the cross-section shape of roadway of sensor mounting location, cross-sectional area and coal breakage amount
Calculation method determines coefficient A and B in following equation, calculate the equivalent relative gas burst quantity sequence of working face in real time
Column:
C- gas density, V- wind speed, S- drift section product, M- coal breakage amount, A and B are calibrated and calculated coefficient, WiEquivalent watt
This relative amount of mine gas emission；
Step 2, if the gas emission sequence { W of working facei, according to coal and gas prominent event and uneven emission quantity
The historical record of event, setting early warning calculate time interval length Dt, pre-warning time section is Q=[T-Dt, T), before being related to
Million information time sections are Q1=[T-4Dt,T-3Dt), Q2=[T-3Dt,T-2Dt), Q3=[T-3Dt,T-2Dt), and hypothesis watt
This relative amount of mine gas emission sequence { WiIn section Q1、Q2、Q3, mean value in Q and trend oscillation variance be
Step 3 utilizesGas emission sequence { W is calculated with σiModal parameter N in day part:
Step 4, according to the mine gas geological conditions of early warning working face, exploiting field ocurrence of coal seam situation and production technology, ginseng
The precursor information record for examining gas effusion intensity historical record and similar operation face coal and gas prominent accident, provides parameter N phase
Alarm threshold value corresponding for 4 ranks=(Nr, No, Ny, Nb)；
Step 5 records according to this working face and its environment and the precursor information of history anomalous event, determines that gas is opposite
Outburst amount sequence { WiPre- and each section Q1、Q2、Q3With the modal parameter N in Q1、N2、N3It is calculated with N pre- in the Q of early warning section
Alert value Y, according to the rank value interval of modal parameter incremental rate coefficient a, b, c (a > b > c > 1) and early warning value Y of setting
Sr=[Yr,1),So=[Yo,Yr),Sy=[Yy,Yo),Sb=[Yb,Yy),Sg=[0, Yb) carry out respectively it is at different levels
Early warning；
Step 6, according to each section modal parameter N1、N2、N3It is clipped to low level from advanced according to following rules with N and gradually counts
Calculate the early warning value Y in the Q of early warning section；
Step 7, according to Y value, system at regular intervals sends the Gas Disaster warning level and early warning value of each working face to terminal
Y。
In some embodiments, step 1 further include: gas density sensing is installed in the tailentry road of mine
Device and air velocity transducer obtain gas density data and air speed data in mine tailentry road.
In some embodiments, step 2 further include:
Assuming that having each sampled data of n, as y in some sampling interval1,y2,...,yn,
Then with the sampling order in the section；
I=1,2 ..., n are independent variable x, obtain trend fitting straight line by dependent variable y of relative gas burst quantity W:
Y=kx+h
Calculate the match value of each point:
Computation interval mean value and trend are poor:
Wherein,
In some embodiments, step 5 further include:
Warning level is divided into
Red, it is as superfine；
It is orange, as level-one；
Yellow, as second level；
Blue, as three-level；
Early warning or green as solve alert grade；
First determine whether red early warning rank meets:
Situation 1, red early warning
Red early warning section SrIt is subdivided into rapidly rising, rapid increase, continuous rising, is rapidly rising, is fast
Speed rising, continuous rising, beginning rapidly rise, beginning rapid increase, start continuously rising, without declining 10 grades,
Discriminate are as follows:
If 1) N >=Nr,N≥aN3And N3≥aN2And N2≥aN1, then Y=Y is takenr+0.9(1-Yr)
If 2) N >=Nr,N≥bN3And N3≥bN2And N2≥bN1, then Y=Y is takenr+0.8(1-Yr)
If 3) N >=Nr,N≥cN3And N3≥cN2And N2≥cN1, then Y=Y is takenr+0.7(1-Yr)
If 4) N >=Nr,N≥aN3And N3≥aN2, then Y=Y is takenr+0.6(1-Yr)
If 5) N >=Nr,N≥bN3And N3≥bN2, then Y=Y is takenr+0.5(1-Yr)
If 6) N >=Nr,N≥cN3And N3≥cN2, then Y=Y is takenr+0.4(1-Yr)
If 7) N >=Nr,N≥aN3, then Y=Y is takenr+0.3(1-Yr)
If 8) N >=Nr,N≥bN3, then Y=Y is takenr+0.2(1-Yr)
If 9) N >=Nr,N≥cN3, then Y=Y is takenr+0.1(1-Yr)
If 10) N >=Nr,N≥N3, then Y=Y is takenr
If discontented red early warning rank, judges orange warning rank:
Situation 2, orange warning
If 0) N >=No,N3≥Nr, then Y=Y is takenr
If 1) N >=No,N≥aN3And N3≥aN2And N2≥aN1, then Y=Y is takeno+0.9(Yr-Yo)
If 2) N >=No,N≥bN3And N3≥bN2And N2≥bN1, then Y=Y is takeno+0.8(Yr-Yo)
If 3) N >=No,N≥cN3And N3≥cN2And N2≥cN1, then Y=Y is takeno+0.7(Yr-Yo)
If 4) N >=No,N≥aN3And N3≥aN2, then Y=Y is takeno+0.6(Yr-Yo)
If 5) N >=No,N≥bN3And N3≥bN2, then Y=Y is takeno+0.5(Yr-Yo)
If 6) N >=No,N≥cN3And N3≥cN2, then Y=Y is takeno+0.4(Yr-Yo)
If 7) N >=No,N≥aN3, then Y=Y is takeno+0.3(Yr-Yo)
If 8) N >=No,N≥bN3, then Y=Y is takeno+0.2(Yr-Yo)
If 9) N >=No,N≥cN3, then Y=Y is takeno+0.1(Yr-Yo)
If 10) N >=No,N≥N3, then Y=Y is takeno
If discontented orange warning rank, judges yellow warning level:
Situation 3, yellow early warning
If 0) N >=Ny,N3≥No, then Y=Y is takeno
1) calculation method -10) is with orange, only NoChange N intoy, YrChange Y intoo, YoChange Y intoy；
If discontented yellow warning level, judges blue warning level:
Situation 4, blue early warning
If 0) N >=Nb,N3≥Ny, then Y=Y is takeny
1) calculation method -10) is with orange, only NoChange N intob, YrChange Y intoy, YoChange Y intob；
If not blue color warning level, judges green warning level:
Situation 5, green early warning
If 0) N < Nb,N3≥Nb, then Y=Y is takenb
If N < Nb, then takeOtherwise, Y=Y is also takenbCarry out blue early warning.
In some embodiments, in step 7, terminal includes: warning data storehouse, the end PC, mobile terminal, and digital indication is set
Standby and caution device.
The present invention also provides a kind of discrete mode early warning sides of coal and gas prominent disaster realized based on Real-time Monitoring Data
The equipment of method, comprising:
Memory, for storing computer program and the discrete mode of coal and gas prominent disaster based on Real-time Monitoring Data
Method for early warning；
Processor, for executing the computer program and coal and gas prominent disaster based on Real-time Monitoring Data is discrete
Mode method for early warning, the step of to realize coal and gas prominent disaster based on Real-time Monitoring Data discrete mode method for early warning.
The present invention also provides a kind of with the discrete mode early warning side of coal and gas prominent disaster based on Real-time Monitoring Data
The computer readable storage medium of method is stored with computer program, the computer journey on the computer readable storage medium
Sequence is executed by processor the step of to realize coal and gas prominent disaster based on Real-time Monitoring Data discrete mode method for early warning.
As can be seen from the above technical solutions, the invention has the following advantages that
The present invention provides the discrete mode method for early warning based on Real-time Monitoring Data, directly utilizes relative gas burst quantity
Discrete time series sequence, so that it may which the on-line early warning reconciliation police for realizing the prominent disaster of coal mine gas has considered not only Gas
Variation tendency and oscillatory condition of (hole) gap with exploitation disturbance and Gas when are split in gas pressure and coal seam in the process, also imply
The environmental evolution rule of Gas Outburst disaster, for the prominent disaster of coal mine gas advanced perception and early warning solution is alert gives one
Simple and easy method.
Specific embodiment
It in order to make the invention's purpose, features and advantages of the invention more obvious and easy to understand, below will be with specific
Embodiment, the technical solution protected of the present invention is clearly and completely described, it is clear that the embodiments described below are only
It is only a part of the embodiment of the present invention, and not all embodiment.Based on the embodiment in this patent, ordinary skill
Personnel's all other embodiment obtained without making creative work belongs to the range of this patent protection.
The discrete mode early warning side of coal and gas prominent disaster based on Real-time Monitoring Data that the present invention is described and/or shown
Method procedure parameter and sequence of steps only provide by way of example and can change as needed.Although for example, based on prison in real time
The step of discrete mode method for early warning of the coal and gas prominent disaster of measured data shows and/or describes can be shown with particular order or
It discusses, but these steps need not be executed with the sequence that shows or discuss.The various exemplary methods for being described herein and/or showing
It can omit one or more of the step of being described herein or showing, or other than those of disclosed step further include in addition
The step of.
Although by the discrete mode method for early warning of the coal and gas prominent disaster of Real-time Monitoring Data in global function based on
The described in the text up and down of calculation system and/or show various embodiments, but one in these exemplary implementation schemes or
It is multiple to can be used as various forms of program products to distribute, without considering the computer-readable medium for being actually allocated
Specific type.Embodiment disclosed in this method can also be realized using the module for executing certain tasks.These modules
May include script file, batch file or be storable on computer readable storage medium or in computing system other are executable
File.In some embodiments, computer system configurations can be to execute exemplary implementation disclosed herein by these modules
One or more of scheme.
The purpose of the present invention is providing a kind of discrete mode method for early warning based on Real-time Monitoring Data, gas is directly utilized
The discrete time series sequence of relative amount of mine gas emission, so that it may realize the on-line early warning reconciliation police of the prominent disaster of coal mine gas.
The present invention through the following steps that realize:
Assuming that the sampling period of monitoring system is t second, often take 10 numbers for an early warning section, i.e. n=10, then precautionary areas
Between time span Dt=nt=10t.In addition, desirable mode increment coefficient a=1.2, b=1.1, c=1.05.Then this patent
Implementation steps are as follows:
Step 1, for the coal and gas prominent disaster alarm problem of the working face in different mines, in the return air of working face
Gas concentration sensor and air velocity transducer are installed, according to cross-section shape of roadway, the cross-sectional area of sensing installation site in tunnel
Gas flow calculation method is demarcated with coal breakage amount, that is, determines the coefficient A and B in following equation, calculates working face in real time
Equivalent relative gas burst quantity sequence:
C- gas density, V- wind speed, S- drift section product, M- coal breakage amount, A and B are calibrated and calculated coefficient, WiEquivalent gas
Relative amount of mine gas emission (hereinafter referred to as gas emission).
Step 2, if the gas emission sequence { W of working facei, according to coal and gas prominent event and uneven emission quantity
The historical record of event, setting early warning calculate time interval length Dt, pre-warning time section is Q=[T-Dt, T), before being related to
Million information time sections are Q1=[T-4Dt,T-3Dt), Q2=[T-3Dt,T-2Dt), Q3=[T-3Dt,T-2Dt), and hypothesis watt
This relative amount of mine gas emission sequence { WiIn section Q1、Q2、Q3, mean value in Q and trend oscillation variance be (relative to becoming in each section
The variance of gesture straight line) beCalculation method is as follows:
Assuming that having each sampled data of n, as y in some sampling interval1,y2,...,yn, then, with the sampling order in the section
I=1,2 ..., n are independent variable x, obtain trend fitting straight line by dependent variable y of relative gas burst quantity W:
Y=kx+h
Calculate the match value of each point:
Wherein:
Computation interval mean value and trend are poor:
Step 3 utilizesGas emission sequence { W is calculated with σiModal parameter N in day part:
Desirable α=0.25
Step 4, according to the mine gas geological conditions of early warning working face, exploiting field ocurrence of coal seam situation and production technology, ginseng
The precursor information record for examining gas effusion intensity historical record and similar operation face coal and gas prominent accident, provides parameter N phase
For (red, orange, yellow, blue) the corresponding alarm threshold value of 4 ranks=(Nr, No, Ny, Nb).
Step 5 records according to this working face and its environment and the precursor information of history anomalous event, determines that gas is opposite
Outburst amount sequence { WiPre- and each section Q1、Q2、Q3With the modal parameter N in Q1、N2、N3It is calculated in the Q of early warning section with N
Early warning value Y, according to the rank value interval of modal parameter incremental rate coefficient a, b, c (a > b > c > 1) and early warning value Y of setting
Sr=[Yr,1),So=[Yo,Yr),Sy=[Yy,Yo),Sb=[Yb,Yy),Sg=[0, Yb) red (superfine), orange is carried out respectively
(level-one), yellow (second level), blue (three-level) early warning or green (solution police).
Step 6, according to each section modal parameter N1、N2、N3It is clipped to low level from advanced according to following rules with N and gradually counts
Calculate the early warning value Y in the Q of early warning section:
First determine whether red early warning rank meets: situation 1, red early warning
Red early warning section SrIt is subdivided into rapidly rising, rapid increase, continuous rising, is rapidly rising, is fast
Speed rising, continuous rising, beginning rapidly rise, beginning rapid increase, start continuously rising, without declining 10 grades,
Discriminate are as follows:
If 1) N >=Nr,N≥aN3And N3≥aN2And N2≥aN1, then Y=Y is takenr+0.9(1-Yr)
If 2) N >=Nr,N≥bN3And N3≥bN2And N2≥bN1, then Y=Y is takenr+0.8(1-Yr)
If 3) N >=Nr,N≥cN3And N3≥cN2And N2≥cN1, then Y=Y is takenr+0.7(1-Yr)
If 4) N >=Nr,N≥aN3And N3≥aN2, then Y=Y is takenr+0.6(1-Yr)
If 5) N >=Nr,N≥bN3And N3≥bN2, then Y=Y is takenr+0.5(1-Yr)
If 6) N >=Nr,N≥cN3And N3≥cN2, then Y=Y is takenr+0.4(1-Yr)
If 7) N >=Nr,N≥aN3, then Y=Y is takenr+0.3(1-Yr)
If 8) N >=Nr,N≥bN3, then Y=Y is takenr+0.2(1-Yr)
If 9) N >=Nr,N≥cN3, then Y=Y is takenr+0.1(1-Yr)
If 10) N >=Nr,N≥N3, then Y=Y is takenr
If discontented red early warning rank, judges orange warning rank:
Situation 2, orange warning
If 0) N >=No,N3≥Nr, then Y=Y is takenr
If 1) N >=No,N≥aN3And N3≥aN2And N2≥aN1, then Y=Y is takeno+0.9(Yr-Yo)
If 2) N >=No,N≥bN3And N3≥bN2And N2≥bN1, then Y=Y is takeno+0.8(Yr-Yo)
If 3) N >=No,N≥cN3And N3≥cN2And N2≥cN1, then Y=Y is takeno+0.7(Yr-Yo)
If 4) N >=No,N≥aN3And N3≥aN2, then Y=Y is takeno+0.6(Yr-Yo)
If 5) N >=No,N≥bN3And N3≥bN2, then Y=Y is takeno+0.5(Yr-Yo)
If 6) N >=No,N≥cN3And N3≥cN2, then Y=Y is takeno+0.4(Yr-Yo)
If 7) N >=No,N≥aN3, then Y=Y is takeno+0.3(Yr-Yo)
If 8) N >=No,N≥bN3, then Y=Y is takeno+0.2(Yr-Yo)
If 9) N >=No,N≥cN3, then Y=Y is takeno+0.1(Yr-Yo)
If 10) N >=No,N≥N3, then Y=Y is takeno
If discontented orange warning rank, judges yellow warning level:
Situation 3, yellow early warning
If 0) N >=Ny,N3≥No, then Y=Y is takeno
1) calculation method -10) is with orange, only NoChange N intoy, YrChange Y intoo, YoChange Y intoy.
If discontented yellow warning level, judges blue warning level:
Situation 4, blue early warning
If 0) N >=Nb,N3≥Ny, then Y=Y is takeny
1) calculation method -10) is with orange, only NoChange N intob, YrChange Y intoy, YoChange Y intob.
If not blue color warning level, judges green warning level:
Situation 5, green early warning
If 0) N < Nb,N3≥Nb, then Y=Y is takenb
If N < Nb, then takeOtherwise, Y=Y is also takenbCarry out blue early warning.
Step 7, according to Y value, system at regular intervals is to related warning data storehouse, the end PC, mobile terminal and digital indication and warning
Equipment sends the Gas Disaster warning level and early warning value Y of each working face.
System at regular intervals sends the Gas Disaster warning level and early warning value Y of each working face to terminal.Here terminal include but
It is not limited to laptop computer, tablet computer, desktop computer, server, cellular phone, personal digital assistant (PDA), more matchmakers
Body player, embedded system, wearable device (for example, smartwatch, intelligent glasses etc.), one or more above-mentioned variant
With combination or any other suitable computing system.
The present invention can carry out managing and controlling for system information, including but not limited to storage service based on server
Device, database server, apps server and/or web server are configured as running certain software applications
And/or provide various storages, database and/or web services.
Communication network of the present invention includes but is not limited to: Intranet, wide area network (WAN), local area network (LAN), individual
Regional network (PAN), internet, power line communication (PLC), cellular network (for example, global system for mobile communications (GSM) network),
It is above-mentioned one or more part, one or more above-mentioned variant or combination or any other suitable network.In order to energy
Enough by sensing data, warning data is effectively transmitted.
The present invention also provides a kind of discrete mode early warning sides of coal and gas prominent disaster realized based on Real-time Monitoring Data
The equipment of method, comprising:
Memory, for storing computer program and the discrete mode of coal and gas prominent disaster based on Real-time Monitoring Data
Method for early warning；Processor, for execute the computer program and coal and gas prominent disaster based on Real-time Monitoring Data from
Mode method for early warning is dissipated, to realize the step of the discrete mode method for early warning of coal and gas prominent disaster based on Real-time Monitoring Data
Suddenly.
And provide the calculating with the discrete mode method for early warning of coal and gas prominent disaster based on Real-time Monitoring Data
Machine readable storage medium storing program for executing is stored with computer program on the computer readable storage medium, and the computer program is processed
Device executes the step of to realize coal and gas prominent disaster based on Real-time Monitoring Data discrete mode method for early warning.
May be implemented the discrete mode method for early warning of the coal and gas prominent disaster based on Real-time Monitoring Data be in hardware, it is soft
Part, firmware or any combination of them.The various features are module, and unit or assembly may be implemented together in integration logic
Device or separately as discrete but interoperable logical device or other hardware devices.In some cases, electronic circuit
Various features may be implemented as one or more integrated circuit device, such as IC chip or chipset.
The discrete mode method for early warning of coal and gas prominent disaster of the present invention based on Real-time Monitoring Data, such as can
Using as processor or IC apparatus, such as IC chip or chipset.Alternatively or additionally, if it is soft
It is realized in part or firmware, the technology can be realized at least partly by computer-readable data storage medium, including instruct, when
When execution, processor is made to execute one or more above methods.For example, computer-readable data storage medium can store
The instruction such as executed by processor.
Store computer program and the discrete mode method for early warning of coal and gas prominent disaster based on Real-time Monitoring Data
Computer-readable medium its may include packaging material.The computer-readable medium of data may include computer storage medium,
Such as random access memory (RAM), read-only memory (ROM), nonvolatile RAM (NVRAM), electrically erasable
Programmable read only memory (EEPROM), flash memory, magnetically or optically data storage medium and analog.In some embodiments, one
Kind manufacture product may include one or more computer-readable storage mediums.
The foregoing description of the disclosed embodiments enables those skilled in the art to implement or use the present invention.
Various modifications to these embodiments will be readily apparent to those skilled in the art, as defined herein
General Principle can be realized in other embodiments without departing from the spirit or scope of the present invention.Therefore, of the invention
It is not intended to be limited to the embodiments shown herein, and is to fit to and the principles and novel features disclosed herein phase one
The widest scope of cause.
Claims (7)
1. a kind of discrete mode method for early warning of coal and gas prominent disaster based on Real-time Monitoring Data, which is characterized in that method
Include:
Step 1 is demarcated gas flow according to the cross-section shape of roadway of sensor mounting location, cross-sectional area and coal breakage amount and is calculated
Method determines coefficient A and B in following equation, calculate the equivalent relative gas burst quantity sequence of working face in real time:
C- gas density, V- wind speed, S- drift section product, M- coal breakage amount, A and B are calibrated and calculated coefficient, WiEquivalent gas is opposite
Outburst amount；
Step 2, if the gas emission sequence { W of working facei, according to coal and gas prominent event and uneven emission quantity event
Historical record, setting early warning calculate time interval length Dt, pre-warning time section is Q=[T-Dt, T), when the precursor information being related to
Between section be Q1=[T-4Dt,T-3Dt), Q2=[T-3Dt,T-2Dt), Q3=[T-3Dt,T-2Dt), and assume that gas is opposite and gush out
Measure sequence { WiIn section Q1、Q2、Q3, mean value in Q and trend oscillation variance be
Step 3 utilizesGas emission sequence { W is calculated with σiModal parameter N in day part:
Step 4, according to the mine gas geological conditions of early warning working face, exploiting field ocurrence of coal seam situation and production technology, with reference to watt
This gushes out exception history record and the precursor information of similar operation face coal and gas prominent accident records, and provides parameter N relative to 4
The corresponding alarm threshold value of rank=(Nr, No, Ny, Nb)；
Step 5 is recorded according to this working face and its environment and the precursor information of history anomalous event, is determined that gas is opposite and is gushed out
Measure sequence { WiPre- and each section Q1、Q2、Q3With the modal parameter N in Q1、N2、N3The early warning value in the Q of early warning section is calculated with N
Y, according to the rank value interval of modal parameter incremental rate coefficient a, b, c (a > b > c > 1) and early warning value Y of setting
Sr=[Yr,1),So=[Yo,Yr),Sy=[Yy,Yo),Sb=[Yb,Yy),Sg=[0, Yb) early warning at different levels are carried out respectively
Prompt；
Step 6, according to each section modal parameter N1、N2、N3It is clipped to low level from advanced according to following rules with N and gradually calculates
Early warning value Y in the Q of early warning section；
Step 7, according to Y value, system at regular intervals sends the Gas Disaster warning level and early warning value Y of each working face to terminal.
2. the discrete mode method for early warning of the coal and gas prominent disaster according to claim 1 based on Real-time Monitoring Data,
It is characterized in that,
Step 1 further include: install gas concentration sensor and air velocity transducer in the tailentry road of mine, obtain mine
Gas density data and air speed data in the tailentry road of mountain.
3. the discrete mode method for early warning of the coal and gas prominent disaster according to claim 1 based on Real-time Monitoring Data,
It is characterized in that,
Step 2 further include:
Assuming that having each sampled data of n, as y in some sampling interval1,y2,...,yn, then, with the sampling order in the section
I=1,2 ..., n are independent variable x, obtain trend fitting straight line by dependent variable y of relative gas burst quantity W:
Y=kx+h
Calculate the match value of each point:
Computation interval mean value and trend are poor:
Wherein,
4. the discrete mode method for early warning of the coal and gas prominent disaster according to claim 1 based on Real-time Monitoring Data,
It is characterized in that,
Step 5 further include:
Warning level is divided into
Red, it is as superfine；
It is orange, as level-one；
Yellow, as second level；
Blue, as three-level；
Early warning or green as solve alert grade；
First determine whether red early warning rank meets:
Situation 1, red early warning
Red early warning section SrOn being subdivided into rapidly rising, rapid increase, continuously rising, rapidly rise, is quick
Liter, continuous rising, beginning rapidly rise, beginning rapid increase, start continuously rising, without declining 10 grades, differentiate
Formula are as follows:
If 1) N >=Nr,N≥aN3And N3≥aN2And N2≥aN1, then Y=Y is takenr+0.9(1-Yr)
If 2) N >=Nr,N≥bN3And N3≥bN2And N2≥bN1, then Y=Y is takenr+0.8(1-Yr)
If 3) N >=Nr,N≥cN3And N3≥cN2And N2≥cN1, then Y=Y is takenr+0.7(1-Yr)
If 4) N >=Nr,N≥aN3And N3≥aN2, then Y=Y is takenr+0.6(1-Yr)
If 5) N >=Nr,N≥bN3And N3≥bN2, then Y=Y is takenr+0.5(1-Yr)
If 6) N >=Nr,N≥cN3And N3≥cN2, then Y=Y is takenr+0.4(1-Yr)
If 7) N >=Nr,N≥aN3, then Y=Y is takenr+0.3(1-Yr)
If 8) N >=Nr,N≥bN3, then Y=Y is takenr+0.2(1-Yr)
If 9) N >=Nr,N≥cN3, then Y=Y is takenr+0.1(1-Yr)
If 10) N >=Nr,N≥N3, then Y=Y is takenr
If discontented red early warning rank, judges orange warning rank:
Situation 2, orange warning
If 0) N >=No,N3≥Nr, then Y=Y is takenr
If 1) N >=No,N≥aN3And N3≥aN2And N2≥aN1, then Y=Y is takeno+0.9(Yr-Yo)
If 2) N >=No,N≥bN3And N3≥bN2And N2≥bN1, then Y=Y is takeno+0.8(Yr-Yo)
If 3) N >=No,N≥cN3And N3≥cN2And N2≥cN1, then Y=Y is takeno+0.7(Yr-Yo)
If 4) N >=No,N≥aN3And N3≥aN2, then Y=Y is takeno+0.6(Yr-Yo)
If 5) N >=No,N≥bN3And N3≥bN2, then Y=Y is takeno+0.5(Yr-Yo)
If 6) N >=No,N≥cN3And N3≥cN2, then Y=Y is takeno+0.4(Yr-Yo)
If 7) N >=No,N≥aN3, then Y=Y is takeno+0.3(Yr-Yo)
If 8) N >=No,N≥bN3, then Y=Y is takeno+0.2(Yr-Yo)
If 9) N >=No,N≥cN3, then Y=Y is takeno+0.1(Yr-Yo)
If 10) N >=No,N≥N3, then Y=Y is takeno
If discontented orange warning rank, judges yellow warning level:
Situation 3, yellow early warning
If 0) N >=Ny,N3≥No, then Y=Y is takeno
1) calculation method -10) is with orange, only NoChange N intoy, YrChange Y intoo, YoChange Y intoy；
If discontented yellow warning level, judges blue warning level:
Situation 4, blue early warning
If 0) N >=Nb,N3≥Ny, then Y=Y is takeny
1) calculation method -10) is with orange, only NoChange N intob, YrChange Y intoy, YoChange Y intob；
If not blue color warning level, judges green warning level:
Situation 5, green early warning
If 0) N < Nb,N3≥Nb, then Y=Y is takenb
If N < Nb, then takeOtherwise, Y=Y is also takenbCarry out blue early warning.
5. the discrete mode method for early warning of the coal and gas prominent disaster according to claim 1 based on Real-time Monitoring Data,
It is characterized in that,
In step 7, terminal includes: warning data storehouse, the end PC, mobile terminal, digital indication equipment and caution device.
6. a kind of equipment for the discrete mode method for early warning of coal and gas prominent disaster realized based on Real-time Monitoring Data, feature
It is, comprising:
Memory, for storing computer program and the discrete mode early warning of coal and gas prominent disaster based on Real-time Monitoring Data
Method；
Processor, for executing the computer program and the discrete mode of coal and gas prominent disaster based on Real-time Monitoring Data
Method for early warning, with realize coal and gas prominent disaster as described in claim 1 to 5 any one based on Real-time Monitoring Data from
The step of dissipating mode method for early warning.
7. a kind of with the computer-readable of the discrete mode method for early warning of coal and gas prominent disaster based on Real-time Monitoring Data
Storage medium, which is characterized in that computer program, the computer program quilt are stored on the computer readable storage medium
Processor is executed to realize the coal and gas prominent disaster as described in claim 1 to 5 any one based on Real-time Monitoring Data
The step of discrete mode method for early warning.
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