CN109026130A - A kind of recognition methods of mine gas data exception - Google Patents
A kind of recognition methods of mine gas data exception Download PDFInfo
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- CN109026130A CN109026130A CN201810938698.XA CN201810938698A CN109026130A CN 109026130 A CN109026130 A CN 109026130A CN 201810938698 A CN201810938698 A CN 201810938698A CN 109026130 A CN109026130 A CN 109026130A
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- 238000000034 method Methods 0.000 title claims abstract description 32
- 238000012544 monitoring process Methods 0.000 claims abstract description 29
- 230000002159 abnormal effect Effects 0.000 claims abstract description 11
- 238000004519 manufacturing process Methods 0.000 claims abstract description 6
- 230000000694 effects Effects 0.000 claims abstract description 4
- 238000004364 calculation method Methods 0.000 claims description 8
- 238000009826 distribution Methods 0.000 claims description 4
- 238000005259 measurement Methods 0.000 claims description 4
- VNWKTOKETHGBQD-UHFFFAOYSA-N methane Chemical compound C VNWKTOKETHGBQD-UHFFFAOYSA-N 0.000 claims description 4
- 238000012360 testing method Methods 0.000 claims description 4
- 206010011416 Croup infectious Diseases 0.000 claims description 3
- 238000004458 analytical method Methods 0.000 claims description 3
- 230000001174 ascending effect Effects 0.000 claims description 3
- 201000010549 croup Diseases 0.000 claims description 3
- 238000005070 sampling Methods 0.000 claims description 3
- 238000003756 stirring Methods 0.000 claims description 3
- 238000012545 processing Methods 0.000 claims description 2
- 229910017435 S2 In Inorganic materials 0.000 claims 1
- 239000007789 gas Substances 0.000 abstract description 71
- 230000008030 elimination Effects 0.000 abstract 1
- 238000003379 elimination reaction Methods 0.000 abstract 1
- 239000012495 reaction gas Substances 0.000 abstract 1
- 239000003245 coal Substances 0.000 description 4
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- 230000009286 beneficial effect Effects 0.000 description 1
- 238000010586 diagram Methods 0.000 description 1
- 238000002360 preparation method Methods 0.000 description 1
Classifications
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- E—FIXED CONSTRUCTIONS
- E21—EARTH OR ROCK 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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- E—FIXED CONSTRUCTIONS
- E21—EARTH OR ROCK DRILLING; MINING
- E21F—SAFETY DEVICES, TRANSPORT, FILLING-UP, RESCUE, VENTILATION, OR DRAINING IN OR OF MINES OR TUNNELS
- E21F7/00—Methods or devices for drawing- off gases with or without subsequent use of the gas for any purpose
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q50/00—Information and communication technology [ICT] specially adapted for implementation of business processes of specific business sectors, e.g. utilities or tourism
- G06Q50/02—Agriculture; Fishing; Forestry; Mining
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Abstract
The invention discloses a kind of recognition methods of mine gas data exception in safety production technique field, and specific step is as follows for the recognition methods: S1: gas density Moving Average is established；S2: the speed degree that reaction gas density changes；S3: gas density departure degree is calculated by variance；S4: All Time sequence data is taken to be analyzed；S5: data handle by difference and take its characteristic value；S6: judged and analyzed for abnormal dubious value；S7: abnormal data elimination reduces screen effect, the present invention passes through the characteristic to Gas Outburst eve variation ofgas density in mine, it realizes to the prediction outstanding of gas in mine, it extracted for gas monitor data of the gas in different time sequence, handled by difference simultaneously, obtain suspicious monitoring data, analyze and determine whether gas density is more than defined warning concentration and power-off required concentration critical value based on Moving Average, recognition methods is simple and effective, and the result accuracy rate of identification is high.
Description
Technical field
The invention discloses a kind of recognition methods of mine gas data exception, specially safety production technique field.
Background technique
Gas is one of major casualty of coal mine, seriously threatens the safety in production of coal mine, finds after study, in gas
Before protrusion, some exceptions often occur for the gas density of working face, but the concentration of gas does not transfinite, and are easy to be neglected
Depending on.There are stronger schedule dependence and front and back inheritance, the original state letter of gas density data between gas density data
It include the characteristic information of succeeding state in number feature.The variation of face gas concentration reflects the coal mine inside working face wall
The situation of change of the factors such as working stress, gas pressure and coal body mechanical property.For this purpose, we have proposed a kind of mine gases
The recognition methods of data exception is come into operation, to solve the above problems.
Summary of the invention
The purpose of the present invention is to provide a kind of recognition methods of mine gas data exception, to solve above-mentioned background technique
The problem of middle proposition.
To achieve the above object, the invention provides the following technical scheme: a kind of recognition methods of mine gas data exception,
Specific step is as follows for the recognition methods:
S1: using the situation of change of gas density in Moving Average reaction mine, i.e. gas density is before protrusion, prison
The variation tendency of measured data will continue for some time, until external force forces it to change this trend；
S2: introducing gas concentration monitoring data movement rate ROC, for reacting the speed degree of gas density variation；
S3: the degree that gas density currently deviates mean value is reacted by calculating variance, value is bigger, the variation of gas density
Amplitude is bigger, on the contrary then smaller；
S4: it takes the All Time sequence data of measuring point in a mine to be analyzed, is denoted as Y={ Y1,Y2,…,Ym, if prison
The variation random rates of measured frequency are larger, then to data routinely monitoring frequency variation sampling；
S5: to Y={ Y1,Y2,…,YmIn data press Xi=Yi+1- Y handle by difference, if partial period monitors number
According to missing, data thereafter are handled by difference again, data is obtained and constitutes sample space X={ X1,X2,…,Xn, and obey or
Approximate Normal Distribution, characteristic value are as follows:
S6: determining the dubious value distributed area of X with little probability method, take level of significance α=5%, according to point of α and X
Cloth function, obtainsAs X > XmaxOr X < Xmin, then X is suspicious；
S7: after there is abnormal data, emergent management measure is taken, it is ensured that production safety, next time is in use, then by abnormal number
It according to rejecting, tests in the same way, avoids the screen effect between exceptional value.
Preferably, in the step S1, the calculation formula of Moving Average isIn formulaIt is n watts
This Concentration Testing statistical average, n are gas concentration monitoring data record number in a period of time, CiIn i-th of gas density
Monitoring data record.
Preferably, in the step S2, a time parameter N, generation are contained only in gas concentration monitoring data movement rate ROC
Table is same, and how long previous gas density is compared, its calculation formula isROC in formula(n)For n
The gas concentration data rate of change, C in a timetFor t moment gas concentration monitoring data, C(t-n)For (t-n) moment gas monitor
Data.
Preferably, in the step S3, the calculation formula of variance isFormula
Middle S2For the variance of gas concentration monitoring data sample,For the mean value for monitoring gas density data sample.
Preferably, in the step S5, work as XiWith Xi+1It is suspicious, then Yi+1For cusp form exceptional value；Work as XiSingle-point is suspicious
When, then Yi+1For stepped ramp type exceptional value, the exceptional value as caused by spurious errors is rejected in analysis and processing to exceptional value,
And adjustment is carried out to monitoring system.
Preferably, in the step S6, this method of croup is also can be used in the identification for abnormal data, i.e., analyzes gas
The ascending arrangement of data: X1,X2,X3,X4…Xn-1,Xn+1, wherein dubious value is X1Or Xn, first reorganize being averaged for data at calculating
ValueAnd standard deviation S, then Counting statistics amount,According to pre-determined confidence level and survey
Determine number to table look-up, if G is greater than looked into numerical value, the X relative to G1Or XnFor exceptional value.
Preferably, in the step S7, gas rate of change curve graph is established, if the peaks and troughs variation of curve graph is more
Gently, it stirs and belongs within the scope of normality, then the change rate of gas belongs to normal epoch, if if the peaks and troughs of curve graph change
It is more significant, illustrate that gas will protrude, variation ofgas density is further frequent, makes early warning to Gas Outburst.
Compared with prior art, the beneficial effects of the present invention are: the present invention passes through to Gas Outburst eve gas in mine
The characteristic of concentration variation is realized to the prediction outstanding of gas in mine, while for gas in different time sequence
Gas monitor data are extracted, are handled by difference, and suspicious monitoring data are obtained, and analyze and determine gas density based on Moving Average
It whether is more than defined warning concentration and power-off required concentration critical value, recognition methods is simple and effective, and the result accuracy rate of identification is high.
Detailed description of the invention
Fig. 1 is work flow diagram of the present invention.
Specific embodiment
Following will be combined with the drawings in the embodiments of the present invention, and technical solution in the embodiment of the present invention carries out clear, complete
Site preparation description, it is clear that described embodiments are only a part of the embodiments of the present invention, instead of all the embodiments.It is based on
Embodiment in the present invention, it is obtained by those of ordinary skill in the art without making creative efforts every other
Embodiment shall fall within the protection scope of the present invention.
Referring to Fig. 1, the present invention provides a kind of technical solution: a kind of recognition methods of mine gas data exception, the knowledge
Specific step is as follows for other method:
S1: using the situation of change of gas density in Moving Average reaction mine, i.e. gas density is before protrusion, prison
The variation tendency of measured data will continue for some time, until external force forces it to change this trend, the calculating of Moving Average
Formula isIn formulaFor n methane Concentration Measurement statistical average, n is gas density prison in a period of time
Measured data records number, CiIn i-th of gas concentration monitoring data record；
S2: introduce gas concentration monitoring data movement rate ROC, for react gas density variation speed degree, watt
This concentration monitor data movement rate ROC contains only a time parameter N, represents with how long previous gas density is compared
Compared with, its calculation formula isROC in formula(n)For the gas concentration data rate of change, C in n timetFor t
Moment gas concentration monitoring data, C(t-n)For (t-n) moment gas monitor data；
S3: the degree that gas density currently deviates mean value is reacted by calculating variance, value is bigger, the variation of gas density
Amplitude is bigger, on the contrary then smaller, and the calculation formula of variance is S in formula2For watt
The variance of this concentration monitor data sample,For the mean value for monitoring gas density data sample；
S4: it takes the All Time sequence data of measuring point in a mine to be analyzed, is denoted as Y={ Y1,Y2,…,Ym, if prison
The variation random rates of measured frequency are larger, then to data routinely monitoring frequency variation sampling；
S5: to Y={ Y1,Y2,…,YmIn data press Xi=Yi+1- Y handle by difference, if partial period monitors number
According to missing, data thereafter are handled by difference again, data is obtained and constitutes sample space X={ X1,X2,…,Xn, and obey or
Approximate Normal Distribution, characteristic value are as follows: Work as XiWith Xi+1?
It doubts, then Yi+1For cusp form exceptional value；Work as XiWhen single-point is suspicious, then Yi+1For stepped ramp type exceptional value, analysis and place to exceptional value
Reason, the exceptional value as caused by spurious errors is rejected, and carries out adjustment to monitoring system；
S6: determining the dubious value distributed area of X with little probability method, take level of significance α=5%, according to point of α and X
Cloth function, obtainsAs X > XmaxOr X < Xmin, then X is suspicious,
This method of croup also can be used in identification for abnormal data, i.e., gas is analyzed the ascending arrangement of data: X1,X2,X3,
X4…Xn-1,Xn+1, wherein dubious value is X1Or Xn, first reorganize the average value of data at calculatingAnd standard deviation S, then calculate system
Metering,It is tabled look-up according to pre-determined confidence level and measurement number, if G is greater than looked into number
Value, then relative to the X of G1Or XnFor exceptional value；
S7: after there is abnormal data, emergent management measure is taken, it is ensured that production safety, next time is in use, then by abnormal number
It according to rejecting, tests in the same way, avoids the screen effect between exceptional value, gas rate of change curve graph is established, if bent
The peaks and troughs variation of line chart is more gentle, stirs and belongs within the scope of normality, then the change rate of gas belongs to normal epoch, if
If the peaks and troughs variation of curve graph is more significant, illustrate that gas will protrude, variation ofgas density is further frequent, to gas
Protrusion makes early warning.
The present invention is realized by the characteristic to Gas Outburst eve variation ofgas density in mine to Gas Outburst in mine
Prediction, while being extracted for gas monitor data of the gas in different time sequence, being handled by difference, obtaining can
Monitoring data are doubted, analyze and determine whether gas density is more than that defined warning concentration and power-off required concentration are critical based on Moving Average
Value, recognition methods is simple and effective, and the result accuracy rate of identification is high.
It although an embodiment of the present invention has been shown and described, for the ordinary skill in the art, can be with
A variety of variations, modification, replacement can be carried out to these embodiments without departing from the principles and spirit of the present invention by understanding
And modification, the scope of the present invention is defined by the appended.
Claims (7)
1. a kind of recognition methods of mine gas data exception, it is characterised in that: specific step is as follows for the recognition methods:
S1: using the situation of change of gas density in Moving Average reaction mine, i.e. gas density monitors number before protrusion
According to variation tendency will continue for some time, until external force forces it to change this trend；
S2: introducing gas concentration monitoring data movement rate ROC, for reacting the speed degree of gas density variation；
S3: the degree that gas density currently deviates mean value is reacted by calculating variance, value is bigger, the amplitude of variation of gas density
It is bigger, it is on the contrary then smaller；
S4: it takes the All Time sequence data of measuring point in a mine to be analyzed, is denoted as Y={ Y1,Y2,…,Ym, if monitoring frequency
The variation random rates of rate are larger, then to data routinely monitoring frequency variation sampling；
S5: to Y={ Y1,Y2,…,YmIn data press Xi=Yi+1- Y handle by difference, if partial period monitoring data lack
It loses, data thereafter is handled by difference again, data is obtained and constitutes sample space X={ X1,X2,…,Xn, and obedience or approximate
Normal Distribution, characteristic value are as follows:
S6: determining the dubious value distributed area of X with little probability method, take level of significance α=5%, according to the distribution letter of α and X
Number, obtainsAs X > XmaxOr X < Xmin, then X is suspicious；
S7: after there is abnormal data, emergent management measure is taken, it is ensured that production safety, next time is in use, then pick abnormal data
It removes, tests in the same way, avoid the screen effect between exceptional value.
2. a kind of recognition methods of mine gas data exception according to claim 1, it is characterised in that: the step S1
In, the calculation formula of Moving Average isIn formulaFor n methane Concentration Measurement statistical average, n is
Gas concentration monitoring data record number, C in a period of timeiIn i-th of gas concentration monitoring data record.
3. a kind of recognition methods of mine gas data exception according to claim 1, it is characterised in that: the step S2
In, contain only a time parameter N in gas concentration monitoring data movement rate ROC, represent with how long before gas it is dense
Degree is compared, its calculation formula isROC in formula(n)It is changed for gas concentration data in n time
Rate, CtFor t moment gas concentration monitoring data, C(t-n)For (t-n) moment gas monitor data.
4. a kind of recognition methods of mine gas data exception according to claim 1, it is characterised in that: the step S3
In, the calculation formula of variance isS in formula2For gas concentration monitoring data sample
This variance,For the mean value for monitoring gas density data sample.
5. a kind of recognition methods of mine gas data exception according to claim 1, it is characterised in that: the step S5
In, work as XiWith Xi+1It is suspicious, then Yi+1For cusp form exceptional value；Work as XiWhen single-point is suspicious, then Yi+1For stepped ramp type exceptional value, to different
The analysis and processing of constant value, the exceptional value as caused by spurious errors is rejected, and carries out adjustment to monitoring system.
6. a kind of recognition methods of mine gas data exception according to claim 1, it is characterised in that: the step S6
In, this method of croup also can be used in the identification for abnormal data, i.e., gas is analyzed the ascending arrangement of data: X1,X2,X3,
X4…Xn-1,Xn+1, wherein dubious value is X1Or Xn, first reorganize the average value of data at calculatingAnd standard deviation S, then calculate system
Metering,It is tabled look-up according to pre-determined confidence level and measurement number, if G is greater than looked into number
Value, then relative to the X of G1Or XnFor exceptional value.
7. a kind of recognition methods of mine gas data exception according to claim 1, it is characterised in that: the step S7
In, gas rate of change curve graph is established, if the peaks and troughs variation of curve graph is more gentle, stirs and belongs within the scope of normality,
Then the change rate of gas belongs to normal epoch, if illustrating that gas will dash forward if the peaks and troughs variation of curve graph is more significant
Out, variation ofgas density is further frequent, makes early warning to Gas Outburst.
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Cited By (6)
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| CN110163442A (en) * | 2019-05-27 | 2019-08-23 | 华北理工大学 | A kind of gas well plug-ging prediction technique based on integrated study |
| CN111582603A (en) * | 2020-05-19 | 2020-08-25 | 中煤科工集团重庆研究院有限公司 | Intelligent early warning method for coal and gas outburst based on multi-source information fusion |
| CN112963205A (en) * | 2021-03-15 | 2021-06-15 | 太原理工大学 | Coal mine goaf gas combustion emergency treatment system and method |
| CN113506007A (en) * | 2021-07-19 | 2021-10-15 | 上海抉真网络科技有限责任公司 | Well drilling type data sampling method and application thereof in big data value risk assessment |
| CN113743486A (en) * | 2021-08-23 | 2021-12-03 | 北京科技大学 | Method for predicting tunneling head coal and gas outburst danger by applying gas concentration after blasting |
| CN116070163A (en) * | 2023-03-07 | 2023-05-05 | 深圳市特安电子有限公司 | Indoor harmful gas concentration anomaly monitoring data processing method |
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| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110163442A (en) * | 2019-05-27 | 2019-08-23 | 华北理工大学 | A kind of gas well plug-ging prediction technique based on integrated study |
| CN111582603A (en) * | 2020-05-19 | 2020-08-25 | 中煤科工集团重庆研究院有限公司 | Intelligent early warning method for coal and gas outburst based on multi-source information fusion |
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| CN113506007A (en) * | 2021-07-19 | 2021-10-15 | 上海抉真网络科技有限责任公司 | Well drilling type data sampling method and application thereof in big data value risk assessment |
| CN113506007B (en) * | 2021-07-19 | 2022-05-20 | 上海抉真网络科技有限责任公司 | Well drilling type data sampling method and application thereof in big data value risk assessment |
| CN113743486A (en) * | 2021-08-23 | 2021-12-03 | 北京科技大学 | Method for predicting tunneling head coal and gas outburst danger by applying gas concentration after blasting |
| CN113743486B (en) * | 2021-08-23 | 2023-09-29 | 北京科技大学 | Method for predicting heading coal and gas outburst risk by using post-blasting gas concentration |
| CN116070163A (en) * | 2023-03-07 | 2023-05-05 | 深圳市特安电子有限公司 | Indoor harmful gas concentration anomaly monitoring data processing method |
| CN116070163B (en) * | 2023-03-07 | 2023-07-11 | 深圳市特安电子有限公司 | Indoor harmful gas concentration anomaly monitoring data processing method |
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Application publication date: 20181218 |