CN109800955A - Coal seam bottom water bursting hazard assessment calculation method - Google Patents
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- 230000009172 bursting Effects 0.000 title claims abstract description 16
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- 238000011156 evaluation Methods 0.000 claims abstract description 70
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Abstract
The invention discloses a kind of coal seam bottom water bursting hazard assessment calculation methods, evaluation procedure is as follows: a, determining evaluation factor collection: choosing the influence factor of coal seam bottom water bursting, by the acquisition and analysis to gushing water sample data, influence factor set i.e. evaluation factor collection is established；B, the Comment gathers of Comprehensive Evaluation are determined, c, determine factor weight vector；D, it carries out single factor test fuzzy evaluation and calculates construction jdgement matrix；E, it carries out fuzzy composition and makes decisions: introducing a fuzzy subset on Comment gathers, claim decision set, this is Fuzzy Synthetical Decision Model, obtains evaluation result.The present invention has carried out objective analysis to the capability of influence for influencing coal seam bottom water bursting factor, and effectively filtering out influences significant impact factor, reduces interference of the not strong factor of capability of influence to evaluation result.
Description
Technical field
The present invention relates to a kind of coal seam water inrush evaluation methods more particularly to a kind of coal seam bottom water bursting hazard assessment to calculate
Method.
Background technique
Coal is the important basic energy resource in China, and coal resources in China very abundant, purposes is very extensive, to China
The national economic development is of great significance.The pattern of coal dominance in primary energy production and consumption is not shaken yet.
In consumption of coal, electric power, steel, building materials and chemical industry consumption coal account for 80% of consumption of coal or more.
However, more and more safety problems are also come thick and fast with the continuous improvement of coal production.As it can be seen that carrying out coal
Layer Water Inrush method for evaluating hazard studies the coal resources threatened for liberating China by water, protection staff life security tool
It is of great significance.
For many years, many scholars have conducted extensive research coal seam bottom water bursting hazard assessment.In China, water bursting coefficient
Method is used till today always for 60 years from the upper world, but this method only accounts for hydraulic pressure and impermeable layer thickness, and has ignored other influences
The effect of factor.Over nearly ten or twenty year, scholars are by fuzzy mathematics, analytic hierarchy process (AHP), neural network, GIS-Geographic Information System skill
The methods of art, support vector machines introduce on Prediction of Water Jetting from Coal Bottom and hazard assessment, achieve many achievements.However, this
A little methods have on to Water Inrush influence degree although it is contemplated that influence mode and feature of each factor in Water Inrush
There are certain subjectivity and randomness, it is still not objective enough to calculate analysis, and does not account for each influence factor for evaluation
The effect and influence of system.
There are many factor for influencing coal seam bottom water bursting, but role during gushing water of these factors is different,
Some capability of influence may be very strong, and some then may be very faint.If all factors are all used to establish to comment with not making any distinction between
Valence system not only will increase calculation amount and difficulty in computation, it is also possible to because the correlation between influence factor leads to the drop of computational accuracy
It is low.On the other hand, when introducing the not strong factor of some capability of influence in appraisement system, interference can be generated to evaluation effect, caused
The evaluation model of foundation is unstable.Therefore, influence factor how to be selected to become a particularly important problem.Meanwhile bottom plate is prominent
Water is a nonlinear problem again, thus needs to solve with nonlinear method.Therefore it is badly in need of a kind of more scientific coal seam
Water Inrush method for evaluating hazard.
Summary of the invention
The technical problems to be solved by the present invention are: it is a kind of more steady to provide in place of overcome the deficiencies in the prior art,
More scientific, practical coal seam floor water-inrush risk evaluation method.
The technical solution adopted by the present invention are as follows: a kind of coal seam floor water-inrush risk evaluation method, evaluation procedure are as follows:
I, evaluation factor collection is determined:
According to each mining area many years experience with mining, the influence factor of coal seam bottom water bursting is chosen, by gushing water sample number
According to acquisition and analysis, establish influence factor set i.e. evaluation factor collection；
II, the Comment gathers for determining Comprehensive Evaluation:
Comment gathers are the set that various indexs are made with possible outcome.
III, factor weight vector is determined:
In evaluation, weight is the measurement value of characterization factor relative importance size, by investigating each evaluation to the index
The information content for including in systems is smaller.The difference of object index value and reference value, with the index after quantization, with other indexs
It is radix that index value, which is with reference to sequence difference, finally obtains evaluation result and is asked according to column with the index value of index to compare sequence
It obtains evaluation of result object and carries out ranking.
IV, it carries out single factor test fuzzy evaluation and calculates construction jdgement matrix:
Simple element evaluation is done to the single factor test in set of factors first, from factor to decision grade, that is, Comment gathers degree of membership,
It thus obtains the simple element evaluation collection of each factor, then constructs a total evaluations matrix.The solution of degree of membership passes through
Membership function is constructed, the method for the membership function of construction can be Statistical self similarity method, the method for undetermined coefficients, Multivariate Membership Function method
Deng.
V, it carries out fuzzy composition and makes decisions:
A fuzzy subset on Comment gathers is introduced, decision set is claimed.Enabling it be equal to weight vectors * jdgement matrix, (* is calculation
Subsymbol), this is Fuzzy Synthetical Decision Model, obtains evaluation result.
The solution have the advantages that: objective analysis has been carried out to the capability of influence for influencing coal seam bottom water bursting factor,
Effectively filtering out influences significant impact factor, reduces interference of the not strong factor of capability of influence to evaluation result.According to
The factor filtered out, by fuzzy theory again with combining traditional grey relation theory with norm concept, in existing gushing water sample
On the basis of data, non-linear discriminating analysis model is established.Since the model is on the basis for counting a large amount of influence factor data
The evaluation of upper progress calculates, thus more previous model is more steady, more scientific, practical.
Detailed description of the invention
Fig. 1 is evaluation procedure flow chart of the invention.
Specific embodiment
The present invention will be further described in detail below with reference to the accompanying drawings and specific embodiments.
1. determining evaluation factor collection:
Set of factors is to be set as U={ u to influence the various factors of evaluation object as a set composed by element1,
u2..., un}.U is the n kind factor i.e. evaluation index for portraying evaluation object.
According to each mining area many years experience with mining, the influence factor of coal seam bottom water bursting is chosen, by gushing water sample number
According to acquisition and analysis, establish influence factor set i.e. evaluation factor collection；
2. determining the Comment gathers of Comprehensive Evaluation:
Comment gathers are the set that various indexs are made with possible outcome, are set as V={ v1, v2, v3 ..., vn}.V is to portray
The n kind resolution of each factor state in which is opinion rating, and n is comment number, is generally divided into 3~5 grades.
3. determining factor weight vector
In evaluation, weight is the measurement value of characterization factor relative importance size, by investigating each evaluation to the index
The information content for including in systems is smaller.The difference of object index value and reference value, with the index after quantization, with other indexs
It is radix that index value, which is with reference to sequence difference, finally obtains evaluation result and is asked according to column with the index value of index to compare sequence
It obtains evaluation of result object and carries out ranking.
Standardization is carried out to achievement data first and sets m as evaluation object number, n is index number, yijFor i-th of evaluation pair
J-th of index value of elephant, and remember ZijFor the index value after standardization.
Then reference sequences x is determined0h, calculate the absolute difference of each evaluation object and reference sequences.
Δih=| zih-x0h|
ΔihFor absolute difference, | zih| it is former sequence after standardization, | x0h| it is reference sequences.
Last parameter weight W
wjFor the weight of jth item, εjFor the difference of jth item.
4. carrying out single factor test fuzzy evaluation calculates construction jdgement matrix
Simple element evaluation is done to the single factor test in set of factors first, from factor to decision grade, that is, Comment gathers degree of membership,
It thus obtains the simple element evaluation collection of each factor, then constructs a total evaluations matrix.The solution of degree of membership passes through
Membership function is constructed, the method for the membership function of construction can be Statistical self similarity method, the method for undetermined coefficients, Multivariate Membership Function method
Deng.
First to the single factor test U in set of factorsi(i=1,2,3 ..., n) does simple element evaluation, from factor UiTo decision grade
VjDegree of membership be Rij, thus obtain the simple element evaluation collection of i-th of factor Ui: Ri=(Ri1, Ri2..., Rin).Such n
The evaluation set of a factor just constructs a total evaluations matrix R.I.e. each is evaluated object and has determined obtains mould from U to V
Paste relational matrix R.
5. carrying out fuzzy composition and making decisions
A fuzzy subset B on V is introduced, decision set, i.e. B=(b are claimed1, b2, b3..., bn).Enabling B=A*R, (* is calculation
Subsymbol), this is Fuzzy Synthetical Decision Model.In order to keep the result of decision clear, using information principle of centrality, first by feasibility
Degree demarcation interval simultaneously takes single section median to be used as set Ci=(c1, c2, c3..., cn), formula is concentrated by information:
Wherein biFor element in decision set, ciFor demarcation interval set element.
According to final score S, coal seam bottom water bursting risk degree can be calculated by compareing demarcation interval.
The above described is only a preferred embodiment of the present invention, be not intended to limit the present invention in any form, it is all
It is any simple modification, equivalent change and modification to the above embodiments according to the technical essence of the invention, still falls within
In the range of technical solution of the present invention.
Claims (1)
1. a kind of coal seam bottom water bursting hazard assessment calculation method, comprising the following steps:
A. evaluation factor collection is determined:
Set of factors is to be set as U={ u to influence the various factors of evaluation object as a set composed by element1, u2...,
un, U is the n kind factor i.e. evaluation index for portraying evaluation object；
According to each mining area many years experience with mining, the influence factor of coal seam bottom water bursting is chosen, by gushing water sample data
Acquisition and analysis, establish influence factor set i.e. evaluation factor collection；
B. the Comment gathers of Comprehensive Evaluation are determined:
Comment gathers are the set that various indexs are made with possible outcome, are set as V={ v1, v2, v3 ..., vn, V be portray it is each because
The n kind resolution of plain state in which is opinion rating, and n is comment number, is generally divided into 3~5 grades；
C. factor weight vector is determined:
In evaluation, weight is the measurement value of characterization factor relative importance size, is being to the index by investigating each evaluation
The information content for including in system is smaller, the difference of object index value and reference value, with the index after quantization, with the index of other indexs
It is radix that value, which is with reference to sequence difference, finally obtains evaluation result and acquires knot with the index value of index to compare sequence according to column
Fruit evaluation object carries out ranking；
Standardization is carried out to achievement data first and sets m as evaluation object number, n is index number, yijIt is the of i-th of evaluation object
J index value, and remember ZijFor standardization after index value:
Then reference sequences x is determined0h, calculate the absolute difference of each evaluation object and reference sequences:
Δih=| zih-x0h|
ΔihFor absolute difference, | zih| it is former sequence after standardization, | x0h| it is reference sequences,
Last parameter weight W:
wjFor the weight of jth item, εjFor the difference of jth item,
D. it carries out single factor test fuzzy evaluation and calculates construction jdgement matrix:
Simple element evaluation is done to the single factor test in set of factors first, from factor to decision grade, that is, Comment gathers degree of membership, in this way
It just obtains the simple element evaluation collection of each factor, then constructs a total evaluations matrix, the solution of degree of membership passes through construction
The method of membership function, the membership function of construction uses Statistical self similarity method, the method for undetermined coefficients, Multivariate Membership Function method；
First to the single factor test U in set of factorsi(i=1,2,3 ..., n) does simple element evaluation, from factor UiTo decision grade Vj's
Degree of membership is Rij, thus obtain i-th of factor UiSimple element evaluation collection: Ri=(Ri1, Ri2..., Rin), such n factor
Evaluation set just construct a total evaluations matrix R, i.e., each is evaluated object and has determined obtains fuzzy relation from U to V
Matrix R；
E. it carries out fuzzy composition and makes decisions:
A fuzzy subset B on V is introduced, decision set, i.e. B=(b are claimed1, b2, b3..., bn), enable B=A*R, wherein * is operator
Symbol, this is Fuzzy Synthetical Decision Model, in order to keep the result of decision clear, using information principle of centrality, first by feasibility journey
Degree demarcation interval simultaneously takes single section median to be used as set Ci=(c1, c2, c3..., cn), formula is concentrated by information:
Wherein biFor element in decision set, ciFor demarcation interval set element,
According to final score S, coal seam bottom water bursting risk degree can be calculated by compareing demarcation interval.
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| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114087022A (en) * | 2021-10-28 | 2022-02-25 | 山东科技大学 | Coal seam floor variable parameter water inrush channel early warning system and water inrush danger judgment method |
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