CN112836995A - Fault activation water inrush risk evaluation method based on uncertain entropy weight method - Google Patents

Fault activation water inrush risk evaluation method based on uncertain entropy weight method Download PDF

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CN112836995A
CN112836995A CN202110252855.3A CN202110252855A CN112836995A CN 112836995 A CN112836995 A CN 112836995A CN 202110252855 A CN202110252855 A CN 202110252855A CN 112836995 A CN112836995 A CN 112836995A
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刘伟韬
韩梦珂
秦月云
孟祥喜
杜衍辉
宋增谋
庞立夫
宋伟国
李耀华
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Abstract

The invention relates to a fault activation water inrush risk evaluation method based on an unknown-entropy weight method, which belongs to the field of coal mining and comprises the steps of inducing main factors influencing fault activation water inrush and establishing an evaluation index system; establishing an evaluation index system and establishing a factor set; establishing a grading standard table of each index under an evaluation grade set and a factor set; determining single-index uncertain measure vectors of each influence factor through an uncertain measure function, and combining the uncertain measure vectors of each index to form a single-index uncertain measure evaluation matrix; solving the numerical solution of the evaluation result according to an uncertain-entropy weight method, wherein an uncertain evaluation program is used for determining an uncertain measure evaluation matrix, and the entropy weight method is used for solving the weight to obtain a multi-index comprehensive measure vector; and obtaining an evaluation result according to the confidence coefficient judgment criterion. The fault activation water inrush risk assessment method is based on an uncertain theory and an information entropy theory, can be used for assessing a plurality of main control factors, and provides a new thought for fault activation water inrush risk assessment.

Description

Fault activation water inrush risk evaluation method based on uncertain entropy weight method
Technical Field
The invention relates to a fault activation water inrush risk evaluation method based on an uncertain-entropy weight method, belongs to the technical field of coal mining, and particularly relates to the technical field of fault activation water inrush prevention near a coal mining working face.
Background
The fault activation water inrush has no water conductivity before the fault is not mined, even has better water resistance, and the fault activation is caused by mining stress after the fault is mined, so that the water inrush is induced. For the faults, measures are taken to avoid risks before mining, but for the fault originally with poor water conductivity, even if advanced detection is carried out before mining, the water conductivity is determined to be insufficient to influence coal mining, but mining stress is easy to cause the rock mass near the fault to have the possibility of crack development in the actual mining process, and the fault is easy to activate due to the influence of water pressure, and once the crack penetrates through a water-bearing layer to form a water inrush channel, a water inrush accident can be caused.
At present, some scholars establish mathematical models for evaluating fault activation water inrush risks by using mathematical theories, such as neural networks, fuzzy mathematics, grey correlation degrees and the like. The mathematical quantitative model methods are developed to a certain extent, but have certain limitations and limited application effects, and are mainly reflected in the defects of the mathematical theory, some evaluation methods are not in accordance with the characteristics of the measurement criteria of nonnegative boundedness, additivity and normalization, for example, the fuzzy comprehensive evaluation method takes a large amount of information of intermediate values lost by small and large operations, and the problems of unclear classification and unreasonable results occur.
Disclosure of Invention
Aiming at the defects of the prior art, the invention provides a fault activation water inrush risk evaluation method based on an unknown-entropy weight method, which can evaluate a plurality of main control factors and provides technical support for improving the safety of mine exploitation.
The invention adopts the following technical scheme:
a fault activation water inrush risk evaluation method based on an unknown-entropy weight method comprises the following steps:
step A, inducing main factors influencing fault activation water inrush, and establishing an evaluation index system with a hierarchical structure;
b, establishing a factor set according to the evaluation index system established in the step A;
step C, establishing a grading standard table of each index under an evaluation grade set and a factor set according to field practice and engineering experience;
d, according to an uncertain theory, determining single-index uncertain measure vectors of each influence factor through an uncertain measure function, and combining the single-index uncertain measure vectors of each index to form a single-index uncertain measure evaluation matrix;
according to the information entropy theory, calculating the weight vector of each index, and respectively calculating the multi-index uncertain measure evaluation vectors of 4 influence factors for evaluating the fault activation water inrush risk according to the single-index uncertain measure evaluation matrix and the weight vector; according to the information entropy theory, evaluating index weights corresponding to the 4 influence factors are solved, and finally a multi-index comprehensive measure vector is obtained;
and obtaining an evaluation result according to the confidence coefficient judgment criterion.
Preferably, the main factors influencing fault activation water inrush in the step A comprise engineering hydrogeology, fault properties, mining conditions and bottom plate water blocking;
the evaluation index system sequentially comprises three layersThe highest layer is fault activated water burst A, the middle layer is the main factor including engineering hydrogeology B1Fault property B2And mining conditions B3And bottom water-blocking B4The lowest layer is 8 factors, namely the buried depth C1Hydrogeological conditions C2Fault dip angle C3Fault drop C4Size of working face C5And the width C of the waterproof coal pillar6Pressure-bearing water pressure C7And a water barrier thickness C8Each of the main factors of the middle layer is affected by the bottom 8 factors, namely: engineering hydrogeology B1Buried depth C1Hydrogeological conditions C2Influence of, fault property B2Dip angle C of faulted layer3Fault drop C4Influence of, mining Condition B3Dimension C of receiving working surface5And the width C of the waterproof coal pillar6Influence of (B) water blocking of the sole4Bearing pressure of water C7And a water barrier thickness C8The influence of (c).
Preferably, the set of factors T ═ T is established in step B1、T2、T3、T4And (5) engineering hydrogeology, fault property, mining condition and bottom plate water resistance }.
Preferably, the ranking criteria in step C are divided into four ranks, i.e., S ═ S1，S2，S3，S4Safety, general danger, danger;
the classification criteria table is shown in table 1:
table 1: grading standard table
Figure BDA0002966750610000021
Figure BDA0002966750610000031
Figure BDA0002966750610000041
In Table 1, hydrogeological conditions C2And the width C of the waterproof coal pillar6Directly taking values according to the table 1, and other evaluation indexes: buried depth C1Hydrogeological conditions C2Fault dip angle C3Fault drop C4Size of working face C5Pressure-bearing water pressure C7And a water barrier thickness C8Are all determined by calculation.
Preferably, the function of the uncertainty measure for each evaluation index under the uncertainty theory is as follows:
buried depth C1Function of undetermined measures of (1):
Figure BDA0002966750610000042
Figure BDA0002966750610000043
Figure BDA0002966750610000044
Figure BDA0002966750610000045
fault dip angle C3Function of undetermined measures of (1):
Figure BDA0002966750610000051
Figure BDA0002966750610000052
Figure BDA0002966750610000053
Figure BDA0002966750610000054
fault fall C4Function of undetermined measures of (1):
Figure BDA0002966750610000055
Figure BDA0002966750610000061
Figure BDA0002966750610000062
Figure BDA0002966750610000063
working face size C5Function of undetermined measures of (1):
Figure BDA0002966750610000064
Figure BDA0002966750610000065
Figure BDA0002966750610000071
Figure BDA0002966750610000072
pressure-bearing water pressure C7Function of undetermined measures of (1):
Figure BDA0002966750610000073
Figure BDA0002966750610000074
Figure BDA0002966750610000075
Figure BDA0002966750610000081
thickness C of water barrier layer8Function of undetermined measures of (1):
Figure BDA0002966750610000082
Figure BDA0002966750610000083
Figure BDA0002966750610000084
Figure BDA0002966750610000085
in the formulas (8) to (31), x represents a specific numerical value of each evaluation index, and μ represents a measurement value of each evaluation level to which the evaluation index belongs;
and obtaining a single-index undetermined measurement evaluation matrix according to the condition that the middle layer of the evaluation index system is influenced by the bottommost layer.
The invention is not described in detail, and can be carried out by adopting the prior art.
The invention has the beneficial effects that:
the method is mainly based on an uncertain theory, weights are obtained by utilizing an information entropy theory, the method can evaluate a plurality of main control factors, and the obtained reasonable and reliable experiment proves that the method is basically consistent with the field situation when being applied to the field.
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FIG. 1 is a flow chart of the fault activation water inrush risk evaluation method based on the unknown-entropy weight method;
FIG. 2 is a schematic diagram of an evaluation index system with a hierarchical structure for fault activation water inrush according to an embodiment of the present invention.
The specific implementation mode is as follows:
in order to make the technical problems, technical solutions and advantages of the present invention more apparent, the following detailed description is given with reference to the accompanying drawings and specific examples, but not limited thereto, and the present invention is not described in detail and is in accordance with the conventional techniques in the art.
Example 1:
an uncertain-entropy weight method-based fault activation water inrush risk evaluation method is shown in figure 1 and comprises the following steps:
step A, inducing main factors influencing fault activation water inrush, and establishing an evaluation index system with a hierarchical structure;
b, establishing a factor set according to the evaluation index system established in the step A;
step C, establishing a grading standard table of each index under an evaluation grade set and a factor set according to field practice and engineering experience;
d, according to an uncertain theory, determining single-index uncertain measure vectors of each influence factor through an uncertain measure function, and combining the single-index uncertain measure vectors of each index to form a single-index uncertain measure evaluation matrix;
according to the information entropy theory, calculating the weight vector of each index, and respectively calculating the multi-index uncertain measure evaluation vectors of 4 influence factors for evaluating the fault activation water inrush risk according to the single-index uncertain measure evaluation matrix and the weight vector; according to the information entropy theory, evaluating index weights corresponding to the 4 influence factors are solved, and finally a multi-index comprehensive measure vector is obtained;
and obtaining an evaluation result according to the confidence coefficient judgment criterion.
Example 2:
a fault activation water inrush risk evaluation method based on an unknown entropy weight method is disclosed, as described in example 1, except that main factors influencing fault activation water inrush in the step A comprise engineering hydrogeology, fault properties, mining conditions and bottom plate water blocking;
the evaluation index system sequentially comprises three layers as shown in figure 2, namely a highest layer, a middle layer and a lowest layer, wherein the highest layer is fault activation water inrush A, the middle layer is the main factor and comprises engineering hydrogeology B1Fault property B2And mining conditions B3And bottom water-blocking B4The lowest layer is 8 factors, namely the buried depth C1Hydrogeological conditions C2Fault dip angle C3Fault drop C4Size of working face C5And the width C of the waterproof coal pillar6Pressure-bearing water pressure C7And a water barrier thickness C8Each of the main factors of the middle layer is affected by the bottom 8 factors, namely: engineering hydrogeology B1Buried depth C1Hydrogeological conditions C2Influence of, fault property B2Dip angle C of faulted layer3Fault drop C4Influence of, mining Condition B3Dimension C of receiving working surface5And the width C of the waterproof coal pillar6Influence of (B) water blocking of the sole4Bearing pressure of water C7And a water barrier thickness C8The influence of (c).
Establishing a factor set T ═ T in the step B1、T2、T3、T4And (5) engineering hydrogeology, fault property, mining condition and bottom plate water resistance }.
The ranking criteria in step C are divided into four ranks, i.e., S ═ S1，S2，S3，S4Safety, general safetyGeneral danger, danger };
the classification criteria table is shown in table 1:
table 1: grading standard table
Figure BDA0002966750610000101
Figure BDA0002966750610000111
Some of which cannot be directly evaluated, and table 1 gives qualitative indications, such as hydrogeological conditions C2And the width C of the waterproof coal pillar6，C2For hydrogeological conditions, no specific numerical value is substituted into a formula for calculation, and single index risk level judgment is required according to actual conditions of a mine; c6For the width of the waterproof coal pillar, the width of the waterproof coal pillar actually required by the mine working face is taken as a standard to judge the single index danger level, and in table 1, the hydrogeological condition C2And the width C of the waterproof coal pillar6Directly taking values according to the table 1, and other evaluation indexes: buried depth C1Hydrogeological conditions C2Fault dip angle C3Fault drop C4Size of working face C5Pressure-bearing water pressure C7And a water barrier thickness C8Are all determined by calculation.
Table 2 shows actual values of quantitative indicators in evaluation of the risk of activated water inrush of a certain fault in a certain mine according to the present example, and the description will be given by taking these values as examples.
Table 2: actual value of quantitative index in activated water inrush risk evaluation of certain fault of certain mine
Evaluation index Ci Actual condition of a fault
C1 Buried depth greater than 800m
C2 General hydrogeological conditions and weak aquifer water-rich property
C3 Dip angle of fault of 30 °
C4 Fault drop of 35m
C5 The inclined length of the working face is 93.3m
C6 The width of the waterproof coal pillar is equal to the width of the critical coal pillar
C7 Pressure of pressure-bearing water is 5.2MPa
C8 The thickness of the water-resisting layer of the bottom plate is 49-58 m
According to the conditions in Table 2, in combination with Table 1, C is obtained2With a single index risk rating of S2，C6With a single index risk rating of S3Of note, C1～C8(removal of C)2、C6) Participating in the calculation as x in a function of the single index undetermined measure in step D, C8Taking the intermediate value of 53.5m, directly obtaining a single index measure vector according to the single index risk degree grade,C2with a single index risk rating of S2Its undetermined measure evaluation matrix is (0100), C6With a single index risk rating of S3And its undetermined measure evaluation matrix is (0010).
The step D is specifically as follows:
(1) the theory is not known to be certain:
let a certain evaluation object space be: x ═ X1,X2,X3,…,Xn}, wherein each evaluation object Xi(i-1, 2, … n) has m evaluation indices, namely C1,C2,C3,…,CmThen the index space can be expressed as C ═ C1,C2,C3,…,Cm}. If xijRepresents the ith evaluation object XiRegarding the jth evaluation index CjIs measured, then Xi＝{xi1,xi2,xi3,…,xim}. Let to xijIf there are p evaluation levels and the evaluation space is denoted as U, then the evaluation space vector U ═ S1,S2,S3,…,SpIn which S isk(k-1, 2, …, p) represents the k-th rating, and k is safer than k +1, denoted as Sk＞Sk+1Term U ═ S1,S2,S3,…,SpIs an ordered partition class of the evaluation level space U.
Let the measured value xijBelonging to the kth evaluation level SkDegree of (1) is expressed asijk＝μ(xij∈Sk) Indicating that if μ satisfies:
0≤μijk(xij∈Sk)≤1(i＝1,2,…n；j＝1,2,…,m；k＝1,2,…p) (1)
μ(xij∈U)＝1(i＝1,2,…n；j＝1,2,…m) (2)
Figure BDA0002966750610000131
the formula (1) calls that mu pair of evaluation space U satisfies non-negativity, the formula (2) calls that mu pair of evaluation space U satisfies normalization, and the formula (3) calls that mu pair of evaluation space U satisfies additivity. If the three formulas (1), (2) and (3) are satisfied simultaneously, mu can be called an undetermined measure.
Scale matrix (mu)ijk)m×pAnd evaluating the matrix for the single-index uncertain measure.
Figure BDA0002966750610000132
The construction of the single-index uncertain measure evaluation matrix is premised on determining a single-index uncertain measure function and comprehensively considering the use of a linear type uncertain measure function.
In this embodiment, the fault activation water inrush risk evaluation index is divided into four levels, and an evaluation space is formed according to an unknown theory:
U＝{S1,S2,S3,S4} (5)
in field engineering practice Sk>Sk+1I.e. higher security.
Constructing an uncertain measure function of the evaluation index according to a grading standard, obtaining an index characteristic value by using an interval number, and S1Taking a lower limit value of the interval according to the classification standard; s4The classification criterion of (1) is taken as an interval upper limit value, S2,S3The classification criterion of (2) is median of the number of intervals. A classification criteria matrix is thus obtained:
S1 S2 S3 S4
Figure BDA0002966750610000141
suppose evaluation index xijOf unknown measurement value muijk＝μ(xij∈Sk) And a isj1>aj2>…>ajpThen:
(1) when x isij≥aj1When, muij1＝1，μij2＝…＝μijp＝0
(2)When x isij≤ajpWhen, muijp＝1，μij1＝…＝μijp-1＝0
(3) When a isjl＜xij＜ajl+1Then, a linear equation is constructed according to the uncertain measure theory:
Figure BDA0002966750610000142
according to the three conditions, an uncertain measure function of each evaluation index can be obtained:
buried depth C1Function of undetermined measures of (1):
Figure BDA0002966750610000143
Figure BDA0002966750610000144
Figure BDA0002966750610000145
Figure BDA0002966750610000151
fault dip angle C3Function of undetermined measures of (1):
Figure BDA0002966750610000152
Figure BDA0002966750610000153
Figure BDA0002966750610000154
Figure BDA0002966750610000155
fault fall C4Function of undetermined measures of (1):
Figure BDA0002966750610000161
Figure BDA0002966750610000162
Figure BDA0002966750610000163
Figure BDA0002966750610000164
working face size C5Function of undetermined measures of (1):
Figure BDA0002966750610000165
Figure BDA0002966750610000171
Figure BDA0002966750610000172
Figure BDA0002966750610000173
pressure-bearing water pressure C7Function of undetermined measures of (1):
Figure BDA0002966750610000174
Figure BDA0002966750610000175
Figure BDA0002966750610000181
Figure BDA0002966750610000182
thickness C of water barrier layer8Function of undetermined measures of (1):
Figure BDA0002966750610000183
Figure BDA0002966750610000184
Figure BDA0002966750610000185
Figure BDA0002966750610000191
in the formulas (8) to (31), x represents a specific numerical value of each evaluation index, and μ represents a measurement value of each evaluation level to which the evaluation index belongs;
substituting specific numerical value x of quantitative evaluation index into the above formulas (8) - (31), obtaining measurement values of each grade by uncertain measurement function of the evaluation index, combining measurement vectors of the evaluation index into a previous grade (according to the condition that the middle layer of the evaluation index system is affected by the bottommost layer), namely, evaluatingA single index undetermined measure evaluation matrix of the factors, wherein the qualitative index C2With a single index risk rating of S2Its undetermined measure vector is (0100), C6With a single index risk rating of S3Its undetermined measure vector is (0010).
As can be seen from FIG. 2, the engineering hydrogeology B1Buried depth C1And hydrogeological conditions C2In this embodiment, it is determined that the buried depth C is shown in Table 21If the x is larger than 800m, namely x is larger than 800, the x is substituted into the formulas (8) to (11) to obtain four numerical values which are respectively 0, 0 and 1;
hydrogeological conditions C2The direct values in Table 1 are given in the scale S2Therefore hydrogeological conditions C2Are 0, 1, 0, respectively;
thereby obtaining the engineering hydrogeology B1Undetermined measure evaluation matrix mu1：
Figure BDA0002966750610000192
Fault property B2Dip angle C of faulted layer3And fault throw C4In this example, it is determined that the fault dip C is shown in Table 23The fault dip angle of (3), that is, x is 30, and the four values are obtained by substituting equations (12) to (15), and are 0, and 1, respectively;
as can be seen from Table 2, the fault throw C435m, that is, x is 35, and is substituted into equations (16) to (19) to obtain four numerical values, 0, 0.71, 0.29, and 0, respectively;
thereby obtaining a fault property factor B2Undetermined measure evaluation matrix mu2：
Figure BDA0002966750610000193
In the same way, the following results are obtained:
mining condition factor B3Undetermined measure evaluation matrix mu3：
Figure BDA0002966750610000194
Factor B of water resistance of bottom plate4Undetermined measure evaluation matrix mu4：
Figure BDA0002966750610000195
(2) Determination of the weights:
solving the weight by adopting an information entropy theory:
let P be the number of evaluation levels, νijSize of (A) reflects index CjThe degree of importance of;
wijindicates the evaluation index CjAnd satisfies the relative degree of importance of 0. ltoreq. wij≤1，
Figure BDA0002966750610000201
Then wi＝{wi1,wi2,…,wim}；
Figure BDA0002966750610000202
If suppose CjIndicates the degree of importance with respect to other indexes as
Figure BDA0002966750610000203
Then wijIs namely Cj(j ═ 1,2, …, m) weight:
Figure BDA0002966750610000204
Cjas an evaluation index Cj，νijSize of (A) reflects index CjThe degree of importance of.
According to the evaluation matrix of the single-index uncertain measure of the embodiment, the weight of each index is calculated:
substituting the single-index uncertain measure evaluation matrices obtained by the formulas (8) to (31) into the formula (32) and the formula (33) for calculation to obtain weight matrices of the C level (namely, the evaluation index) to the B level (namely, the evaluation factor), wherein the weight matrices are respectively as follows:
with B1Taking the evaluation index weight vector of (1) as an example, wherein P is the number of evaluation levels, and the value is 4 levels;
B1is evaluated by the uncertainty measure evaluation matrix mu1Is composed of
Figure BDA0002966750610000205
From the formula (32), it can be found
Figure BDA0002966750610000206
Wherein mu111The degree of membership of the first evaluation index representing the first evaluation factor to the first grade is 0; mu.s112A degree of membership, here 0, of a first evaluation index representing a first evaluation factor to a second level; mu.s113A degree of membership of a first evaluation index representing the first evaluation factor to the third level, here 0; mu.s114The degree of membership of the first evaluation index representing the first evaluation factor to the fourth level is 1 here.
Figure BDA0002966750610000211
Wherein mu121A degree of membership, here 0, of a second evaluation index representing the first evaluation factor to the first grade; mu.s122A degree of membership of a second evaluation index representing the first evaluation factor to a second level, here 1; mu.s123A degree of membership of a second evaluation index representing the first evaluation factor to a third level, here 0; mu.s124The degree of membership of the second evaluation index representing the first evaluation factor to the fourth level is 0 here.
The following equation (33) can be obtained:
w11＝v11/(v11+v12)＝0.5000
w12＝v12/(v11+v12)＝0.5000
w1＝(w11，w12)＝(0.5000，0.5000)。
with B2Taking the evaluation index weight vector of (1) as an example, wherein P is the number of evaluation levels, and the value is 4 levels;
B2is evaluated by the uncertainty measure evaluation matrix mu2Is composed of
Figure BDA0002966750610000212
From the formula (32), it can be found
Figure BDA0002966750610000213
Wherein mu211A degree of membership, here 0, of a first evaluation index representing a second evaluation factor to the first ranking; mu.s212The degree of membership, here 0, of the first evaluation index to the second level representing the second evaluation factor; mu.s213A degree of membership of the first evaluation index representing the second evaluation factor to the third level, here 0; mu.s214A degree of membership of the first evaluation index representing the second evaluation factor to the fourth level, here 1;
Figure BDA0002966750610000214
wherein, mu221A degree of membership of a second evaluation index representing a second evaluation factor to the first grade, which is 0; mu.s222A degree of membership of a second evaluation index representing a second evaluation factor to a second rank, here 0.71; mu.s223A degree of membership of a second evaluation index representing a second evaluation factor to a third grade, here 0.29; mu.s224The degree of membership of the second evaluation index representing the second evaluation factor to the fourth grade, here, is 0.
The following equation (33) can be obtained:
w21＝v21/(v21+v22)＝0.6387
w22＝v22/(v21+v22)＝0.3613
to obtain w2＝(w21，w22)＝(0.6387，0.3613)。
Similarly, the weight vector of other factors is:
w3＝(w31，w32)＝(0.4016，0.5984)
w4＝(w41，w42)＝(0.6524，0.3476)
(3) multi-index uncertain measure evaluation vector
Engineering hydrogeology B activating water inrush from fault1Is evaluated by the uncertainty measure evaluation matrix mu1Fault property factor B2Is evaluated by the uncertainty measure evaluation matrix mu2Production condition factor B3Is evaluated by the uncertainty measure evaluation matrix mu3Water-blocking factor B of bottom plate4Is evaluated by the uncertainty measure evaluation matrix mu4And each evaluation index weight vector to obtain a multi-index uncertain measure evaluation vector of each factor, wherein the calculation process is as follows:
B1the multi-index uncertain measure evaluation vector is as follows: mu.sB1＝ω1×μ1＝(0 0.5000 0 0.5000)
B2The multi-index uncertain measure evaluation vector is as follows: mu.sB2＝ω2×μ2＝(0 0.2565 0.1048 0.6387)
B3The multi-index uncertain measure evaluation vector is as follows: mu.sB3＝ω3×μ3＝(0 0.0683 0.9317 0)
B4The multi-index uncertain measure evaluation vector is as follows: mu.sB4＝ω4×μ4＝(0.2259 0.1217 0 0.6524)
Therefore, a multi-index uncertain measure evaluation matrix A of comprehensive evaluation can be determined by four influence factor index vectors of fault activated water inrush:
Figure BDA0002966750610000221
the corresponding evaluation index weight is obtained according to the formulas (32) and (33) as follows:
from the formula (32), it can be found
Figure BDA0002966750610000222
Figure BDA0002966750610000231
Figure BDA0002966750610000232
Figure BDA0002966750610000233
The following equation (33) can be obtained:
Figure BDA0002966750610000235
Figure BDA0002966750610000236
Figure BDA0002966750610000237
Figure BDA0002966750610000238
evaluation index weight w corresponding to AAComprises the following steps: (0.2425,0.1796,0.3976,0.1803)
Comprehensively calculating a multi-index comprehensive measurement vector as follows:
μA＝ωA×A＝(0.0407 0.2164 0.3893 0.3536)
(4) confidence judgment criterion
In order to obtain the final evaluation result of an evaluation object, a 'confidence degree' evaluation is introducedThe criterion is to set λ as the confidence (λ ≧ 0.5, usually λ ═ 0.6 or 0.7), if C1＞C2＞…＞CpAnd order
Figure BDA0002966750610000234
Confidence lambda is more than or equal to 0.5 (34)
μiRepresenting the measure of each evaluation grade of the evaluation object, namely membership; k represents an evaluation grade;
judging that the fault activation water inrush danger level is kth according to the formula (34)0Grade, in this example:
μA＝ωA×A＝(0.0407 0.2164 0.3893 0.3536)
k0min {0.0407+0.2164+0.3893 ═ 0.6464 > 0.6} -. 3, in this formula, it is also the meaning of formula (34), add and sum backward from the measured value of the evaluation object to the first grade, until the value is greater than 0.6 and stop, the number added last is the measured value belonging to the third grade, so k takes the value of 3;
therefore, the water inrush risk level of the activation of a certain fault of the mine is judged to be S in the embodiment3。
While the foregoing is directed to the preferred embodiment of the present invention, it will be understood by those skilled in the art that various changes and modifications may be made without departing from the spirit and scope of the invention as defined in the appended claims.

Claims (5)

1. A fault activation water inrush risk evaluation method based on an unknown-entropy weight method is characterized by comprising the following steps:
step A, inducing main factors influencing fault activation water inrush, and establishing an evaluation index system with a hierarchical structure;
b, establishing a factor set according to the evaluation index system established in the step A;
step C, establishing a grading standard table of each index under an evaluation grade set and a factor set according to field practice and engineering experience;
d, according to an uncertain theory, determining single-index uncertain measure vectors of each influence factor through an uncertain measure function, and combining the single-index uncertain measure vectors of each index to form a single-index uncertain measure evaluation matrix;
according to the information entropy theory, calculating the weight vector of each index, and respectively calculating the multi-index uncertain measure evaluation vectors of 4 influence factors for evaluating the fault activation water inrush risk according to the single-index uncertain measure evaluation matrix and the weight vector; according to the information entropy theory, evaluating index weights corresponding to the 4 influence factors are solved, and finally a multi-index comprehensive measure vector is obtained;
and obtaining an evaluation result according to the confidence coefficient judgment criterion.
2. The method for evaluating the risk of fault activation water inrush based on the unknown-entropy weight method according to claim 1, wherein the main factors influencing fault activation water inrush in the step A comprise engineering hydrogeology, fault properties, mining conditions and floor water blocking;
the evaluation index system sequentially comprises three layers, namely a highest layer, a middle layer and a lowest layer, wherein the highest layer is fault activation water inrush A, the middle layer is the main factor and comprises engineering hydrogeology B1Fault property B2And mining conditions B3And bottom water-blocking B4The lowest layer is 8 factors, namely the buried depth C1Hydrogeological conditions C2Fault dip angle C3Fault drop C4Size of working face C5And the width C of the waterproof coal pillar6Pressure-bearing water pressure C7And a water barrier thickness C8Each of the main factors of the middle layer is affected by the bottom 8 factors, namely: engineering hydrogeology B1Buried depth C1Hydrogeological conditions C2Influence of, fault property B2Dip angle C of faulted layer3Fault drop C4Influence of, mining Condition B3Dimension C of receiving working surface5And the width C of the waterproof coal pillar6Influence of (B) water blocking of the sole4Bearing pressure of water C7And a water barrier thickness C8The influence of (c).
3. The fault activation water inrush risk assessment method based on the unknown-entropy weight method according to claim 2, wherein a factor set T ═ { T ═ T is established in step B1、T2、T3、T4And (5) engineering hydrogeology, fault property, mining condition and bottom plate water resistance }.
4. The method for evaluating the risk of fault activation water inrush according to claim 3, wherein the classification criterion in step C is classified into four classes, i.e., S ═ S { (S) } S1，S2，S3，S4The classification standard table is shown in table 1:
table 1: grading standard table
Figure FDA0002966750600000021
Figure FDA0002966750600000031
In Table 1, hydrogeological conditions C2And the width C of the waterproof coal pillar6Directly taking values according to the table 1, and other evaluation indexes: buried depth C1Hydrogeological conditions C2Fault dip angle C3Fault drop C4Size of working face C5Pressure-bearing water pressure C7And a water barrier thickness C8Are all determined by calculation.
5. The fault activation water inrush risk evaluation method based on the unknown-entropy weight method according to claim 4, wherein an unknown measure function of each evaluation index under an unknown theory is as follows:
buried depth C1Function of undetermined measures of (1):
Figure FDA0002966750600000032
Figure FDA0002966750600000041
Figure FDA0002966750600000042
Figure FDA0002966750600000043
fault dip angle C3Function of undetermined measures of (1):
Figure FDA0002966750600000044
Figure FDA0002966750600000045
Figure FDA0002966750600000051
Figure FDA0002966750600000052
fault fall C4Function of undetermined measures of (1):
Figure FDA0002966750600000053
Figure FDA0002966750600000054
Figure FDA0002966750600000055
Figure FDA0002966750600000061
working face size C5Function of undetermined measures of (1):
Figure FDA0002966750600000062
Figure FDA0002966750600000063
Figure FDA0002966750600000064
Figure FDA0002966750600000065
pressure-bearing water pressure C7Function of undetermined measures of (1):
Figure FDA0002966750600000071
Figure FDA0002966750600000072
Figure FDA0002966750600000073
Figure FDA0002966750600000074
thickness C of water barrier layer8Function of undetermined measures of (1):
Figure FDA0002966750600000075
Figure FDA0002966750600000081
Figure FDA0002966750600000082
Figure FDA0002966750600000083
in the formulas (8) to (31), x represents a specific numerical value of each evaluation index, and μ represents a measurement value of each evaluation level to which the evaluation index belongs;
and obtaining a single-index undetermined measurement evaluation matrix according to the condition that the middle layer of the evaluation index system is influenced by the bottommost layer.
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