CN113222347B - Method for evaluating gray system of safety risk of open-air blasting - Google Patents
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Abstract
The invention discloses an assessment method of a surface blasting security risk gray system, which comprises the steps of establishing a risk level index structure model; obtaining judgment matrixes of each layer by using expert scoring and analytic hierarchy process, and calculating element influence weight vectors of each layer; dividing the influence degree of the risk index into a plurality of gray levels, establishing a fuzzy membership function of the possibility degree of each index item, and calculating a gray scale judgment weight matrix of the risk layer by combining expert scoring; and carrying out synthesis operation on the gray scale judgment weight matrix and the influence weight vector layer by layer to finally obtain a fuzzy comprehensive risk evaluation value of each element of the target layer, and comprehensively analyzing the overall risk evaluation level of the surface blasting. According to the assessment method for the surface blasting safety risk gray system, provided by the invention, the comprehensive risk assessment value of the rock blasting excavation construction on the peripheral protection target object is calculated and analyzed by adopting a hierarchical analysis method and a gray fuzzy evaluation method and combining expert scoring through qualitative and quantitative analysis, and the assessment method is scientific, objective and effective.
Description
Technical Field
The invention relates to safety evaluation, in particular to a method for evaluating a gray system of safety risk of surface blasting.
Background
The engineering blasting technology has the unique advantages of rapidness, high efficiency and economy, plays an important role in traffic infrastructure, and is an important technical means for large-scale stone excavation engineering operation. However, because a large amount of explosive is required for blasting, secondary hazard effects such as blasting flying stones, blasting noise, flying dust and blasting seismic waves are accompanied in the construction process. If the control is not carried out, the blasting flyrock and the blasting earthquake vibration can form the impact of crashing, vibration damage and the like on the buildings in the nearby area of blasting construction or even damage, and the blasting earthquake waves with a longer propagation range have potential impact on the operation function safety of electric and pipeline sensitive facilities in the nearby area.
In recent years, along with the increase of blasting construction activities in complex and sensitive areas, in order to avoid blasting safety accidents and reduce unnecessary contradictions and disputes caused by blasting construction, a safe and reliable risk assessment system must be established, and under the condition that the blasting construction is ensured to meet the construction requirements and the danger is reduced to the lowest point, the reliability of the blasting construction is comprehensively demonstrated, and a reference basis is provided for engineering project decision.
However, on the premise that the known information is insufficient, how to achieve sufficient science and objectivity in risk assessment is a difficulty in achieving accurate assessment.
Disclosure of Invention
The invention aims to: in order to solve the problem that the known information is insufficient and the explosion risk assessment cannot be accurately carried out in the prior art, the invention provides a method for assessing the safety risk gray system of the surface blasting.
The technical scheme is as follows: a method for evaluating a gray system of safety risk of surface blasting comprises the following steps:
(1) Establishing a risk level index structure model, and determining each layer element of the risk level index structure model, wherein the risk level index structure model comprises a target layer, a risk layer and an index layer;
(2) Performing pairwise comparison on elements of the risk layer and the index layer by using expert scoring and analytic hierarchy process to obtain a target layer judgment matrix and a risk layer judgment matrix; calculating a target influence weight vector and a risk influence weight vector according to the target layer judgment matrix and the risk layer judgment matrix respectively;
(3) Providing a safety control standard of each factor of an index layer, comparing the field technical index with the difference degree of the safety control standard to obtain the influence degree of the risk index, dividing the influence degree of the risk index into a plurality of gray levels, establishing a fuzzy membership function of the possibility degree of each index item aiming at each gray level, and calculating a gray scale judgment weight matrix of the risk layer by combining expert scoring;
(4) Combining the gray scale judgment weight matrix of the risk layer with the risk influence weight vector to obtain a gray scale judgment weight vector of the target layer, and forming the gray scale judgment weight matrix of the target layer; combining the gray scale judgment weight matrix of the target layer with the target influence weight vector to obtain a comprehensive risk evaluation value vector of each element of the target layer;
(5) Calculating weight vectors of comprehensive risk evaluation values of all elements of the target layer according to the central values of the gray class level intervals, performing synthesis operation on the comprehensive risk evaluation value vectors of all elements of the target layer and the comprehensive risk evaluation value vectors to obtain fuzzy comprehensive risk evaluation values of all elements of the target layer, and comprehensively analyzing the total risk evaluation level of the surface blasting.
Further, the risk level index structure model in the step (1) sequentially comprises a target layer, a risk layer and an index layer from the highest layer to the lowest layer, the target layer is a risk evaluation item of each protection target, the target layer comprises a highway, a building and a high-voltage line, the risk layer is a risk category of each explosion, the risk layer comprises explosion vibration, explosion noise, explosion flying stones and explosion flying dust, the index layer is an index factor influencing explosion risk, and the index layer comprises total dosage, single-section maximum dosage, a free surface, a minimum resistance line, geological conditions, distances and meteorological conditions.
Further, the step (2) specifically includes:
(21) Expert scoring is carried out on each element of the risk layer under each protection target risk assessment item in the risk level index structure model according to the influence degree on the upper layer, and expert scoring is carried out on each element of the index layer under each blasting risk category in the risk level index structure model;
(22) Performing pairwise comparison on the influence degree of each element of the same layer on a certain element in the previous layer by adopting an analytic hierarchy process to respectively obtain a pairwise comparison target layer judgment matrix and a risk layer judgment matrix;
(23) Respectively calculating a target influence weight vector and a risk influence weight vector according to the target layer judgment matrix and the risk layer judgment matrix;
(24) And (5) carrying out consistency test, and adjusting expert scoring until consistency passes.
Further, in step (23), the weight vector is a sum method, which includes:
(a1) Normalizing the elements of the judgment matrix according to the rows;
(a2) Adding the normalized rows;
(a3) And dividing the added vector by the number of row vectors of the judgment matrix to obtain a weight vector.
Further, in step (23), the weight vector adopts a feature root method, including:
let the judgment matrix be A, and solve the characteristic root of the judgment matrix to obtain:
AW＝λ max W
wherein lambda is max And W is the corresponding feature vector, and the normalized W is used as a weight vector.
Further, the step (24) consistency check includes:
(b1) Calculating a consistency index CI:
where n is the number of row vectors of the judgment matrix,
(b2) Searching a corresponding average random consistency index RI;
(b3) Calculating a consistency ratio CR:
if CR < 0.1, the consistency is acceptable; CR is more than or equal to 0.1, and the expert scoring is required to be adjusted;
(b4) And (3) carrying out consistency check in the steps (b 1) - (b 3) layer by layer according to the weight vector of each group of elements to a certain element in the upper layer.
Further, in the step (3), a fuzzy membership function is set as f i h (x ij )，
1) With very low risk (x ij ∈[0，20％]，h＝1)
2) Low risk (x) ij ∈(20％，40％]，h＝2)
3) Risk general (x ij ∈(40％，60％]，h＝3)
4) High risk (x) ij ∈(60％，80％]，h＝4)
5) Is very dangerous (x ij ∈(80％，100％]，h＝5)
Wherein h is ash class, x ij For the risk influence degree of each index, f i h (x ij ) The likelihood of the degree of risk impact is expressed.
The beneficial effects are that: compared with the prior art, the evaluation method for the surface blasting safety risk gray system provided by the invention adopts a hierarchical analysis method and a gray fuzzy evaluation method, combines expert scoring, and calculates and analyzes the comprehensive risk evaluation value of rock blasting excavation construction on the peripheral protection target object through qualitative and quantitative analysis, and the evaluation method is scientific, objective and effective.
Drawings
Fig. 1 is a structural diagram of a risk level index structural model.
Detailed Description
The invention will be further described with reference to the drawings and examples.
Taking a certain area as an example, carrying out surface blasting safety risk assessment, wherein the surface blasting safety risk gray system assessment method comprises the following steps:
(1) Establishing a risk level index structure model, determining each layer element of the risk level index structure model, wherein the risk level index structure model sequentially comprises a target layer, a risk layer and an index layer from the highest layer to the lowest layer, and the elements of the same layer are used as criteria to play a dominant role on certain elements of the next layer, and are subjected to the dominant role of the sub-elements of the upper layer. The target layer is a risk assessment item of each protection target, and according to the characteristics of the local area, the layer is determined to comprise a highway, a building and a high-voltage line, and fig. 1 illustrates a risk layer and an index layer structure under a class of targets. The risk layer is of various blasting risk categories including blasting vibration, blasting noise, blasting flying stone and blasting flying dust. The index layer is an index factor for influencing the blasting risk and comprises total dosage, single-section maximum dosage, single-hole dosage, hole depth, a blast hole filling mode, blast hole filling quality, a minimum resistance line, a distance, a free face, a relative azimuth relation, an elevation factor, a rock mass internal hole condition, geological conditions, meteorological conditions, protective measures and the like.
(2) And performing expert scoring on each element of the index layer under each blasting risk category in the risk level index structure model according to the influence degree on the upper layer, and performing expert scoring on each element of the risk layer under each protection target risk assessment item in the risk level index structure model. And then carrying out pairwise comparison on the influence degree of each element of the same layer on a certain element in the previous layer by adopting an analytic hierarchy process to respectively obtain a risk layer judgment matrix (comprising a blasting vibration risk judgment matrix, a blasting flying stone risk judgment matrix, a blasting noise risk judgment matrix and a blasting flying dust risk judgment matrix) and a target layer judgment matrix (comprising a building risk judgment matrix, a highway risk judgment matrix and a high-voltage line risk judgment matrix) which are compared in pairs:
the expert scoring table is as follows:
TABLE 1 hierarchical analysis expert scoring table for index layers
TABLE 2 hierarchical analysis expert scoring table for risk layers
1) Explosion vibration risk judgment matrix
2) Explosion flying stone risk judgment matrix
3) Explosion noise risk judgment matrix
4) Explosion flying dust risk judgment matrix
5) Building risk judgment matrix
6) Highway risk judgment matrix
7) High-voltage line risk judgment matrix
Calculating a risk influence weight vector and a target influence weight vector by the risk layer judgment matrix and the target layer judgment matrix respectively, wherein the calculation of the weight vector can adopt a sum method, and specifically comprises the following steps:
(a1) Normalizing the elements of the judgment matrix according to the rows;
(a2) Adding the normalized rows;
(a3) And dividing the added vector by the number of row vectors of the judgment matrix to obtain a weight vector.
The weight vector may also adopt a feature root method, which specifically includes:
let the judgment matrix be A, and solve the characteristic root of the judgment matrix to obtain:
AW＝λ max W
wherein lambda is max And W is the corresponding feature vector, and the normalized W is used as a weight vector.
Calculated, the risk influence weight vector W i ：
Blasting vibration (U) 1 )W 1 ＝(0.2424 0.2121 0.0909 0.1818 0.1212 0.1515)
Blasting flyrock (U) 2 )W 2 ＝(0.1064 0.1702 0.1489 0.1915 0.1170 0.13830.1277)
Blasting noise (U) 3 )W 3 ＝(0.2154 0.2462 0.1538 0.1846 0.2000)
Blasting fly ash (U) 4 )W 4 ＝(0.2000 0.2286 0.1714 0.2143 0.1857)
Target impact weight vector:
building wc= (0.3889 0.3333 0.1667 0.1111)
Expressway wr= (0.2381 0.3810 0.0952 0.2857)
High-voltage line we= (0.2381 0.3333 0.1429 0.2857)
A consistency check must also be performed when calculating the weight vector under a single criterion. The consistency of the judgment matrix is checked, and the specific steps are as follows:
(b1) Calculating a consistency index CI:
wherein n is the number of row vectors of the judgment matrix;
(b2) The corresponding average random consistency index RI is searched, and the average random consistency index obtained by 1000 times of 1-15-order forward and inverse matrix calculation is given in the following table.
TABLE 3 average random uniformity index RI
| Matrix order | 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 |
| RI | 0 | 0 | 0.52 | 0.89 | 1.12 | 1.26 | 1.36 | 1.41 |
| Matrix order | 9 | 10 | 11 | 12 | 13 | 14 | 15 | |
| RI | 1.46 | 1.49 | 1.52 | 1.54 | 1.56 | 1.58 | 1.59 |
(b3) Calculating a consistency ratio CR:
if CR < 0.1, the consistency is acceptable; CR is more than or equal to 0.1, and the expert scoring is required to be adjusted, so that the judgment matrix is properly corrected;
(b4) And (3) carrying out consistency check in the steps (b 1) - (b 3) layer by layer according to the weight vector of each group of elements to a certain element in the upper layer. Through inspection, the consistency of the risk layer judgment matrix and the target layer judgment matrix meets the requirements.
(3) And (3) carrying out gray level fuzzy judgment analysis on the area, and evaluating the possibility degree of the blasting construction risk so as to determine the feasibility of the blasting construction. The gray scale fuzzy comprehensive evaluation method converts qualitative evaluation into quantitative evaluation according to membership theory of fuzzy mathematics, namely, an overall evaluation is carried out on objects affected by various factors. The risk assessment method has the characteristics of clear results and strong systematicness, can better solve the problems of blurring and difficult quantification, and can further improve the reliability of risk assessment.
Providing a safety control standard of each factor of the index layer, comparing the difference degree of the field technical index and the safety control standard to obtain the influence degree of the risk index, wherein in certain blasting, the influence of the blasting vibration of the protection target is 'low risk' or 'no risk' when the blasting vibration safety distance of the protection target is out of 200 meters by calculating, and the risk is very high when the blasting vibration safety distance is within 50 meters. The risk index influence degree is divided into 5 gray levels according to the method: the risk is very low, the risk is generally high, and the risk is high.
And establishing a fuzzy membership function of the possibility of each index item according to each gray class level and combining expert scoring, and calculating a gray scale judgment weight matrix of the risk layer. The selection and determination of the fuzzy membership function is one of the key links of gray level clustering, and the accuracy of the evaluation result is directly affected. The gray fuzzy evaluation and the fuzzy comprehensive evaluation have a plurality of common characteristics, the evaluation results are all sets, the gray fuzzy evaluation and the fuzzy comprehensive evaluation can be applied to multi-level evaluation, the evaluation values of the gray fuzzy evaluation and the fuzzy comprehensive evaluation can be divided into intervals, a fuzzy membership function is set, and the evaluation membership interval is determined.
Defining a fuzzy membership function as A (x), wherein A (x) = [0,1], x is an element in U, U is a value range of an index item, and for any element x in U, a fuzzy membership A (x) corresponds to the element x, namely A is a fuzzy set on U, A (x) is membership degree of x to A, and represents the degree that x belongs to A.
Set up risk index set U i Risk impact index U in i=1, 2,3,4 ij Risk influence probability expert scoring value x ij Let f (x) ij ) As fuzzy membership function, each risk item index set U i The fuzzy membership function (or gray function) of the risk index probability judgment of i=1, 2,3,4 is f i h (x ij )，(h＝1，2，…5)：
1) With very low risk (x ij ∈[0，20％]，h＝1)
2) Low risk (x) ij ∈(20％，40％]，h＝2)
3) Risk general (x ij ∈(40％，60％]，h＝3)
4) High risk (x) ij ∈(60％，80％]，h＝4)
4) Is very dangerous (x ij ∈(80％，100％]，h＝5)
TABLE 4 risk indicator impact expert scoring Table
Table 5 Gray scale judgment matrix of risk layer
(4) Combining the gray scale judgment weight matrix Ri of the risk layer with the risk influence weight vector Wi to obtain a gray scale judgment weight vector Bi of the target layer,
Bi＝Wi×Ri
B 11 ＝W 1 ×R 11 ＝(0 0.4197 0.3850 0.1952 0)
B 12 ＝W 2 ×R 12 ＝(0 0.4811 0.3638 0.1551 0)
B 13 ＝W 3 ×R 13 ＝(0 0.6671 0.3329 0 0)
B 14 ＝W 4 ×R 14 ＝(0 0.4979 0.4031 0.0989 0)
will B 11 、B 12 、B 13 、B 14 Gray scale judgment right matrix B forming target layer 1 ：
B 1 ＝[0 0.4197 0.3850 0.1952 0；
0 0.4811 0.3638 0.1551 0；
0 0.6671 0.3329 0 0：
0 0.4979 0.4031 0.0989 0]
Similarly, the gray scale judgment right matrix B of the target layer 1 Carrying out synthesis operation with the target influence weight vector W (Wc, wr, we) to obtain a comprehensive risk evaluation value vector Z of each element of the target layer;
Z＝W×B 1 T ，i＝1，2，3
taking a building as an example, the integrated risk assessment value vector zc=w for the building c ×B 1 T ＝(0 0.4901 0.3713 0.1386 0)。
(5) And according to the principle of 5 grades corresponding to the risk index expert judgment scores, assigning a risk interval value according to the risk gray scale (namely the risk ambiguity) level. The risk gray level adopts a maximum likelihood principle, namely, the evaluation assignment of each risk level adopts a central value of the allowable range of the risk fuzzy interval index. A total of 5 ash risk intervals ([ 0, 20% ] (20%, 40% ] (40%, 60% ] (60%, 80% ] (80%, 100% ]), and assignment of the central value of each risk interval is calculated as follows:
calculating a weight vector of the comprehensive risk evaluation value of each element of the target layer:
G＝(10 30 50 70 90)
synthesizing the comprehensive Risk evaluation value vector Z of each element of the target layer with the weight vector G of the comprehensive Risk evaluation value to obtain a fuzzy comprehensive Risk evaluation value Risk of each element of the target layer:
Risk＝Z×G T
taking a building as an example, calculating to obtain Risk c ＝42.97，
In contrast to the following table, the fuzzy comprehensive risk evaluation value E (40%, 60%) is the risk general
TABLE 6 Risk level Interval setting Table
And (5) evaluating fuzzy comprehensive risk evaluation values of the high-voltage lines and the expressways by using the same method, and comprehensively analyzing the total risk evaluation grade of the surface blasting.
Claims (4)
1. The method for evaluating the gray system of the safety risk of the surface blasting is characterized by comprising the following steps of:
s1, establishing a risk level index structure model, and determining each layer element of the risk level index structure model, wherein the risk level index structure model sequentially comprises a target layer, a risk layer and an index layer from the highest layer to the lowest layer; the target layer is a risk evaluation item of each protection target, and comprises a highway, a building and a high-voltage line; the risk layers are of various blasting risk categories, and comprise blasting vibration, blasting noise, blasting flying stones and blasting flying dust; the index layer is an index factor influencing the blasting risk and comprises total dosage, single-stage maximum dosage, a temporary surface, a minimum resistance line, geological conditions, distances and meteorological conditions;
s2, performing pairwise comparison on elements of the risk layer and the index layer by using expert scoring and analytic hierarchy process to obtain a target layer judgment matrix and a risk layer judgment matrix; calculating a target influence weight vector and a risk influence weight vector according to the target layer judgment matrix and the risk layer judgment matrix respectively;
s3, providing a safety control standard of each factor of the index layer, comparing the field technical index with the difference degree of the safety control standard to obtain the influence degree of the risk index, dividing the influence degree of the risk index into a plurality of gray levels, establishing a fuzzy membership function of the possibility degree of each index item for each gray level, and calculating a gray scale judgment matrix of the risk layer by combining expert scoring;
s4, carrying out synthesis operation on the gray scale judgment weight matrix of the risk layer and the risk influence weight vector to obtain a gray scale judgment weight vector of the target layer, and forming the gray scale judgment weight matrix of the target layer through the gray scale judgment weight vector of the target layer; combining the gray scale judgment weight matrix of the target layer with the target influence weight vector to obtain a comprehensive risk evaluation value vector of each element of the target layer;
s5, calculating weight vectors of comprehensive risk evaluation values of all elements of the target layer according to the central values of the gray class level intervals, performing synthesis operation on the weight vectors of the comprehensive risk evaluation values of all elements of the target layer and the comprehensive risk evaluation value vectors to obtain fuzzy comprehensive risk evaluation values of all elements of the target layer, and comprehensively analyzing the total risk evaluation level of the surface blasting;
the step S2 specifically comprises the following steps:
s21, performing expert scoring on elements of the risk layer under each protection target risk assessment item in the risk level index structure model according to the influence degree on the previous layer, and performing expert scoring on elements of the index layer under each blasting risk category in the risk level index structure model;
s22, performing pairwise comparison on the influence degree of each element of the same layer on a certain element in the previous layer by adopting an analytic hierarchy process to respectively obtain a pairwise comparison target layer judgment matrix and a risk layer judgment matrix;
s23, respectively calculating a target influence weight vector and a risk influence weight vector according to the target layer judgment matrix and the risk layer judgment matrix;
s24, consistency test is carried out, and expert scoring is adjusted until consistency passes;
in step S3, the fuzzy membership function is set as f i h (x ij )，
1) Low risk, x ij ∈[0,30％),h＝1
2) Low risk, x ij ∈[10％,50％),h＝2
3) Risk is generally, x ij ∈[30％,70％),h＝3
4) High risk, x ij ∈[50％,90％),h＝4
5) Has great risk of x ij ∈[70％,100％],h＝5
Wherein h is ash class, x ij For the risk influence degree of each index, f i h (x ij ) The likelihood of the degree of risk impact is expressed.
2. The method according to claim 1, wherein in step S23, the weight vector is a normalized column average method, comprising:
sa1, normalizing elements of a judgment matrix according to rows;
sa2, adding the normalized rows;
and Sa3, dividing the added vectors by the number of row vectors of the judgment matrix to obtain weight vectors.
3. The method for evaluating a surface blasting security risk gray system according to claim 1, wherein in step S23, the weight vector adopts a feature root method, comprising:
let the judgment matrix be A, and solve the characteristic root of the judgment matrix to obtain:
AW＝λ max W
wherein lambda is max And W is the corresponding feature vector and is normalized to be used as a weight vector.
4. The method for evaluating a strip explosion security risk gray system according to claim 1, wherein the step S24 consistency check includes:
sb1. calculate the consistency index CI:
where n is the number of row vectors of the judgment matrix,
sb2. searching a corresponding average random consistency index RI;
sb3, calculating a consistency ratio CR:
if CR < 0.1, the consistency is acceptable; CR is more than or equal to 0.1, and the expert scoring is required to be adjusted;
and Sb4. carrying out consistency test of the steps Sb1-Sb3 layer by layer according to the weight vector of each group of elements to a certain element in the upper layer.
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