CN113723817A - Enterprise dust explosion risk assessment method, device and equipment - Google Patents
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Abstract
The invention relates to a method, a device and equipment for evaluating dust explosion risks of enterprises, wherein the method comprises the following steps: step 1: establishing a three-dimensional risk assessment system; wherein, three-dimensional risk assessment system includes: a first level index, a second level index and a third level index; step 2: calculating the weight of the three-level index by using a structure entropy weight method; and step 3: determining the scores of the three-level indexes; and 4, step 4: obtaining the index grade of the first-level index based on the weight of the third-level index and the fraction of the third-level index; and 5: and determining the risk level of dust explosion of the enterprise according to the index level of the primary index. According to the technical scheme, the condition that evaluation errors are large due to subjective judgment of people is avoided, and meanwhile, specific process characteristics are combined, so that the enterprise dust explosion risk level evaluation method is more targeted and higher in field feasibility.
Description
Technical Field
The invention belongs to the technical field of enterprise dust explosion risk prevention and control, and particularly relates to an enterprise dust explosion risk assessment method, device and equipment.
Background
Dust explosion risks exist in many powder-related enterprises, such as wood product processing enterprises. The dust explosion risk prevention and control emphasizes the importance of 'prevention in advance', so the dust explosion risk assessment is a key link of the risk prevention and control. The existing dust explosion risk assessment method mainly adopts an analytic hierarchy process, and index weight has certain subjectivity; the importance of the safety management system in the aspect of dust explosion risk prevention and control is not emphasized; the evaluation aiming at the self risk of the dust is not specific, and the practicability of the evaluation combined with other indexes of the dust explosion risk is not strong; in addition, the existing dust explosion risk assessment method does not relate to specific industries, and risk assessment can not be carried out in a targeted manner according to industrial process characteristics.
Disclosure of Invention
In view of the above, the present invention provides a method, an apparatus and a device for evaluating dust explosion risk of an enterprise to solve the problems of the prior art that the evaluation of the risk of dust itself is not specific and the practicability is not strong.
According to a first aspect of the embodiments of the present application, there is provided an enterprise dust explosion risk assessment method, including:
step 1: establishing a three-dimensional risk assessment system; wherein the three-dimensional risk assessment system comprises: a first level index, a second level index and a third level index;
step 2: calculating the weight of the three-level index by using a structural entropy weight method;
and step 3: determining a score of the tertiary indicator;
and 4, step 4: obtaining the index grade of the first-level index based on the weight of the third-level index and the fraction of the third-level index;
and 5: and determining the risk level of dust explosion of the enterprise according to the index level of the primary index.
Further, the step 2 includes:
step 21: collecting the importance of the three-level indexes, and sequencing the importance of the three-level indexes to obtain an index set;
step 22: forming a matrix A (a) using the set of metricsij) (ii) a Wherein, aijThe importance of the jth tertiary index determined for the ith expert; i is an e [1, n ]]N is the total number of experts; j is an element of [1, m ]]M is the total number of the three-level indexes;
step 23: i is calculated byMembership b of importance of j (th) third-level index determined by individual expertij：
In the formula, g is a conversion parameter, and g is m + 2;
step 24: forming a matrix by using the membership of the importance of the three-level index
Determining the average cognition of the importance of the j (th) tertiary index determined by n experts according to the following formula
Determining the cognitive blindness sigma of the importance of the jth tertiary index determined by n experts according to the formulaj：
Determining a comprehensive understanding degree X of the importance degree of the jth tertiary index determined by n experts according to the following formulaj：
Step 25: the weight ω of the jth tertiary index is determined as followsj：
Further, the step 3 includes:
and scoring the three-level indexes in the three-dimensional risk assessment system through experts to obtain the scores of the three-level indexes.
Further, the step 4 includes:
step 41: calculating an index grade of the secondary index by using the weight of the tertiary index and the fraction of the tertiary index;
step 42: and determining the index grade of the primary index according to the index grade of the secondary index.
Further, the step 41 includes:
determining the z tertiary index r in the k secondary index according to the formulakzIndex grade U for secondary indexfDegree of association Kf(rkz)：
In the above formula, k is E [1, T ∈]T is the total number of the secondary indexes; z is equal to [1, Z ]]Z is the total number of the third-level indexes in the second-level indexes; f is an element of [1, F ∈]F is the maximum level of the index grade of the secondary index; v. ofkzIs the fraction of the z tertiary index in the k secondary index; vcAs a fractional total difference value, VfIs an index grade UfA fractional difference of (a); wherein,
in the above formula, dmaxAnd dminAre respectively the z third index r in the k second indexikUpper limit value and lower limit value in the index level section corresponding to the index level of (D)minAnd DmaxAre respectively the z third index r in the k second indexikThe lower limit value and the upper limit value of all index levels corresponding to the index level of (1);
the kth secondary index r is determined as followskIndex grade U for secondary indexfIs given by the correlation matrix Kf(rk)：
In the above formula, ωkzThe weight of the z tertiary index in the k secondary index;
index grade U of k-th secondary index relative to secondary indexfIs given by the correlation matrix Kf(rk) Index grade U of secondary index corresponding to maximum value of medium relevance degreefIs the k-th secondary index rkIndex grade of (1);
the step 42 includes:
determining the h first-order index r according to the formulahIndex grade U off(rh)：
In the above formula, H is E [1, H]H is the total number of the primary indexes; e is an element of [1, E ∈]And E is the primary index rhThe total number of secondary and medium indicators; omegaeIs the weight, U, corresponding to the e-th secondary index in the h-th primary indexf(re) And the index grade corresponding to the e-th secondary index in the h-th primary index.
Further, the step 5 includes:
establishing a three-dimensional magic cube geometric model according to the index grade of the first-level index;
and the distance from the original point in the three-dimensional magic cube geometric model to the target coordinate point in the three-dimensional magic cube geometric model is the risk level of dust explosion of the enterprise.
According to a second aspect of the embodiments of the present application, there is provided an enterprise dust explosion risk assessment device, including:
the establishing module is used for establishing a three-dimensional risk assessment system; wherein the three-dimensional risk assessment system comprises: a first level index, a second level index and a third level index;
the calculating module is used for calculating the weight of the three-level index by using a structure entropy weight method;
a first determination module for determining a score of the tertiary index;
the acquisition module is used for obtaining the index grade of the first-level index based on the weight of the third-level index and the fraction of the third-level index;
and the second determination module is used for determining the risk level of dust explosion of the enterprise according to the index level of the primary index.
According to a third aspect of the embodiments of the present application, there is provided an enterprise dust explosion risk assessment apparatus, the apparatus comprising:
a memory having an executable program stored thereon;
and the processor is used for executing the executable program in the memory so as to realize the steps of the enterprise dust explosion risk assessment method.
By adopting the technical scheme, the invention can achieve the following beneficial effects: the method comprises the steps of establishing a three-dimensional risk assessment system, calculating the weight of a three-level index by using a structure entropy weight method, determining the score of the three-level index, obtaining the index grade of a first-level index based on the weight of the three-level index and the score of the three-level index, and determining the risk grade of dust explosion of an enterprise according to the index grade of the first-level index, so that the condition that assessment errors are large due to subjective judgment of people is avoided, the enterprise dust explosion risk grade assessment method is more targeted, and the field feasibility is higher.
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In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, it is obvious that the drawings in the following description are only some embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to the drawings without creative efforts.
FIG. 1 is a flow chart illustrating a method for enterprise dust explosion risk assessment in accordance with an exemplary embodiment;
figure 2 is a schematic diagram of a corresponding three-dimensional puzzle showing dust explosion sensitivity according to an exemplary embodiment;
FIG. 3 is a schematic diagram of a three-dimensional magic cube geometric model showing dust explosion sensitivity correspondence, according to an exemplary embodiment;
fig. 4 is a schematic structural diagram of an enterprise dust explosion risk assessment device according to an exemplary embodiment.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the technical solutions of the present invention will be described in detail below. It is to be understood that the described embodiments are merely exemplary of the invention, and not restrictive of the full scope of the invention. All other embodiments, which can be derived by a person skilled in the art from the examples given herein without any inventive step, are within the scope of the present invention.
Fig. 1 is a flow chart illustrating a method for assessing risk of dust explosion in an enterprise, which may be used in a terminal, but is not limited to being used in the terminal, according to an exemplary embodiment, and includes the following steps:
step 1: establishing a three-dimensional risk assessment system; wherein, three-dimensional risk assessment system includes: a first level index, a second level index and a third level index;
step 2: calculating the weight of the three-level index by using a structure entropy weight method;
and step 3: determining the scores of the three-level indexes;
and 4, step 4: obtaining the index grade of the first-level index based on the weight of the third-level index and the fraction of the third-level index;
and 5: and determining the risk level of dust explosion of the enterprise according to the index level of the primary index.
According to the enterprise dust explosion risk assessment method provided by the embodiment of the invention, a three-dimensional risk assessment system is established, the weight of the three-level index is calculated by using a structure entropy weight method, the score of the three-level index is determined, the index grade of the first-level index is obtained based on the weight of the three-level index and the score of the third-level index, and the enterprise dust explosion risk grade is determined according to the index grade of the first-level index, so that the condition that the assessment error is large due to subjective judgment of people is avoided, the enterprise dust explosion risk grade assessment method is more targeted, and the field feasibility is higher.
Further optionally, before step 1, the method further includes:
collecting enterprise dust explosion related data, and determining indexes in a three-dimensional risk assessment system according to the enterprise dust explosion related data.
In some optional embodiments, the risk point of dust explosion of a specific wood product processing plant can be identified by, but not limited to, visiting and investigating an enterprise site and associating with a dust explosion related theory, combining with dust explosion accident cases at home and abroad, and combining with laws, regulations and technical standards, so as to establish a three-dimensional risk assessment system.
Further optionally, the three-dimensional risk assessment system comprises: three first-level indexes, six second-level indexes and twenty-eight third-level indexes;
further optionally, the primary indicators include: accident occurrence probability, accident consequence severity and safety management system;
the secondary indexes corresponding to the accident occurrence probability comprise: dust explosion environment and dust explosion sensitivity;
the secondary indicators corresponding to the severity of the accident consequence include: dust explosion sites, dust explosion intensity and accident loss degree.
Further optionally, the three levels of indicators corresponding to the dust explosion environment include: static/lightning control, spark control, high temperature surface control, dust control, building layout and process layout;
the corresponding three-level indexes of dust explosion sensitivity comprise: minimum ignition energy, minimum ignition temperature, and minimum explosive concentration.
The three-level indexes corresponding to the dust explosion places comprise: explosion suppression measures, explosion venting measures, explosion suppression measures, building layout, evacuation layout and fire fighting equipment;
the three-level indexes corresponding to the dust explosion intensity comprise: maximum explosion pressure and explosion index;
the three-level indexes corresponding to the accident loss degree comprise: personal injury and loss of economy.
The three-level indexes corresponding to the safety management system comprise: regulation and regulation, hidden danger investigation, operation regulation, education and training, equipment inspection and maintenance, dust cleaning, fire operation, behavior regulation and emergency management.
It should be noted that the enterprise dust explosion risk level evaluation method is more targeted and has higher field feasibility by establishing a three-dimensional risk evaluation system and determining each index in the three-dimensional risk evaluation system by combining specific process characteristics.
Further optionally, step 2 includes:
step 21: collecting the importance of the three-level indexes, and sequencing the importance of the three-level indexes to obtain an index set;
wherein, the importance of the three-level index comprises: 1. 2, 3, 4 and 5, the importance degree of the three-level indexes is ranked as follows: 1>2>3>4> 5;
step 22: forming a matrix A (a) using the set of indicesij) (ii) a Wherein, aijThe importance of the jth index determined for the ith expert; i is an e [1, n ]]N is the total number of experts; j is an element of [1, m ]]M is the total number of the three-level indexes;
step 23: calculating the membership b of the importance of the jth tertiary index determined by the ith expert according to the following formulaij：
In the formula, g is a conversion parameter, and g is m + 2;
step 24: forming a matrix by using membership of importance of three-level index
Determining the average cognition of the importance of the j (th) tertiary index determined by n experts according to the following formula
Determining the cognitive blindness sigma of the importance of the jth tertiary index determined by n experts according to the formulaj：
Determining a comprehensive understanding degree X of the importance degree of the jth tertiary index determined by n experts according to the following formulaj：
Step 25: the weight ω of the jth tertiary index is determined as followsj：
It should be noted that, the weight calculation is performed by using a structure entropy weight method, and the importance of each three-level index is subjected to 'typical ordering' by collecting expert opinions, so that the occurrence of abnormal weight coefficients is reduced, and the accuracy can be improved. In order to avoid errors caused by pure quantitative analysis and pure qualitative analysis in the weight determination process, the weights of some indicators can be revised by combining accident cases, but not limited to.
Further optionally, step 3 includes:
and (4) scoring the three-level indexes in the three-dimensional risk assessment system by experts to obtain the scores of the three-level indexes.
Further optionally, step 4 includes:
step 41: calculating the index grade of the secondary index by using the weight of the tertiary index and the fraction of the tertiary index;
step 42: and determining the index grade of the primary index according to the index grade of the secondary index.
Further optionally, step 41 includes:
determining the z tertiary index r in the k secondary index according to the formulakzIndex grade U for secondary indexfDegree of association Kf(rkz)：
In the above formula, k is E [1, T ∈]T is the total number of the secondary indexes; z is equal to [1, Z ]]Z is the total number of the third-level indexes in the second-level indexes; f is an element of [1, F ∈]F is the maximum level of the index grade of the secondary index; v. ofkzIs the fraction of the z tertiary index in the k secondary index; vcAs a fractional total difference value, VfIs an index grade UfA fractional difference of (a); wherein,
in the above formula, dmaxAnd dminAre respectively the z third index r in the k second indexikUpper limit value and lower limit value in the index level section corresponding to the index level of (D)minAnd DmaxAre respectively the z third index r in the k second indexikThe lower limit value and the upper limit value of all index levels corresponding to the index level of (1);
for example, assuming that 5 levels are equally divided from 0 to 100, the "upper limit value and lower limit value in the index level section corresponding to the index level" are 0 and 20, 20 and 40, 40 and 60, 60 and 80, 80 and 100; "the lower limit value and the upper limit value of all index levels corresponding to the index levels" are 0 and 100;
the kth secondary index r is determined as followskIndex grade U for secondary indexfIs given by the correlation matrix Kf(rk)：
In the above formula, ωkzThe weight of the z tertiary index in the k secondary index;
index grade U of k-th secondary index relative to secondary indexfIs given by the correlation matrix Kf(rk) Index grade U of secondary index corresponding to maximum value of medium relevance degreefIs the kth secondary index rkIndex grade of (1);
for example, using a two-level index r1Three-level index static/lightning control r11For example, the calculation process of the index correlation is described, the index grade of the secondary index is 1-5, and the score interval from grade 1 to grade 5 is set to [90,100 ]]、[80,90]、[70,80]、[60,70]、[0,60]An example of the calculation is as follows:
ρ(v11,V1)＝|60-(90+100)/2|-(100-90)/2＝30；
ρ(v11,V2)＝|60-(80+90)/2|-(90-80)/2＝20；
ρ(v11,V3)＝|60-(70+80)/2|-(80-70)/2＝10；
ρ(v11,V4)＝|60-(60+70)/2|-(70-60)/2＝0；
ρ(v11,V5)＝|60-(0+60)/2|-(60-0)/2＝0；
ρ(v11,Vc)＝|60-(0+100)/2|-(100-0)/2＝-40；
K1(r11)＝ρ(v11,V1)/[ρ(v11,Vc)-ρ(v11,V1)]＝30/(-40-30)＝-0.429
K2(r11)＝ρ(v11,V2)/[ρ(v11,Vc)-ρ(v11,V2)]＝20/(-40-20)＝-0.333
K3(r11)＝ρ(v11,V3)/[ρ(v11,Vc)-ρ(v11,V3)]＝10/(-40-10)＝-0.2
K4(r11)＝ρ(v11,V4)/[ρ(v11,Vc)-ρ(v11,V4)]＝0/(-40-0)＝0
K5(r11)＝ρ(v11,V5)/[ρ(v11,Vc)-ρ(v11,V5)]＝0/(-40-0)＝0
in the above formula, v11Electrostatic/lightning control r for three-level index11Fraction of (V)1-V5Respectively, a score difference, V, of index levels 1-5cIs the fractional total difference;
similarly, the spark control r influencing the dust explosion environment possibility grade can be calculated12High temperature surface control r13Dust control14Building layout r15And process layout r16The degree of correlation of each index of (1), then
According to the principle of maximum membership degree, a correlation matrix K (r)1) The maximum value of the medium relevance degree is 0.053, and the index grade U of the secondary index corresponding to the maximum value of the relevance degreefIs 5, so r1Class v;
step 42, comprising:
determining the h first-order index r according to the formulahIndex grade U off(rh)：
In the above formula, H is E [1, H]H is the total number of the primary indexes; e is an element of [1, E ∈]E is a primary index rhThe total number of secondary and medium indicators; omegaeIs the weight, U, corresponding to the e-th secondary index in the h-th primary indexf(re) And the index grade corresponding to the e-th secondary index in the h-th primary index.
It should be noted that, the weight of the secondary indicator may be obtained, but not limited to, through experimental data or expert experience, for example, a plurality of experts may obtain the weight of the secondary indicator according to experience.
For example, if the level of the explosive environment of the secondary index dust is 5, the level of the self explosion sensitivity of the dust is 4, and the weighting coefficients of the two are 0.6 and 0.4, respectively, the level of the probability of the accident of the primary index is calculated: 0.6 × 5+0.4 × 4 ═ 4.6, grade v. It should be noted that the calculated risk level has a decimal digit less than 0.6, and is not carried. For example, 1 is assumed to be the calculated risk level of 1.5, and 2 is assumed to be the calculated risk level of 1.6.
In some embodiments, the three-level index number Minimum Ignition Energy (MIE), Minimum Ignition Temperature (MIT), and Minimum Explosive Concentration (MEC) in the dust explosion sensitivity of the secondary index are graded such that MIT takes a lower value of both MITC (minimum ignition temperature of dust layer) or MITL (minimum ignition temperature of dust cloud). Three dust explosion sensitivity parameter classifications can be, but are not limited to, as shown in table 1:
TABLE 1 dust explosion sensitivity parameter grading
| Grade | 1 | 2 | 3 | 4 |
| MITC or MITL (. degree. C.) | >450 | 300-450 | 135-300 | ≤135 |
| MIE(mJ) | >100 | 30-100 | 10-30 | ≤10 |
| MEC(g/m3) | >100 | 50-100 | 25-50 | ≤25 |
In some embodiments, as shown in fig. 2, a dust explosion sensitivity three-dimensional evaluation magic cube can be established according to the grading of each sensitivity parameter, and the three-dimensional magic cube body is divided into 5 grades in parallel and is assigned with the value of 1-5. Data from experimental testing of three dust explosion sensitivity parameters.
In some embodiments, the dust explosion intensity grade is divided according to the characteristic parameter of the dust, namely the maximum explosion pressure PmaxAnd an explosion index KstDust explosion severity was graded as an index as shown in table 2:
table 2 dust explosion severity rating
In some embodiments, when the severity level of the accident consequence is divided by the secondary index, the severity level is comprehensively determined mainly by two aspects of personal casualty loss and economic loss. The number of personnel and economic property in the dust operation range are taken as the basis of conservative evaluation. The personal casualties caused by accidents comprise two parameters of death number and injured number, and the specific grading standard is shown in table 3:
TABLE 3 personal injury and death rating
F is the number of deaths, and SI is the number of serious injuries; death: the disability injury caused by the loss of working days equal to or more than 6000 days; light injury: disability injury caused by a loss working day of less than 105 days;
the economic loss caused by the accident is mainly represented by the sum of direct economic loss and indirect economic loss, and the specific index classification is shown in table 4:
TABLE 4 economic loss rating
| Economic loss division (E) | Grade | Assignment of value |
| E < 10 ten thousand | 1 | 1 |
| E is more than or equal to 10 ten thousand and less than 1000 ten thousand | 2 | 2 |
| E is more than or equal to 1000 ten thousand and less than 5000 ten thousand | 3 | 3 |
| E is more than or equal to 5000 ten thousand and less than 1 hundred million | 4 | 4 |
| E is more than or equal to 1 hundred million | 5 | 5 |
Further optionally, step 5 includes:
establishing a three-dimensional magic cube geometric model according to the index grade of the first-level index;
and the distance from the original point in the three-dimensional magic cube geometric model to the target coordinate point in the three-dimensional magic cube geometric model is the risk level of dust explosion of the enterprise.
For example, as shown in fig. three, the horizontal axis of the three-dimensional magic cube geometric model may be but is not limited to the primary index accident consequence severity, the vertical axis of the three-dimensional magic cube geometric model may be but is not limited to the primary index accident occurrence probability, and the vertical axis of the three-dimensional magic cube geometric model may be but is not limited to the primary index safety management system.
In some embodiments, the "three-dimensional magic cube geometric model" may be, but is not limited to being, fused on the basis of a two-dimensional risk matrix (P-S)And (4) combining the models constructed by the third factor. Dust explosion accidents in wood processing enterprises can greatly reduce the occurrence possibility and the severity of consequences of the dust explosion accidents by perfecting a safety management system and establishing a supervision and inspection mechanism. Thus, but not limited to, the probability of an accident, the severity of the outcome, the security management system may be given a weight λ1＝0.3、λ2＝0.3、λ3The enterprise dust explosion risk level corresponding to each index is substituted into the formula (11)
Calculating the distance from the coordinate point (x ', y ', z ') to the origin to determine the explosion risk level of the wood dust of the enterprise, wherein the grade division interval is shown in table 5:
TABLE 5 three-dimensional computational grading
| Ranking | Grade |
| 1＜R≤1.5 | 1 |
| 1.5＜R≤2.5 | 2 |
| 2.5＜R≤3.5 | 3 |
| 3.5＜R≤4.5 | 4 |
| 4.5＜R≤5 | 5 |
In some optional embodiments, on the premise of determining the occurrence probability of a dust explosion accident, the severity of accident consequences and the level of a safety management system, the evaluation results are combined according to the idea of a risk matrix, and the dust explosion risk levels of the wood product processing enterprises are preliminarily divided into 5 levels, namely, a very low risk level (level I), a low risk level (level II), a medium risk level (level III), a high risk level (level IV) and a very high risk level (level V). The accident occurrence probability corresponding grade representation symbols are A-E, the accident consequence severity corresponding grade representation symbols are a-E, the safety management system representation symbols are 1-5, and as shown in the table 6, a grade division three-dimensional magic cube visual view is finally formed, and the figure is shown in figure 3.
TABLE 6 dust explosion risk grade division and corresponding element risk combination for wood product processing enterprises
Further optionally, after step 5, the method further includes: and reversely deducing weak links of the enterprise dust explosion risk system according to the enterprise dust explosion risk level and the enterprise dust explosion risk level corresponding to each index in the three-dimensional risk assessment system, and providing an improvement suggestion.
The enterprise dust explosion risk assessment method provided by the embodiment of the invention establishes a dust explosion risk assessment index system and detailed rules aiming at the process characteristics of the wood product processing enterprise, has pertinence and practicability, and is convenient for assessing the risk level with higher efficiency and more accuracy. The method is beneficial to reversely pushing weak links of dust explosion safety measures and safety management systems of enterprises, and has important significance for improving the dust explosion risk level of the woodwork processing factory. In the risk evaluation index, the self explosion characteristic of the dust is reasonably combined with the explosive environmental factor, and a three-dimensional magic cube is established to evaluate the self sensitivity of the dust, so that the practicability is improved in the evaluation process of a specific enterprise. Meanwhile, the index weight is calculated by using a structure entropy weight method, the weight can be corrected through case data, and the index weight is finally determined through a method combining reasonable qualitative research and quantitative research, so that the method has certain scientificity.
An embodiment of the present invention further provides an enterprise dust explosion risk assessment apparatus, as shown in fig. 4, the apparatus includes:
the establishing module is used for establishing a three-dimensional risk assessment system; wherein, three-dimensional risk assessment system includes: a first level index, a second level index and a third level index;
the calculating module is used for calculating the weight of the three-level index by using a structure entropy weight method;
the first determination module is used for determining the scores of the three-level indexes;
the acquisition module is used for acquiring the index grade of the first-level index based on the weight of the third-level index and the fraction of the third-level index;
and the second determination module is used for determining the risk level of dust explosion of the enterprise according to the index level of the primary index.
Further, the calculation module includes:
the acquisition submodule is used for acquiring the importance of the three-level indexes, and sequencing the importance of the three-level indexes to acquire an index set;
a first determining submodule for forming a matrix A (a) using the index setij) (ii) a Wherein, aijThe importance of the jth tertiary index determined for the ith expert; i is an e [1, n ]]N is the total number of experts; j is an element of [1, m ]]M is the total number of the three-level indexes;
a first calculating submodule for calculating membership b of importance of jth tertiary index determined by ith expert according to the following formulaij：
In the formula, g is a conversion parameter, and g is m + 2;
a second determining submodule for forming a matrix using the membership of the importance of the three-level index
Determining the average cognition of the importance of the j (th) tertiary index determined by n experts according to the following formula
Determining the cognitive blindness sigma of the importance of the jth tertiary index determined by n experts according to the formulaj：
Determining a comprehensive understanding degree X of the importance degree of the jth tertiary index determined by n experts according to the following formulaj：
A third determining submodule for determining a weight ω of a jth tertiary index according to the following equationj：
Further, the first determining module is specifically configured to:
and (4) scoring the three-level indexes in the three-dimensional risk assessment system by experts to obtain the scores of the three-level indexes.
Further, the obtaining module includes:
the second calculation submodule is used for calculating the index grade of the secondary index by utilizing the weight of the tertiary index and the fraction of the tertiary index;
and the fourth determining submodule is used for determining the index grade of the primary index according to the index grade of the secondary index.
Further, the second calculation submodule is specifically configured to:
determining the z tertiary index r in the k secondary index according to the formulakzIndex grade U for secondary indexfDegree of association Kf(rkz)：
In the above formula, k is E [1, T ∈]T is the total number of the secondary indexes; z is equal to [1, Z ]]Z is the total number of the third-level indexes in the second-level indexes; f is an element of [1, F ∈]F is the maximum level of the index grade of the secondary index; v. ofkzIs the fraction of the z tertiary index in the k secondary index; vcAs a fractional total difference value, VfIs an index grade UfA fractional difference of (a); wherein,
in the above formula, dmaxAnd dminAre respectively the z third index r in the k second indexikUpper limit value and lower limit value in the index level section corresponding to the index level of (D)minAnd DmaxAre respectively the z third index r in the k second indexikThe lower limit value and the upper limit value of all index levels corresponding to the index level of (1);
the kth secondary index r is determined as followskIndex grade U for secondary indexfIs given by the correlation matrix Kf(rk)：
In the above formula, ωkzThe weight of the z tertiary index in the k secondary index;
index grade U of k-th secondary index relative to secondary indexfIs given by the correlation matrix Kf(rk) Index grade U of secondary index corresponding to maximum value of medium relevance degreefIs the kth secondary index rkIndex grade of (1);
a fourth determination submodule, configured to:
determining the h first-order index r according to the formulahIndex grade U off(rh)：
In the above formula, H is E [1, H]H is the total number of the primary indexes; e is an element of [1, E ∈]E is a primary index rhThe total number of secondary and medium indicators; omegaeIs the weight, U, corresponding to the e-th secondary index in the h-th primary indexf(re) And the index grade corresponding to the e-th secondary index in the h-th primary index.
Further, the second determining module is specifically configured to:
establishing a three-dimensional magic cube geometric model according to the index grade of the first-level index;
and the distance from the original point in the three-dimensional magic cube geometric model to the target coordinate point in the three-dimensional magic cube geometric model is the risk level of dust explosion of the enterprise.
According to the enterprise dust explosion risk assessment device provided by the embodiment of the invention, a three-dimensional risk assessment system is established through an establishing module, a calculating module calculates the weight of a three-level index by using a structure entropy weight method, a first determining module determines the score of the three-level index, an obtaining module obtains the index grade of a first-level index based on the weight of the three-level index and the score of the three-level index, and a second determining module determines the risk grade of dust explosion of an enterprise according to the index grade of the first-level index, so that the condition that the assessment error is large due to human subjective judgment is avoided, the enterprise dust explosion risk grade assessment method is more targeted, and the field feasibility is higher.
It is to be understood that the apparatus embodiments provided above correspond to the method embodiments described above, and corresponding specific contents may be referred to each other, which are not described herein again.
The embodiment of the invention also provides enterprise dust explosion risk assessment equipment, which comprises:
a memory having an executable program stored thereon;
and the processor is used for executing the executable program in the memory so as to realize the steps of the enterprise dust explosion risk assessment method provided by the embodiment.
As will be appreciated by one skilled in the art, embodiments of the present application may be provided as a method, system, or computer program product. Accordingly, the present application may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present application may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, optical storage, and the like) having computer-usable program code embodied therein.
The present application is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the application. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
The above description is only for the specific embodiments of the present invention, but the scope of the present invention is not limited thereto, and any person skilled in the art can easily conceive of the changes or substitutions within the technical scope of the present invention, and all the changes or substitutions should be covered within the scope of the present invention. Therefore, the protection scope of the present invention shall be subject to the protection scope of the appended claims.
Claims (8)
1. An enterprise dust explosion risk assessment method is characterized by comprising the following steps:
step 1: establishing a three-dimensional risk assessment system; wherein the three-dimensional risk assessment system comprises: a first level index, a second level index and a third level index;
step 2: calculating the weight of the three-level index by using a structural entropy weight method;
and step 3: determining a score of the tertiary indicator;
and 4, step 4: obtaining the index grade of the first-level index based on the weight of the third-level index and the fraction of the third-level index;
and 5: and determining the risk level of dust explosion of the enterprise according to the index level of the primary index.
2. The method of claim 1, wherein the step 2 comprises:
step 21: collecting the importance of the three-level indexes, and sequencing the importance of the three-level indexes to obtain an index set;
step 22: forming a matrix A (a) using the set of metricsij) (ii) a Wherein, aijThe importance of the jth tertiary index determined for the ith expert; i is an e [1, n ]]N is the total number of experts; j is an element of [1, m ]]M is the total number of the three-level indexes;
step 23: calculating the membership b of the importance of the jth tertiary index determined by the ith expert according to the following formulaij：
In the formula, g is a conversion parameter, and g is m + 2;
step 24: forming a matrix B (B) by using the membership degree of the importance degree of the three-level indexij)k*n；
Determining the average cognition of the importance of the j (th) tertiary index determined by n experts according to the following formula
Determining the cognitive blindness sigma of the importance of the jth tertiary index determined by n experts according to the formulaj：
Determining a comprehensive understanding degree X of the importance degree of the jth tertiary index determined by n experts according to the following formulaj：
Step 25: is pressed downFormula determines the weight ω of the jth three-level indexj：
3. The method of claim 1, wherein step 3 comprises:
and scoring the three-level indexes in the three-dimensional risk assessment system through experts to obtain the scores of the three-level indexes.
4. The method of claim 1, wherein the step 4 comprises:
step 41: calculating an index grade of the secondary index by using the weight of the tertiary index and the fraction of the tertiary index;
step 42: and determining the index grade of the primary index according to the index grade of the secondary index.
5. The method of claim 4, wherein the step 41 comprises:
determining the z tertiary index r in the k secondary index according to the formulakzIndex grade U for secondary indexfDegree of association Kf(rkz)：
In the above formula, k is E [1, T ∈]T is the total number of the secondary indexes; z is equal to [1, Z ]]Z is the total number of the third-level indexes in the second-level indexes; f is an element of [1, F ∈]F is the maximum level of the index grade of the secondary index; v. ofkzIs the fraction of the z tertiary index in the k secondary index; vcAs a fractional total difference value, VfIs an index grade UfA fractional difference of (a); wherein,
in the above formula, dmaxAnd dminAre respectively the z third index r in the k second indexikUpper limit value and lower limit value in the index level section corresponding to the index level of (D)minAnd DmaxAre respectively the z third index r in the k second indexikThe lower limit value and the upper limit value of all index levels corresponding to the index level of (1);
the kth secondary index r is determined as followskIndex grade U for secondary indexfIs given by the correlation matrix Kf(rk)：
In the above formula, ωkzThe weight of the z tertiary index in the k secondary index;
index grade U of k-th secondary index relative to secondary indexfIs given by the correlation matrix Kf(rk) Index grade U of secondary index corresponding to maximum value of medium relevance degreefIs the k-th secondary index rkIndex grade of (1);
the step 42 includes:
determining the h first-order index r according to the formulahIndex grade U off(rh)：
In the above formula, H is E [1, H]H is the total number of the primary indexes; e is an element of [1, E ∈]And E is the primary index rhMiddle and second gradeThe total number of indicators; omegaeIs the weight, U, corresponding to the e-th secondary index in the h-th primary indexf(re) And the index grade corresponding to the e-th secondary index in the h-th primary index.
6. The method of claim 1, wherein the step 5 comprises:
establishing a three-dimensional magic cube geometric model according to the index grade of the first-level index;
and the distance from the original point in the three-dimensional magic cube geometric model to the target coordinate point in the three-dimensional magic cube geometric model is the risk level of dust explosion of the enterprise.
7. An enterprise dust explosion risk assessment device, characterized in that the device includes:
the establishing module is used for establishing a three-dimensional risk assessment system; wherein the three-dimensional risk assessment system comprises: a first level index, a second level index and a third level index;
the calculating module is used for calculating the weight of the three-level index by using a structure entropy weight method;
a first determination module for determining a score of the tertiary index;
the acquisition module is used for obtaining the index grade of the first-level index based on the weight of the third-level index and the fraction of the third-level index;
and the second determination module is used for determining the risk level of dust explosion of the enterprise according to the index level of the primary index.
8. An enterprise dust explosion risk assessment apparatus, the apparatus comprising:
a memory having an executable program stored thereon;
a processor for executing the executable program in the memory to implement the steps of the method of any one of claims 1-6.
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