CN113723817A - Enterprise dust explosion risk assessment method, device and equipment - Google Patents

Abstract

The invention relates to an enterprise dust explosion risk assessment method, device and equipment. The method includes: step 1: establishing a three-dimensional risk assessment system; wherein, the three-dimensional risk assessment system includes: a first-level index, a second-level index and a third-level index; 2: Calculate the weight of the third-level index using the structural entropy weight method; Step 3: Determine the score of the third-level index; Step 4: Obtain the index level of the first-level index based on the weight of the third-level index and the score of the third-level index; Step 5: According to the index level of the first-level index, the risk level of dust explosion in the enterprise is determined. The technical solution provided by this application avoids the situation of large evaluation error caused by human subjective judgment, and at the same time combines the specific process characteristics, making the enterprise dust explosion risk level evaluation method more targeted and more feasible on site.

Description

An enterprise dust explosion risk assessment method, device and equipment

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 technique

There is a risk of dust explosions in many powder-related enterprises, such as wood products processing enterprises. Dust explosion risk prevention and control emphasizes the importance of "pre-prevention", so dust explosion risk assessment is a key link in risk prevention and control. At present, the dust explosion risk assessment method mainly adopts the analytic hierarchy process, and the index weight has a certain degree of subjectivity; it does not emphasize the importance of the safety management system in the prevention and control of dust explosion risk; the assessment of the risk of dust itself is not specific, and it is related to the risk of dust explosion. The combination of other indicators is not very practical; in addition, the existing dust explosion risk assessment method does not involve specific industries, and it is impossible to carry out risk assessment in a targeted manner according to the industry process characteristics.

SUMMARY OF THE INVENTION

In view of this, the purpose of the present invention is to overcome the deficiencies of the prior art, and to provide a method, device and equipment for enterprise dust explosion risk assessment, so as to solve the problem that the assessment of the risk of dust itself in the prior art is not specific and the practicability is not strong. question.

According to a first aspect of the embodiments of the present application, a method for assessing dust explosion risk in an enterprise is provided, the method comprising:

Step 1: establish a three-dimensional risk assessment system; wherein, the three-dimensional risk assessment system includes: first-level indicators, second-level indicators and third-level indicators;

Step 2: Calculate the weight of the three-level index by using the structural entropy weight method;

Step 3: determine the score of the three-level indicator;

Step 4: obtaining the index level of the first-level index based on the weight of the third-level index and the score of the third-level index;

Step 5: Determine the risk level of enterprise dust explosion according to the index level of the first-level index.

Further, the step 2 includes:

Step 21: Collect the importance of the three-level indicators, and sort the importance of the three-level indicators to obtain an indicator set;

Step 22: Use the indicator set to form a matrix A(a _ij ); where a _ij is the importance of the jth third-level indicator determined by the ith expert; i∈[1,n], n is the total number of experts. Number of people; j∈[1,m], m is the total number of three-level indicators;

Step 23: Calculate the membership degree b _ij of the importance of the jth third-level index determined by the ith expert as follows:

In the above formula, g is the conversion parameter, g=m+2;

Step 24: Form a matrix using the membership degrees of the importance degrees of the three-level indicators

Determine the average awareness of the importance of the jth third-level index determined by n experts as follows

The cognitive blindness σ _j of the importance of the jth third-level index determined by n experts is determined as follows:

The comprehensive understanding degree X _j of the importance of the jth third-level index determined by n experts is determined as follows:

Step 25: Determine the weight ω _j of the jth third-level index as follows:

Further, the step 3 includes:

Scores of the third-level indicators in the three-dimensional risk assessment system are obtained by experts scoring the third-level indicators.

Further, the step 4 includes:

Step 41: Calculate the index level of the second-level index by using the weight of the third-level index and the score of the third-level index;

Step 42: Determine the index level of the first-level index according to the index level of the second-level index.

Further, the step 41 includes:

The correlation degree K _f (r _kz ) of the z-th third-level index r _kz with respect to the index level U _f of the second-level index in the k-th second-level index is determined as follows:

In the above formula, k∈[1,T], T is the total number of secondary indicators; z∈[1,Z], Z is the total number of tertiary indicators in the secondary indicators; f∈[1,F], F is the maximum level of the index level of the second-level index; v _kz is the score of the zth third-level index in the k-th second-level index; V _c is the total score difference, and V _f is the score difference of the index level U _f ;in,

In the above formula, _dmax and _dmin are the upper and lower limit values in the index level interval corresponding to the index level of the zth third-level index r _ik in the kth second-level index, respectively, and _Dmin and _Dmax are respectively is the lower limit value and upper limit value of all index levels corresponding to the index level of the zth third-level index r _ik in the kth second-level index;

The correlation matrix K _f (r _k ) of the kth secondary indicator r _k with respect to the indicator level U _f of the secondary indicator is determined as follows:

In the above formula, ω _kz is the weight of the zth third-level index in the kth second-level index;

Let the index level U _f of the second-level index corresponding to the maximum correlation degree in the correlation degree matrix K _f (r _k ) of the k-th second-level index with respect to the index level U _f of the second-level index be the k-th second-level index the index level of the index r _k ;

The step 42 includes:

The index level U _f (r _h ) of the h-th first-level index r _h is determined as follows:

In the above formula, h∈[1,H], H is the total number of the first-level indicators; e∈[1,E], E is the total number of second-level indicators in the first-level index r _h ; ω _e is the weight corresponding to the e-th second-level index in the h-th first-level index, and U _f (re ) is the index level corresponding to the _e -th second-level index in the h-th first-level index.

Further, the step 5 includes:

Establish a three-dimensional Rubik's cube geometric model according to the index level of the first-level index;

The distance from the origin in the three-dimensional cube geometric model to the target coordinate point in the three-dimensional cube geometric model is the risk level of the dust explosion in the enterprise.

According to a second aspect of the embodiments of the present application, an enterprise dust explosion risk assessment device is provided, the device comprising:

establishing a module for establishing a three-dimensional risk assessment system; wherein, the three-dimensional risk assessment system includes: first-level indicators, second-level indicators and third-level indicators;

a calculation module, used for calculating the weight of the three-level index by using the structural entropy weight method;

a first determination module, used for determining the score of the three-level indicator;

an obtaining module, configured to obtain the index level of the first-level index based on the weight of the third-level index and the score of the third-level index;

The second determination module is used for determining the risk level of dust explosion in the enterprise according to the index level of the first-level index.

According to a third aspect of the embodiments of the present application, an enterprise dust explosion risk assessment device is provided, the device comprising:

a memory on which an executable program is stored;

The processor is configured to execute the executable program in the memory, so as to realize the steps of the above-mentioned enterprise dust explosion risk assessment method.

The present invention adopts the above technical scheme, and the beneficial effects that can be achieved include: by establishing a three-dimensional risk assessment system, using the structural entropy weight method to calculate the weight of the third-level index, determining the score of the third-level index, and based on the weight of the third-level index and the third-level index. According to the index level of the first-level index, the risk level of enterprise dust explosion is determined, which avoids the situation of large evaluation error caused by human subjective judgment, and makes the evaluation method of enterprise dust explosion risk level more effective. Targeted, on-site feasibility is higher.

Description of drawings

In order to explain the embodiments of the present invention or the technical solutions in the prior art more clearly, the following briefly introduces the accompanying drawings that need to be used in the description of the embodiments or the prior art. Obviously, the accompanying drawings in the following description are only These are some embodiments of the present invention. For those of ordinary skill in the art, other drawings can also be obtained according to these drawings without creative efforts.

FIG. 1 is a flowchart of a method for assessing dust explosion risk in an enterprise according to an exemplary embodiment;

Fig. 2 is a schematic diagram of a three-dimensional Rubik's cube corresponding to dust explosion sensitivity according to an exemplary embodiment;

3 is a schematic diagram of a three-dimensional Rubik’s cube geometric model corresponding to dust explosion sensitivity 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 ways

In order to make the objectives, technical solutions and advantages of the present invention clearer, the technical solutions of the present invention will be described in detail below. Obviously, the described embodiments are only some, but not all, embodiments of the present invention. Based on the embodiments of the present invention, all other implementations obtained by those of ordinary skill in the art without creative work fall within the protection scope of the present invention.

Fig. 1 is a flow chart showing a method for assessing dust explosion risk in an enterprise according to an exemplary embodiment. As shown in Fig. 1, the method can be used in a terminal, but is not limited to, including the following steps:

Step 1: establish a three-dimensional risk assessment system; wherein, the three-dimensional risk assessment system includes: first-level indicators, second-level indicators and third-level indicators;

Step 2: Calculate the weight of the three-level index by using the structural entropy weight method;

Step 3: Determine the score of the three-level indicator;

Step 4: Obtain the index level of the first-level index based on the weight of the third-level index and the score of the third-level index;

Step 5: Determine the risk level of enterprise dust explosion according to the index level of the first-level index.

The embodiment of the present invention provides an enterprise dust explosion risk assessment method. By establishing a three-dimensional risk assessment system, the weight of the third-level index is calculated by using the structural entropy weight method, and the score of the third-level index is determined. Based on the weight of the third-level index and the third-level index The score of the index gets the index level of the first-level index. According to the index level of the first-level index, the risk level of dust explosion in the enterprise is determined, which avoids the situation of large evaluation error caused by human subjective judgment, and makes the evaluation method of dust explosion risk level in the enterprise more accurate. Targeted and more feasible on-site.

Further optional, before step 1, it also includes:

Collect enterprise dust explosion-related data, and determine indicators in the three-dimensional risk assessment system based on enterprise dust explosion-related data.

In some optional embodiments, it is possible, but not limited to, to identify dust explosions in specific wood product processing plants by conducting on-site visits and investigations of enterprises and contacting relevant dust explosion theories, combining domestic and foreign dust explosion accident cases, and combining laws, regulations and technical standards. established a three-dimensional risk assessment system.

Further optional, the three-dimensional risk assessment system includes: three first-level indicators, six second-level indicators, and twenty-eight third-level indicators;

Further optional, the first-level indicators include: possibility of accident, severity of accident consequences and safety management system;

The secondary indicators corresponding to the possibility of accident include: dust explosion environment and dust explosion sensitivity;

The secondary indicators corresponding to the severity of the accident consequences include: dust explosion site, dust explosion intensity and accident loss degree.

Further optional, the three-level 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 three-level indicators corresponding to dust explosion sensitivity include: minimum ignition energy, minimum ignition temperature and minimum explosion concentration.

The three-level indicators corresponding to dust explosion sites include: explosion suppression measures, explosion venting measures, explosion prevention measures, building layout, evacuation layout and fire fighting equipment;

The three-level indicators corresponding to dust explosion intensity include: maximum explosion pressure and explosion index;

The three-level indicators corresponding to the degree of accident losses include: personal casualties and economic losses.

The three-level indicators corresponding to the safety management system include: rules and regulations, hidden danger investigation, operation procedures, education and training, equipment inspection and maintenance, dust cleaning, hot work, code of conduct and emergency management.

It should be noted that by establishing a three-dimensional risk assessment system and determining each index in the three-dimensional risk assessment system in combination with specific process characteristics, the assessment method of dust explosion risk level of enterprises is more targeted and the on-site feasibility is higher.

Further optional, step 2, including:

Step 21: Collect the importance of the three-level indicators, and sort the importance of the three-level indicators to obtain an indicator set;

Among them, the importance of the three-level indicators includes: 1, 2, 3, 4, and 5, and the order of the importance of the three-level indicators is: 1>2>3>4>5;

Step 22: Use the index set to form a matrix A(a _ij ); wherein, a _ij is the importance of the jth index determined by the ith expert; i∈[1,n], n is the total number of experts; j∈ [1,m], m is the total number of three-level indicators;

Step 23: Calculate the membership degree b _ij of the importance of the jth third-level index determined by the ith expert as follows:

In the above formula, g is the conversion parameter, g=m+2;

Step 24: Use the membership degree of the importance of the three-level indicators to form a matrix

Determine the average awareness of the importance of the jth third-level index determined by n experts as follows

The cognitive blindness σ _j of the importance of the jth third-level index determined by n experts is determined as follows:

The comprehensive understanding degree X _j of the importance of the jth third-level index determined by n experts is determined as follows:

Step 25: Determine the weight ω _j of the jth third-level index as follows:

It should be noted that the structural entropy weight method is used for weight calculation, and the importance of each three-level index is "typically ranked" by collecting expert opinions, so as to reduce the occurrence of abnormal weight coefficients and improve the accuracy. In order to avoid errors caused by pure quantitative analysis and pure qualitative analysis in the process of weight determination, the weights of some indicators can be revised, but not limited to, by combining accident cases.

Further optional, step 3, including:

Experts score the three-level indicators in the three-dimensional risk assessment system to obtain the scores of the three-level indicators.

Further optional, step 4, including:

Step 41: Calculate the index level of the second-level index by using the weight of the third-level index and the score of the third-level index;

Step 42: Determine the index level of the first-level index according to the index level of the second-level index.

Further optional, step 41 includes:

The correlation degree K _f (r _kz ) of the z-th third-level index r _kz with respect to the index level U _f of the second-level index in the k-th second-level index is determined as follows:

In the above formula, k∈[1,T], T is the total number of secondary indicators; z∈[1,Z], Z is the total number of tertiary indicators in the secondary indicators; f∈[1,F], F is the maximum level of the index level of the second-level index; v _kz is the score of the zth third-level index in the k-th second-level index; V _c is the total score difference, and V _f is the score difference of the index level U _f ;in,

In the above formula, _dmax and _dmin are the upper and lower limit values in the index level interval corresponding to the index level of the zth third-level index r _ik in the kth second-level index, respectively, and _Dmin and _Dmax are respectively is the lower limit value and upper limit value of all index levels corresponding to the index level of the zth third-level index r _ik in the kth second-level index;

For example, assuming that from 0 to 100, it is equally divided into 5 levels, then the "upper and lower limit values in the index level interval corresponding to the index level" are 0 and 20, 20 and 40, 40 and 60, 60 and 80 , 80 and 100; "the lower limit and upper limit of all index levels corresponding to the index level" are 0 and 100;

The correlation matrix K _f (r _k ) of the kth secondary indicator r _k with respect to the indicator level U _f of the secondary indicator is determined as follows:

In the above formula, ω _kz is the weight of the zth third-level index in the kth second-level index;

Let the index level U _f of the second-level index corresponding to the maximum correlation degree in the correlation degree matrix K _f (r _k ) of the k-th second-level index about the index level U _f of the second-level index be the k-th second-level index r The index level of _k ;

For example, taking the correlation degree of the third-level indicator electrostatic/lightning control r ₁₁ under the second-level indicator r ₁ as an example, the calculation process of the indicator correlation degree is introduced. The index level of the second-level indicator is 1-5, from level 1 to level 5 The score interval is set to [90,100], [80,90], [70,80], [60,70], [0,60]. The calculation example is as follows:

ρ(v ₁₁ , V ₁ )=|60-(90+100)/2|-(100-90)/2=30;

ρ(v ₁₁ , V ₂ )=|60-(80+90)/2|-(90-80)/2=20;

ρ(v ₁₁ , V ₃ )=|60-(70+80)/2|-(80-70)/2=10;

ρ(v ₁₁ , V ₄ )=|60-(60+70)/2|-(70-60)/2=0;

ρ(v ₁₁ , V ₅ )=|60-(0+60)/2|-(60-0)/2=0;

ρ(v ₁₁ , V _c )=|60-(0+100)/2|-(100-0)/2=-40;

K ₁ (r ₁₁ )=ρ(v ₁₁ ,V ₁ )/[ρ(v ₁₁ ,V _c )-ρ(v ₁₁ ,V ₁ )]=30/(-40-30)=-0.429

K ₂ (r ₁₁ )=ρ(v ₁₁ ,V ₂ )/[ρ(v ₁₁ ,V _c )-ρ(v ₁₁ ,V ₂ )]=20/(-40-20)=-0.333

K ₃ (r ₁₁ )=ρ(v ₁₁ ,V ₃ )/[ρ(v ₁₁ ,V _c )-ρ(v ₁₁ ,V ₃ )]=10/(-40-10)=-0.2

K ₄ (r ₁₁ )=ρ(v ₁₁ ,V ₄ )/[ρ(v ₁₁ ,V _c )-ρ(v ₁₁ ,V ₄ )]=0/(-40-0)=0

K ₅ (r ₁₁ )=ρ(v ₁₁ ,V ₅ )/[ρ(v ₁₁ ,V _c )-ρ(v ₁₁ ,V ₅ )]=0/(-40-0)=0

In the above formula, v ₁₁ is the score of the three-level indicator electrostatic/lightning control r ₁₁ , V ₁ -V ₅ are the score differences of index levels 1-5 respectively, and V _c is the total score difference;

In the same way, the correlation degree of each index of spark control r ₁₂ , high temperature surface control r ₁₃ , dust control r ₁₄ , building layout r ₁₅ , and process layout r ₁₆ that affect the possibility level of dust explosion environment can be calculated, then

According to the principle of maximum membership degree, the maximum value of the correlation degree in the correlation degree matrix K(r ₁ ) is 0.053, and the index level U _f of the secondary index corresponding to the maximum degree of correlation degree is 5, so the level of r ₁ is level V ;

Step 42, including:

The index level U _f (r _h ) of the h-th first-level index r _h is determined as follows:

In the above formula, h∈[1,H], H is the total number of first-level indicators; e∈[1,E], E is the total number of second-level indicators in the first-level index r _h ; ω _e is the hth index The weight corresponding to the e-th second-level index in the first-level index, and U _f (re ) is the index level corresponding to the _e -th second-level index in the h-th first-level index.

It should be noted that the weight of the secondary indicator can be obtained, but is not limited to, through experimental data or expert experience. For example, multiple experts discuss and obtain the weight of the secondary indicator based on experience.

For example, assuming that the dust explosive environment level of the secondary indicator is level 5, the dust self-explosion sensitivity level is level 4, and the weight coefficients of the two are 0.6 and 0.4, respectively, then the probability level of the accident occurrence of the primary indicator is calculated: 0.6*5+ 0.4*4=4.6, which is grade V. It should be noted that the calculated risk level, if the number of digits after the decimal point is less than 0.6, will not be rounded up. For example, if the calculated risk level is 1.5, take 1, and if the calculated risk level is 1.6, take 2.

In some embodiments, when classifying the third-level index numbers of minimum ignition energy (MIE), minimum ignition temperature (MIT), and minimum explosion concentration (MEC) in the second-level index dust explosion susceptibility, MIT is taken as MITC (the value of the dust layer). Minimum ignition temperature) or MITL (minimum ignition temperature of dust cloud) whichever is lower. The three dust explosion susceptibility parameters can be graded, but not limited to, as shown in Table 1:

Table 1 Classification of dust explosion sensitivity parameters

grade 1 2 3 4 MITC or MITL(℃) >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 three-dimensional evaluation Rubik's cube for dust explosion sensitivity can be established according to the classification of each sensitivity parameter, but is not limited to, and the three-dimensional Rubik's cube is divided into 5 levels in parallel, and assigned values 1-5. Data based on experimental testing of three dust explosion susceptibility parameters.

In some embodiments, when classifying the dust explosion intensity level of the secondary index, the dust explosion severity is classified by the characteristic parameter maximum explosion pressure _Pmax and explosion index _Kst of the dust as indicators, as shown in Table 2:

Table 2 Classification of dust explosion severity levels

In some embodiments, when classifying the severity level of the secondary indicator accident consequences, the severity level is mainly determined comprehensively from the two aspects of personal injury loss and economic loss. The conservative evaluation is based on the number of personnel and economic property within the scope of dust-related operations. The personal casualties caused by the accident include two parameters: the number of deaths and the number of injured. The specific grading standards are shown in Table 3:

Table 3 Classification of personal casualties

It should be noted that, F = the number of deaths, SI = the number of serious injuries; death: refers to the incapacitating injury with lost working days equal to or more than 6,000 days; minor injury: refers to the incapacitating injury with lost working days less than 105 days;

Among them, the economic loss caused by the accident is mainly represented by the sum of the direct economic loss and the indirect economic loss. The specific index classification is shown in Table 4:

Table 4 Classification of economic losses

Economic Loss Division (E) grade assign E < 100,000 1 1 100,000≤E＜10,000,000 2 2 10 million≤E<50 million 3 3 50 million≤E<100 million 4 4 E≥100 million 5 5

Further optional, step 5, including:

Establish a three-dimensional Rubik's cube geometric model according to the index level of the first-level index;

The distance from the origin in the 3D Rubik's Cube geometric model to the target coordinate point in the 3D Rubik's Cube geometric model is the risk level of enterprise dust explosion.

For example, as shown in Figure 3, the horizontal axis of the 3D Rubik's Cube geometric model can be, but is not limited to, the severity of the accident consequences of the first-level indicator; The vertical axis of the geometric model can be, but is not limited to, the first-level indicator of the safety management system.

计算坐标点(x′,y′,z′)到原点的距离来确定企业木粉尘爆炸风险等级，等级划分区间如表5所示：In some embodiments, the "three-dimensional Rubik's cube geometric model" may be, but is not limited to, a model constructed by integrating a third factor on the basis of a two-dimensional risk matrix (PS). In wood processing enterprises, dust explosion accidents can greatly reduce the possibility of dust explosion accidents and the seriousness of consequences by improving the safety management system and establishing a supervision and inspection mechanism. Therefore, it is possible but not limited to give weights λ ₁ = 0.3, λ ₂ = 0.3, λ ₃ = 0.4 to the possibility of accidents, the severity of consequences, and the safety management system, and substitute the enterprise dust explosion risk level corresponding to each index into the formula (11)

Calculate the distance from the coordinate point (x', y', z') to the origin to determine the risk level of wood dust explosion in the enterprise. The level division interval is shown in Table 5:

Table 5 Classification of three-dimensional computing levels

classification 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 probability of occurrence of dust explosion accident, the severity of accident consequences and the level of safety management system, the evaluation results are combined according to the idea of risk matrix, and the dust explosion risk of wood product processing enterprises is combined. The grades were initially divided into five levels: very low risk (grade I), low risk (grade II), moderate risk (grade III), high risk (grade IV), and extremely high risk (grade V). Among them, the corresponding level of the accident probability is A-E, the corresponding level of the accident consequence severity is a-e, and the safety management system is 1-5, as shown in Table 6. Finally, a three-dimensional Rubik's cube visual view is formed, as shown in the figure. 3.

Table 6 Classification of dust explosion risk levels of wood product processing enterprises and risk combination of corresponding elements

Further optionally, after step 5, it also includes: 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, infer the weak links of the enterprise dust explosion risk system, and propose rectification. Opinion.

The embodiment of the present invention provides an enterprise dust explosion risk assessment method, which establishes a dust explosion risk assessment index system and specific scoring rules according to the technological characteristics of wood product processing enterprises, which is pertinent and practical, and facilitates higher efficiency and more accurate assessment. Risk level. It is beneficial to push back the weak links of enterprise dust explosion safety measures and safety management system, and it is of great significance to improve the dust explosion risk level of wood product processing plants. In the risk assessment index, the self-explosive characteristics of dust and the factors of the explosive environment are reasonably combined, and a three-dimensional Rubik's cube is established to evaluate the sensitivity of dust itself, so as to improve the practicability in the evaluation process of specific enterprises. At the same time, the embodiment of the present invention uses the structural entropy weight method to calculate the index weight, and can also correct the weight through case data, and finally determine the index weight through a combination of reasonable qualitative and quantitative research, which is more scientific.

The embodiment of the present invention also provides an enterprise dust explosion risk assessment device, as shown in FIG. 4 , the device includes:

The establishment module is used to establish a three-dimensional risk assessment system; wherein, the three-dimensional risk assessment system includes: first-level indicators, second-level indicators and third-level indicators;

The calculation module is used to calculate the weight of the three-level index by using the structural entropy weight method;

The first determination module is used to determine the score of the third-level indicator;

an acquisition module, used to obtain the index level of the first-level index based on the weight of the third-level index and the score of the third-level index;

The second determination module is used to determine the risk level of dust explosion in the enterprise according to the index level of the first-level index.

Further, computing modules, including:

The collection sub-module is used to collect the importance of the three-level indicators, sort the importance of the three-level indicators, and obtain the indicator set;

The first determination sub-module is used to form a matrix A(a _ij ) by using the index set; wherein, a _ij is the importance of the jth third-level index determined by the ith expert; i∈[1,n], n is The total number of experts; j∈[1,m], m is the total number of three-level indicators;

The first calculation submodule is used to calculate the membership degree b _ij of the importance degree of the jth third-level index determined by the ith expert as follows:

In the above formula, g is the conversion parameter, g=m+2;

The second determination sub-module is used to form a matrix using the membership degree of the importance of the three-level indicators

Determine the average awareness of the importance of the jth third-level index determined by n experts as follows

The cognitive blindness σ _j of the importance of the jth third-level index determined by n experts is determined as follows:

The comprehensive understanding degree X _j of the importance of the jth third-level index determined by n experts is determined as follows:

The third determination sub-module is used to determine the weight ω _j of the jth third-level indicator as follows:

Further, the first determination module is specifically used for:

Experts score the three-level indicators in the three-dimensional risk assessment system to obtain the scores of the three-level indicators.

Further, get modules, including:

The second calculation submodule is used to calculate the index level of the second-level index by using the weight of the third-level index and the score of the third-level index;

The fourth determination submodule is used for determining the index level of the first-level index according to the index level of the second-level index.

Further, the second calculation submodule is specifically used for:

The correlation degree K _f (r _kz ) of the z-th third-level index r _kz with respect to the index level U _f of the second-level index in the k-th second-level index is determined as follows:

In the above formula, k∈[1,T], T is the total number of secondary indicators; z∈[1,Z], Z is the total number of tertiary indicators in the secondary indicators; f∈[1,F], F is the maximum level of the index level of the second-level index; v _kz is the score of the zth third-level index in the k-th second-level index; V _c is the total score difference, and V _f is the score difference of the index level U _f ;in,

In the above formula, _dmax and _dmin are the upper and lower limit values in the index level interval corresponding to the index level of the zth third-level index r _ik in the kth second-level index, respectively, and _Dmin and _Dmax are respectively is the lower limit value and upper limit value of all index levels corresponding to the index level of the zth third-level index r _ik in the kth second-level index;

The correlation matrix K _f (r _k ) of the kth secondary indicator r _k with respect to the indicator level U _f of the secondary indicator is determined as follows:

In the above formula, ω _kz is the weight of the zth third-level index in the kth second-level index;

Let the index level U _f of the second-level index corresponding to the maximum correlation degree in the correlation degree matrix K _f (r _k ) of the k-th second-level index about the index level U _f of the second-level index be the k-th second-level index r The index level of _k ;

The fourth determination sub-module is specifically used for:

The index level U _f (r _h ) of the h-th first-level index r _h is determined as follows:

In the above formula, h∈[1,H], H is the total number of first-level indicators; e∈[1,E], E is the total number of second-level indicators in the first-level index r _h ; ω _e is the hth index The weight corresponding to the e-th second-level index in the first-level index, and U _f (re ) is the index level corresponding to the _e -th second-level index in the h-th first-level index.

Further, the second determination module is specifically used for:

Establish a three-dimensional Rubik's cube geometric model according to the index level of the first-level index;

The distance from the origin in the 3D Rubik's Cube geometric model to the target coordinate point in the 3D Rubik's Cube geometric model is the risk level of enterprise dust explosion.

In the enterprise dust explosion risk assessment device provided by the embodiment of the present invention, a three-dimensional risk assessment system is established by establishing a module, the calculation module uses the structure entropy weight method to calculate the weight of the third-level index, the first determination module determines the score of the third-level index, and obtains The module obtains the index level of the first-level index based on the weight of the third-level index and the score of the third-level index, and the second determination module determines the risk level of the enterprise dust explosion according to the index level of the first-level index, avoiding the evaluation error caused by the subjective judgment of people. If the situation is larger, the assessment method of dust explosion risk level of enterprises is more targeted, and the on-site feasibility is higher.

It can be understood that the above-mentioned apparatus embodiments correspond to the above-mentioned method embodiments, and the corresponding specific contents can be referred to each other, which will not be repeated here.

The embodiment of the present invention also provides an enterprise dust explosion risk assessment device, the device includes:

a memory on which an executable program is stored;

The processor is configured to execute the executable program in the memory, so as to implement the steps of the enterprise dust explosion risk assessment method provided by the above embodiments.

As will be appreciated by those skilled in the art, the embodiments of the present application may be provided as a method, a system, or a 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 having computer-usable program code embodied therein, including but not limited to disk storage, optical storage, and the like.

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 present application. It will be understood that each flow and/or block in the flowchart illustrations and/or block diagrams, and combinations of flows and/or blocks in the flowchart illustrations and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to the processor of a general purpose computer, special purpose computer, embedded processor or other programmable data processing device to produce a machine such that the instructions executed by the processor of the computer or other programmable data processing device produce Means for implementing the functions specified in a flow or flow of a flowchart and/or a block or blocks of a block diagram.

The computer program instructions may also be stored in a computer readable memory capable of directing a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer readable memory result in an article of manufacture comprising the method of the instructions, the instructions A method implements the functions specified in the flow diagram or flow diagrams and/or the block diagram diagram block or blocks.

These computer program instructions can also be loaded on a computer or other programmable data processing device to cause a series of operational steps to be performed on the computer or other programmable device to produce a computer-implemented process such that The instructions provide steps for implementing the functions specified in the flow or blocks of the flowcharts and/or the block or blocks of the block diagrams.

The above are only specific embodiments of the present invention, but the protection scope of the present invention is not limited thereto. Any person skilled in the art can easily think of changes or substitutions within the technical scope disclosed by the present invention. should be included within the protection scope of the present invention. Therefore, the protection scope of the present invention should be based on the protection scope of the 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 metrics_ij) (ii) a Wherein, a_ijThe 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 formula_ij：

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 index_ij)_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 formula_j：

Determining a comprehensive understanding degree X of the importance degree of the jth tertiary index determined by n experts according to the following formula_j：

Step 25: is pressed downFormula determines the weight ω of the jth three-level index_j：

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 formula_kzIndex grade U for secondary index_fDegree of association K_f(r_kz)：

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. of_kzIs the fraction of the z tertiary index in the k secondary index; v_cAs a fractional total difference value, V_fIs an index grade U_fA fractional difference of (a); wherein,

in the above formula, d_maxAnd d_minAre respectively the z third index r in the k second index_ikUpper limit value and lower limit value in the index level section corresponding to the index level of (D)_minAnd D_maxAre respectively the z third index r in the k second index_ikThe 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 follows_kIndex grade U for secondary index_fIs given by the correlation matrix K_f(r_k)：

In the above formula, ω_kzThe weight of the z tertiary index in the k secondary index;

index grade U of k-th secondary index relative to secondary index_fIs given by the correlation matrix K_f(r_k) Index grade U of secondary index corresponding to maximum value of medium relevance degree_fIs the k-th secondary index r_kIndex grade of (1);

the step 42 includes:

determining the h first-order index r according to the formula_hIndex grade U of_f(r_h)：

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 r_hMiddle and second gradeThe total number of indicators; omega_eIs the weight, U, corresponding to the e-th secondary index in the h-th primary index_f(r_e) 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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