CN117575312A - Port facility operation security risk evaluation method based on fuzzy comprehensive evaluation - Google Patents
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Abstract
The invention discloses a harbor facility operation security risk evaluation method based on fuzzy comprehensive evaluation, which comprises the following steps: establishing an influence factor set; establishing a risk judgment set; establishing a factor weight set; performing fuzzy comprehensive evaluation; and (5) processing the evaluation result. The invention starts from four aspects of man-machine-ring-pipe, analyzes the fusion relation among four factors, combines with the actual situation of a port, and constructs a port high-risk facility operation safety risk early warning index system comprising 4 primary evaluation indexes and 33 secondary evaluation indexes, wherein the number of the considered risk factors is large, the range is wide and the hierarchy is deep. According to the invention, the factor weight set is established by adopting an expert scoring method and an analytic hierarchy process, and a qualitative and quantitative method is combined, so that subjectivity is considered, objectivity of research object evaluation is improved, and calculation errors of index weights can be effectively reduced. The invention effectively avoids the ambiguity and the randomness of the security risk evaluation process and improves the accuracy of the evaluation result.
Description
Technical Field
The invention relates to the field of security management and control of risk facilities, in particular to a harbour facility operation security risk evaluation method based on fuzzy comprehensive evaluation.
Background
The port production is a multi-variety and multi-link combined operation, has the characteristics of multiple operation points, dispersion and large influence by natural factors, and has high continuity and complexity, so that the port production has potential greater danger and unsafe factors than those of the general industry. While harbour high risk operations facilities (e.g. lifting equipment, handling equipment and transport equipment) are important components of harbour production operations, the safety of their operation determines the stability and efficiency of harbour production operations.
In recent years, with the rapid development of the mechanical industry, the reliability of the operation of high-risk operation facilities in ports is remarkably improved, but the safety of the high-risk operation facilities is always a dynamic complex problem due to the influence of multiple factors such as people, machines, rings, pipes and the like, and the fault condition of the mechanical facilities has uncertainty and variability. Therefore, the method has important practical significance in developing the operation safety study of the high-risk operation facilities of the port.
The risk evaluation of the high-risk operation facilities of the port is an important content of safety research, is also a precondition of safety risk early warning, and lays a foundation for the subsequent construction and operation of a safety technical index system. The modern concept and method of safety management are introduced into the safety supervision work practice of the port high-risk equipment, the risk degree of the port high-risk equipment is determined by identifying, analyzing and evaluating the hazard factors, reasonable and feasible countermeasures and suggestions are provided, the whole process safety operation of port risk facilities is ensured, and further the stable performance of port production operation is ensured.
The current popular security evaluation methods mainly comprise a security index evaluation method, a security check list method, a hierarchical analysis method, a gray correlation analysis method, a fuzzy comprehensive evaluation method and the like. Numerous studies are carried out around the methods by students at home and abroad, but the method for evaluating the operation safety of high-risk facilities of ports has some limitations: only man-machine loop factors are considered, and the influence of management factors is not considered; the secondary evaluation index is divided into too wide and not refined; weights of risk factors are not considered; subjective factors of expert evaluation have great influence on the evaluation result, and the like.
Disclosure of Invention
Aiming at the defects of the existing port facility operation security risk evaluation method, the invention provides the port facility operation security risk evaluation method based on fuzzy comprehensive evaluation, which can master the actual security condition and risk degree of the port high-risk facility and is beneficial to predicting, preventing, reasonably controlling and avoiding the occurrence of port equipment accidents in advance.
The basic idea of the invention is as follows: based on the standardized construction requirements of safety production and the actual conditions of ports, risk evaluation influence factors are analyzed, and management factors are brought into an evaluation index system (further comprising personnel, equipment and environment). The evaluation indexes are scientifically screened around four dimensions of a man-machine-ring-pipe, and a port high risk facility operation security risk early warning index system (shown in figure 1) comprising 4 primary evaluation indexes and 33 secondary evaluation indexes is constructed: the first-level evaluation index comprises: personnel factors, equipment factors, management factors, and environmental factors. The personnel factors comprise 8 secondary evaluation indexes such as site safety ratio, safety training condition accepted by staff and the like; the equipment factors comprise 10 secondary evaluation indexes such as the safety condition of the main device of the metal structure, the safety condition of parts and accessories and the like; the management factors comprise 9 secondary evaluation indexes such as the ratio of a safety management system to a standard complete condition and a safety management professional; the environmental factors comprise 6 secondary evaluation indexes such as natural disaster influence, regional social environment influence and the like.
And determining an evaluation index weight set of the port high-risk facility operation safety risk early warning index system by combining an analytic hierarchy process and an expert scoring process.
And based on the evaluation index weight set, carrying out multi-factor fuzzy comprehensive evaluation by adopting a fuzzy comprehensive evaluation method, and determining a safety risk evaluation result.
According to the safety risk assessment result, the actual safety condition and the risk degree of the high-risk facilities of the port can be mastered, and the method is beneficial to predicting, preventing, reasonably controlling and avoiding the occurrence of accidents of the port equipment in advance.
In order to achieve the above purpose, the technical scheme of the invention is as follows:
a harbor facility operation security risk evaluation method based on fuzzy comprehensive evaluation comprises the following steps:
step 1: establishing a set of influencing factors
And determining an influence factor set U of the judging object, namely an evaluation index system. Assume that the influence factor set U is expressed by:
U＝{U 1 ,U 2 ,…,U n }
in U 1 ,U 2 ,…,U n Representing different subsets of influencing factors and being a primary evaluation index. n represents the number of first-order evaluation indexes. The subelement of the first level of evaluation index is referred to as the second level of evaluation index.
Step 2: establishing risk judgment set
The risk judgment set V is a total set composed of elements of various judgment results made by a judge on a judgment object, and is expressed as follows:
V＝{V 1 ,V 2 ,…,V m }
wherein V is 1 ,V 2 ,…,V m Representing various evaluation results, m represents the number of evaluation results.
Step 3: establishing a factor weight set
To reflect the importance degree of each first-level evaluation index, each first-level evaluation index U i Giving corresponding weight A i I=1, 2, …, n, calculated as follows:
an h expert is arranged to score the ith first-level evaluation index, and the score is marked as d ih And meet the followingFor each U i By calculating all specialistsThe weight of the ith first-level evaluation index is obtained by averaging the scoring values of the ith first-level evaluation index; after the weights of all the first-level evaluation indexes are completed, a set formed by the weights is called a factor weight set, and is marked as:
A＝(A 1 ,A 2 ,…,A n ) Wherein
The second-level evaluation index weight is determined according to the method for determining the same first-level evaluation index weight, and the specific method is as follows:
setting n under the ith first-level evaluation index by h-bit expert i Scoring the two secondary evaluation indexes, and marking the result as d ikh ，k＝1,2,…,n i ，n i Representing the number of the second-level evaluation indexes contained in the ith first-level evaluation index, and obtaining an expert pair U i Scoring matrix D of lower secondary evaluation index i ：
Wherein matrix D i Each column represents the scoring value of one expert on each secondary evaluation index of the ith primary evaluation index, and meets the following requirementsEach row represents the scoring value of h-bit expert on the same two-level evaluation index, and the weight of the two-level evaluation index is obtained by averaging each row and is marked as +.>
After scoring of each secondary evaluation index under all the primary evaluation indexes is completed, the weight of each secondary evaluation index under each primary evaluation index is obtained according to the calculation steps and is recorded as:
a i ＝[a i1 ,a i2 ,…,a imi ]wherein
Step 4: performing fuzzy comprehensive evaluation
The method adopts multi-factor fuzzy comprehensive evaluation and comprises the following specific steps:
step 4-1: is provided withI.e. first-level evaluation index U i Contains n i And (5) two-level evaluation indexes. And the following conditions are satisfied:
step 4-2: performing first-level fuzzy comprehensive evaluation
Set a first level evaluation index U i For risk determination set v= { V 1 ,V 2 ,…,V m Membership degree of R i ，R i Is to U i Of the element rr kj Is V (V) j J=1, 2 … m. Thereby obtaining a first-order fuzzy relation evaluation matrix R I The following are provided:
wherein->
For each ofN below i The second-level evaluation indexes are evaluated according to a first-level fuzzy comprehensive evaluation model to obtain a first-level fuzzy comprehensive evaluation set:
B i ＝a i ×R i
step 4-3: performing secondary fuzzy comprehensive evaluation
Set a two-level fuzzy relation evaluation of the influence factor set UMatrix R II The method comprises the following steps:
when factor weight set A and secondary fuzzy relation evaluation matrix R II After the determination, a secondary fuzzy comprehensive evaluation set B is obtained, and the calculation is as follows:
step 5: processing the evaluation results
Obtaining a comprehensive evaluation result b 1 ,b 2 ,…,b m Then, in order to obtain a determined security risk evaluation level, the fuzzy comprehensive evaluation set b= [ B ] is subjected to the following level parameter method 1 ,b 2 ,…,b m ]And (5) performing accuracy.
According to the risk judgment set V= { V 1 ,V 2 ,…,V m Dividing an evaluation interval for each grade, and then establishing a corresponding evaluation scale set:
E＝{E 1 ,E 2 ,…,E m }
then the second level evaluation index U ik The rank calculation formula of (2) is:
first-level evaluation index U i The rank calculation formula of (2) is:
the grade calculation formula of the second-grade fuzzy comprehensive evaluation is as follows:
further, the first-level evaluation index includes a personnel factor, an equipment factor, a management factor and an environmental factor; the personnel factors comprise 8 secondary evaluation indexes including site safety ratio, safety training condition accepted by staff, working capacity of command and management staff, technical level and working capacity of operation staff, evidence holding condition of operation staff, operation labor intensity, unsafe behavior of operation staff and investment of safety protection tools and facilities; the equipment factors comprise 10 secondary evaluation indexes including the safety condition of a main device of a metal structure, the safety condition of parts and accessories, the safety condition of a lubricating vehicle, the safety condition of an electric instrument, the safety protection design of operation facilities, the working reliability of the safety device of the operation facilities, the service duration of the facilities, the operation difficulty and automation degree of the facilities, the maintenance qualification rate of mechanical equipment and the disease operation rate of the facilities; the management factors comprise 9 secondary evaluation indexes including organization mechanism soundness degree, safety management system and standard complete condition, safety management professional ratio, production operation complexity degree, emergency measure formulation and implementation condition, quality management system authentication condition, major hazard source identification and accident management, safety technical measure formulation and implementation condition and operation facility safety inspection acceptance table utilization condition; the environment factors comprise 6 secondary evaluation indexes including external ship and train influences, regional social environment influences, climate, hydrogeology, natural environment influences, natural disaster influences, living and accommodation conditions of port workers and operation lighting conditions.
Compared with the prior art, the invention has the following advantages:
1. the method is not widely used for researching port safety, but a research object is set as port risk operation facilities, and the method has strong popularization and can be suitable for risk assessment tasks of different port high-risk facilities;
2. the invention starts from four aspects of human-machine-ring-pipe, analyzes the fusion relation among four factors, combines with the actual situation of a port, and constructs the system comprising 4 first-level evaluation indexes U i And 33 secondary evaluation indexes U ik The port high-risk facility operation safety risk early warning index system with a large number of considered risk factorsWide range and deep level;
3. according to the invention, an expert scoring method and an analytic hierarchy process are adopted to establish a factor weight set, and a qualitative and quantitative method is combined, so that subjectivity is considered, objectivity of research object evaluation is improved, and calculation errors of index weights can be effectively reduced;
4. the evaluation method provided by the invention absorbs the advantages of an expert scoring method, a hierarchical analysis method and a fuzzy comprehensive evaluation method, reasonably combines the three methods for application, effectively avoids the ambiguity and the randomness of the safety risk evaluation process, improves the accuracy of the evaluation result and has a certain practical application value.
5. According to the method of the invention, the second-level evaluation index U can be obtained ik Evaluation score and grade of (a), first-level evaluation index U i The evaluation score and grade of the second-order fuzzy comprehensive evaluation. The overall situation of the operation safety of the port high-risk facility can be mastered through the secondary fuzzy comprehensive evaluation result, the index with lower safety in the operation process of the port high-risk facility can be known through the evaluation results of the primary evaluation index and the secondary evaluation index, the problem can be found out in time, the reason is analyzed, and reasonable improvement measures are provided for the worse index. Helps prevent and control harbour facility accidents that may occur.
Drawings
FIG. 1 is a diagram of a system for early warning indicators of operational security risk of a port high risk facility according to the present invention;
fig. 2 is a flowchart of a harbor facility operation security risk evaluation method based on fuzzy comprehensive evaluation.
Detailed Description
The invention is further described below with reference to the accompanying drawings.
According to the structural diagram shown in fig. 1, a harbor high risk facility operation security risk early warning index system table (example) can be obtained. As shown in the table below.
Table 1: port high-risk facility operation security risk early warning index system table
From table 1, a set of influencing factors can be obtained:
U＝{U 1 ,U 2 ,U 3 ,U 4 u, where 1 ＝{U 11 ,U 12 ,U 13 ,U 14 ,U 15 ,U 16 ,U 17 ,U 18 }；
U 2 ＝{U 21 ,U 22 ,U 23 ,U 24 ,U 25 ,U 26 ,U 27 ,U 28 ,U 29 ,U 210 }；
U 3 ＝{U 31 ,U 32 ,U 33 ,U 34 ,U 35 ,U 36 ,U 37 ,U 38 ,U 39 }；
U 4 ＝{U 41 ,U 42 ,U 43 ,U 44 ,U 45 ,U 46 }。
The invention adopts the Liket five-level scale to divide the security risk level of the second-level evaluation index into 5 levels. Obtaining a risk judgment set:
V＝{V 1 ,V 2 ,V 3 ,V 4 ,V 5 }
wherein V is 1 The risk is the first-level risk, the safety condition is better, and the danger is basically avoided; v (V) 2 For the secondary risk, the safety condition is good, but the safety check should be carried out regularly; v (V) 3 As a three-level risk, representing that the safety condition is general, improvement measures should be taken; v (V) 4 For the fourth-level risk, the safety condition is poor, and safety measures are needed to be immediately taken; v (V) 5 The safety condition is poor, and accident injury can be caused. The evaluation sections of the five evaluation levels were set as: v (V) 1 ＝[0.8,1]，V 2 ＝[0.6,0.8]，V 3 ＝[0.4,0.6]，V 4 ＝[0.2,0.4]，V 5 ＝[0,0.2]。
In the case of performing the comprehensive evaluation, the median value of each evaluation section is selected as the parameter of each grade. Then evaluate the set of scales:
E＝{E 1 ,E 2 ,E 3 ,E 4 ,E 5 }＝{0.9,0.7,0.5,0.3,0.1}
determining the index weight requires scoring by a panel of experts first and then specific calculation using analytic hierarchy process. Referring to the relevant literature, weight values for empirical references are given as examples, as shown in table 1.
The factor weight sets of the respective primary and secondary evaluation indexes are as follows:
A＝{A 1 ,A 2 ,A 3 ,A 4 ,A 5 }＝{0.49,0.17,0.21,0.13}；
a 1 ＝{a 11 ,a 12 ,a 13 ,a 14 ,a 15 ,a 16 ,a 17 ,a 18 }＝
{0.05,0.10,0.18,0.20,0.10,0.15,0.12,0.10}；
a 2 ＝{a 21 ,a 22 ,a 23 ,a 24 ,a 25 ,a 26 ,a 27 ,a 28 ,a 29 ,a 210 }＝{0.11,0.11,0.10,0.10,0.07,0.09,0.11,0.14,0.12,0.05}；
a 3 ＝{a 31 ,a 32 ,a 33 ,a 34 ,a 35 ,a 36 ,a 37 ,a 38 ,a 39 }＝{0.09,0.22,0.08,0.10,0.14,0.11,0.11,0.10,0.05}；
a 4 ＝{a 41 ,a 42 ,a 43 ,a 44 ,a 45 ,a 46 }＝{0.13,0.20,0.26,0.19,0.08,0.14}。
according to the flow shown in fig. 2, the secondary evaluation index is subjected to fuzzy evaluation according to the weight factor set of the secondary evaluation index. Establishing a membership matrix R i First-order fuzzy relation evaluation matrix R I ＝(R 1 ,R 2 ,R 3 ,R 4 ) And thus table 2 can be obtained. At the second levelPrice index evaluation matrix R i In (1), element rr thereof kj ＝h kj And/h. Wherein h represents the number of experts participating in the evaluation, h kj Representing the second level evaluation index U ik Make E th j Expert numbers on the scale of evaluation.
Table 2: fuzzy relation of secondary evaluation index
From table 2, a second-level evaluation index evaluation matrix can be obtained:
wherein R is 1 ，R 2 ，R 3 ，R 4 Respectively U 1 ，U 2 ，U 3 ，U 4 Is a one-factor evaluation matrix of (a).
And respectively carrying out first-level fuzzy comprehensive evaluation on the divided multiple evaluation indexes. First-level evaluation index U i The fuzzy comprehensive evaluation vector of (1) is:
the fuzzy comprehensive evaluation vectors of personnel factors, equipment factors, management factors and environmental factors are obtained as follows:
B 1 ＝(0.2690，0.5125，0.1960，0.0400，0.0075)；
B 2 ＝(0.4770，0.4220，0.0840，0.0170，0)；
B 3 ＝(0.3870，0.4520，0.0940，0.0480，0.0190)；
B 4 ＝(0.2030，0.4140，0.2300，0.1250，0.0280)。
then U i Is determined by the evaluation results of (1):
similarly, for each second-level evaluation index in each first-level evaluation index, the evaluation result is as follows:
the primary fuzzy comprehensive evaluation results of the primary evaluation index and the secondary evaluation index are shown in the following table:
table 3: first-order fuzzy comprehensive evaluation result of first-order evaluation index and second-order evaluation index
As can be seen from Table 3, personnel factor V 1 = 0.7116, rated as secondary risk; factor V of the apparatus 2 ＝0.7718>0.75, rated as secondary risk (preference); management factor V 3 =0.7280, rated as secondary risk; environmental factor V 4 ＝0.6278<0.65, price as secondary risk(deviation).
The first-level fuzzy comprehensive evaluation is only to integrate each second-level evaluation index in each first-level evaluation index, and the comprehensive influence of each first-level evaluation index is also required to be considered, namely, the second-level fuzzy comprehensive evaluation is carried out. The evaluation matrix is the fuzzy comprehensive evaluation vector B of personnel, equipment, management and environmental factors obtained in the first-level evaluation 1 ,B 2 ,B 3 ,B 4 The matrix is formed, namely a secondary fuzzy relation evaluation matrix R II ＝[B 1 ,B 2 ,B 3 ,B 4 ] T 。
The second-level fuzzy comprehensive evaluation set B is:
the result V of the second-level fuzzy comprehensive evaluation (port high-risk facility operation safety risk evaluation) can be obtained through calculation as follows:
from the total evaluation result, the operation safety of the port high-risk facility is secondary risk, which indicates that the port high-risk facility has a certain problem in safety management, and related regulations are required to be further improved and perfected.
The present invention is not limited to the present embodiment, and any equivalent concept or modification within the technical scope of the present invention is listed as the protection scope of the present invention.
Claims (2)
1. A harbor facility operation security risk evaluation method based on fuzzy comprehensive evaluation is characterized in that: the method comprises the following steps:
step 1: establishing a set of influencing factors
Determining an influence factor set U of the judging object, namely an evaluation index system; assume that the influence factor set U is expressed by:
U＝{U 1 ,U 2 ,...,U n }
in U 1 ,U 2 ,…,U n Representing different influence factor subsets and being a first-level evaluation index; n represents the number of first-level evaluation indexes; the subelement of the first-level evaluation index is called a second-level evaluation index;
step 2: establishing risk judgment set
The risk judgment set V is a total set composed of elements of various judgment results made by a judge on a judgment object, and is expressed as follows:
V＝{V 1 ,V 2 ,...,V m }
wherein V is 1 ,V 2 ,…,V m Representing various judgment results, m representing the number of the judgment results;
step 3: establishing a factor weight set
To reflect the importance degree of each first-level evaluation index, each first-level evaluation index U i Giving corresponding weight A i I=1, 2, …, n, calculated as follows:
an h expert is arranged to score the ith first-level evaluation index, and the score is marked as d ih And meet the followingFor each U i The weight of the ith grade evaluation index is obtained by calculating the average value of scoring values of all experts on the ith grade evaluation index; after the weights of all the first-level evaluation indexes are completed, a set formed by the weights is called a factor weight set, and is marked as:
A＝(A 1 ,A 2 ,…,A n ) Wherein
The second-level evaluation index weight is determined according to the method for determining the same first-level evaluation index weight, and the specific method is as follows:
setting n under the ith first-level evaluation index by h-bit expert i Scoring the two secondary evaluation indexes, and marking the result as d ikh ，k＝1,2,…,n i ，n i Representing the number of the second-level evaluation indexes contained in the ith first-level evaluation index, and obtaining an expert pair U i Scoring matrix D of lower secondary evaluation index i ：
Wherein matrix D i Each column represents the scoring value of one expert on each secondary evaluation index of the ith primary evaluation index, and meets the following requirementsEach row represents the scoring value of h-bit expert on the same two-level evaluation index, and the weight of the two-level evaluation index is obtained by averaging each row and is marked as +.>
After scoring of each secondary evaluation index under all the primary evaluation indexes is completed, the weight of each secondary evaluation index under each primary evaluation index is obtained according to the calculation steps and is recorded as:
wherein->
Step 4: performing fuzzy comprehensive evaluation
The method adopts multi-factor fuzzy comprehensive evaluation and comprises the following specific steps:
step 4-1: is provided withI.e. first-level evaluation index U i Contains n i A second-level evaluation index; and the following conditions are satisfied:
step 4-2: performing first-level fuzzy comprehensive evaluation
Set a first level evaluation index U i For risk determination set v= { V 1 ,V 2 ,…,V m Membership degree of R i ，R i Is to U i Of the element rr kj Is V (V) j J=1, 2 … m; thereby obtaining a first-order fuzzy relation evaluation matrix R I The following are provided:
wherein->
For each ofN below i The second-level evaluation indexes are evaluated according to a first-level fuzzy comprehensive evaluation model to obtain a first-level fuzzy comprehensive evaluation set:
B i ＝a i ×R i
step 4-3: performing secondary fuzzy comprehensive evaluation
Set a two-level fuzzy relation evaluation matrix R of an influence factor set U II The method comprises the following steps:
when factor weight set A and secondary fuzzy relation evaluation matrix R II After the determination, a secondary fuzzy comprehensive evaluation set B is obtained, and the calculation is as follows:
step 5: processing the evaluation results
Obtaining a comprehensive evaluation result b 1 ,b 2 ,…,b m Then, in order to obtain a determined security risk evaluation level, the fuzzy comprehensive evaluation set b= [ B ] is subjected to the following level parameter method 1 ,b 2 ,…,b m ]Performing accuracy;
according to the risk judgment set V= { V 1 ,V 2 ,…,V m Dividing an evaluation interval for each grade, and then establishing a corresponding evaluation scale set:
E＝{E 1 ,E 2 ,…,E m }
then the second level evaluation index U ik The rank calculation formula of (2) is:
first-level evaluation index U i The rank calculation formula of (2) is:
the grade calculation formula of the second-grade fuzzy comprehensive evaluation is as follows:
2. the port facility operation security risk evaluation method based on fuzzy comprehensive evaluation according to claim 1, wherein the port facility operation security risk evaluation method is characterized in that: the first-level evaluation index comprises personnel factors, equipment factors, management factors and environmental factors; the personnel factors comprise 8 secondary evaluation indexes including site safety ratio, safety training condition accepted by staff, working capacity of command and management staff, technical level and working capacity of operation staff, evidence holding condition of operation staff, operation labor intensity, unsafe behavior of operation staff and investment of safety protection tools and facilities; the equipment factors comprise 10 secondary evaluation indexes including the safety condition of a main device of a metal structure, the safety condition of parts and accessories, the safety condition of a lubricating vehicle, the safety condition of an electric instrument, the safety protection design of operation facilities, the working reliability of the safety device of the operation facilities, the service duration of the facilities, the operation difficulty and automation degree of the facilities, the maintenance qualification rate of mechanical equipment and the disease operation rate of the facilities; the management factors comprise 9 secondary evaluation indexes including organization mechanism soundness degree, safety management system and standard complete condition, safety management professional ratio, production operation complexity degree, emergency measure formulation and implementation condition, quality management system authentication condition, major hazard source identification and accident management, safety technical measure formulation and implementation condition and operation facility safety inspection acceptance table utilization condition; the environment factors comprise 6 secondary evaluation indexes including external ship and train influences, regional social environment influences, climate, hydrogeology, natural environment influences, natural disaster influences, living and accommodation conditions of port workers and operation lighting conditions.
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