CN112926861A - Storage tank safety performance evaluation method - Google Patents

Storage tank safety performance evaluation method Download PDF

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CN112926861A
CN112926861A CN202110237613.7A CN202110237613A CN112926861A CN 112926861 A CN112926861 A CN 112926861A CN 202110237613 A CN202110237613 A CN 202110237613A CN 112926861 A CN112926861 A CN 112926861A
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田红岩
山程
白健
李宁
孙秀敏
刘佰承
高旭
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Tianjin Zhonghang Yida Technology Co ltd
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Abstract

The invention provides a storage tank safety performance evaluation method, which comprises the following steps of S1: selecting index parameters and constructing a storage tank state judgment model; s2: dividing basic events, and establishing an evaluation rule according to the importance degree sequence of the basic events; s3: determining index combination weight; s4: obtaining the evaluation grade result of the storage tank; s5: and verifying the evaluation grade result. Compared with the traditional fuzzy comprehensive evaluation method, the method has reliability, can be clearly displayed in a graph in a cloud model form, can well reflect the randomness and the fuzziness of risk factors, and is suitable for the evaluation of the risk level of the storage tank.

Description

Storage tank safety performance evaluation method
Technical Field
The invention relates to the technical field of equipment detection, in particular to a storage tank safety performance evaluation method.
Background
The storage tank is an important facility in an oil transportation system, and is mainly used for storing inflammable and explosive media with environmental pollution, and the storage tank materials inevitably have the defects of aging, corrosion and the like along with the prolonging of the service time and the influence of the environmental media, so that the safety degree of the storage tank is reduced, the sudden load resistance is reduced, the value pressure or the liquid level is continuously changed, the leakage of the media is easily caused, and the serious economic loss and the environmental ecological pollution are caused.
In a risk evaluation index system, index weight is the key influencing a risk evaluation result, and reasonable distribution of the weight directly influences the risk evaluation result. In multi-index risk evaluation, index weights are generally evaluated by an expert group consisting of a plurality of experts, and experts and experience and knowledge thereof serving as evaluation subjects have important significance in the whole process of index weighting, index evaluation and risk evaluation. That is, the evaluation level of the expert largely determines the reliability of the evaluation result. Due to the restriction of each expert on the recognition degree of the indexes, the knowledge background of the individual and the like, the evaluation result of the expert has certain subjectivity, and the problem of weight errors is caused by the subjectivity of the expert.
Disclosure of Invention
In view of the above, the present invention provides a method for evaluating safety performance of a storage tank.
In order to solve the technical problems, the invention adopts the technical scheme that: a storage tank safety performance evaluation method comprises the following steps:
s1: selecting index parameters and constructing a storage tank state judgment model;
s2: dividing basic events, and establishing an evaluation rule according to the importance degree sequence of the basic events;
s3: determining index combination weight;
s4: obtaining the evaluation grade result of the storage tank;
s5: and verifying the evaluation grade result.
In the present invention, preferably, establishing the evaluation rule according to the importance ranking specifically includes the following steps:
s21: obtaining a top event expression;
s22: acquiring a minimum cut set according to the top event expression;
s23: according to
Figure BDA0002960485430000021
Obtaining the structural importance of the basic event, and comparing the structural importance, wherein Iφ(i)Structural importance, K, representing the ith elementary eventjDenotes the number of minimal cut sets, njThe representation includes a total number of base events.
In the present invention, preferably, the determining of the index combination weight is performed according to an expert evaluation strategy, and specifically includes the following steps:
s31: acquiring subjective weight of the index;
s32: obtaining objective weight of the index;
s33: acquiring the combination weight of the indexes;
s34: and verifying the combination weight by adopting a hierarchical analysis strategy.
In the present invention, preferably, the hierarchical analysis strategy specifically includes the following steps:
s341: constructing a comparison matrix;
s342: converting the comparison matrix into a fuzzy consistent matrix;
s343: and summing the matrixes according to rows, and normalizing to obtain an index weight set.
In the present invention, preferably, the obtaining of the subjective weight of the index specifically includes the following steps:
s311: setting the confidence level (1-alpha) to 0.95, and obtaining Z according to a standard normal distribution tableα/2＝1.96；
S312: calculating the average value of the abscissa of the cloud drop of the cloud image falling in the rejection region to obtain base points XH and XL of the rejection region;
s313: judging whether the average value satisfies the formula
Figure BDA0002960485430000031
If yes, accepting the evaluation result; otherwise, the evaluation result is not accepted, and the characteristic value is corrected by adopting a Bayesian feedback algorithm.
In the invention, preferably, the bayesian feedback algorithm is used for removing cloud drop points outside the (1-alpha) confidence range and correcting the digital characteristics of the cloud image by using the residual cloud drop points according to a cloud drop correction formula.
In the present invention, preferably, the cloud droplet correction formula is:
Figure BDA0002960485430000032
wherein x isiIndicating the cloud drop point within the confidence range,
Figure BDA0002960485430000033
mean values of cloud points within the confidence range, s is the sample square of the corrected cloud point, ExcExpected value, En, representing modified cloudcEntropy value, He, representing the corrected cloudcRepresenting the entropy of the modified cloud.
In the present invention, preferably, the obtaining the objective weight of the index includes: for m indexes i, k experts give corresponding scores to index values of n evaluated objects, and the evaluation mean value of the k experts to the index i is expressed as XijWherein i is 1,2, …, m, j is 1,2, …, n, andijaccording to the formula
Figure BDA0002960485430000034
Calculating to obtain entropy e of index i after standardizationiAnd its objective weight Wi.
Figure BDA0002960485430000035
In the present invention, preferably, the obtaining of the combination weight of the indicator includes: according to the formula
Figure BDA0002960485430000036
Let omegajTaking the maximum value to determine k1、k2Is selected from the group consisting of1Undetermined combining coefficient, k, representing subjective weight2The pending combining coefficients representing the objective weights,
Figure BDA0002960485430000037
the subjective weight of the index j is represented,
Figure BDA0002960485430000038
representing the objective weight of the index j.
Figure BDA0002960485430000041
Figure BDA0002960485430000042
In the present invention, preferably, the verifying the evaluation level result specifically includes the following steps:
s51: establishing a factor set U and an evaluation set V, wherein U is { U ═ U1，U2，…，Un}，V＝{V1，V2，…，Vm}；
S52: establishing a fuzzy evaluation matrix R;
s53: inputting the weight coefficient A to obtain comprehensive judgment
Figure BDA0002960485430000043
S54: and obtaining the corresponding comprehensive evaluation grade according to the maximum membership rule.
The invention has the advantages and positive effects that: the grade level obtained by the storage tank risk evaluation method based on the cloud theory is consistent with the grade level obtained by calculation of the traditional fuzzy comprehensive evaluation method, compared with the traditional fuzzy comprehensive evaluation method, the method has reliability, the method can be clearly displayed in a graph in a cloud model form, randomness and fuzziness of risk factors can be well reflected, and the method is suitable for storage tank risk grade evaluation.
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The accompanying drawings, which are included to provide a further understanding of the invention and are incorporated in and constitute a part of this specification, illustrate embodiments of the invention and together with the description serve to explain the principles of the invention and not to limit the invention. In the drawings:
FIG. 1 is a schematic flow chart of a method for evaluating the safety performance of a storage tank according to the present invention;
FIG. 2 is a schematic diagram of the steps of establishing evaluation rules according to the importance ranking in the storage tank safety performance evaluation method of the present invention;
FIG. 3 is a schematic diagram of the step of determining the combined weights of the indicators in the method for evaluating the safety performance of the storage tank according to the present invention;
FIG. 4 is a schematic diagram of the steps of the hierarchical analysis strategy of the tank safety performance evaluation method according to the present invention;
FIG. 5 is a schematic diagram of subjective weighting steps for obtaining indicators in the method for evaluating the safety performance of a storage tank according to the present invention;
fig. 6 is a schematic diagram of the verification step of the evaluation grade result of the tank safety performance evaluation method according to the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
It will be understood that when an element is referred to as being "secured to" another element, it can be directly on the other element or intervening elements may also be present. When a component is referred to as being "connected" to another component, it can be directly connected to the other component or intervening components may also be present. When a component is referred to as being "disposed on" another component, it can be directly on the other component or intervening components may also be present. The terms "vertical," "horizontal," "left," "right," and the like as used herein are for illustrative purposes only.
Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs. The terminology used in the description of the invention herein is for the purpose of describing particular embodiments only and is not intended to be limiting of the invention. As used herein, the term "and/or" includes any and all combinations of one or more of the associated listed items.
As shown in FIG. 1, the invention provides a method for evaluating the safety performance of a storage tank, which comprises the following steps:
s1: selecting index parameters and constructing a storage tank state judgment model;
s2: dividing basic events, and establishing an evaluation rule according to the importance degree sequence of the basic events;
s3: determining index combination weight;
s4: obtaining the evaluation grade result of the storage tank;
s5: and verifying the evaluation grade result.
Index parameters are meant to include the expectation ExEntropy EnAnd super entropy HeThree numerical characteristics inside, expectation ExEntropy E, the value representing a qualitative concept as the central value of the concept in the discourse domainnThe measure of the ambiguity of the qualitative concept reflects the value range and the margin which can be accepted by the qualitative concept in the domain of discourse, namely, the larger the entropy, the larger the value range accepted by the concept is, the more fuzzy the corresponding concept is; hyper entropy HeThe uncertainty of the entropy is represented, the dispersion degree of the cloud droplets is reflected, the larger the super entropy is, the larger the dispersion degree of the cloud droplets is, and the larger the randomness of the membership degree is. For a domain of discourse U ═ x }, C is the linguistic value associated with U, the element x in U is a random number with a tendency to stabilize with respect to the degree of membership μ (x) of the qualitative concept represented by C, and μ (x) has a value in the range of [, [ 2 ], [ deg. ]0，1]The cloud is from domain U to interval [0, 1 ]]I.e.:
Figure BDA0002960485430000061
the distribution of membership degrees on a domain of discourse is cloud, corresponding x is cloud drops, the cloud drops are used as quantitative representation of qualitative concepts, uncertainty description between the qualitative concepts and the quantitative values is disclosed, the cloud drops are random values, and the more the cloud drops, the higher the accuracy of the overall characteristics of the qualitative concepts is.
When determining the expectation ExEntropy EnAnd super entropy HeAnd the number of cloud droplets, the above parameters are input to a cloud generator, which generates a corresponding number of cloud droplets according to an inference rule in the form of if a, then B, where A, B is a linguistic value representation such as: if the "tank is corroded seriously", the "possibility of tank failure" is high.
As shown in fig. 2, in this embodiment, further, establishing an evaluation rule according to the importance ranking specifically includes the following steps:
s21: obtaining a top event expression;
s22: acquiring a minimum cut set according to the top event expression;
s23: according to
Figure BDA0002960485430000062
Obtaining the structural importance of the basic event, and comparing the structural importance, wherein Iφ(i)Structural importance, K, representing the ith elementary eventjDenotes the number of minimal cut sets, njThe representation includes a total number of base events. The structural importance is used for reflecting the degree of influence of a certain basic event on the top event, and the greater the number of times of the certain basic event appearing in different minimal cut sets means that the structural importance is greater, and if the certain basic event appears in a first-order minimal cut set, the structural importance of the basic event is 1. In the invention, a storage tank failure is taken as a top event, a storage tank failure tree is established, a cut set refers to a set of basic events for triggering the top event, and a minimum cut set refers to a cut set in which if any element does not occur, the minimum cut set refers to the condition that the element does not occurThe top event will not occur, thus resulting in a minimal cut set according to the top event expression. The factors causing the failure of the storage tank are obtained by analyzing the minimum cut set and the structural importance degree and comprise corrosion factors, equipment hardware factors and artificial uncontrollable factors.
As shown in fig. 3, in this embodiment, further, the determining the index combination weight according to an expert evaluation strategy specifically includes the following steps:
s31: acquiring subjective weight of the index;
s32: obtaining objective weight of the index;
s33: acquiring the combination weight of the indexes;
s34: and verifying the combination weight by adopting a hierarchical analysis strategy.
As shown in fig. 4, in this embodiment, further, the hierarchical analysis policy specifically includes the following steps:
s341: constructing a comparison matrix;
s342: converting the comparison matrix into a fuzzy consistent matrix;
s343: and summing the matrixes according to rows, and normalizing to obtain an index weight set.
As shown in fig. 5, in this embodiment, further, because the opinions of the experts have subjective factors and the judgments among the experts have differences, and the degree of dispersion of some cloud droplets is large, which causes a problem of large deviation in actual evaluation, the invention adopts the bayesian feedback algorithm to correct the feature value of the cloud droplet. Not accepting the evaluation result means that the evaluation result is too discrete, and the characteristic value of the cloud droplet needs to be corrected. The subjective weight of the obtained index specifically comprises the following steps:
s311: setting the confidence level (1-alpha) to 0.95, and obtaining Z according to a standard normal distribution tableα/2＝1.96，Zα/2The standard normally distributed bilateral quantiles are shown;
s312: calculating the average value of the abscissa of the cloud drop of the cloud image falling in the rejection region to obtain base points XH and XL of the rejection region;
s313: judging whether the average value satisfies the formula
Figure BDA0002960485430000081
If yes, accepting the evaluation result; otherwise, the evaluation result is not accepted, and the characteristic value is corrected by adopting a Bayesian feedback algorithm. For a certain notion of cognitive confidence (1- α), the cloud droplets obey a normal distribution N (E)x，En 2+He 2) According to the central limit theorem
Figure BDA0002960485430000082
It can be known that when
Figure BDA0002960485430000083
In time, the cooperative awareness of the uncertain concept can reach (1- α). When alpha is close to 0, x falls within the interval range
Figure BDA0002960485430000084
Out of small probability events, get satisfied
Figure BDA0002960485430000085
And
Figure BDA0002960485430000086
mean value of cloud droplet under conditions
Figure BDA0002960485430000087
And
Figure BDA0002960485430000088
as a base point for the concept rejection domain.
In this embodiment, further, the bayesian feedback algorithm removes cloud drops outside the (1- α) confidence range, and corrects the digital features of the cloud image according to the cloud drop correction formula with respect to the remaining cloud drops.
In this embodiment, further, the cloud droplet correction formula is:
Figure BDA0002960485430000089
wherein x isiIndicating a confidence rangeThe cloud point of the inner part of the water tank,
Figure BDA0002960485430000091
mean values of cloud points within the confidence range, s is the sample square of the corrected cloud point, ExcExpected value, En, representing modified cloudcEntropy value, He, representing the corrected cloudcRepresenting the entropy of the modified cloud.
In this embodiment, further, the obtaining the objective weight of the index includes the following steps: for m indexes i, k experts give corresponding scores to index values of n evaluated objects, and the evaluation mean value of the k experts to the index i is expressed as XijWherein i is 1,2, …, m, j is 1,2, …, n, andijaccording to the formula
Figure BDA0002960485430000092
Calculating to obtain entropy e of index i after standardizationiAnd its objective weight Wi.
Figure BDA0002960485430000093
In this embodiment, further, the obtaining of the combination weight of the index includes: according to the formula
Figure BDA0002960485430000094
Let omegajTaking the maximum value to determine k1、k2Is selected from the group consisting of1Undetermined combining coefficient, k, representing subjective weight2The pending combining coefficients representing the objective weights,
Figure BDA0002960485430000095
the subjective weight of the index j is represented,
Figure BDA0002960485430000096
expressing the objective weight of the index j, and obtaining k by applying Lagrange conditional extremum calculation1And k2Numerical values. The subjective weight obtained by the subjective weight determination method is a weight cloud, so that the user can be associated with the weight cloudAnd during the observation and weight combination, computing according to a cloud and an accurate numerical value computing method, normalizing the expectation of the weight cloud according to the level of the index, wherein the final index weight result after the weight combination is in a weight cloud form.
Figure BDA0002960485430000097
Figure BDA0002960485430000098
As shown in fig. 6, in this embodiment, further, the verifying the evaluation level result specifically includes the following steps:
s51: establishing a factor set U and an evaluation set V, wherein U is { U ═ U1，U2，…，Un}，V＝{V1，V2，…，Vm}；
S52: establishing a fuzzy evaluation matrix R;
s53: inputting the weight coefficient A to obtain comprehensive judgment
Figure BDA0002960485430000101
S54: and obtaining the corresponding comprehensive evaluation grade according to the maximum membership rule.
Determining a basic event triggering the failure of the storage tank as a corrosion factor U according to the storage tank failure tree analysis1Hardware factor U of equipment2And artificial uncontrollable factors U3Obtaining a factor set U ═ U1，u2，u3And determining the evaluation set as a comment set V ═ V1，V2，V3，V4，V5The evaluation grades are respectively light, general, severe and severe risk evaluation grades, respectively correspond to comprehensive evaluation grades of I grade, II grade, III grade, IV grade and V grade, and the risk evaluation grade is obtained according to the comprehensive evaluation grades, wherein U is1Belonging to class III, U2Belonging to class III, U3Belong toAnd II, level II. The grade level obtained by the storage tank risk evaluation method based on the cloud theory is consistent with the grade level obtained by calculation of the traditional fuzzy comprehensive evaluation method, compared with the traditional fuzzy comprehensive evaluation method, the method has reliability, the method can be clearly displayed in a graph in a cloud model form, randomness and fuzziness of risk factors can be well reflected, and the method is suitable for storage tank risk grade evaluation, so that a reliability basis is provided for storage tank risk evaluation.
The embodiments of the present invention have been described in detail, but the description is only for the preferred embodiments of the present invention and should not be construed as limiting the scope of the present invention. All equivalent changes and modifications made within the scope of the present invention should be covered by the present patent.

Claims (10)

1. The method for evaluating the safety performance of the storage tank is characterized by comprising the following steps of:
s1: selecting index parameters and constructing a storage tank state judgment model;
s2: dividing basic events, and establishing an evaluation rule according to the importance degree sequence of the basic events;
s3: determining index combination weight;
s4: obtaining the evaluation grade result of the storage tank;
s5: and verifying the evaluation grade result.
2. The storage tank safety performance evaluation method according to claim 1, wherein establishing the evaluation rule according to the importance ranking specifically comprises the following steps:
s21: obtaining a top event expression;
s22: acquiring a minimum cut set according to the top event expression;
s23: according to
Figure FDA0002960485420000011
Obtaining the structural importance of the basic event, and comparing the structural importance, wherein Iφ(i)Represents the ith basic eventStructural importance of, KjDenotes the number of minimal cut sets, njThe representation includes a total number of base events.
3. The method for evaluating the safety performance of the storage tank according to claim 1, wherein the determining of the combined weight of the indexes is performed according to an expert evaluation strategy, and the method specifically comprises the following steps:
s31: acquiring subjective weight of the index;
s32: obtaining objective weight of the index;
s33: acquiring the combination weight of the indexes;
s34: and verifying the combination weight by adopting a hierarchical analysis strategy.
4. The tank safety performance evaluation method according to claim 3, wherein the hierarchical analysis strategy specifically comprises the following steps:
s341: constructing a comparison matrix;
s342: converting the comparison matrix into a fuzzy consistent matrix;
s343: and summing the matrixes according to rows, and normalizing to obtain an index weight set.
5. The method for evaluating the safety performance of the storage tank according to claim 3, wherein the obtaining of the subjective weight of the index specifically comprises the following steps:
s311: setting the confidence level (1-alpha) to 0.95, and obtaining Z according to a standard normal distribution tableα/2＝1.96；
S312: calculating the average value of the abscissa of the cloud drop of the cloud image falling in the rejection region to obtain base points XH and XL of the rejection region;
s313: judging whether the average value satisfies the formula
Figure FDA0002960485420000021
If yes, accepting the evaluation result; otherwise, the evaluation result is not accepted, and the characteristic value is corrected by adopting a Bayesian feedback algorithm.
6. The method for evaluating the safety performance of the storage tank according to claim 5, wherein the Bayesian feedback algorithm is used for removing cloud drop points outside the (1-alpha) confidence range and correcting the digital characteristics of the cloud image according to a cloud drop correction formula by using the residual cloud drop points.
7. The tank safety performance evaluation method according to claim 6, wherein the cloud drop correction formula is as follows:
Figure FDA0002960485420000022
wherein x isiIndicating the cloud drop point within the confidence range,
Figure FDA0002960485420000023
mean values of cloud points within the confidence range, s is the sample square of the corrected cloud point, ExcExpected value, En, representing modified cloudcEntropy value, He, representing the corrected cloudcRepresenting the entropy of the modified cloud.
8. The tank safety performance evaluation method according to claim 3, wherein the obtaining of the objective weight of the indicator comprises the following steps: for m indexes i, k experts give corresponding scores to index values of n evaluated objects, and the evaluation mean value of the k experts to the index i is expressed as XijWherein i is 1,2, …, m, j is 1,2, …, n, andijaccording to the formula
Figure FDA0002960485420000024
Calculating to obtain entropy e of index i after standardizationiAnd its objective weight Wi.
9. The method according to claim 3, wherein the step of obtaining the combined weight of the indicators comprises the steps of: according to the formula
Figure FDA0002960485420000025
j is 1,2, …, m, let ωjTaking the maximum value to determine k1、k2Is selected from the group consisting of1Undetermined combining coefficient, k, representing subjective weight2The pending combining coefficients representing the objective weights,
Figure FDA0002960485420000031
the subjective weight of the index j is represented,
Figure FDA0002960485420000032
representing the objective weight of the index j.
10. The method for evaluating the safety performance of the storage tank according to claim 1, wherein the step of verifying the evaluation grade result specifically comprises the following steps:
s51: establishing a factor set U and an evaluation set V, wherein U is { U ═ U1，U2，…，Un}，V＝{V1，V2，…，Vm}；
S52: establishing a fuzzy evaluation matrix R;
s53: inputting the weight coefficient A to obtain comprehensive judgment
Figure FDA0002960485420000033
S54: and obtaining the corresponding comprehensive evaluation grade according to the maximum membership rule.
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CN117870775A (en) * 2024-03-11 2024-04-12 山东港源管道物流有限公司 Storage tank detection system and method based on intelligent oil depot

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