CN112907122A - Natural gas filling station safety evaluation model and evaluation method - Google Patents
Natural gas filling station safety evaluation model and evaluation method Download PDFInfo
- Publication number
- CN112907122A CN112907122A CN202110300344.4A CN202110300344A CN112907122A CN 112907122 A CN112907122 A CN 112907122A CN 202110300344 A CN202110300344 A CN 202110300344A CN 112907122 A CN112907122 A CN 112907122A
- Authority
- CN
- China
- Prior art keywords
- station
- safety
- evaluation
- fault tree
- weight
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Withdrawn
Links
- 238000011156 evaluation Methods 0.000 title claims abstract description 56
- VNWKTOKETHGBQD-UHFFFAOYSA-N methane Chemical compound C VNWKTOKETHGBQD-UHFFFAOYSA-N 0.000 title claims abstract description 38
- 238000013210 evaluation model Methods 0.000 title claims abstract description 19
- 239000003345 natural gas Substances 0.000 title claims abstract description 19
- 239000007789 gas Substances 0.000 claims abstract description 52
- 238000000034 method Methods 0.000 claims abstract description 40
- 238000013461 design Methods 0.000 claims abstract description 6
- 238000011835 investigation Methods 0.000 claims abstract description 5
- 239000011159 matrix material Substances 0.000 claims description 27
- 230000002087 whitening effect Effects 0.000 claims description 15
- 230000007613 environmental effect Effects 0.000 claims description 12
- 238000012935 Averaging Methods 0.000 claims description 3
- 239000003949 liquefied natural gas Substances 0.000 abstract description 44
- 238000012423 maintenance Methods 0.000 description 9
- 238000004364 calculation method Methods 0.000 description 7
- 238000004458 analytical method Methods 0.000 description 5
- 238000007689 inspection Methods 0.000 description 5
- 238000009434 installation Methods 0.000 description 3
- 239000013598 vector Substances 0.000 description 3
- 238000005553 drilling Methods 0.000 description 2
- 238000004519 manufacturing process Methods 0.000 description 2
- 238000011160 research Methods 0.000 description 2
- 230000006399 behavior Effects 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 230000007797 corrosion Effects 0.000 description 1
- 238000005260 corrosion Methods 0.000 description 1
- 230000007547 defect Effects 0.000 description 1
- 238000001514 detection method Methods 0.000 description 1
- 238000011161 development Methods 0.000 description 1
- 239000006185 dispersion Substances 0.000 description 1
- 230000000694 effects Effects 0.000 description 1
- 238000012854 evaluation process Methods 0.000 description 1
- 238000012544 monitoring process Methods 0.000 description 1
- 238000010606 normalization Methods 0.000 description 1
- 230000000737 periodic effect Effects 0.000 description 1
- 238000007789 sealing Methods 0.000 description 1
- 239000000126 substance Substances 0.000 description 1
- 238000012549 training Methods 0.000 description 1
Images
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
- G06Q10/067—Enterprise or organisation modelling
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
- G06Q10/063—Operations research, analysis or management
- G06Q10/0635—Risk analysis of enterprise or organisation activities
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
- G06Q10/063—Operations research, analysis or management
- G06Q10/0639—Performance analysis of employees; Performance analysis of enterprise or organisation operations
- G06Q10/06393—Score-carding, benchmarking or key performance indicator [KPI] analysis
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q50/00—Information and communication technology [ICT] specially adapted for implementation of business processes of specific business sectors, e.g. utilities or tourism
- G06Q50/06—Energy or water supply
Landscapes
- Business, Economics & Management (AREA)
- Human Resources & Organizations (AREA)
- Engineering & Computer Science (AREA)
- Strategic Management (AREA)
- Economics (AREA)
- Entrepreneurship & Innovation (AREA)
- General Physics & Mathematics (AREA)
- General Business, Economics & Management (AREA)
- Theoretical Computer Science (AREA)
- Marketing (AREA)
- Development Economics (AREA)
- Educational Administration (AREA)
- Tourism & Hospitality (AREA)
- Physics & Mathematics (AREA)
- Quality & Reliability (AREA)
- Operations Research (AREA)
- Game Theory and Decision Science (AREA)
- Health & Medical Sciences (AREA)
- Public Health (AREA)
- Water Supply & Treatment (AREA)
- General Health & Medical Sciences (AREA)
- Primary Health Care (AREA)
- Management, Administration, Business Operations System, And Electronic Commerce (AREA)
Abstract
The invention relates to the technical field of LNG (liquefied natural gas) station safety evaluation, in particular to a natural gas station safety evaluation model and an evaluation method, wherein the evaluation model comprises the following steps: s1, establishing an index system based on a fault tree, S2, determining index weight based on an analytic hierarchy process, and S3, performing safety evaluation on the station based on gray weight-determining clustering; and the evaluation method comprises the following steps: step 1: risk indexes influencing the safety of the LNG filling station are combed and classified through design files, field investigation, daily work experience and the like, and are merged into different levels according to classification results. According to the method, an index system is established based on the fault tree, and the weight and the importance of the influence indexes of the LNG gas station system are calculated by comprehensively using an analytic hierarchy process and a gray clustering process, so that the conclusion of the safety evaluation of the LNG gas station is more scientific, more accurate and more comprehensive, and the technical practicability is strong.
Description
Technical Field
The invention relates to the technical field of LNG (liquefied natural gas) station safety evaluation, in particular to a natural gas station safety evaluation model and an evaluation method.
Background
Compared with a CNG gas station, the LNG gas station is relatively late in development, and LNG automobiles are gradually developed on a large scale all over the country from 2010, so that safety management research on the LNG gas station is not relatively many, and the research period is not long. Because natural gas has the characteristics of flammability and explosiveness, and LNG gas station is towards social service, is essential to LNG gas station's safety evaluation.
At present, the safety evaluation of the LNG gas station mainly adopts one or two of main methods such as a chemical fire index method, a safety check list method, a fault tree analysis method and the like, and is only completed by an evaluator, and then an expert evaluates results. However, as the safety indexes of the LNG gas station are relatively more, the index levels are relatively more, and a plurality of uncertain factors exist in the aspect of safety management, the subjective factor accounts for a relatively large proportion, and from the current practical results, the evaluation method adopting one or two combined methods also has some weak points, for example, the safety index evaluation is not comprehensive, the subjective factor influence of evaluators is relatively large, the weight of the risk factor is not clear, the comprehensive evaluation result cannot be reflected, and the like, so that objective, comprehensive and complete reference basis cannot be provided for the safety management of the LNG gas station.
Therefore, a safety evaluation model and an evaluation method for a natural gas filling station are provided for solving the problems.
Disclosure of Invention
The invention aims to solve the defects in the prior art and provides a safety evaluation model and an evaluation method for a natural gas filling station.
A safety evaluation model of a natural gas filling station comprises the following steps:
s1, establishing an index system based on the fault tree;
s2, determining index weight based on an analytic hierarchy process;
and S3, performing safety evaluation on the station based on the gray weighting cluster.
An evaluation method of a safety evaluation model of a natural gas filling station comprises the following steps:
step 1: risk indexes influencing the safety of the LNG filling station are combed and classified through design files, field investigation, daily work experience and the like, and are merged into different levels according to classification results;
step 2: establishing a hierarchical structure model according to the hierarchy of the step 1, and reflecting the hierarchical relation of each risk element by using a fault tree form;
and step 3: analyzing the risk factors according to the established fault tree index system;
and 4, step 4: according to the knowledge of the structure of the analytic hierarchy process matrix, multiple experts assign values to indexes of all levels of the established fault tree of the standard LNG gas station to construct a gray judgment matrix;
and 5: then, calculating the constructed matrix by adopting a geometric averaging method, and finally obtaining the weight of each layer of index;
step 6: according to the established evaluation indexes and grading standards, grading index elements listed in a fault tree of the LNG gas station by multiple experts according to the grading standards;
and 7: establishing a whitening weight function according to whitening weight function knowledge in a gray weight-determining clustering evaluation method and according to a grading standard and a gray class grade evaluated by an LNG gas station operating system;
and 8: calculating the first-level and second-level index weights of the risk factors by adopting a gray evaluation weight matrix;
and step 9: and assigning 5 ash grades of 'good', 'common', 'poor' and 'poor' respectively, and obtaining the total score of the standard LNG gas station according to the risk factor score result and the occupied weight in the standard LNG gas station system.
Preferably, the fault tree form adopts fault tree symbols.
Preferably, the fault tree symbol comprises a logical and gate, a logical or gate, a basic event, a middle time, a top time, an output event, and an input event.
Preferably, the risk factors include equipment safety, environmental factors inside and outside the station, and personnel and safety management inside the station.
Preferably, the assignment adopts a 1-9 scaling method.
Preferably, the grey class rating is assigned by: "good" is 9, "good" is 7, "general" is 5, "poor" is 3, "poor" is 1.
Compared with the prior art, the invention has the beneficial effects that:
the method is characterized in that an index system is established based on a fault tree, the weight and the importance of the influence indexes of the LNG gas station system are calculated by comprehensively utilizing an analytic hierarchy process and a gray clustering process, the conclusion of the safety evaluation of the LNG gas station is more scientific, more accurate and more comprehensive, meanwhile, the technical practicability is strong, when the safety evaluation is carried out on the LNG gas station, only one complete safety risk index list needs to be combed, a scoring table is designed, then a plurality of experts are invited to assign and score the indexes of the list, and finally the evaluation conclusion is obtained through calculation.
Drawings
FIG. 1 is a hierarchical relationship between risk elements of a safety evaluation model and an evaluation method for a natural gas station according to the present invention;
fig. 2 is a further hierarchical relationship based on fig. 1.
Detailed Description
The present invention will be further illustrated with reference to the following specific examples.
A safety evaluation model of a natural gas filling station comprises the following steps:
s1, establishing an index system based on the fault tree;
s2, determining index weight based on an analytic hierarchy process;
and S3, performing safety evaluation on the station based on the gray weighting cluster.
An evaluation method of a safety evaluation model of a natural gas filling station comprises the following steps:
step 1: risk indexes influencing the safety of the LNG filling station are combed and classified through design files, field investigation, daily work experience and the like, and are merged into different levels according to classification results;
step 2: establishing a hierarchical structure model according to the hierarchy of the step 1, and reflecting the hierarchical relation of each risk element by using a fault tree form;
and step 3: analyzing the risk factors according to the established fault tree index system;
and 4, step 4: according to the knowledge of the structure of the analytic hierarchy process matrix, multiple experts assign values to indexes of all levels of the established fault tree of the standard LNG gas station to construct a gray judgment matrix;
and 5: then, calculating the constructed matrix by adopting a geometric averaging method, and finally obtaining the weight of each layer of index;
step 6: according to the established evaluation indexes and grading standards, grading index elements listed in a fault tree of the LNG gas station by multiple experts according to the grading standards;
and 7: establishing a whitening weight function according to whitening weight function knowledge in a gray weight-determining clustering evaluation method and according to a grading standard and a gray class grade evaluated by an LNG gas station operating system;
and 8: calculating the first-level and second-level index weights of the risk factors by adopting a gray evaluation weight matrix;
and step 9: and assigning 5 ash grades of 'good', 'common', 'poor' and 'poor' respectively, and obtaining the total score of the standard LNG gas station according to the risk factor score result and the occupied weight in the standard LNG gas station system.
Further, the fault tree form adopts fault tree symbols.
Further, the fault tree symbol includes a logical AND gate, a logical OR gate, a base event, a middle time, a top time, an output event, and an input event.
Further, the risk factors include equipment safety, environmental factors inside and outside the station, and personnel and safety management inside the station.
Further, the assignment adopts a 1-9 scale method.
Further, the gray class grade is assigned in the following manner: "good" is 9, "good" is 7, "general" is 5, "poor" is 3, "poor" is 1.
In this example, five experts participated in the following evaluation process:
s1, establishing index system based on fault tree
Before safety evaluation is carried out on the LNG filling station, an index system is established firstly, and the establishment of the index system is in accordance with the existing national laws, regulations and standard. Risk indexes influencing the safety of the LNG filling station are combed and classified through design files, field investigation, daily work experience and the like, and are merged into different levels according to classification results;
then, a hierarchical structure model is established, and the hierarchical relationship of each risk element is reflected by a fault tree formula (see fig. 1 and fig. 2), wherein each parameter in the graph is shown as the following table:
analyzing the risk factors according to the established fault tree index system (see the following table);
(1) safety of equipment
There are 31 basic events under this item, and the minimum cut set number is 29, and almost all events under this item can lead to dangerous incident directly to take place, so need to guarantee the normal operating of equipment, regularly patrol and examine the maintenance, and do well and maintain.
(2) Environmental factors inside and outside the station
There are 6 basic event factors under this term, 2 first order minimal cut sets, so to ensure the gas filling device design and installation are reasonable and maintenance is carried out according to relevant regulations after installation is completed, and to ensure no accident happens in the safety interval.
(3) Personnel and safety management in station
13 basic events exist under the project, wherein 5 first-order minimum cut sets exist, so that attention must be paid to the fact that the condition of personnel in the station is the main body of operation and maintenance of each device, and the quality and the attitude of the personnel are correct or not directly related to the safety in the station, so that the popularization of personnel training and safety knowledge is in place, the personnel are certified and put on duty, and the safety is kept in mind; safety management in the station accounts for 4 first-order minimum cut sets, the safety management is a core system for safe operation of the gas station, all systems of the safety management are required to be executed in place, equipment maintenance and updating are done regularly, safety inspection and fire drilling are carried out regularly, and the safety management is ensured to run through the operation process of the gas station all the time.
| Serial number | Minimal cut set | Serial number | Minimal cut set | Serial number | Minimal cut set |
| 1 | D11 | 13 | D24 | 25 | D43 |
| 2 | D12 | 14 | D25 | 26 | D51 |
| 3 | D13 | 15 | D26 | 27 | D52 |
| 4 | D14 | 16 | D27 | 28 | D53 |
| 5 | D15 | 17 | D31 | 29 | D54 |
| 6 | D16 | 18 | D32 | 30 | D61 |
| 7 | D17 | 19 | D33 | 31 | |
| 8 | D18 | 20 | D34 | 32 | D86 |
| 9 | D19 | 21 | D35 | 33 | D91 |
| 10 | D21 | 22 | D36 | 34 | D92 |
| 11 | D22 | 23 | D37 | 35 | D93 |
| 12 | D23 | 24 | D42 | 36 | D94 |
S2, determining index weight based on analytic hierarchy process
According to the knowledge of the structure of the analytic hierarchy process matrix, 5 experts are requested to assign values to all levels of indexes of the established fault tree of the standard LNG gas station to construct a gray judgment matrix, the values are assigned by a 1-9 scale method (see the following table), then a geometric mean method is adopted to calculate the constructed matrix, and finally the weight of each layer of indexes is obtained;
1 to 9 scale method
| Scale | Means of |
| 1 | Of equal importance in comparison of two elements |
| 3 | Two element ratio, front to back, is slightly more important |
| 5 | Two element ratio, front to back, is of significant importance |
| 7 | Two element ratio, front strongly important to back |
| 9 | Two element ratio, front to back, is extremely important |
| 2，4，6，8 | Two element ratios, a scaling which requires a compromise between the two criteria mentioned above |
| Reciprocal of the | Inverse ratio of two elements with greater importance |
(1) First-level index weight determination hypothesis expert 1 assignment
| A | B1 | B2 | B3 |
| B1 | [1,1] | [4,5] | [2,3] |
| B2 | [1/5,1/4] | [1,1] | [1/3,1/2] |
| B3 | [1/3,1/2] | [2,3] | [1,1] |
Assume expert 2 assignment
| A | B1 | B2 | B3 |
| B1 | [1,1] | [7,8] | [5,6] |
| B2 | [1/8,1/7] | [1,1] | [1/4,1/2] |
| B3 | [1/6,1/5] | [2,4] | [1,1] |
Assume expert 3 assignment
Assume expert 4 assignment
| A | B1 | B2 | B3 |
| B1 | [1,1] | [6,7] | [3,4] |
| B2 | [1/7,1/6] | [1,1] | [1/4,1/3] |
| B3 | [1/4,1/3] | [3,4] | [1,1] |
Assume expert 5 assignment
| A | B1 | B2 | B3 |
| B1 | [1,1] | [6,7] | [4,5] |
| B2 | [1/7,1/6] | [1,1] | [1/3,1] |
| B3 | [1/5,1/4] | [1,3] | [1,1] |
Calculating process (directly outputting calculation results by compiling a calculation program formula): considering practical considerations, the comparison weight of 5 experts is taken as an average number, and the w of each expert is calculated according to the gray judgment matrix calculation methodkThe following is calculated from the matrix obtained above, 0.2:
a 12＝5.50，
a 13＝3.44，
a 23＝0.32，
and constructing a 5-bit expert comprehensive gray judgment matrix according to the calculated result as follows:
five-expert comprehensive grey judgment matrix
Whitening the comprehensive grey judgment matrix, and taking a positioning coefficient rho from practical considerationij0.5 in terms of grayAnd judging a matrix calculation method to obtain the following whitening matrix:
whitening array of five-expert comprehensive gray judgment matrix
| A | B1 | B2 | B3 |
| B1 | 1.00 | 5.99 | 3.93 |
| B2 | 0.16 | 1.00 | 0.44 |
| B3 | 0.25 | 2.25 | 1.00 |
And calculating the weight vector of the whitening array by using a geometric mean method:
multiplying index values of each line of the whitening array to obtain Mi：
M＝[M1，M2，M3]＝[23.5407，0.0704，0.5625]T
② calculating MiRoot of cubic (n times)
③ will
Normalization was performed to obtain W ═ 0.698, 0.101, 0.201]T
Fourthly, calculating the maximum characteristic root to calculate the lambdamax
Obtained (AW)1＝2.093，(AW)2＝0.301，(AW)3＝0.603，
Calculating the consistency index
The consistency ratio CR is 0.0061<0.1, the requirement of consistency is met
Sixthly, determining the first-level index weight of the fault tree of the LNG gas station as W ═ 0.698, 0.101 and 0.201
And calculating the second-stage index weight and the third-stage index weight of the fault tree of the LNG gas station by adopting the same method.
Second level index weight
Three level index weight
S3, safety evaluation is carried out on the station based on gray weight-setting clustering
According to the established rating standards (shown in the table below) of the evaluation indexes of ' good ', ' general ', ' poor ', ' bad ', ' the index elements listed in the fault tree of the LNG gas station are rated by five experts according to the rating standards.
Rating scale
| Between scoring areas | 0～2 | 2～4 | 4～6 | 6～8 | 8～10 |
| Qualitative evaluation | Is very poor | Is poor | In general | Is preferably used | Is very good |
The evaluation scoring of the LNG filling station by five experts is assumed as shown in the following table:
secondary indicator of equipment safety
| Expert 1 | Expert 2 | Expert 3 | Expert 4 | Expert 5 | |
| C1 gas filling system | 7 | 8 | 7 | 9 | 8 |
| C2 unloading pump and booster pump system | 9 | 8 | 9 | 8 | 7 |
| C3 storage system security | 7 | 7 | 8 | 8 | 9 |
| C4 |
8 | 8 | 7 | 7 | 6 |
| C5 pipeline safety | 9 | 8 | 7 | 9 | 8 |
Equipment safety three-level index gas filling system
Three-level index unloading pump and booster pump system for equipment safety
| Expert 1 | Expert 2 | Expert 3 | Expert 4 | Expert 5 | |
| D21 electric explosion-proof | 7 | 7 | 6 | 5 | 6 |
| D22 mechanical vibrator noise | 6 | 7 | 5 | 4 | 5 |
| D23 overrun alarm and stop | 6 | 7 | 8 | 7 | 8 |
| D24 sealing system | 6 | 5 | 6 | 7 | 6 |
| D25 safety valve arrangement | 7 | 7 | 8 | 6 | 8 |
| D26 |
8 | 8 | 6 | 8 | 7 |
| D27 temperature detection device | 6 | 6 | 7 | 8 | 9 |
Equipment safety three-level index storage system safety
Safety of equipment safety three-level index control system
| Expert 1 | Expert 2 | Expert 3 | Expert 4 | Expert 5 | |
| D41 gas filling system control | 6 | 5 | 6 | 5 | 6 |
| D42 arrangement for unloading and pressurizing pump | 6 | 7 | 5 | 4 | 5 |
| D43 storage system control | 6 | 7 | 8 | 7 | 8 |
| D44 lighting and monitoring system control | 6 | 5 | 6 | 7 | 6 |
Equipment safety three-level index pipeline safety
| Expert 1 | Expert 2 | Expert 3 | Expert 4 | Expert 5 | |
| Corrosion of D51 pipeline | 7 | 5 | 6 | 8 | 6 |
| D52 weld quality | 6 | 7 | 6 | 6 | 5 |
| D53 pipeline compensation | 5 | 8 | 8 | 7 | 9 |
| D54 connection reliability | 6 | 5 | 6 | 7 | 6 |
Secondary indexes of influence of environment inside and outside station
| Expert 1 | Expert 2 | Expert 3 | Expert 4 | Expert 5 | |
| C6 in-station environmental impact | 6 | 7 | 6 | 7 | 6 |
| C7 outdoor environmental impact | 6 | 7 | 5 | 4 | 5 |
Three-level index station internal environment influence of station internal and external environment influence
Three-level index station external environment influence of station internal and external environment influence
| Expert 1 | Expert 2 | Expert 3 | Expert 4 | Expert 5 | |
| D71 outdoor installation fire-proof space | 6 | 5 | 6 | 8 | 5 |
| D72 gas cylinder vehicle | 6 | 7 | 5 | 4 | 5 |
Personnel and safety management second-level index in station
| Expert 1 | Expert 2 | Expert 3 | Expert 4 | Expert 5 | |
| C8 personal Condition effects | 6 | 5 | 6 | 5 | 6 |
| C9 Security management | 7 | 6 | 6 | 6 | 8 |
Influence of personnel conditions of three-level index of personnel in station and safety management
| Expert 1 | Expert 2 | Expert 3 | Expert 4 | Expert 5 | |
| Degree of education of |
8 | 8 | 7 | 8 | 8 |
| Average seniority of D82 workers | 6 | 7 | 5 | 5 | 5 |
| D83 worker certified job rate | 9 | 8 | 8 | 9 | 8 |
| Age of education for D84 manager | 6 | 5 | 6 | 7 | 6 |
| D85 average seniority of |
8 | 7 | 7 | 7 | 8 |
| D86 Security awareness | 7 | 5 | 6 | 8 | 7 |
| D87 personal factors | 9 | 8 | 8 | 6 | 6 |
| D88 physical quality | 5 | 7 | 9 | 9 | 9 |
Three-level index safety management of personnel and safety management in station
| Expert 1 | Expert 2 | Expert 3 | Expert 4 | Expert 5 | |
| D91 device management | 7 | 5 | 6 | 8 | 6 |
| D92 fire management | 6 | 7 | 6 | 6 | 5 |
| D93 emergency treatment plan | 5 | 8 | 8 | 7 | 9 |
| D94 periodic inspection of conditions | 6 | 5 | 6 | 7 | 6 |
Calculating process (directly outputting calculation results by compiling a calculation program formula):
(1) establishing a gray-based whitening weight function
The evaluation scoring interval of the LNG gas station operation system is 0-10, corresponding to 5 gray grades of 'good', 'general', 'poor' and 'poor', the higher the score is, the smaller the influence of the index on the event on the top of the fault tree is shown, and according to whitening weight function knowledge in the gray weight-fixed clustering evaluation method, a whitening weight function is established according to the evaluation scoring standard and the gray grade of the LNG gas station operation system evaluation.
Whitening weight function established for the station
(2) Calculating a gray evaluation weight matrix
Firstly, weight calculation is carried out by using a secondary index 'gas filling system (C1)' in a first-layer evaluation index 'equipment safety (B1)' of an LNG gas station operation system, knowledge is calculated according to a gray evaluation weight matrix, and the evaluation value number of an expert is as follows:
rC1＝[0.5429，0.4，0.0571，0，0]
the other secondary index r in "facility safety (B1)" was obtained by the same method as described aboveC1、rC2、rC3、rC4、rC5
rC2＝[0.5879，0.3819，0.0301，0，0]；
rC3＝[0.5429，0.4，0.0571，0，0]；
rC4＝[0.4737，0.4211，0.1053，0，0]；
rC5＝[0.5879，0.3819，0.0301，0，0]。
Combining the secondary index weight vectors of the equipment safety (B1) into a weight matrix, and obtaining a gray evaluation weight matrix of the equipment safety (B1) by 5 experts as follows:
the same method is adopted to calculate the secondary indexes of equipment safety, the primary and secondary indexes of the influence of the environment inside and outside the station, and the primary and secondary index weight results of personnel inside the station and safety management are as follows:
gas filling system (C1):
unloading pump, booster pump system (C2):
storage system security (C3):
control system safety (C4):
pipeline safety (C5):
intra-and-outdoor environmental impact (B2):
secondary indexes of the environment inside and outside the station:
in-station environmental impact (C6):
off-site environmental impact (C7):
in-station personnel and security management (B3):
personnel and safety management secondary indexes in the station:
personnel impact (C8):
security management (C9):
(3) calculating index comprehensive evaluation value
Each gray class level is assigned "good", "general", "poor", "very poor" 5 gray class levels are assigned "good" ═ 9, "good" ═ 7, "general" ═ 5, "poor" ═ 3, "very poor" ═ 1, and a vector C ═ 9, 7, 5, 3, 1 is obtained, then:
1. safety of equipment
(1) Gas filling system
According to the weight of the index, the gas filling system C1The method comprises the following steps:
(2) unloading pump and booster pump system
The same method is adopted to obtain the unloading pump and the booster pump system C2The score was 7.5.
(3) Storage system security C3A score of 7.74
(4) Control system security C4Score 7.29
(5) Safety of the pipeline C5Score 7.37
The total safety of the equipment is as follows:
B1＝7.64×0.302+7.5×0.241+7.74×0.235+7.29×0.101+7.37×0.121＝7.6
2. environmental impact inside and outside a station
(1) Environmental impact in a station C6Score 7.31
(2) Environmental impact outside the station C7Score 7.17
The total influence of the inside and outside environment of the station is as follows:
B2＝7.31×0.598+7.17×0.402＝7.25
3. personnel and safety management in station
(1) Influence of personnel Condition C8A score of 7.9
(2) Security management C9Score 7.44
The general scores of personnel and safety management in the station are as follows:
B3＝7.9×0.492+7.44×0.508＝7.67
4. total score for a standard LNG station
According to the equipment safety, the influence of the environment inside and outside the station, the scoring results of the 3 index factors of personnel and safety management inside the station and the occupied weight in the standard LNG gas station system, the total score of the standard LNG gas station is obtained as follows:
from the results of the above calculation, it can be seen that the device safety holds 0.698 in terms of weight, and it is consistent with the recognition that the device safety is regarded as the primary risk factor in the conventional evaluation method, in our practical work, we also put the device safety at the top and most important of the safety production management work, which is consistent with the results of the fault tree method analysis.
The influence of the environment inside and outside the station, the proportion of personnel inside the station and safety management are relatively small, which are respectively 0.101 and 0.201, and from the past accident case of the LNG gas station, the accident analysis is combined with the safety production accident analysis which occurs in recent years in China, the accidents caused by the influence of the environment inside and outside the station are relatively small, the accidents caused by the problems of personnel and safety management are relatively large, so the weighting result is similar to the practical experience, and the occupation amount of the minimum cut sets in the fault tree analysis is consistent with each other.
According to the result calculated by the gray level method, according to the standard of 10 points, the gas charging system score is 7.64, the unloading pump system score is 7.5, the storage system safety score is 7.74, the control system safety score is 7.29, the pipeline safety score is 7.37, the in-station environment influence score is 7.31, the out-station environment influence score is 7.17, the personnel condition influence score is 7.9, and the safety management score is 7.44. Therefore, the maintenance of the control system in the station is enhanced, the regular inspection and maintenance are carried out, the equipment operation and maintenance are well carried out, and the equipment is ensured to be in a good operation state all the time; in the aspects of the inside and outside environment of the station, the management needs to be enhanced, safety signs and safety facilities in the station need to be updated and maintained in time, traffic dispersion in the station is well done, various safety leads are drawn, safety inspection outside the station needs to be enhanced, and various harmful behaviors outside the station are found and stopped in time; the safety management is a center for the operation and maintenance of the gas station, so that various systems of the safety management are required to be executed in place, equipment maintenance and updating are done regularly, safety inspection and fire drilling are carried out frequently, and the safety management is ensured to run through the operation process of the gas station all the time.
The above description is only for the preferred embodiment of the present invention, but the scope of the present invention is not limited thereto, and any person skilled in the art should be considered to be within the technical scope of the present invention, and the technical solutions and the inventive concepts thereof according to the present invention should be equivalent or changed within the scope of the present invention.
Claims (7)
1. The safety evaluation model of the natural gas filling station is characterized by comprising the following steps:
s1, establishing an index system based on the fault tree;
s2, determining index weight based on an analytic hierarchy process;
and S3, performing safety evaluation on the station based on the gray weighting cluster.
2. The evaluation method of the safety evaluation model of the natural gas filling station is characterized by comprising the following steps of:
step 1: risk indexes influencing the safety of the LNG filling station are combed and classified through design files, field investigation, daily work experience and the like, and are merged into different levels according to classification results;
step 2: establishing a hierarchical structure model according to the hierarchy of the step 1, and reflecting the hierarchical relation of each risk element by using a fault tree form;
and step 3: analyzing the risk factors according to the established fault tree index system;
and 4, step 4: according to the knowledge of the structure of the analytic hierarchy process matrix, multiple experts assign values to indexes of all levels of the established fault tree of the standard LNG gas station to construct a gray judgment matrix;
and 5: then, calculating the constructed matrix by adopting a geometric averaging method, and finally obtaining the weight of each layer of index;
step 6: according to the established evaluation indexes and grading standards, grading index elements listed in a fault tree of the LNG gas station by multiple experts according to the grading standards;
and 7: establishing a whitening weight function according to whitening weight function knowledge in a gray weight-determining clustering evaluation method and according to a grading standard and a gray class grade evaluated by an LNG gas station operating system;
and 8: calculating the first-level and second-level index weights of the risk factors by adopting a gray evaluation weight matrix;
and step 9: and assigning 5 ash grades of 'good', 'common', 'poor' and 'poor' respectively, and obtaining the total score of the standard LNG gas station according to the risk factor score result and the occupied weight in the standard LNG gas station system.
3. The evaluation method of the safety evaluation model of the natural gas filling station according to claim 2, wherein the fault tree form adopts a fault tree symbol.
4. The evaluation method of the safety evaluation model of the natural gas station according to claim 3, wherein the fault tree symbol comprises a logical AND gate, a logical OR gate, a basic event, a middle time, a top time, an output event and an input event.
5. The evaluation method of the safety evaluation model of the natural gas filling station according to claim 2, wherein the risk factors comprise equipment safety, environmental factors inside and outside the station, and personnel and safety management inside the station.
6. The evaluation method of the safety evaluation model of the natural gas filling station according to claim 2, wherein the assignment adopts a 1-9 scaling method.
7. The evaluation method of the safety evaluation model of the natural gas station according to claim 2, wherein the grey scale is assigned in a manner that: "good" =9, "good" =7, "general" =5, "poor" =3, "bad" = 1.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202110300344.4A CN112907122A (en) | 2021-03-22 | 2021-03-22 | Natural gas filling station safety evaluation model and evaluation method |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202110300344.4A CN112907122A (en) | 2021-03-22 | 2021-03-22 | Natural gas filling station safety evaluation model and evaluation method |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN112907122A true CN112907122A (en) | 2021-06-04 |
Family
ID=76106105
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202110300344.4A Withdrawn CN112907122A (en) | 2021-03-22 | 2021-03-22 | Natural gas filling station safety evaluation model and evaluation method |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN112907122A (en) |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN115619292A (en) * | 2022-12-19 | 2023-01-17 | 云账户技术(天津)有限公司 | Method and device for problem management |
| CN118134206A (en) * | 2024-04-30 | 2024-06-04 | 陕西黑石绿能能源科技有限公司 | Safety control method and system for hydrogen adding station |
-
2021
- 2021-03-22 CN CN202110300344.4A patent/CN112907122A/en not_active Withdrawn
Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN115619292A (en) * | 2022-12-19 | 2023-01-17 | 云账户技术(天津)有限公司 | Method and device for problem management |
| CN115619292B (en) * | 2022-12-19 | 2023-03-21 | 云账户技术(天津)有限公司 | Method and device for problem management |
| CN118134206A (en) * | 2024-04-30 | 2024-06-04 | 陕西黑石绿能能源科技有限公司 | Safety control method and system for hydrogen adding station |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN107886235A (en) | A kind of Fire risk assessment method for coupling certainty and uncertainty analysis | |
| CN106384210B (en) | A kind of power transmission and transforming equipment maintenance prioritization method based on maintenance risk income | |
| CN112907122A (en) | Natural gas filling station safety evaluation model and evaluation method | |
| CN109146293A (en) | One kind being based on the Municipal Gas Pipeline Risk Assessment Technique method of " five scaling laws " | |
| CN101853320B (en) | Fuzzy comprehensive evaluation method suitable for aircraft structure corrosion damage | |
| CN109102157A (en) | A kind of bank's work order worksheet processing method and system based on deep learning | |
| CN113592359B (en) | Method and device for evaluating health degree of power transformer | |
| CN112529327A (en) | Method for constructing fire risk prediction grade model of buildings in commercial areas | |
| CN103606062A (en) | Relay protection state evaluation and aid decision-making maintenance method | |
| CN112632765B (en) | Combat capability assessment method combining weighting method and SEM method | |
| CN113642922A (en) | Small and medium-sized micro enterprise credit evaluation method and device | |
| CN109214625A (en) | A kind of oil tank evaluation method for failure and device | |
| CN114819680A (en) | Enterprise health degree evaluation model construction method and system and storage medium | |
| CN115587653A (en) | Transportation enterprise risk prediction method and system based on hazardous chemical substance risk portrait | |
| CN115496353A (en) | Intelligent risk assessment method for compressed natural gas filling station | |
| CN116739399A (en) | High-voltage cable running state evaluation method | |
| CN114881374A (en) | Multi-element heterogeneous energy consumption data fusion method and system for building energy consumption prediction | |
| CN117494950B (en) | Optical storage, filling and inspection micro-grid integrated station operation safety evaluation method | |
| CN114742402A (en) | Information monitoring method, device, equipment and medium | |
| CN112949745B (en) | Fusion processing method and device for multi-source data, electronic equipment and storage medium | |
| CN105741184B (en) | Transformer state evaluation method and device | |
| CN110991878A (en) | Evaluation method for conducting crowd environment risk perception standardization measurement based on Lekter scale | |
| CN116501865A (en) | Electric power marketing inspection information analysis system and method | |
| CN115907719A (en) | Hierarchical operation and maintenance management method and device for charging station | |
| Kong et al. | User group portrait method of integrated energy system based on multi-source big data |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| WW01 | Invention patent application withdrawn after publication |
Application publication date: 20210604 |
|
| WW01 | Invention patent application withdrawn after publication |