CN117236477A - Natural gas station risk detection method and detection system - Google Patents
Natural gas station risk detection method and detection system Download PDFInfo
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Abstract
The application discloses a natural gas station risk detection method and a detection system, wherein the detection method comprises the following steps: acquiring risk influence factor data of a natural gas station to be detected; constructing a risk evaluation system with a hierarchical structure based on the risk influence factor data; adopting an analytic hierarchy process, and calculating the evaluation index weight of the natural gas station to be detected based on the risk evaluation system; processing the risk evaluation system by adopting a quantization index method to obtain an index quantization value of the risk evaluation system; constructing a risk index model based on the evaluation index weight and the index quantized value; analyzing and detecting the real-time risk of the natural gas station to be detected by the risk index model, and outputting a risk index for representing the natural gas station to be detected; the application has the beneficial effects of improving the accuracy of classifying the risk grades of the natural gas station and increasing the safety of the natural gas station.
Description
Technical Field
The application relates to the technical field of risk judgment, in particular to a natural gas station risk detection method and a natural gas station risk detection system.
Background
In a natural gas station, the scientific classification of the existing risk level has important significance, the classification and supervision are carried out, the supervision resources are integrated, the supervision efficiency is improved, the working mechanisms of linkage, up-down coordination, classification responsibility and classification and supervision of all levels of safety supervision departments are constructed, the working patterns with clear responsibility, full coverage and effective management and control are formed, the limited supervision force can be concentrated to high-risk production and management units, the contradiction of wide safety production supervision scope, large quantity, heavy tasks and serious shortage of supervision force is effectively relieved, the supervision efficacy is fully exerted, and various production safety accidents are prevented.
As a green energy source, natural gas has increasingly increased in proportion in energy consumption structures in China. The natural gas exploration and development is a high-risk industry, and the production place of the natural gas exploration and development is often provided with hazard factors such as inflammable and explosive gas, toxic gas and the like, high-risk operations such as high-rise operation, fire operation, temporary electricity utilization, entering a limited space and the like are involved in the risk operation process, meanwhile, the natural gas exploration and development is influenced by the overlapping of risks such as the capability of operators, the implementation of safety management measures, the integrity of equipment and the like, more dynamic risks exist, and once the safety management measures are out of control, casualties of the operators are extremely easy to occur, so that the risk accidents existing in a natural gas station are required to be classified for realizing the safety management of the natural gas station.
However, in the management classification in the prior art, risk events included in the aspects of process, management, personnel, environment and the like related to the production process are generally utilized to be combed and classified, the risk level is quantified by establishing a mathematical model, and the risk classification with certain accuracy is realized according to the set risk classification condition. However, when the risk classification is carried out by adopting the method, different risk classes are classified based on factors such as accident results, probability and the like, and the influence of risk factors behind the accident results and the occurrence probability is not fully considered, and the casualties can be caused in serious cases.
In view of this, the present application has been made.
Disclosure of Invention
The application aims to provide a natural gas station risk detection method and a detection system, which realize the fusion of various factors affecting a natural gas station into an assessment risk level and increase the safety of the natural gas station.
The application is realized by the following technical scheme:
the application provides a natural gas station risk detection method, which comprises the following steps:
acquiring risk influence factor data of a natural gas station to be detected;
constructing a risk evaluation system with a hierarchical structure based on the risk influence factor data;
adopting an analytic hierarchy process, and calculating the evaluation index weight of the natural gas station to be detected based on the risk evaluation system;
processing the risk evaluation system by adopting a quantization index method to obtain an index quantization value of the risk evaluation system;
constructing a risk index model based on the evaluation index weight and the index quantized value;
and analyzing and detecting the real-time risk of the natural gas station to be detected by the risk index model, and outputting a risk index for representing the natural gas station to be detected.
In the conventional risk level evaluation of the natural gas station, the risk level in the natural gas station is usually judged by taking the result after the accident and the probability factor of the accident as main factors after the accident occurs, but when the risk level of the station is judged by adopting the method, various risk factors after the accident is detected are usually ignored, the situation of inaccurate judgment on the risk level is caused, and secondary disasters can occur when the risk level is serious; the application provides a risk detection method for a natural gas station, which combines various factors possibly causing risk in the natural gas station to be detected, dynamically evaluates risk indexes on the natural gas station to be detected in a manner of a hierarchical analysis method and an index quantification method, improves the accuracy of risk classification of the natural gas station, and increases the safety of the natural gas station.
Preferably, the risk evaluation system comprises a first-level evaluation system, a second-level evaluation system and a third-level evaluation system, wherein the second-level evaluation system is a subclass of each index system in the first-level evaluation system, and the third-level evaluation system is a subclass of each index system in the second-level evaluation system;
the first-level evaluation system comprises a personnel structure system, a fixed facility system, an environment system and a management system.
Preferably, the staff architecture includes staff knowledge skill level index, staff psychology index, physiological index and staff behavior index;
the fixed facility system comprises production equipment facility operation indexes, public and auxiliary production facility indexes, safety protection facility indexes and dangerous chemical storage and use indexes;
the environment system comprises a station surrounding environment index, a station plane arrangement index, a working environment index and a social environment index;
the management system comprises an organization management index, a file management index, a risk identification and hidden danger investigation management index, an emergency management index, a professional health management index, an operation permission management index, a contractor operation management index, a process and equipment change management index, an accident and time management index and an environmental protection measure implementation condition index.
Preferably, the step of specifically calculating the evaluation index weight of the natural gas station to be detected includes:
constructing a judgment matrix between each index system and each index system in each evaluation system;
calculating the maximum characteristic root of each judgment matrix and the corresponding characteristic vector thereof by adopting a hierarchical ordering method;
carrying out normalization processing on each maximum feature root and the corresponding feature vector, and carrying out consistency inspection on the normalized data to obtain index weight of the evaluation system;
and carrying out hierarchical total sequencing on the index weights of all the evaluation systems to obtain the evaluation index weights.
Preferably, the index quantized values include a static index quantized value, a dynamic index quantized value and an additional coefficient quantized value,
the static index quantized value is used for acquiring a reference comprehensive risk index of the natural gas station to be detected, and serves as a basis of dynamic risk management;
the dynamic index quantized value is used for acquiring a dynamic risk index of the natural gas station to be detected;
the additional coefficient quantized value is used for obtaining a risk index of a process scale of the natural gas station to be detected, a risk index of production running time and a risk index of a treatment medium.
Preferably, the static index quantized value is a quantized standard table established by enterprise site security inspection specifications and HSE management system quantized audit standards.
Preferably, the additional coefficient quantized value obtaining method includes:
acquiring historical risk index additional coefficient data parameters and constructing a risk index additional coefficient model;
and acquiring risk characteristics on the natural gas station to be detected, and inputting the risk characteristics into the risk index additional coefficient model to obtain an additional coefficient quantized value.
Preferably, the specific expression of the risk index model is:
R t is a risk index, x i Quantized value, x, of an evaluation index subordinate to production facility operation risk factor data and common and auxiliary production facility risk factor data j To divide by x i Evaluation index quantization value, ω, of the subordinate evaluation index factor data other than the evaluation index quantization value i Is x i Corresponding weight value omega j Is x j Corresponding weight value, k 1 Adding a coefficient k to indexes of station gas risk factor data 2 Adding a coefficient k to the index of the safety condition risk factor data of the pressure vessel 3 Adding a coefficient, k, to an index of process scale risk factor data 4 Adding a coefficient k to the index of the station operation period risk factor data 5 Appending coefficients, k, to the index of the system audit risk factor data 6 And adding a coefficient to the index of the total risk factor data of the problem.
Preferably, the risk index for characterizing the natural gas field station to be detected is specifically: a step of
When R is t <4.0, the natural gas station to be detected is in a low risk state;
when R is more than or equal to 4.0 t <6.0, the natural gas station to be detected is in a general risk state;
when R is more than or equal to 6.0 t <8.0, the natural gas station to be detected is in a state of greater risk;
when R is t And the natural gas station to be detected is in a major risk state more than or equal to 8.0.
The application also provides a natural gas station risk detection system, which comprises a data acquisition module, a system construction module, a weight calculation module, a quantization value calculation module, a model construction module and a risk index calculation module;
the data acquisition module is used for acquiring risk influence factor data of the natural gas station to be detected;
the system construction module is used for constructing a risk evaluation system with a hierarchical structure based on the risk influence factor data;
the weight calculation module is used for calculating the evaluation index weight of the natural gas station to be detected based on the risk evaluation system by adopting an analytic hierarchy process;
the quantized value calculation module is used for processing the risk evaluation system by adopting a quantized index method to obtain an index quantized value of the risk evaluation system;
the model construction module is used for constructing a risk index model based on the evaluation index weight and the index quantification value;
the risk index construction module is used for analyzing and detecting the real-time risk of the natural gas station to be detected by the risk index model and outputting a risk index used for representing the natural gas station to be detected.
Compared with the prior art, the application has the following advantages and beneficial effects:
according to the risk detection method and the risk detection system for the natural gas station, provided by the embodiment of the application, the risk indexes on the natural gas station to be detected are dynamically evaluated by combining all factors possibly causing the risk in the natural gas station to be detected and adopting a hierarchical analysis method and an index quantification method, so that the accuracy of risk classification of the natural gas station is improved, and the safety of the natural gas station is improved.
Drawings
In order to more clearly illustrate the technical solutions of the exemplary embodiments of the present application, the drawings that are needed in the examples will be briefly described below, it being understood that the following drawings only illustrate some examples of the present application and therefore should not be considered as limiting the scope, and that other related drawings may be obtained from these drawings without inventive effort for a person skilled in the art.
FIG. 1 is a schematic flow chart of a detection method
FIG. 2 is a schematic diagram of a detection system
Detailed Description
For the purpose of making apparent the objects, technical solutions and advantages of the present application, the present application will be further described in detail with reference to the following examples and the accompanying drawings, wherein the exemplary embodiments of the present application and the descriptions thereof are for illustrating the present application only and are not to be construed as limiting the present application.
In the following description, numerous specific details are set forth in order to provide a thorough understanding of the present application. However, it will be apparent to one of ordinary skill in the art that: no such specific details are necessary to practice the application. In other instances, well-known structures, circuits, materials, or methods have not been described in detail in order not to obscure the application.
Throughout the specification, references to "one embodiment," "an embodiment," "one example," or "an example" mean: a particular feature, structure, or characteristic described in connection with the embodiment or example is included within at least one embodiment of the application. Thus, the appearances of the phrases "in one embodiment," "in an example," or "in an example" in various places throughout this specification are not necessarily all referring to the same embodiment or example. Furthermore, the particular features, structures, or characteristics may be combined in any suitable combination and/or sub-combination in one or more embodiments or examples. Moreover, those of ordinary skill in the art will appreciate that the illustrations provided herein are for illustrative purposes and that the illustrations are not necessarily drawn to scale. The term "and/or" as used herein includes any and all combinations of one or more of the associated listed items.
In the description of the present application, the terms "front", "rear", "left", "right", "upper", "lower", "vertical", "horizontal", "high", "low", "inner", "outer", etc. indicate orientations or positional relationships based on the orientations or positional relationships shown in the drawings, merely to facilitate description of the present application and simplify description, and do not indicate or imply that the devices or elements referred to must have a specific orientation, be configured and operated in a specific orientation, and therefore should not be construed as limiting the scope of the present application.
Example 1
The embodiment discloses a natural gas station risk detection method, as shown in fig. 1, the detection method comprises the following steps:
s1: in step S1, the obtained risk influencing factors include all factors that can influence the risk of the natural gas station, and in this embodiment, the influencing factors in all aspects can be comprehensively considered from personnel factors, management factors, environmental factors and factors of fixed equipment, so that the risk level of the natural gas station can be comprehensively judged, and the indexes include personnel qualification and capability, on-site production equipment facilities, environment and working conditions of the station, system construction and responsibility implementation, risk management, operation permission management, emergency management, contractors, change management, accident event management, supervision and inspection and the like.
S2: constructing a risk evaluation system with a hierarchical structure based on the risk influence factor data;
in step S2, the obtained various risk influence data are hierarchically divided, and a hierarchical evaluation system is constructed. Classifying the determined evaluation indexes to form a natural gas station evaluation index hierarchical structure, perfecting the rated evaluation indexes, and finally establishing a natural gas station risk classification evaluation index system, wherein 4 first-level risk classification evaluation indexes, 21 second-level risk classification evaluation indexes, 72 third-level risk classification evaluation indexes and 30 fourth-level risk classification evaluation indexes are set in total.
The risk evaluation system specifically divided comprises a first-level evaluation system, a second-level evaluation system and a third-level evaluation system, wherein the second-level evaluation system is a subclass of each index system in the first-level evaluation system, and the third-level evaluation system is a subclass of each index system in the second-level evaluation system;
the first-level evaluation system includes a personnel structure system, a fixed facility system, an environment system, and a management system, in this embodiment, the personnel structure system is a factor of a person, the fixed facility system is a factor of a substance, the environment system is an environment factor, and the management system is a management factor.
All risk influencing factors are divided into different index standards according to different layers of systems.
The staff structure system comprises staff knowledge skill level indexes, staff psychology indexes, physiological indexes and staff behavior indexes;
the fixed facility system comprises production equipment facility operation indexes, public and auxiliary production facility indexes, safety protection facility indexes and dangerous chemical storage and use indexes;
the environment system comprises a station surrounding environment index, a station plane arrangement index, a working environment index and a social environment index;
the management system comprises an organization management index, a file management index, a risk identification and hidden danger investigation management index, an emergency management index, a professional health management index, an operation permission management index, a contractor operation management index, a process and equipment change management index, an accident and time management index and an environmental protection measure implementation condition index.
Specific grading indexes are shown in table one according to personnel system as an example:
list one
S3: adopting an analytic hierarchy process, and calculating the evaluation index weight of the natural gas station to be detected based on the risk evaluation system;
the specific calculation of the evaluation index weight of the natural gas station to be detected comprises the following steps:
constructing a judgment matrix between each index system and each index system in each evaluation system;
judging the values of matrix elements reflects the knowledge of the relative importance (such as the quality, preference, strength, etc.) of each factor, and a scale method of 1-9 and the reciprocal thereof is generally adopted. When the important performance of the mutual comparison factors is described by the ratio with practical meaning, the value of the corresponding element of the judgment matrix can be taken as the ratio, and the second table is the judgment matrix scale and the meaning thereof.
Watch II
According to a natural gas station risk grading evaluation index system, 34 judgment matrixes are constructed in total. As shown in the third table to the sixth table, the third table is a judgment evidence between the first-level evaluation systems, and the fourth table is a judgment matrix between index systems under the fixed facility systems; watch III
| Factor A1 of human | Factor A2 of the object | Environmental factor A3 | Management factor A4 | |
| Factor A1 of human | 1 | 1/4 | 4 | 1/2 |
| Factor A2 of the object | 4 | 1 | 5 | 3 |
| Environmental factor A3 | 1/4 | 1/5 | 1 | 1/4 |
| Management factor A4 | 2 | 1/3 | 4 | 1 |
Table four
TABLE five
TABLE six
| Emergency exercise frequency D25 | EmergencyExercise cover D26 | Emergency exercise type D27 | |
| Emergency exercise frequency D25 | 1 | 4 | 5 |
| Emergency exercise cover D26 | 1/4 | 1 | 3 |
| Emergency exercise type D27 | 1/5 | 1/3 | 1 |
Calculating the maximum characteristic root of each judgment matrix and the corresponding characteristic vector thereof by adopting a hierarchical ordering method; carrying out normalization processing on each maximum feature root and the corresponding feature vector, and carrying out consistency inspection on the normalized data to obtain index weight of the evaluation system;
and carrying out hierarchical total sequencing on the index weights of all the evaluation systems to obtain the evaluation index weights.
And (5) calculating and judging the maximum characteristic root of the matrix and the corresponding characteristic vector by using the hierarchical sequence. Computing the power of the matrix feature root makes it possible to obtain the maximum feature root and its corresponding feature vector with arbitrary accuracy using a computer. Carrying out maximum feature root and feature vector calculation by MATLAB software, carrying out normalization processing and consistency inspection, and obtaining index weight results of each level after inspection, wherein the table seven is a first-level evaluation index weight calculation result, the table eight is a second-level evaluation index weight calculation result, and the table nine is a total sorting weight example of risk grading evaluation indexes of a natural gas station;
watch seven
Table eight
Table nine
S4: processing the risk evaluation system by adopting a quantization index method to obtain an index quantization value of the risk evaluation system;
in step S4, by quantifying the factors of each evaluation index obtained, the quantified requirement is obtained according to the enterprise site security inspection specification and the quantitative auditing standard of the HSE management system, and the intrinsic risks of the station in terms of energy or dangerous substances related to equipment and facilities and the potential risks in terms of personnel, environment and management are considered, and the basic risk values are considered in the quantitative scoring. If the station does not relate to a certain index, the value is 0; if the index exists, but no unsafe state or condition exists, the basic risk value is basically set to be 2 points; the rest of the cases are quantized according to the actual conditions.
The index quantized values include a static index quantized value, a dynamic index quantized value, and an additional coefficient quantized value,
the static index quantized value is used for acquiring a reference comprehensive risk index of the natural gas station to be detected, and serves as a basis of dynamic risk management;
the natural gas station initial scoring quantification is used for acquiring station basic risk level, namely reference comprehensive risk index, and taking the station basic risk level, namely reference comprehensive risk index as a basis for dynamic risk management. In the quantification of the initial score, partial indexes are quantified by mainly considering and establishing an initial score quantification standard table from the aspect of inherent risk factors according to national laws and regulations, standard specifications and enterprise related management requirements; other indexes are classified into different cases according to 0, 2, 5 and 10 based on interpolation, and scoring is carried out according to the on-site actual condition comparison scoring instruction.
The dynamic index quantized value is used for acquiring a dynamic risk index of the natural gas station to be detected; the natural gas station dynamic scoring quantification is used for acquiring station dynamic risk changes and realizing dynamic management of risks. The index is established mainly according to each level of management system, and is mainly based on factors of continuous management and change, such as system execution, risk operation, process, personnel change and the like in a period, and meanwhile results of each level of supervision and inspection, HSE system examination, security diagnosis evaluation, evaluation and the like are included for dynamic adjustment and grading.
The additional coefficient quantized value is used for obtaining a risk index of a process scale of the natural gas station to be detected, a risk index of production running time and a risk index of a treatment medium.
The static index quantized value is a scoring quantized standard table established by the quantitative auditing standard of the enterprise site safety inspection standard and the HSE management system.
The natural gas station initial scoring quantification is used for acquiring station basic risk level, namely reference comprehensive risk index, and taking the station basic risk level, namely reference comprehensive risk index as a basis for dynamic risk management. In the quantification of the initial score, partial indexes are scored according to national laws and regulations, standard specifications and enterprise related management requirements mainly from the aspect of inherent risk factors and an initial scoring quantification standard table is established; other indexes are classified into different conditions based on interpolation methods, and are assigned with scores of 0, 2, 5 and 10, and scoring is directly carried out according to the obtained characteristic point comparison scoring instruction, so that subjective scoring errors are reduced.
The natural gas station dynamic scoring quantification is used for acquiring station dynamic risk changes and realizing dynamic management of risks. The index is established mainly according to each level of management system, and is mainly based on factors of continuous management and change, such as system execution, risk operation, process, personnel change and the like in a period, and meanwhile results of each level of supervision and inspection, HSE system examination, security diagnosis evaluation, evaluation and the like are included for dynamic adjustment and grading.
The method for acquiring the quantized value of the additional coefficient comprises the following steps:
acquiring historical risk index additional coefficient data parameters and constructing a risk index additional coefficient model;
and acquiring risk characteristics on the natural gas station to be detected, and inputting the risk characteristics into the risk index additional coefficient model to obtain an additional coefficient quantized value.
For example, when the risk characteristic collected is station gas quality, there is no risk index additional coefficient when it is sulfur-free natural gas/shale gas, the additional coefficient quantized value is 0.4 when it is low sulfur-containing natural gas, the additional coefficient quantized value is 0.8 when it is medium high sulfur-containing natural gas, the additional coefficient quantized value is 0.2 when it contains water, and the additional coefficient characteristic is 0.4 when it contains condensate.
If a certain index is quantized to more than 10 minutes after the risk index additional coefficient is considered, the index is used as a key attention item for field station hidden trouble shooting and security inspection at all levels;
if a certain index relates to multiple risk features, additional coefficients are superimposed. If an initial risk assessment is carried out on a station, the station is a four-level station, sulfur is contained in the station, the station is operated for 7 years, and the safety condition of a pressure container in the station is rated as 3 levels, namely: k (k) 1 ＝0.8,k 2 ＝0.2,k 3 ＝0.4,k 4 =0.2, other additional coefficients are not involved. In the evaluation process, the risk additional coefficient of the subordinate indexes of the production facility running risk B4 and the public and auxiliary production facility risk B5 is 0.8, the quantitative values of all the related indexes are multiplied by 1.8, and the initial risk evaluation value of the station is multiplied by 1.8 (k 1 ＝0.8)；
If the total score of the station risk score after the additional coefficient is greater than the set total score, the station risk grade is directly determined as the grade IV risk.
S5: constructing a risk index model based on the evaluation index weight and the index quantized value;
the specific expression of the risk index model is as follows:
R t is a risk index, x i Quantized value, x, of an evaluation index subordinate to production facility operation risk factor data and common and auxiliary production facility risk factor data j To divide by x i Evaluation index quantization value, ω, of the subordinate evaluation index factor data other than the evaluation index quantization value i Is x i Corresponding weight value omega j Is x j Corresponding weight value, k 1 Adding a coefficient k to indexes of station gas risk factor data 2 Adding a coefficient k to the index of the safety condition risk factor data of the pressure vessel 3 Adding a coefficient, k, to an index of process scale risk factor data 4 Adding a coefficient k to the index of the station operation period risk factor data 5 Appending coefficients, k, to the index of the system audit risk factor data 6 And adding a coefficient to the index of the total risk factor data of the problem.
For a certain natural gas station, recording the first calculated comprehensive risk index as an initial risk, namely x i ，x j Adopting an initial scoring quantized value; the subsequent risk classification evaluation results are dynamic risks, namely x i ，x j Dynamic scoring quantization values are employed.
The risk change is dynamically perceived, the safety supervision targeting and accuracy of enterprises are enhanced, and the supervision efficiency is effectively improved; the actual dynamic conditions such as increase, sales items and risk factor change of hidden trouble investigation are compared with the change trend and risk scoring information displayed by the evaluation model, so that the weak link of station management and control can be intuitively reflected, corrective measures can be formulated in time, and the supervision center of gravity can be dynamically determined for the safety supervision department; meanwhile, the monitoring and checking key points are timely adjusted through periodical grading evaluation of the natural gas station.
S6: and analyzing and detecting the real-time risk of the natural gas station to be detected by the risk index model, and outputting a risk index for representing the natural gas station to be detected.
The risk index for representing the natural gas station to be detected specifically comprises the following steps: a step of
When R is t <4.0, the natural gas station to be detected is in a low risk state;
when R is more than or equal to 4.0 t <6.0, the natural gas station to be detected is in a general risk state;
when R is more than or equal to 6.0 t <8.0, the natural gas station to be detected is in a state of greater risk;
when R is t And the natural gas station to be detected is in a major risk state more than or equal to 8.0.
Establishing a station risk file based on the station comprehensive risk index, more intuitively reflecting the dynamic change trend of the risk, and promoting enterprise security decision management; the comprehensive risk index model of the station is defined and established, enterprises can track the risk change of the station according to the comprehensive risk index, the station risk file is established, a basis is provided for the enterprises to make security management decisions, and a foundation is laid for realizing scientific risk prediction.
The embodiment discloses a natural gas station risk detection method, which couples inherent risk factors and dynamic risk factors together through a hierarchical analysis method in terms of factors of people, factors of objects, environmental factors and management factors in an accident system, builds and perfects a landing application and HSE management system of a trampling dual prevention mechanism, integrates actual management into an evaluation model, and aims management problems through evaluation implementation, so that management perfection is promoted.
Scientific refinement risk index quantitative assignment mode, reasonable simplification of the evaluation implementation process and improvement of the applicability and operability of the evaluation method; the enterprise system auditing requirements and the security inspection key points are fused, the basis and the standard of the initial scoring and the dynamic scoring of the risks are provided, the evaluation is objective and simpler, and particularly, the dynamic scoring can recalculate the overall risk of the station yard only by inputting the changed risk factors, so that the operation is easy.
Example two
The embodiment discloses a natural gas station risk detection system, which aims to realize the detection method in the first embodiment, and as shown in fig. 2, the detection system comprises a data acquisition module, a system construction module, a weight calculation module, a quantization value calculation module, a model construction module and a risk index calculation module;
the data acquisition module is used for acquiring risk influence factor data of the natural gas station to be detected;
the system construction module is used for constructing a risk evaluation system with a hierarchical structure based on the risk influence factor data;
the weight calculation module is used for calculating the evaluation index weight of the natural gas station to be detected based on the risk evaluation system by adopting an analytic hierarchy process;
the quantized value calculation module is used for processing the risk evaluation system by adopting a quantized index method to obtain an index quantized value of the risk evaluation system;
the model construction module is used for constructing a risk index model based on the evaluation index weight and the index quantification value;
the risk index construction module is used for analyzing and detecting the real-time risk of the natural gas station to be detected by the risk index model and outputting a risk index used for representing the natural gas station to be detected.
The foregoing description of the embodiments has been provided for the purpose of illustrating the general principles of the application, and is not meant to limit the scope of the application, but to limit the application to the particular embodiments, and any modifications, equivalents, improvements, etc. that fall within the spirit and principles of the application are intended to be included within the scope of the application.
Claims (10)
1. A natural gas station risk detection method, which is characterized by comprising the following steps:
acquiring risk influence factor data of a natural gas station to be detected;
constructing a risk evaluation system with a hierarchical structure based on the risk influence factor data;
adopting an analytic hierarchy process, and calculating the evaluation index weight of the natural gas station to be detected based on the risk evaluation system;
processing the risk evaluation system by adopting a quantization index method to obtain an index quantization value of the risk evaluation system;
constructing a risk index model based on the evaluation index weight and the index quantized value;
and analyzing and detecting the real-time risk of the natural gas station to be detected by the risk index model, and outputting a risk index for representing the natural gas station to be detected.
2. The method for detecting the risk of a natural gas station according to claim 1, wherein the risk evaluation system comprises a first-level evaluation system, a second-level evaluation system and a third-level evaluation system, the second-level evaluation system is a subclass of each index system in the first-level evaluation system, and the third-level evaluation system is a subclass of each index system in the second-level evaluation system;
the first-level evaluation system comprises a personnel structure system, a fixed facility system, an environment system and a management system.
3. A natural gas terminal risk detection method according to claim 2, wherein the staff architecture includes staff knowledge skill level indicators, staff psychology, physiology indicators and staff behavioral indicators;
the fixed facility system comprises production equipment facility operation indexes, public and auxiliary production facility indexes, safety protection facility indexes and dangerous chemical storage and use indexes;
the environment system comprises a station surrounding environment index, a station plane arrangement index, a working environment index and a social environment index;
the management system comprises an organization management index, a file management index, a risk identification and hidden danger investigation management index, an emergency management index, a professional health management index, an operation permission management index, a contractor operation management index, a process and equipment change management index, an accident and time management index and an environmental protection measure implementation condition index.
4. A natural gas terminal risk detection method according to claim 3, wherein the step of specifically calculating the evaluation index weight of the natural gas terminal to be detected comprises:
constructing a judgment matrix between each index system and each index system in each evaluation system;
calculating the maximum characteristic root of each judgment matrix and the corresponding characteristic vector thereof by adopting a hierarchical ordering method;
carrying out normalization processing on each maximum feature root and the corresponding feature vector, and carrying out consistency inspection on the normalized data to obtain index weight of the evaluation system;
and carrying out hierarchical total sequencing on the index weights of all the evaluation systems to obtain the evaluation index weights.
5. The method of claim 4, wherein the index quantization values include a static index quantization value, a dynamic index quantization value, and an additional coefficient quantization value,
the static index quantized value is used for acquiring a reference comprehensive risk index of the natural gas station to be detected, and serves as a basis of dynamic risk management;
the dynamic index quantized value is used for acquiring a dynamic risk index of the natural gas station to be detected;
the additional coefficient quantized value is used for obtaining a risk index of a process scale of the natural gas station to be detected, a risk index of production running time and a risk index of a treatment medium.
6. The method for detecting the risk of the natural gas terminal according to claim 5, wherein the static index quantification value is a quantification standard table established by enterprise site security inspection standards and quantitative audit standards of an HSE management system.
7. The method for risk detection of a natural gas terminal according to claim 6, wherein the additional coefficient quantized value obtaining method comprises the steps of:
acquiring historical risk index additional coefficient data parameters and constructing a risk index additional coefficient model;
and acquiring risk characteristics on the natural gas station to be detected, and inputting the risk characteristics into the risk index additional coefficient model to obtain an additional coefficient quantized value.
8. The method for risk detection of a natural gas terminal according to claim 7, wherein the specific expression of the risk index model is:
R t is a risk index, x i Quantized value, x, of an evaluation index subordinate to production facility operation risk factor data and common and auxiliary production facility risk factor data j To divide by x i Evaluation index quantization value, ω, of the subordinate evaluation index factor data other than the evaluation index quantization value i Is x i Corresponding weight value omega j Is x j Corresponding weight value, k 1 Adding a coefficient k to indexes of station gas risk factor data 2 Adding a coefficient k to the index of the safety condition risk factor data of the pressure vessel 3 Adding a coefficient, k, to an index of process scale risk factor data 4 Adding a coefficient k to the index of the station operation period risk factor data 5 Index for auditing risk factor data for a hierarchyMark additional coefficient, k 6 And adding a coefficient to the index of the total risk factor data of the problem.
9. The natural gas terminal risk detection method according to claim 1, wherein the risk index for characterizing the natural gas terminal to be detected is specifically: a step of
When R is t <4.0, the natural gas station to be detected is in a low risk state;
when R is more than or equal to 4.0 t <6.0, the natural gas station to be detected is in a general risk state;
when R is more than or equal to 6.0 t <8.0, the natural gas station to be detected is in a state of greater risk;
when R is t And the natural gas station to be detected is in a major risk state more than or equal to 8.0.
10. The natural gas station risk detection system is characterized by comprising a data acquisition module, a system construction module, a weight calculation module, a quantization value calculation module, a model construction module and a risk index calculation module;
the data acquisition module is used for acquiring risk influence factor data of the natural gas station to be detected;
the system construction module is used for constructing a risk evaluation system with a hierarchical structure based on the risk influence factor data;
the weight calculation module is used for calculating the evaluation index weight of the natural gas station to be detected based on the risk evaluation system by adopting an analytic hierarchy process;
the quantized value calculation module is used for processing the risk evaluation system by adopting a quantized index method to obtain an index quantized value of the risk evaluation system;
the model construction module is used for constructing a risk index model based on the evaluation index weight and the index quantification value;
the risk index construction module is used for analyzing and detecting the real-time risk of the natural gas station to be detected by the risk index model and outputting a risk index used for representing the natural gas station to be detected.
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