A natural gas station risk detection method and detection system

Abstract

The application discloses a kind of natural gas station risk detection method and detection system, and detection method steps include: obtaining the risk influencing factor data of natural gas station to be detected;Based on the risk influencing factor data, a risk evaluation system with hierarchical structure is constructed;Using analytic hierarchy process, based on the risk evaluation system, the evaluation index weight of the natural gas station to be detected is calculated;The risk evaluation system is processed using the method of quantitative index, and the index quantization value of the risk evaluation system is obtained;Based on the evaluation index weight and the index quantization value, a risk index model is constructed;The real-time risk of the natural gas station to be detected is analyzed and detected by the risk index model, and the risk index for representing the natural gas station to be detected is output;The beneficial effect of the application is to improve the accuracy of the risk level division of natural gas station, and increase the safety of natural gas station.

Description

Technical Field

[0001] This invention relates to the field of risk assessment technology, and more specifically, to a risk detection method and system for natural gas stations. Background Technology

[0002] In natural gas stations, it is of great significance to scientifically classify the risk levels they present. By implementing classified and categorized supervision, integrating regulatory resources, improving regulatory efficiency, and building a working mechanism that links safety regulatory departments at all levels, coordinates vertically and horizontally, assigns responsibilities at different levels, and monitors by category, a working pattern with clear responsibilities, comprehensive coverage, and effective control can be formed. This can concentrate limited regulatory resources on high-risk production and operation units, effectively alleviating the contradiction between the wide scope, large number, and heavy tasks of safety production supervision and the serious shortage of regulatory resources, giving full play to regulatory effectiveness, and preventing various production safety accidents.

[0003] As a green energy source, natural gas is playing an increasingly important role in my country's energy consumption structure. Natural gas exploration and development is a high-risk industry. Its production sites often contain hazardous factors such as flammable and explosive gases and toxic gases. High-risk operations involve working at heights, hot work, temporary power supply, and entry into confined spaces. At the same time, due to the combined effects of risks such as the capabilities of workers, the implementation of safety control measures, and the integrity of equipment, there are many "dynamic risks." Once safety management measures are out of control, accidents causing personal injury or death can easily occur. Therefore, it is necessary to investigate and classify the risks and accidents existing in natural gas stations to achieve safe management of natural gas stations.

[0004] However, current management classification methods typically involve analyzing and categorizing risk events related to processes, management, personnel, and the environment involved in production. Mathematical models are then used to quantify risk levels and achieve a certain degree of accuracy in risk grading based on predetermined risk classifications. However, this method relies on factors such as accident consequences and probabilities to determine different risk levels, failing to fully consider the impact of underlying risk factors on accident consequences and probabilities. Furthermore, in severe cases, this can lead to personal injury or death.

[0005] In view of the above, this application is hereby submitted. Summary of the Invention

[0006] The technical problem to be solved by this invention is that the existing technology does not take the risk factors behind the consequences and probability of an accident into account when judging the risk level, which leads to errors in the risk assessment of natural gas stations. The purpose is to provide a risk detection method and system for natural gas stations, which integrates various factors affecting natural gas stations into the risk level assessment, thereby increasing the safety of natural gas stations.

[0007] This invention is achieved through the following technical solution:

[0008] This invention provides a risk detection method for natural gas stations, the method comprising the following steps:

[0009] Obtain data on risk factors affecting the natural gas station to be tested;

[0010] Based on the aforementioned risk influencing factor data, a hierarchical risk assessment system is constructed.

[0011] Using the analytic hierarchy process (AHP), the weights of the evaluation indicators for the natural gas station under test are calculated based on the aforementioned risk assessment system.

[0012] The risk assessment system is processed using quantitative indicators to obtain the quantitative values ​​of the indicators of the risk assessment system.

[0013] Based on the weights of the evaluation indicators and the quantitative values ​​of the indicators, a risk index model is constructed.

[0014] The risk index model is used to analyze and detect the real-time risk of the natural gas station under test, and outputs a risk index to characterize the natural gas station under test.

[0015] Traditional risk assessments of natural gas stations typically rely on the aftermath of an accident, using the consequences and probability of such an event as primary factors to determine the station's risk level. However, this method often overlooks various post-accident risk factors, leading to inaccurate risk assessments and potentially causing secondary disasters. This invention provides a risk detection method for natural gas stations. By combining various potential risk factors at the station and employing the analytic hierarchy process (AHP) and index quantification, the method dynamically assesses the risk index of the station, improving the accuracy of risk level classification and enhancing the station's safety.

[0016] Preferably, the risk assessment system includes a primary assessment system, a secondary assessment system, and a tertiary assessment system, wherein the secondary assessment system is a subclass of each indicator system within the primary assessment system, and the tertiary assessment system is a subclass of each indicator system within the secondary assessment system;

[0017] The primary evaluation system includes personnel structure system, fixed facilities system, environmental system, and management system.

[0018] Preferably, the personnel structure system includes employee knowledge and skills level indicators, employee psychological and physiological indicators, and employee behavior indicators;

[0019] The fixed infrastructure system includes indicators for the operation of production equipment and facilities, indicators for public and auxiliary production facilities, indicators for safety protection facilities, and indicators for the storage and use of hazardous chemicals;

[0020] The environmental system includes indicators of the surrounding environment of the station, indicators of the station's layout, indicators of the working environment, and indicators of the social environment.

[0021] The management system includes organizational management indicators, document management indicators, risk identification and hazard investigation and management indicators, emergency management indicators, occupational health management indicators, work permit management indicators, contractor work management indicators, process and equipment change management indicators, accident and time management indicators, and environmental protection measure implementation indicators.

[0022] Preferably, the specific steps for calculating the evaluation index weights of the natural gas station to be tested include:

[0023] Construct a judgment matrix between each indicator system in each evaluation system;

[0024] A hierarchical sorting method is used to calculate the maximum eigenvalue of each judgment matrix and its corresponding eigenvector.

[0025] Normalize each largest eigenvalue and its corresponding eigenvector, and perform a consistency check on the normalized data to obtain the index weights of the evaluation system.

[0026] The weights of all evaluation system indicators are ranked hierarchically to obtain the weights of the evaluation indicators.

[0027] Preferably, the quantified values ​​of the indicators include static indicator quantified values, dynamic indicator quantified values, and additional coefficient quantified values.

[0028] The static index quantification value is used to obtain the benchmark comprehensive risk index of the natural gas station to be tested, and the static index quantification value serves as the basis for dynamic risk management.

[0029] The dynamic index quantification value is used to obtain the dynamic risk index of the natural gas station to be tested;

[0030] The additional coefficient quantification value is used to obtain the risk index of the process scale, the risk index of the production operation time, and the risk index of the processing medium of the natural gas station to be tested.

[0031] Preferably, the static indicator quantification value is a quantification standard table established through the enterprise's on-site safety inspection specifications and HSE management system quantification audit standards.

[0032] Preferably, the method for obtaining the quantized value of the additional coefficient includes the following steps:

[0033] Obtain historical risk indicator additional coefficient data parameters and construct a risk indicator additional coefficient model;

[0034] The risk characteristics of the natural gas station to be tested are obtained, and the risk characteristics are input into the risk index additional coefficient model to obtain the quantitative value of the additional coefficient.

[0035] Preferably, the specific expression of the risk index model is as follows:

[0036]

[0037] R t x is the risk index. i x represents the quantified values ​​of evaluation indicators under the risk factor data for production equipment operation and the risk factor data for shared and auxiliary production facilities. j To divide x i The quantitative value of the evaluation index under the evaluation index factor data other than ω i For x i The corresponding weight value, ω j For x j The corresponding weight values ​​are as follows: k1 is the index addition coefficient for the site's gas quality risk factor data, k2 is the index addition coefficient for the pressure vessel safety status risk factor data, k3 is the index addition coefficient for the process scale risk factor data, k4 is the index addition coefficient for the site's operating years risk factor data, k5 is the index addition coefficient for the system audit risk factor data, and k6 is the index addition coefficient for the total problem risk factor data.

[0038] Preferably, the risk index used to characterize the natural gas station to be tested specifically includes:

[0039] When R t <4.0, the natural gas station to be tested is in a low-risk state;

[0040] When 4.0≤R t <6.0, the natural gas station to be tested is in a general risk state;

[0041] When 6.0≤R t <8.0, the natural gas station to be tested is in a state of high risk;

[0042] When R t If the value is ≥8.0, the natural gas station to be tested is in a state of significant risk.

[0043] The present invention also provides a natural gas station risk detection system, the detection system including a data acquisition module, a system construction module, a weight calculation module, a quantitative value calculation module, a model construction module, and a risk index calculation module;

[0044] The data acquisition module is used to acquire risk impact factor data of the natural gas station to be tested;

[0045] The system construction module is used to construct a hierarchical risk assessment system based on the risk influencing factor data.

[0046] The weight calculation module is used to calculate the weights of the evaluation indicators of the natural gas station to be tested based on the risk assessment system using the analytic hierarchy process.

[0047] The quantitative value calculation module is used to process the risk assessment system using a quantitative index method to obtain the quantitative values ​​of the risk assessment system indicators.

[0048] The model building module is used to build a risk index model based on the evaluation index weights and the index quantification values.

[0049] The risk index construction module is used to analyze and detect the real-time risk of the natural gas station to be tested using the risk index model, and output a risk index to characterize the natural gas station to be tested.

[0050] Compared with the prior art, the present invention has the following advantages and beneficial effects:

[0051] This invention provides a risk detection method and system for natural gas stations. By combining various factors that may lead to risks in the natural gas station under test, and using the analytic hierarchy process (AHP) and index quantification method, the risk index of the natural gas station under test is dynamically evaluated, which improves the accuracy of risk level classification of natural gas stations and increases the safety of natural gas stations. Attached Figure Description

[0052] To more clearly illustrate the technical solutions of the exemplary embodiments of the present invention, the accompanying drawings used in the embodiments will be briefly described below. It should be understood that the following drawings only show some embodiments of the present invention and should not be regarded as a limitation of the scope. For those skilled in the art, other related drawings can be obtained based on these drawings without creative effort.

[0053] Figure 1 A flowchart of the detection method

[0054] Figure 2 Schematic diagram of the detection system Detailed Implementation

[0055] To make the objectives, technical solutions, and advantages of the present invention clearer, the present invention will be further described in detail below with reference to the embodiments and accompanying drawings. The illustrative embodiments and descriptions of the present invention are only used to explain the present invention and are not intended to limit the present invention.

[0056] In the following description, numerous specific details are set forth in order to provide a thorough understanding of the invention. However, it will be apparent to those skilled in the art that these specific details are not necessary to practice the invention. In other embodiments, well-known structures, circuits, materials, or methods have not been specifically described in order to avoid obscuring the invention.

[0057] Throughout this specification, references to "an embodiment," "an example," or "an example" mean that a particular feature, structure, or characteristic described in connection with that embodiment or example is included in at least one embodiment of the present invention. Therefore, the phrases "an embodiment," "an example," "an example," or "an example" appearing in various places throughout the specification do not necessarily refer to the same embodiment or example. Furthermore, specific features, structures, or characteristics can be combined in one or more embodiments or examples in any suitable combination and / or sub-combination. Moreover, those skilled in the art will understand that the illustrations provided herein are for illustrative purposes and 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.

[0058] In the description of this invention, the terms "front", "rear", "left", "right", "up", "down", "vertical", "horizontal", "high", "low", "inner", and "outer" indicate the orientation or positional relationship based on the orientation or positional relationship shown in the accompanying drawings. They are only for the convenience of describing this invention and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation. Therefore, they should not be construed as limiting the scope of protection of this invention.

[0059] Example 1

[0060] This embodiment discloses a risk detection method for natural gas stations, such as... Figure 1 As shown, the detection method steps include:

[0061] S1: Obtain risk impact factor data for the natural gas station to be tested. In step S1, the risk impact factors include all factors that may affect the risk of the natural gas station. In this embodiment, factors such as personnel, management, environment, and fixed equipment are considered comprehensively. This allows for the combination of various influencing factors to make a comprehensive judgment on the risk level of the natural gas station. The indicators cover personnel qualifications and capabilities, on-site production equipment and facilities, the environment and working conditions of the station, system construction and responsibility implementation, risk management, work permit management, emergency management, contractors, change management, accident and incident management, and supervision and inspection.

[0062] S2: Based on the aforementioned risk influencing factor data, construct a risk assessment system with a hierarchical structure;

[0063] In step S2, the obtained risk impact data are hierarchically divided to construct a hierarchical evaluation system. The determined evaluation indicators are categorized to form a hierarchical structure of evaluation indicators for natural gas stations. The evaluation content of the proposed evaluation indicators is improved, and finally, a risk classification evaluation indicator system for natural gas stations is established, which includes 4 primary risk classification evaluation indicators, 21 secondary risk classification evaluation indicators, 72 tertiary risk classification evaluation indicators, and 30 quaternary risk classification evaluation indicators.

[0064] The risk assessment system specifically includes a primary assessment system, a secondary assessment system, and a tertiary assessment system. The secondary assessment system is a subclass of each indicator system within the primary assessment system, and the tertiary assessment system is a subclass of each indicator system within the secondary assessment system.

[0065] The primary evaluation system includes a personnel structure system, a fixed facility system, an environmental system, and a management system. In this embodiment, the personnel structure system is a human factor, the fixed facility system is a physical factor, the environmental system is an environmental factor, and the management system is a management factor.

[0066] All risk factors are categorized into different indicator standards according to different levels of the system.

[0067] The personnel structure system includes employee knowledge and skills level indicators, employee psychological and physiological indicators, and employee behavior indicators.

[0068] The fixed infrastructure system includes indicators for the operation of production equipment and facilities, indicators for public and auxiliary production facilities, indicators for safety protection facilities, and indicators for the storage and use of hazardous chemicals;

[0069] The environmental system includes indicators of the surrounding environment of the station, indicators of the station's layout, indicators of the working environment, and indicators of the social environment.

[0070] The management system includes organizational management indicators, document management indicators, risk identification and hazard investigation and management indicators, emergency management indicators, occupational health management indicators, work permit management indicators, contractor work management indicators, process and equipment change management indicators, accident and time management indicators, and environmental protection measure implementation indicators.

[0071] The specific grading indicators, taking the personnel system as an example, are shown in Table 1:

[0072] Table 1

[0073]

[0074] S3: Using the analytic hierarchy process (AHP), based on the aforementioned risk assessment system, calculate the weights of the evaluation indicators for the natural gas station to be tested;

[0075] The specific steps for calculating the weights of the evaluation indicators for the natural gas station to be tested include:

[0076] Construct a judgment matrix between each indicator system in each evaluation system;

[0077] The values ​​of the elements in the judgment matrix reflect people's understanding of the relative importance of various factors (such as superiority, inferiority, preference, intensity, etc.), and are generally scaled from 1 to 9 and their reciprocals. When the importance of the factors being compared can be expressed by a ratio with practical significance, the value of the corresponding element in the judgment matrix can be taken as this ratio. Table 2 shows the scale of the judgment matrix and its meaning.

[0078] Table 2

[0079]

[0080] Based on the risk classification and evaluation index system for natural gas stations, a total of 34 judgment matrices were constructed. As shown in Tables 3 to 6, Table 3 presents the judgment evidence between the primary evaluation systems, and Table 4 presents the judgment matrices between the index systems under the fixed facility system; Table 3

[0081] Human Factors A1 1 1 / 4 4 1 / 2 Factor A2 of the object 4 1 5 3 Environmental Factors A3 1 / 4 1 / 5 1 1 / 4 Management Factors A4 2 1 / 3 4 1

[0082] Table 4

[0083]

[0084]

[0085] Table 5

[0086]

[0087] Table 6

[0088] Emergency Drill Frequency D25 1 4 5 Emergency drill coverage D26 1 / 4 1 3 Emergency Drill Type D27 1 / 5 1 / 3 1

[0089] The hierarchical sorting method is used to calculate the maximum eigenvalue and its corresponding eigenvector of each judgment matrix; the maximum eigenvalue and its corresponding eigenvector are normalized, and the consistency of the normalized data is checked to obtain the index weights of the evaluation system.

[0090] The weights of all evaluation system indicators are ranked hierarchically to obtain the weights of the evaluation indicators.

[0091] The maximum eigenvalue and its corresponding eigenvector of the matrix are calculated using hierarchical sorting. The power method for calculating matrix eigenvalues ​​allows us to obtain the maximum eigenvalue and its corresponding eigenvector with arbitrary precision using a computer. MATLAB software was used to calculate the maximum eigenvalue and eigenvector, followed by normalization and consistency checks. The weights of each level of indicators were then obtained, as shown in Tables 7-9. Table 7 shows the weight calculation results for the first-level evaluation indicators, Table 8 shows the weight calculation results for the second-level evaluation indicators, and Table 9 shows an example of the total ranking weights of the risk grading evaluation indicators for natural gas stations.

[0092] Table 7

[0093]

[0094]

[0095] Table 8

[0096]

[0097] Table 9

[0098]

[0099] S4: The risk assessment system is processed using quantitative indicators to obtain the quantitative values ​​of the indicators of the risk assessment system;

[0100] In step S4, the factors of each evaluation indicator are quantified. The quantification requirements are based on the enterprise's on-site safety inspection specifications and HSE management system quantitative audit standards. The inherent risks of energy or hazardous substances involved in the equipment and facilities, as well as potential risks in personnel, environment, and management, are also considered. A basic risk value is taken into account in the quantitative scoring. If the site does not involve a certain indicator, the value is 0; if the indicator exists but there are no unsafe conditions or situations, the basic risk value is generally set at 2 points; other cases are quantified according to the actual situation.

[0101] The quantitative values ​​of the indicators include static indicator values, dynamic indicator values, and additional coefficient values.

[0102] The static index quantification value is used to obtain the benchmark comprehensive risk index of the natural gas station to be tested, and the static index quantification value serves as the basis for dynamic risk management.

[0103] The initial scoring quantification of natural gas stations aims to obtain the station's basic risk level, i.e., the benchmark comprehensive risk index, which serves as the basis for dynamic risk management. In the initial scoring quantification, some indicators are quantified based on inherent risk factors, considering national laws, regulations, standards, and relevant corporate management requirements, and establishing an initial scoring quantification standard table. Other indicators are scored using interpolation, assigned scores of 0, 2, 5, and 10 for different scenarios, and scored according to the actual site conditions and the scoring instructions.

[0104] The dynamic indicator quantification value is used to obtain the dynamic risk index of the natural gas station under test; the dynamic scoring quantification of natural gas stations is to obtain the dynamic risk changes of the station and realize dynamic risk management. The indicators are mainly established based on the management system at all levels, focusing on continuous management and changing factors, such as the implementation of the system within the cycle, risky operations, process and personnel changes, etc., and also incorporate the results of supervision and inspection at all levels, HSE system audit, safety diagnosis and assessment, evaluation, etc. for dynamic adjustment of the score.

[0105] The additional coefficient quantification value is used to obtain the risk index of the process scale, the risk index of the production operation time, and the risk index of the processing medium of the natural gas station to be tested.

[0106] The static indicator quantification values ​​are established through a scoring and quantification standard table based on the enterprise's on-site safety inspection specifications and HSE management system quantitative audit standards.

[0107] The initial scoring quantification of natural gas stations aims to obtain the station's basic risk level, i.e., the benchmark comprehensive risk index, which serves as the basis for dynamic risk management. In the initial scoring quantification, some indicators are scored based on inherent risk factors, considering national laws, regulations, standards, and relevant corporate management requirements, and an initial scoring quantification standard table is established for scoring. Other indicators are scored using interpolation methods, assigned scores of 0, 2, 5, and 10 for different scenarios, directly based on the obtained characteristic points and the scoring instructions, reducing subjective scoring errors.

[0108] The purpose of dynamic scoring quantification for natural gas stations is to obtain dynamic risk changes at the stations and achieve dynamic risk management. The indicators are mainly established based on management systems at all levels, focusing on continuous management and changing factors, such as the implementation of systems, risky operations, and changes in processes and personnel within a cycle. At the same time, the results of supervision and inspection at all levels, HSE system audits, safety diagnosis and assessment, and evaluations are incorporated to dynamically adjust the scoring.

[0109] The method for obtaining the quantized value of the additional coefficient includes the following steps:

[0110] Obtain historical risk indicator additional coefficient data parameters and construct a risk indicator additional coefficient model;

[0111] The risk characteristics of the natural gas station to be tested are obtained, and the risk characteristics are input into the risk index additional coefficient model to obtain the quantitative value of the additional coefficient.

[0112] For example, when the risk characteristics collected are the gas quality of the site, there is no risk index additional coefficient when it is sulfur-free natural gas / shale gas. When it is low-sulfur natural gas, the additional coefficient is quantified as 0.4. When it is medium-high sulfur natural gas, the additional coefficient is quantified as 0.8. When it contains water, the additional coefficient is quantified as 0.2. When it contains condensate oil, the additional coefficient is 0.4.

[0113] If a certain indicator, after considering the risk indicator additional coefficient, is quantified to more than 10 points, it will be regarded as a key focus item for site hazard investigation and safety inspections at all levels.

[0114] If an indicator involves multiple risk characteristics, the additional coefficients are added together. For example, in the initial risk assessment of a certain station, which is a Class IV station with medium sulfur content, has been in operation for 7 years, and has a pressure vessel safety rating of Level 3, i.e., k1 = 0.8, k2 = 0.2, k3 = 0.4, k4 = 0.2, and other additional coefficients are not involved. During the evaluation process, the risk additional coefficient for the indicators under the production equipment and facility operation risk B4 and the public and auxiliary production facility risk B5 is 0.8, and the quantitative values ​​of all related indicators need to be multiplied by 1.8. The initial risk assessment value of this station should also be multiplied by 1.8 (k1 = 0.8).

[0115] If the total score of the site risk assessment after adding a coefficient is greater than the set total score, the site risk level will be directly set as Level IV risk.

[0116] S5: Construct a risk index model based on the weights of the evaluation indicators and the quantitative values ​​of the indicators;

[0117] The specific expression for the risk index model is as follows:

[0118]

[0119] R t x is the risk index. i x represents the quantified values ​​of evaluation indicators under the risk factor data for production equipment operation and the risk factor data for shared and auxiliary production facilities. j To divide x i The quantitative value of the evaluation index under the evaluation index factor data other than ω i For x i The corresponding weight value, ω jFor x j The corresponding weight values ​​are as follows: k1 is the index addition coefficient for the site's gas quality risk factor data, k2 is the index addition coefficient for the pressure vessel safety status risk factor data, k3 is the index addition coefficient for the process scale risk factor data, k4 is the index addition coefficient for the site's operating years risk factor data, k5 is the index addition coefficient for the system audit risk factor data, and k6 is the index addition coefficient for the total problem risk factor data.

[0120] For a specific natural gas station, the comprehensive risk index calculated in the first instance is recorded as the initial risk, i.e., x. i x j An initial score is used as the quantitative value; subsequent risk grading assessments are then performed based on dynamic risk, i.e., x. i x j Dynamic scoring quantification is used.

[0121] Dynamically sensing changes in risks enhances the targeting and precision of enterprise safety supervision, effectively improving regulatory efficiency. By comparing the actual dynamic situation of hazard investigation, such as the increase and elimination of items and changes in risk factors, with the changing trends and risk scoring information displayed by the evaluation model, it can intuitively reflect the weak links in station management and control, formulate rectification measures in a timely manner, and dynamically determine the regulatory focus for safety supervision departments. At the same time, through regular graded evaluation of natural gas stations, the focus of supervision and inspection can be adjusted in a timely manner.

[0122] S6: Analyze and detect the real-time risk of the natural gas station to be tested using the risk index model, and output a risk index to characterize the natural gas station to be tested.

[0123] The risk index used to characterize the natural gas station under test is specifically:

[0124] When R t <4.0, the natural gas station to be tested is in a low-risk state;

[0125] When 4.0≤R t <6.0, the natural gas station to be tested is in a general risk state;

[0126] When 6.0≤R t <8.0, the natural gas station to be tested is in a state of high risk;

[0127] When R t If the value is ≥8.0, the natural gas station to be tested is in a state of significant risk.

[0128] Establishing a site risk profile based on the site comprehensive risk index provides a more intuitive reflection of dynamic risk trends and facilitates enterprise safety decision-making and management. A site comprehensive risk index model has been defined and established, allowing enterprises to track site risk changes and establish site risk profiles, providing a basis for enterprises to make safety management decisions and laying the foundation for scientific risk prediction.

[0129] This embodiment discloses a risk detection method for natural gas stations. It couples inherent risk factors and dynamic risk factors together through the hierarchical analysis method from four aspects: human factors, material factors, environmental factors, and management factors in the accident system. This method implements the dual prevention mechanism and promotes the construction and improvement of the HSE management system. It integrates actual management into the evaluation model and identifies management problems through evaluation implementation, thereby promoting management improvement.

[0130] The method of quantifying and scoring risk indicators is scientifically refined, the evaluation implementation process is reasonably simplified, and the applicability and operability of the evaluation method are improved. It integrates the enterprise system audit requirements and safety inspection points, and provides the basis and standards for initial risk scoring and dynamic scoring. The evaluation is objective and simpler. In particular, dynamic scoring only requires the input of the risk factors that have changed, and the overall risk of the station can be recalculated, which is easy to operate.

[0131] Example 2

[0132] This embodiment discloses a risk detection system for natural gas stations. This embodiment aims to implement the detection method described in Embodiment 1. Figure 2 As shown, the detection system includes a data acquisition module, a system construction module, a weight calculation module, a quantification value calculation module, a model construction module, and a risk index calculation module;

[0133] The data acquisition module is used to acquire risk impact factor data of the natural gas station to be tested;

[0134] The system construction module is used to construct a hierarchical risk assessment system based on the risk influencing factor data.

[0135] The weight calculation module is used to calculate the weights of the evaluation indicators of the natural gas station to be tested based on the risk assessment system using the analytic hierarchy process.

[0136] The quantitative value calculation module is used to process the risk assessment system using a quantitative index method to obtain the quantitative values ​​of the risk assessment system indicators.

[0137] The model building module is used to build a risk index model based on the evaluation index weights and the index quantification values.

[0138] The risk index construction module is used to analyze and detect the real-time risk of the natural gas station to be tested using the risk index model, and output a risk index to characterize the natural gas station to be tested.

[0139] The specific embodiments described above further illustrate the purpose, technical solution, and beneficial effects of the present invention. It should be understood that the above description is only a specific embodiment of the present invention and is not intended to limit the scope of protection of the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

Claims

1. A natural gas field station risk detection method, characterized by, The detection method steps include: Obtain data on risk factors affecting the natural gas station to be tested; Based on the aforementioned risk influencing factor data, a hierarchical risk assessment system is constructed. Using the analytic hierarchy process (AHP), the weights of the evaluation indicators for the natural gas station under test are calculated based on the aforementioned risk assessment system. The specific steps for calculating the weights of the evaluation indicators for the natural gas station to be tested include: Construct a judgment matrix between each indicator system in each evaluation system; A hierarchical sorting method is used to calculate the maximum eigenvalue of each judgment matrix and its corresponding eigenvector. Normalize each largest eigenvalue and its corresponding eigenvector, and perform a consistency check on the normalized data to obtain the index weights of the evaluation system. The weights of all evaluation system indicators are ranked hierarchically to obtain the weights of the evaluation indicators. The risk assessment system is processed using quantitative indicators to obtain the quantitative values ​​of the indicators of the risk assessment system. Based on the weights of the evaluation indicators and the quantitative values ​​of the indicators, a risk index model is constructed. The quantitative values ​​of the indicators include static indicator values, dynamic indicator values, and additional coefficient values. The static index quantification value is used to obtain the benchmark comprehensive risk index of the natural gas station to be tested, and the static index quantification value serves as the basis for dynamic risk management. The dynamic index quantification value is used to obtain the dynamic risk index of the natural gas station to be tested; The additional coefficient quantification value is used to obtain the risk index of the process scale, the risk index of the production operation time, and the risk index of the processing medium of the natural gas station to be tested. The specific expression for the risk index model is as follows: ； As a risk index, These are the quantified values ​​of the evaluation indicators under the risk factor data for production equipment operation and the risk factor data for shared and auxiliary production facilities. To remove The quantitative values ​​of evaluation indicators under the evaluation indicator factors other than those mentioned above. for The corresponding weight value, for The corresponding weight value, This is an additional coefficient for the indicators of air quality risk factors at the site. Additional coefficients are added to the indicators of risk factors for the safety status of pressure vessels. Add coefficients to the indicators of process scale risk factor data. Add a coefficient to the indicators of risk factors related to the service life of the station. Add coefficients to the indicators of risk factor data for system auditing. Add a coefficient to the index of the total risk factor data of the problem; The risk index model is used to analyze and detect the real-time risk of the natural gas station under test, and outputs a risk index to characterize the natural gas station under test.

2. The method for risk detection at a natural gas station according to claim 1, characterized in that, The risk assessment system includes a primary assessment system, a secondary assessment system, and a tertiary assessment system. The secondary assessment system is a subclass of each indicator system within the primary assessment system, and the tertiary assessment system is a subclass of each indicator system within the secondary assessment system. The primary evaluation system includes personnel structure system, fixed facilities system, environmental system, and management system.

3. The method for risk detection at a natural gas station according to claim 2, characterized in that, The personnel structure system includes employee knowledge and skills level indicators, employee psychological and physiological indicators, and employee behavior indicators. The fixed infrastructure system includes indicators for the operation of production equipment and facilities, indicators for public and auxiliary production facilities, indicators for safety protection facilities, and indicators for the storage and use of hazardous chemicals; The environmental system includes indicators of the surrounding environment of the station, indicators of the station's layout, indicators of the working environment, and indicators of the social environment. The management system includes organizational management indicators, document management indicators, risk identification and hazard investigation and management indicators, emergency management indicators, occupational health management indicators, work permit management indicators, contractor work management indicators, process and equipment change management indicators, accident and time management indicators, and environmental protection measure implementation indicators.

4. The method for risk detection at a natural gas station according to claim 1, characterized in that, The static indicator quantification values ​​are established through a quantitative standard table based on the enterprise's on-site safety inspection specifications and HSE management system quantitative audit standards.

5. The method for risk detection at a natural gas station according to claim 4, characterized in that, The method for obtaining the quantized value of the additional coefficient includes the following steps: Obtain historical risk indicator additional coefficient data parameters and construct a risk indicator additional coefficient model; The risk characteristics of the natural gas station to be tested are obtained, and the risk characteristics are input into the risk index additional coefficient model to obtain the quantitative value of the additional coefficient.

6. The method for risk detection at a natural gas station according to claim 1, characterized in that, The risk index used to characterize the natural gas station under test is specifically as follows: When R t <4.0, the natural gas site to be detected is in a low-risk state; when 4.0 < R t <6.0, the natural gas site to be detected is in a general risk state; when 6.0 < R t <8.0, the natural gas site to be detected is in a high risk state; When R t ≥ 8.0, the natural gas field station to be detected is in a state of major risk.

7. A risk detection system for natural gas stations, characterized in that, The detection system, used to implement the method as described in any one of claims 1-6, includes a data acquisition module, a system construction module, a weight calculation module, a quantification value calculation module, a model construction module, and a risk index calculation module. The data acquisition module is used to acquire risk impact factor data of the natural gas station to be tested; The system construction module is used to construct a hierarchical risk assessment system based on the risk influencing factor data. The weight calculation module is used to calculate the weights of the evaluation indicators of the natural gas station to be tested based on the risk assessment system using the analytic hierarchy process. The quantitative value calculation module is used to process the risk assessment system using a quantitative index method to obtain the quantitative values ​​of the risk assessment system indicators. The model building module is used to build a risk index model based on the evaluation index weights and the index quantification values. The risk index calculation module is used to analyze and detect the real-time risk of the natural gas station to be tested using the risk index model, and output a risk index to characterize the natural gas station to be tested.

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