A gas pipeline leak detection technique and method

Abstract

A gas pipeline leak detection technology and method, belonging to the interdisciplinary field of risk assessment and information technology, includes: collecting various parameters of the gas pipeline; based on the collected parameters, using an improved Kent evaluation model to adjust and score the first set of indicators for urban environmental adaptability, determining the weights of the adjusted indicators using the analytic hierarchy process (AHP), and calculating the relative risk value of each pipe segment unit in combination with a second index; simulating an accident using a leak scenario model based on leak scenario parameters, and outputting the accident simulation results; spatially overlaying the relative risk value and the accident simulation results on the same electronic map, and outputting emergency response measures. This invention achieves accurate risk assessment of urban gas pipeline networks by combining an improved Kent evaluation model with the AHP, and provides intuitive and scientific technical support for risk management and emergency decision-making in gas pipeline networks by combining multi-model fusion leak accident simulation and visualization technology.

Description

Technical Field

[0001] This invention relates to a gas pipeline leak detection technology and method, which falls under the interdisciplinary field of risk assessment and information technology. Background Technology

[0002] With the adjustment of urban energy structures, natural gas, as a clean and efficient energy source, has become more widespread and developed. As a component of urban public infrastructure, gas pipeline systems are evolving towards larger capacity, larger scale, longer distance transmission, and multi-pressure levels.

[0003] However, with the expansion of the pipeline network and the increase in service life, the safe operation of gas pipeline systems faces many challenges. Most gas pipelines are laid underground and are subject to long-term effects such as soil corrosion, resulting in defects such as thinning and cracking of the pipe walls. At the same time, some construction units have not followed proper construction standards, and users have a weak sense of safety. These factors can all lead to gas leak accidents. Gas pipeline failure has serious consequences and may cause significant casualties and property damage.

[0004] To ensure the safe operation of gas pipeline networks, it is necessary to scientifically evaluate and manage pipeline risks. Currently, commonly used pipeline risk assessment methods include quantitative risk assessment, hazard and operability analysis (HAZOP), and fault tree analysis. Among these, quantitative risk assessment requires high-level basic information and is technically challenging. HAZOP and fault tree analysis are suitable for investigating specific situations, such as determining the optimal valve location or installing safety protection systems, but they are not suitable for systematically assessing the overall risk of the pipeline.

[0005] The Kent Rating Scale, proposed by W. Kent Muhlbauer in the UK, is a relatively complete and practical index-based rating method. It examines the likelihood of pipeline failure through four aspects: third-party damage, corrosion, design and operational errors, and combines the hazard of the medium and the impact of leakage to evaluate the consequences of failure, calculating the relative risk value of each pipe segment. However, this method is primarily designed for long-distance pipelines, and its direct application to urban gas pipeline networks has the following shortcomings: the evaluation indicators are not entirely applicable (e.g., direct calling systems, atmospheric corrosion, and internal corrosion protection measures are absent or infeasible in urban pipeline networks); factors such as frequent excavation, dense public facilities, and complex emergency response conditions in urban environments are not fully considered; and the weight allocation of each evaluation indicator lacks optimization and adjustment for urban pipeline networks. Summary of the Invention

[0006] To address the shortcomings of existing technologies, the present invention aims to provide a gas pipeline leak detection technology and method to solve the technical problems of existing gas pipeline network risk assessment methods, such as evaluation indicators not being applicable to urban environments, lack of targeted optimization of weight allocation, and lack of dynamic simulation and visualization of accident consequences.

[0007] To achieve the above objectives, the present invention provides a technical solution as follows: a gas pipeline leakage detection technology and method, the method comprising the following steps: S1. Data Acquisition Steps: Collect basic parameters, environmental parameters, and geographic information parameters of the gas pipeline; S2. Risk assessment steps: Based on the aforementioned basic parameters, environmental parameters, and geographic information parameters, the improved Kent evaluation model is used to adjust and score the urban environmental adaptability of the first indicator set. The weights of each indicator in the adjusted first indicator set were determined using the analytic hierarchy process (AHP); and The relative risk of each gas pipeline segment is calculated by combining a second index used to characterize the severity of the accident's consequences.

[0008] Furthermore, the first set of indicators includes third-party damage assessment indicators, corrosion assessment indicators, design assessment indicators, and misoperation assessment indicators, and the second index is the leakage impact index; The localization adjustments to the first set of indicators in the improved Kent evaluation model include: deleting the "direct call system" indicator from the third-party damage evaluation indicators and adding the "engineering excavation probability" indicator; deleting the "atmospheric corrosion", "internal anti-corrosion layer" and "pipeline cleaning" indicators from the corrosion evaluation indicators; and the localization adjustments to the second index include: adding "number of public facilities", "probability of secondary accident risk" and "distance to fire and rescue roads" as evaluation indicators in the calculation of the leakage impact index.

[0009] Furthermore, in the risk assessment step, the gas pipeline is divided into multiple independent pipe segment units according to geographical environment, population density, and burial conditions, and each pipe segment unit is scored based on various evaluation indicators in the first indicator set; and By combining the final weight values ​​obtained through the analytic hierarchy process (AHP) and the second index, the relative risk value of each pipe segment unit is calculated.

[0010] Furthermore, the reconstruction of the evaluation index weights using the analytic hierarchy process specifically includes: Construct the judgment matrix for each evaluation indicator in the first indicator set; Calculate the eigenvectors of the judgment matrix to obtain the initial weights of each indicator; A consistency test is performed on the judgment matrix. When the random consistency ratio CR is less than 0.1, the eigenvectors are normalized and used as the final weight values ​​of each indicator.

[0011] Furthermore, the relative risk value is calculated as follows: The scores of each evaluation indicator in the first indicator set for each pipe segment unit are multiplied by the final weight values ​​obtained through the analytic hierarchy process (AHP) to obtain a weighted index sum; and The weighted index is divided by the second index to obtain the relative risk value of each pipe segment unit.

[0012] Furthermore, it also includes accident simulation steps: Based on preset or real-time input leakage scenario parameters, the system uses a leakage accident model to simulate an accident and outputs the accident simulation results.

[0013] Furthermore, the leakage accident model is divided into a continuous leakage diffusion sub-model, a uniformly distributed diffusion sub-model, and an instantaneous leakage superimposed diffusion sub-model according to different wind speeds; Each sub-model calculates the natural gas concentration at each point downwind based on the input parameters of pipeline pressure, crack area, wind speed, and atmospheric stability.

[0014] Furthermore, in the accident simulation step, based on the calculated natural gas concentration, combined with the preset explosion limit concentration and toxic load criteria, the lethal zone, the seriously injured zone, the slightly injured zone, and the affected zone are automatically divided and rendered.

[0015] Furthermore, it also includes visualization and emergency decision-making steps: The relative risk value and the accident simulation results are spatially overlaid on the same electronic map, and emergency response measures corresponding to the current risk level or accident scenario are matched and output according to the preset emergency knowledge base.

[0016] Furthermore, in the visualization and emergency decision-making step, based on the overlaid risk level or accident scenario, a graded emergency response procedure is automatically matched from the emergency knowledge base and output. The graded emergency response procedure includes evacuation range suggestions, emergency organization responsibilities, and repair measures.

[0017] The beneficial effects of this invention are: This invention employs an improved Kent evaluation model, adapting the traditional evaluation index set to the unique operating environment of urban gas pipeline networks. This effectively solves the problem of poor applicability of traditional long-distance pipeline evaluation methods in complex urban environments. Furthermore, it innovatively introduces the analytic hierarchy process (AHP) to reconstruct the weights of key risk factors such as third-party damage, corrosion, design flaws, and operational errors. This avoids the arbitrariness of subjective weighting and makes the risk assessment results more objective and accurate in reflecting the actual risk level of each pipeline segment.

[0018] This application also integrates multiple leakage accident diffusion models, which can dynamically select the optimal model to calculate the diffusion of natural gas leakage based on different environmental parameters such as wind speed and atmospheric stability. Combined with preset explosion limit concentration and toxic load criteria, it automatically divides and visualizes the lethal zone, serious injury zone, minor injury zone and affected zone, providing a scientific basis for the quantitative assessment of accident consequences and making up for the shortcomings of existing technologies in accident simulation being single and having low visualization. By spatially overlaying risk assessment results and accident simulation results on the same geographic information system electronic map, unified management and interaction of risk distribution maps and accident damage area layers are achieved. This visual display enables managers to quickly identify high-risk areas and predict the scope of accident impact. At the same time, the system can automatically match and output graded emergency response procedures from the preset emergency knowledge base based on the current risk level or accident scenario displayed on the overlay, including specific evacuation range suggestions, emergency organization responsibilities and repair measures, providing accurate and efficient decision support for emergency command. Attached Figure Description

[0019] Other features, objects, and advantages of the present invention will become more apparent from the following detailed description of non-limiting embodiments with reference to the accompanying drawings: Figure 1 This is a schematic diagram illustrating the steps of a gas pipeline leak detection technology and method according to the present invention; Figure 2 This is a detailed schematic diagram illustrating the steps of Embodiment 1 of the present invention; Figure 3 This is a diagram of a natural gas pipeline in a certain city in Embodiment 3 of the present invention; Figure 4 This is a line graph showing the relative risk value of the natural gas pipeline in Embodiment 3 of the present invention. Detailed Implementation

[0020] To make the technical means, creative features, objectives and effects of this invention easier to understand, the invention will be further described below in conjunction with specific embodiments.

[0021] Example 1: Reference Figure 1 and Figure 2 As shown, this embodiment aims to provide a gas pipeline leak detection technology and method, which includes the following steps: S1. Data Acquisition Steps: Collect basic parameters, environmental parameters, and geographic information parameters of the gas pipeline; Specifically, the basic parameters include pipeline design pressure, working pressure, pipe diameter, material, wall thickness, burial depth, service life, and valve location. These data serve as the foundational inputs for risk assessment and accident simulation. Environmental parameters include soil corrosivity, groundwater conditions, frequency of surrounding construction activities, wind speed, wind direction, atmospheric stability, and weather conditions, which are used for subsequent accident diffusion simulation and corrosion risk assessment. Geographic information data includes the geographical environment along the pipeline (such as the distribution of roads, rivers, and buildings), population density, distribution of public facilities (such as schools, hospitals, and shopping malls), and distances to fire and rescue roads. These data are not only important bases for calculating the leakage impact index in the risk assessment module but also provide a spatial analysis basis for emergency decision-making after accident simulation.

[0022] S2. Risk assessment steps: Based on the aforementioned basic parameters, environmental parameters, and geographic information parameters, the improved Kent evaluation model is used to adjust and score the urban environmental adaptability of the first indicator set. The weights of each indicator in the adjusted first indicator set were determined using the analytic hierarchy process (AHP); and The relative risk of each gas pipeline segment is calculated by combining a second index used to characterize the severity of the accident's consequences.

[0023] Specifically, the first set of indicators refers to the general term for multiple indicators used to evaluate the possibility of pipeline failure. In this embodiment, it specifically includes four major categories of evaluation indicators: third-party damage, corrosion, design, and misoperation. The second index refers to the quantitative index used to evaluate the severity of the consequences of an accident. In this embodiment, it is specifically the leakage impact index. Specifically, the improved Kent evaluation model includes two parts: failure probability assessment and consequence severity assessment. In the failure probability assessment, four categories of evaluation indicators—third-party damage, corrosion, design flaws, and operational errors—are adjusted and scored to adapt to the urban environment. Specifically, considering the characteristics of urban pipe networks, the "direct access system" indicator in the third-party damage assessment is removed, and the "engineering excavation probability" indicator is added. The "atmospheric corrosion," "internal anti-corrosion layer," and "pipe cleaning" indicators in the corrosion assessment are removed. In the consequence severity assessment, a leakage impact index is used, and its calculation incorporates "number of public facilities," "probability of secondary accident hazards," and "distance to fire and rescue roads" as evaluation indicators to reflect the impact of the complex urban environment on accident consequences. During the risk assessment process, the gas pipeline is divided into multiple independent pipe segment units according to geographical environment, population density and burial conditions, and each pipe segment unit is scored by the first indicator set of various evaluation indicators. Subsequently, the weights of the evaluation indicators were reconstructed using the analytic hierarchy process (AHP), specifically including: Construct the judgment matrix for each evaluation indicator in the first indicator set; Calculate the eigenvectors of the judgment matrix to obtain the initial weights of each indicator; A consistency test is performed on the judgment matrix. When the random consistency ratio CR is less than 0.1, the eigenvectors are normalized and used as the final weight values ​​of each indicator. Finally, combining the final weight values ​​obtained through the analytic hierarchy process (AHP) and the second index, the relative risk value of each pipe segment unit is calculated. The calculation method for this relative risk value is as follows: The scores of each evaluation indicator in the first indicator set for each pipe segment unit are multiplied by the final weight values ​​obtained through the analytic hierarchy process (AHP) to obtain a weighted index sum; and The weighted index is divided by the second index to obtain the relative risk value of each pipe segment unit.

[0024] S3. Accident Simulation Steps: Based on the preset or real-time input leakage scenario parameters, use the leakage accident model to simulate the accident and output the accident simulation results. The leakage accident model is divided into three sub-models according to different wind speeds: when the wind speed is greater than 1 m / s, the continuous leakage diffusion sub-model is used; when the wind speed is less than 0.5 m / s, the uniform distribution diffusion sub-model is used; and when the wind speed is between 0.5 m / s and 1 m / s, the instantaneous leakage superposition diffusion model is used. Each sub-model calculates the natural gas concentration at each point downwind based on input parameters such as pipeline pressure, crack area, wind speed, and atmospheric stability.

[0025] Atmospheric stability is classified into six AF levels using the Pasquill method, as detailed in the table below: Table 1 Pasquill Atmospheric Stability Classification The diffusion coefficient was determined using the PG diffusion curve method, as recommended in the national standard GB3890-83. The PG diffusion curve method is a modification of the Pasquill and Gifford diffusion parameter estimation, used to represent the diffusion parameter as a curve, expressed as a near-power function. (1) In the formula, The crosswind diffusion coefficient represents the degree of diffusion of a natural gas cloud in the horizontal direction perpendicular to the wind direction. The vertical wind diffusion coefficient represents the degree of diffusion of a natural gas cloud in the vertical direction. Indicates the distance downwind. b, c, and d are coefficients that depend on atmospheric stability and ground roughness, and are taken from Table 2.

[0026] Table 2 Values ​​of diffusion parameters Based on the calculated natural gas concentration, combined with the preset lower explosive limit concentration (35800 mg / m³), upper explosive limit concentration (107500 mg / m³), and toxicity load criteria, the system automatically delineates the hazard zone. The toxic load criterion is calculated using the following formula: (2) In the formula, —Toxic load determines the degree of poisoning in victims (ppm·s); — Target dose-related coefficients; —Concentration of toxic substances (ppm); n —Correction factor, reflecting the role of the concentration of the reading material in the toxic effect; —Time of exposure to toxic substances (s); m —Correction factor, reflecting the role of exposure time in the poisoning effect; Based on the above concentration limits and toxic load criteria, the accident simulation process automatically divides and outputs the lethal zone, the seriously injured zone, the slightly injured zone, and the affected zone, and generates accident simulation results that include the division of the injury areas.

[0027] S4. Visualization and Emergency Decision-Making Steps: The relative risk value and the accident simulation results are spatially overlaid on the same electronic map; and based on the preset emergency knowledge base, emergency response measures corresponding to the current risk level or accident scenario are matched and output. In terms of visualization, this step plots the relative risk values ​​on an electronic map as a risk distribution map or risk contour map, intuitively displaying the risk level of each pipe section unit. At the same time, the accident simulation results are overlaid on the same electronic map with injury area layers rendered in different colors (such as fatal area, serious injury area, minor injury area, and impact area), realizing the spatial correlation between risk assessment results and accident simulation results, enabling managers to quickly identify high-risk areas and predict the scope of accident impact. In terms of emergency decision-making and response measures, the emergency knowledge base stores the physical and chemical properties of natural gas, emergency response procedures, and accident handling methods. Based on the visualization, it automatically matches and outputs graded emergency response procedures from the emergency knowledge base according to the overlaid risk level or accident scenario. The graded emergency response procedures include evacuation range suggestions, emergency organization responsibilities, and repair measures, providing intuitive and scientific technical support for the risk management and accident emergency response of gas pipelines, and realizing closed-loop management of the entire process from risk identification, evaluation, prediction to emergency response.

[0028] Example 2: This embodiment describes the specific implementation of the leakage accident model in Embodiment 1. Based on different wind speed conditions, the leakage accident model is divided into three sub-models: a continuous leakage diffusion sub-model, a uniformly distributed diffusion sub-model, and a transient leakage superimposed diffusion sub-model. 1. Leakage source strength calculation: Before performing leakage diffusion calculations, it is necessary to determine the leakage source strength (i.e., leakage rate). The formula for calculating the leakage source strength is as follows: (3) In the formula, —Natural gas leakage rate (kg / s); —Natural gas expansion factor; Inflation factor The calculation formula is as follows: (4) In the formula, —Specific heat ratio of natural gas (1.315); —Natural gas leakage coefficient, usually 1.00 for circular leaks (0.95 for triangular leaks; 0.90 for rectangular leaks); A — Leakage area (m²). —Natural gas pressure in the pipeline (Pa, the default value can be the rated pressure value of high-pressure and medium-pressure pipelines); —Natural gas density (0.76 kg / m³) 3 ); —Ambient pressure (Pa, default value can be standard atmospheric pressure 101.293×10) 3 ); 2. Leakage concentration calculation: This involves selecting an appropriate diffusion model based on the wind speed u. 2.1. Continuous Leakage Diffusion Sub-model (Wind Speed ​​> 1 m / s): When the wind speed is greater than 1 m / s, the natural gas concentration at each point downwind is calculated using the Gaussian plume model. In a spatial coordinate system with the leak source as the origin and the wind direction as the X-axis, the concentration at any point (x, y, z) is: (5) Where C(x,y,z) is the concentration (mg / m³) at the spatial point (x,y,z); —Leakage source strength (kg / s); u —Wind speed (m / s); — Gap width in the x-direction (m); — Gap width in the y direction (m); —Leakage time (s); —The downwind diffusion coefficient can be taken as 0 (m) since the leakage is continuous; —Crosswind diffusion coefficient (m); —Vertical wind diffusion coefficient (m); —Effective source height (m), which is equal to the sum of the leakage source height and the rise height (the default value can be 0), and its calculation formula is as follows: (6) in, — Leakage source height (m), the default value can be 0; — Lifting height, obtained from the lifting model, can be set to 0 by default.

[0029] 2.2. Uniformly Distributed Diffusion Sub-Model (Wind Speed ​​< 0.5 m / s): When the wind speed is less than 0.5 m / s, assuming the natural gas cloud is uniformly distributed around the leak source in all directions, the concentration at a distance r from the leak source is: (7) In the formula, —Concentration at a distance r (m) from the leak source ( ); —Leakage source strength (leakage rate); —Distance to the leak source (radial distance); —High effective source; , —Diffusion parameters, see Table 2 above; —Duration of calm wind, 2.3. Instantaneous leakage superimposed diffusion sub-model (0.5m / s≤wind speed≤1m / s): When the wind speed is between 0.5 m / s and 1 m / s, the continuous leakage is considered as the superposition of multiple instantaneous leakage gas clouds. The concentration at a point (x, y, z) in three-dimensional space with the leakage source as the origin and the downwind direction as the x-axis is: (8) (9) In the formula, C(x,y,z) is the concentration (mg / m³) at the spatial point (x,y,z). —The concentration contribution of a single instantaneous leaking plume at a spatial point (x,y,z); —Leakage source strength (leakage rate); —Downwind diffusion coefficient (m); —Crosswind diffusion coefficient (m); — Vertical wind diffusion coefficient (m); u — Wind speed (m / s); —Leakage time (s); —High effective source.

[0030] This model discretizes continuous leakage into instantaneous leakage within a time interval Δt, and superimposes the contributions of the leaking gas cloud at each time point to obtain the spatial concentration distribution at any time.

[0031] Example 3: This embodiment uses actual data from a high-pressure gas transmission pipeline in a certain city as an example to explain in detail the specific application process of the risk assessment module in Embodiment 1: 1. Piping Overview and Unit Division: A high-pressure gas pipeline in a certain city originates from the city gate station, bypasses an electric control valve, and is buried underground via a pig launcher. The pipeline has a design pressure of 4.0 MPa and a maximum working pressure of 3.5 MPa. The pipeline material is L360, with a nominal diameter of DN500. The main pipeline is 21.65 km long, and along the route are installed five DN500 control valves and one DN300 valve. The Chunjiang high- and medium-pressure regulating station is equipped with one DN500 pig launcher and receiver unit, one high- and medium-pressure regulating skid, two DN500 valves, and five DN300 valves. The pipeline route is as follows: Figure 3 As shown, the route passes through Qingyang Road, Shanghai-Nanjing Expressway, Changcheng Road, Laozaojiang River, Tongjiang Avenue, S338 Provincial Highway, and other places.

[0032] Based on the differences in geographical environment, population density and burial conditions along the pipeline route, the pipeline is divided into 28 pipe segment units, of which 19 are buried pipe segments and 9 are crossing pipe segments (including river crossings, road crossings, etc.).

[0033] 2. Evaluation Indicator Scoring: Taking pipe segment 1, pipe segment 5, and crossing 3 as examples, the first set of indicators for each pipe segment unit is scored. The evaluation indicators are shown in Tables 3-6 below: Table 3 Third-Party Factor Scoring Table 4 Corrosion Factor Scoring Table 5 Design Factor Scoring Table 6 Scoring of Error Factors 3. Weight Reconstruction using the Analytic Hierarchy Process (AHP): The weights of each indicator in the first indicator set (specifically: third-party damage (B1), corrosion (B2), design (B3), and misoperation (B4)) were reconstructed using the analytic hierarchy process. Based on the statistical data of buried pipeline accident factors in the region and combined with the opinions of pipeline construction technicians, operation and maintenance personnel, and safety management personnel, a judgment matrix was constructed as shown in Table 7.

[0034] Table 7 Two-Factor Judgment Table for a Buried Pipeline The eigenvectors of the judgment matrix B are calculated to be W = [0.444 0.283 0.165 0.107]. T ; Maximum eigenvalue =4.04, Consistency Index = (4.04-4) / (4-1)=0.013, average consistency index RI=0.9, n represents the number of evaluation indicators; random consistency ratio CR=CI / RI=0.013 / 0.9=0.014<0.10, so the hierarchical ranking results have satisfactory consistency. Therefore, the weights of the four factors of third-party damage, corrosion, design, and operation in pipeline accidents are 0.444, 0.283, 0.165, and 0.107, respectively.

[0035] 4. Calculation of relative risk value: Taking pipe section 1 as an example, the scores for each indicator in its first indicator set are as follows: third-party damage 77 points, corrosion 53 points, design 54 points, and misoperation 69 points. The weighted index is calculated as follows: The weighted index sum = 77 × 0.444 + 53 × 0.283 + 54 × 0.165 + 69 × 0.107 = 65.48; Based on the leakage impact index of this pipe section (assumed to be 4.0), calculate the relative risk value: Relative risk value = weighted index / leakage impact index = 65.48 / 4.0 = 16.37; The relative risk values ​​for all 28 pipe segment units were calculated using the same method, and the results are as follows: Figure 4 As shown in the figure, "line 1" represents the relative risk value before weight adjustment, and "line 2" represents the relative risk value after weight reconstruction using the analytic hierarchy process. The comparison shows that before adjustment (line 1), the risk values ​​of each pipe segment were not significantly different, making it difficult to effectively distinguish the risk levels; after adjustment (line 2), the distinguishability of the risk values ​​was significantly improved, and high-risk pipe segments could be clearly identified. according to Figure 4 The results shown by “Broken Line 2” indicate that the relative risk values ​​of pipe sections 7, crossing 4, pipe 8, pipe 9, pipe 12, pipe 13, crossing 7, and pipe 15 are relatively low (i.e., relatively high risk), belonging to relatively high-risk areas. The main reasons for this are that these pipe sections are located in areas with high population density, strong soil corrosivity, and relatively large impact from alternating current. For the aforementioned high-risk areas, this method can provide the following management recommendations: strengthen pipeline safety protection publicity in the area to raise public awareness of safety; increase the frequency of cathodic protection testing and strengthen corrosion protection measures; and assign dedicated personnel to supervise the excavation work of construction units near the pipeline to prevent third-party damage.

[0036] As can be seen from this embodiment, the improved Kent evaluation model proposed in this invention can effectively identify high-risk pipe sections in urban gas pipeline networks, providing a scientific basis for the hierarchical management and targeted protection of pipelines.

[0037] The foregoing has shown and described the basic principles, main features, and advantages of the present invention. It will be apparent to those skilled in the art that the present invention is not limited to the details of the exemplary embodiments described above, and that the invention can be implemented in other specific forms without departing from its spirit or essential characteristics. Therefore, the embodiments should be considered illustrative and non-limiting in all respects, and the scope of the invention is defined by the appended claims rather than the foregoing description. Thus, all variations falling within the meaning and scope of equivalents of the claims are intended to be included within the present invention. No reference numerals in the claims should be construed as limiting the scope of the claims.

[0038] Furthermore, it should be understood that although this specification describes embodiments, not every embodiment contains only one independent technical solution. This narrative style is merely for clarity. Those skilled in the art should consider the specification as a whole, and the technical solutions in each embodiment can also be appropriately combined to form other embodiments that can be understood by those skilled in the art.

Claims

1. A gas pipeline leak detection technology and method, characterized in that: The method includes the following steps: S1. Data Acquisition Steps: Collect basic parameters, environmental parameters, and geographic information parameters of the gas pipeline; S2. Risk assessment steps: Based on the aforementioned basic parameters, environmental parameters, and geographic information parameters, the improved Kent evaluation model is used to adjust and score the urban environmental adaptability of the first indicator set. The weights of each indicator in the adjusted first indicator set are determined using the analytic hierarchy process (AHP). and The relative risk value of each gas pipeline segment is calculated by combining a second index used to characterize the severity of the accident consequences.

2. The gas pipeline leakage detection technology and method according to claim 1, characterized in that: The first set of indicators includes third-party damage assessment indicators, corrosion assessment indicators, design assessment indicators, and misoperation assessment indicators, while the second index is the leakage impact index.

3. The gas pipeline leakage detection technology and method according to claim 2, characterized in that: In the risk assessment step, the gas pipeline is divided into multiple independent pipe segment units according to geographical environment, population density and burial conditions, and each pipe segment unit is scored by various evaluation indicators in the first indicator set. and By combining the final weight values ​​obtained through the analytic hierarchy process (AHP) and the second index, the relative risk value of each pipe segment unit is calculated.

4. The gas pipeline leakage detection technology and method according to claim 3, characterized in that: The reconstruction of evaluation index weights using the analytic hierarchy process specifically includes: Construct the judgment matrix for each evaluation indicator in the first indicator set; Calculate the eigenvectors of the judgment matrix to obtain the initial weights of each indicator; A consistency test is performed on the judgment matrix. When the random consistency ratio CR is less than 0.1, the eigenvectors are normalized and used as the final weight values ​​of each indicator.

5. The gas pipeline leak detection technology and method according to claim 4, characterized in that: The relative risk value is calculated as follows: The scores of each evaluation indicator in the first indicator set for each pipe segment unit are multiplied by the final weight values ​​obtained through the analytic hierarchy process (AHP) to obtain a weighted index sum; and The weighted index is divided by the second index to obtain the relative risk value of each pipe segment unit.

6. The gas pipeline leakage detection technology and method according to claim 1, characterized in that: It also includes accident simulation steps: Based on preset or real-time input leakage scenario parameters, the system uses a leakage accident model to simulate an accident and outputs the accident simulation results.

7. The gas pipeline leak detection technology and method according to claim 6, characterized in that: The leakage accident model is divided into three sub-models based on wind speed: continuous leakage diffusion sub-model, uniform distribution diffusion sub-model, and instantaneous leakage superposition diffusion sub-model. Each sub-model calculates the natural gas concentration at each point downwind based on the input parameters of pipeline pressure, crack area, wind speed, and atmospheric stability.

8. The gas pipeline leakage detection technology and method according to claim 7, characterized in that: In the accident simulation step, based on the calculated natural gas concentration, combined with the preset explosion limit concentration and toxic load criteria, the lethal zone, serious injury zone, minor injury zone and affected zone are automatically divided and rendered.

9. The gas pipeline leakage detection technology and method according to claim 1, characterized in that: It also includes visualization and emergency decision-making steps: The relative risk value and the accident simulation results are spatially overlaid on the same electronic map, and emergency response measures corresponding to the current risk level or accident scenario are matched and output according to the preset emergency knowledge base.

10. The gas pipeline leakage detection technology and method according to claim 9, characterized in that: In the visualization and emergency decision-making step, based on the overlaid risk level or accident scenario, a graded emergency response procedure is automatically matched from the emergency knowledge base and output. The graded emergency response procedure includes evacuation range suggestions, emergency organization responsibilities, and repair measures.

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