A method and system for gas system hazard grading early warning and decision-making

Abstract

The application provides a kind of method and system based on gas system hidden danger grading early warning and decision-making, belongs to gas pipeline grading early warning and decision-making field.To solve the problem that existing gas system early warning grading is single, response efficiency is low, integration is insufficient, and it is difficult to continuously optimize.The application carries out identity verification and permission control through a user management module;import and clean multi-source monitoring data through a data management module;quantitative analysis is carried out on single and coupled hidden dangers through a risk assessment module, and five-level early warning is generated based on a preset scoring threshold;disposal suggestions and emergency plans are automatically generated and recommended according to the early warning level through a decision support module;spatial annotation is carried out on an electronic map through a visualization module, and multi-sensory warning is carried out through icon dynamic flashing and hierarchical sound alarm with level linkage.The application realizes accurate grading evaluation of hidden dangers, intelligent decision support and stereoscopic alarm, significantly improves the intelligent level and emergency response efficiency of gas pipeline safety management.

Description

Technical Field

[0001] This invention relates to the field of gas pipeline classification early warning and decision-making technology, and more specifically, to a method and system based on gas system hidden danger classification early warning and decision-making. Background Technology

[0002] As a crucial component of urban lifeline engineering, the safe and stable operation of gas pipeline networks directly impacts public safety, environmental protection, and the normal order of the economy and society. With the acceleration of urbanization and the increasing scale of pipeline networks, the risks of safety accidents such as leaks and explosions caused by corrosion, third-party construction damage, equipment aging, and geological subsidence persist. Current technologies, at the early warning level, suffer from rudimentary warning grading and a lack of models for professionally assessing "coupled hazards" formed by the interaction of multiple factors, easily leading to false alarms and missed alarms. At the decision support level, system alarm information is simple, making it difficult to intelligently link emergency plans and knowledge bases, resulting in low response efficiency. At the information presentation level, it mainly relies on central audible and visual alarms, lacking tiered multi-sensory warnings, hindering rapid and intuitive perception. At the system management level, functional modules are scattered, making it difficult to form a complete closed loop from "multi-source data perception," "intelligent risk assessment," "precise decision support," to "three-dimensional warnings," resulting in insufficient integration and maintainability.

[0003] In summary, the current field of gas pipeline safety monitoring still has significant shortcomings in areas such as multi-dimensional data collaborative analysis and fusion diagnosis, coupled hazard quantitative assessment, intelligent hierarchical decision support, and immersive multi-sensory early warning presentation. There is an urgent need for an integrated technical solution to achieve accurate hazard identification, scientific classification, and efficient handling, thereby comprehensively improving the safety assurance capabilities and intelligent management level of gas pipeline networks. Summary of the Invention

[0004] The technical problem to be solved by this invention is:

[0005] To address the problems of existing gas systems having a single early warning level, low response efficiency, insufficient integration, and difficulty in continuous optimization.

[0006] The technical solution adopted by the present invention to solve the above-mentioned technical problems is as follows:

[0007] This invention provides a method for risk classification, early warning, and decision-making in gas system systems, comprising the following steps:

[0008] S100. Provide users with registration and login functions by entering their username and password in the user management module;

[0009] S200: Import the raw pipeline monitoring data from multiple sources into the data management module for data preprocessing to eliminate noise and outliers, and perform normalization.

[0010] S300. Input the pipeline monitoring data preprocessed in step S200 into the risk assessment calculation module, calculate the risk score, and conduct an early warning level assessment.

[0011] S400. The risk score and warning level obtained in step S300 are visualized through the visualization module. That is, the warning level is displayed graphically, and alarm prompts are given in combination with dynamic flashing lights and graded sounds.

[0012] After receiving the risk score and warning level from the risk assessment module in step S300, S500 generates corresponding emergency response suggestions for different warning levels through the decision knowledge base in the decision support module; for single hazards and coupled hazards, it provides single solutions and comprehensive solutions respectively, and recommends suitable emergency plans for commanders to refer to.

[0013] The S600 incorporates a design feedback optimization mechanism that transmits real-time status information from the visualization module back to the data management model. The decision support module records the actual application effects of the processing solutions, which are then fed back to the risk assessment module as feedback data to drive the continuous iteration and optimization of the risk assessment calculation model.

[0014] Furthermore, in step S200, when importing the original pipeline monitoring data, the data is imported according to the type of hidden danger, which includes encroachment, damage caused by third-party construction, ground subsidence, landslides, and pipeline aging and corrosion.

[0015] Furthermore, when the hazard type is a single hazard, the corresponding parameters for this single hazard need to be imported; when the hazard type is a coupled hazard, the corresponding parameters for each type of hazard need to be imported separately.

[0016] Furthermore, in step S300, the risk score is calculated as follows:

[0017] Suppose that each type of hidden danger contains m feature indicators, which correspond to m risk weights respectively. The risk score is calculated based on the normalized feature indicators and the risk weights. When n types of hidden dangers occur at the same time, the coupled risk score of the hidden danger is calculated based on the individual hidden danger risk score, the coupling enhancement factor, and the coupling matching factor.

[0018] Based on the risk scores of coupled hazards, graded early warnings are issued, and the risk score of an individual hazard is calculated using the following formula:

[0019] (1)

[0020] In the formula, This represents the risk score for the i-th individual hidden danger. The number of characteristic indicators for a single hidden danger; This is the normalized value of the k-th feature index; The risk weight of the k-th feature indicator;

[0021] The normalization method for feature indicators is as follows:

[0022] (2)

[0023] In the formula, The value of the k-th feature index; The maximum value of the kth feature index is used as the normalization benchmark.

[0024] The risk score for multiple coupled hidden dangers is calculated using the following formula:

[0025] (3)

[0026] In the formula, A risk score for the coupling of multiple hidden dangers; The number of types of hazards occurring simultaneously; This represents the risk score for the i-th type of hazard. Let be the coupling matching factor for the i-th type of hidden danger;

[0027] The coupling matching factor of the potential hazard is calculated using the following formula:

[0028] (4)

[0029] In the formula, Let be the coupling matching factor for the i-th type of hidden danger; This represents the maximum risk score among all types of potential hazards. This is the coupling enhancement factor for the i-th type of hidden danger;

[0030] The coupling enhancement factor of the hidden danger is calculated by the following formula:

[0031] (5)

[0032] The calculation method for the risk score of multiple coupled hidden dangers is as follows:

[0033]

[0034] (6).

[0035] Furthermore, in step S300, the preset risk score warning levels are divided as follows: 0≤risk score<20, no warning; 20≤score<40, level four warning; 40≤score<60, level three warning; 60≤score<80, level two warning; 80≤score<100, level one warning.

[0036] Furthermore, in step S400, the five warning levels are distinguished by the color of the light as black, red, orange, yellow and blue, and the flashing frequencies of the corresponding colors are 0.15s / time, 0.4s / time, 0.6s / time, 0.8s / time and 0s / time, respectively.

[0037] Furthermore, in step S400, five warning levels are distinguished by sound volume and frequency: 0.3s / time, 120dB, 0.8s / time, 100dB, 1.2s / time, 80dB, 1.6s / time, 60dB, and 0s / time, 0dB.

[0038] A system for classifying, warning, and making decisions regarding potential hazards in gas systems is provided. This system has program modules corresponding to the steps described above, and executes the steps in the method for classifying, warning, and making decisions regarding potential hazards in gas systems during runtime.

[0039] A computer-readable storage medium storing a computer program configured to, when invoked by a processor, implement steps of a method for graded early warning and decision-making regarding potential hazards in a gas system.

[0040] Compared with the prior art, the beneficial effects of the present invention are:

[0041] 1. A scientific leap has been achieved in hazard assessment, moving from qualitative to quantitative methods and from singular to coupled approaches. Through multi-dimensional data fusion technology, manually entered data, documented data, and real-time sensor data are effectively integrated. Not only are individual hazards independently quantified and scored, but innovatively, professional interaction analysis and comprehensive assessment of multi-factor "coupled hazards" are conducted, achieving scientific risk quantification and precise five-level early warning, overcoming the shortcomings of traditional methods that rely on single indicators and produce crude early warnings.

[0042] 2. An automated and intelligent response chain has been constructed, from intelligent early warning to precise decision-making. The system's decision support module has a built-in rule engine and is connected to a knowledge base, which can automatically generate tiered handling suggestions based on the early warning level. It provides collaborative solutions and intelligent matching of emergency plans for complex and coupled hidden dangers, significantly improving the scientific nature of emergency decision-making and response efficiency.

[0043] 3. It provides a three-dimensional, highly perceptive, multi-sensory early warning interactive experience. The visualization module uses dynamically flashing icons and tiered sound alarms that are strictly linked to the risk level, ensuring that alarms can be quickly and intuitively perceived under different environmental conditions, greatly enhancing the impact of the warnings and the operator's situational awareness.

[0044] 4. A closed-loop management system with self-optimization capabilities has been established. The system has an embedded feedback optimization loop that can feed back the actual application effect of the disposal plan to the risk assessment module, enabling the system to learn and evolve from historical data and practical experience, and continuously improve the accuracy of early warnings and the effectiveness of decision-making.

[0045] 5. This invention fundamentally promotes the innovation of gas safety management models. It deeply integrates data-driven approaches, intelligent analysis, and collaborative decision-making, changing the traditional passive management model that relies on manual experience. This significantly improves the ability to detect potential hazards early, the level of precision in risk control, and the scientific rigor and timeliness of emergency response, providing a solid technical guarantee for the safe and stable operation of urban gas pipeline networks. Attached Figure Description

[0046] Figure 1 This is a flowchart of a method for risk classification, early warning, and decision-making in a gas system according to an embodiment of the present invention. Detailed Implementation

[0047] To make the above-mentioned objects, features and advantages of the present invention more apparent and understandable, specific embodiments of the present invention will be described in detail below with reference to the accompanying drawings.

[0048] Specific Implementation Plan 1: Combining Figure 1 As shown, this invention provides a method for risk assessment, early warning, and decision-making based on gas system hazards, comprising the following steps:

[0049] S100: By entering a username and password in the user management module, users are provided with registration and login functions, and access security is ensured with strict identity verification. After the user enters the system, this module implements role-based access control to distinguish the operation scope and data access permissions of different identities such as administrators, operators, and viewers.

[0050] S200. Import various formats of raw pipeline monitoring data into the data management module. This raw pipeline monitoring data includes: for encroachment hazards (encroachment area, encroachment time, pipeline material, burial depth); for third-party construction damage (construction distance, construction type, protective measures, duration); for ground settlement (settlement amount, settlement rate, affected area, pipeline material); for landslides (displacement amount, slope, soil type, monitoring frequency); for pipeline aging and corrosion (corrosion depth, pipe age, pipe material type, anti-corrosion measures); and for other hazards (hazard description, discovery time, location description, urgency level). The module also preprocesses the raw pipeline monitoring data using a data cleaning function to effectively eliminate noise and outliers, providing a high-quality data foundation for subsequent analysis. Standardized data entry templates are provided to regulate data formats, and all processed monitoring data is stored and managed in a long-term, orderly manner to ensure efficient retrieval and backtracking of historical data.

[0051] The data management module supports manual parameter input for structured tables and documents, and enables quick hazard identification through preset drop-down menus, as well as file import functionality compatible with multiple data formats, thus effectively solving the problem of diverse data sources.

[0052] The data management module first performs intelligent cleaning on imported data in various formats, uses a threshold detection mechanism to monitor the data stream in real time to capture abnormal fluctuations, and can use the Naive Bayes algorithm to identify and correct abnormal data. At the same time, it converts multi-source heterogeneous data into a standardized format that can be processed internally by the system, providing high-quality input data for downstream analysis models.

[0053] S300. Through the risk assessment calculation module, the pipeline monitoring data preprocessed in step S200 is used to calculate the risk score using quantitative and qualitative methods. The warning level is divided according to which preset risk score threshold range the risk score falls into. The warning level includes five levels: black, red, orange, yellow and blue.

[0054] It should be noted that the risk assessment calculation model can not only independently and deeply assess and analyze a single hidden danger factor, but also handle complex coupled hidden dangers, analyze the interaction and superposition effect between multiple risk factors, and provide a basis for risk assessment of the entire platform.

[0055] In the risk assessment calculation module, a progressive calculation strategy is adopted. First, a weighted scoring model is used to independently quantify individual risk factors such as corrosion and abnormal pressure. Then, the interaction and superposition effects between multiple risk factors are coupled and analyzed. Finally, all parameters are integrated and machine learning algorithms such as random forest are used to calculate risk scores and generate five levels of early warning results. The preset scores are: 0 ≤ risk score < 20, no warning; 20 ≤ score < 40, level four warning; 40 ≤ score < 60, level three warning; 60 ≤ score < 80, level two warning; 80 ≤ score < 100, level one warning. Five warning levels are determined and output as black, red, orange, yellow, and blue, corresponding to level one (high risk), level two (relatively high risk), level three (moderate risk), level four (low risk), and no warning, respectively.

[0056] S400: The data and analysis results obtained in step S300 are transformed into easily understandable graphical information through the visualization module. The risk level is displayed intuitively using icons of different colors. High-risk levels are dynamically flashed to enhance visual warning. At the same time, tiered sound alarm prompts are provided to ensure that the alarm is perceived through multiple channels and in all aspects.

[0057] The visualization module can also display multi-dimensional evaluation results in rich charts, which greatly improves the efficiency and depth of situational understanding.

[0058] After the warning level is output in step S300, the visualization module is activated, transforming the abstract warning and decision-making information into an intuitive interactive interface. The visualization module displays the warnings visually using color icons corresponding to the warning levels, and simultaneously implements dynamic flashing of the warning icons at different time intervals for each level to enhance visual alertness. The five warning levels—black, red, orange, yellow, and blue—correspond to flashing times of 0.15s / time, 0.4s / time, 0.6s / time, 0.8s / time, and 0s / time, respectively. Simultaneously, the control center provides audible alarm prompts at different time intervals and volumes for each level. The five warning levels—black, red, orange, yellow, and blue—correspond to flashing times of 0.3s / time, 120dB, 0.8s / time, 100dB, 1.2s / time, 80dB, 1.6s / time, 60dB, and 0s / time, 0dB, respectively, ensuring that the alarm is perceived through multiple channels. Furthermore, it can display risk assessment results, historical trends, and other multi-dimensional information in rich chart formats, greatly improving the depth of understanding of the security situation and decision-making efficiency.

[0059] S500 receives the risk score obtained from the risk assessment module in step S300, and generates corresponding emergency response suggestions for different warning levels through the decision support module's built-in decision knowledge base that combines expert experience and existing knowledge base; especially in the face of complex coupled hidden dangers, it provides comprehensive solutions and recommends suitable emergency plans for commanders to refer to.

[0060] The decision support module receives analysis results and generates preliminary decision recommendations with priorities based on different warning levels. Simultaneously, the decision knowledge base matches historical cases and standard emergency plans to provide commanders with validated and optimal response strategies. For complex coupled risks, this module can also generate comprehensive solutions. All operations and decision-making processes based on system recommendations are fully recorded, forming a traceable handling archive. To ensure the stable operation and continuous optimization of the entire platform, the system management module is integrated throughout, allowing administrators to globally configure and personalize system parameters, export key assessment results and reports in standard formats, and meticulously record all operation logs and security audit logs for traceability.

[0061] It should be noted that this invention fully records all operations and decision-making processes performed based on system recommendations, forming a traceable and complete handling archive; it allows administrators to perform global configuration and personalized settings of system parameters to meet the needs of different application scenarios; the module supports exporting evaluation results, analysis reports, and other data in a standard format for easy reporting and archiving; it records system operation logs and security audit logs to provide a basis for troubleshooting and security tracing, and integrates system help and user manuals to provide users with timely technical support and usage guidance;

[0062] The S600 incorporates a feedback optimization mechanism that transmits real-time status information from the visualization module back to the data management model. The actual application effects of the processing solutions recorded by the decision support module are fed back to the risk assessment module as feedback data. This drives the continuous iteration and optimization of the risk assessment calculation model, enabling the system to learn from practice and continuously improve the accuracy of early warnings and the effectiveness of decision-making.

[0063] The specific steps of execution step S100 include:

[0064] (1) On the registration page, enter your username, a password of no less than six digits, and confirm the password to complete the registration;

[0065] (2) Login interface: Enter username and password to complete login.

[0066] Specifically, set the registered username to "user" and the password to "123456", confirm the password to "user", and enter the username "user" and password "123456" on the login screen to display a successful login message.

[0067] The specific steps of step S200 include:

[0068] (1) Select a single hazard assessment and choose the type of hazard;

[0069] (2) Input the hazard parameters in the hazard table;

[0070] (3) In step (1), select to switch to coupled hazard assessment, and select the first hazard type and the second hazard type;

[0071] (4) Enter the hazard parameters in the hazard table (as shown in Table 1 below) for the first and second hazard types respectively;

[0072] (5) After step (1) or step (3), select to import the values ​​from the Excel document;

[0073] (6) After step (1) or step (3), selecting the template will generate an Excel document containing the values ​​of potential hazards;

[0074] (7) After step (1) or step (3), select data preview to preview the data imported in step (5);

[0075] (8) Click to start the evaluation.

[0076] Table 1

[0077]

[0078] The specific steps of step S300 include:

[0079] (1) After jumping to the evaluation results, you can view the flashing icon and the interval sound alarm;

[0080] Specifically, a single hazard assessment is selected, with preset scores: 0 ≤ risk score < 20, no warning; 20 ≤ score < 40, Level 4 warning; 40 ≤ score < 60, Level 3 warning; 60 ≤ score < 80, Level 2 warning; 80 ≤ score < 100, Level 1 warning. The system accurately determines and outputs five warning levels: black, red, orange, yellow, and blue, corresponding to Level 1 (high risk), Level 2 (relatively high risk), Level 3 (moderate risk), Level 4 (low risk), and no warning, respectively.

[0081] The system selects a coupled hazard assessment, choosing the first and second hazard types to obtain assessment results: scores for Hazard 1 and Hazard 2. By introducing machine learning algorithms such as Random Forest and a coupled analysis model, a comprehensive score is obtained after coupling. Preset scores are: 0 ≤ risk score < 20, no warning; 20 ≤ score < 40, Level 4 warning; 40 ≤ score < 60, Level 3 warning; 60 ≤ score < 80, Level 2 warning; 80 ≤ score < 100, Level 1 warning. The system accurately determines and outputs five warning levels: black, red, orange, yellow, and blue, corresponding to Level 1 (high risk), Level 2 (relatively high risk), Level 3 (moderate risk), Level 4 (low risk), and no warning, respectively.

[0082] Specifically, to ensure the comparability of feature data with different dimensions and ranges, feature normalization is required. Each category implicitly contains m feature indicators, corresponding to m risk weights. A percentage-based risk score can be calculated based on the normalized feature indicators and risk weights. When n types of hazards occur simultaneously, a percentage-based hazard coupling risk score can be calculated based on the individual hazard risk score, coupling enhancement factor, and coupling matching factor. Graded early warnings are then implemented based on the hazard coupling risk score. The risk score for an individual hazard is calculated using the following formula:

[0083] (1)

[0084] In the formula, The risk score for the i-th individual hidden danger is expressed on a percentage basis. The number of characteristic indicators for a single hidden danger; This is the normalized value of the k-th feature index; The risk weight of the k-th feature indicator.

[0085] The general normalization method for feature indicators is as follows:

[0086] (2)

[0087] In the formula, The value of the k-th feature index; The maximum value of the k-th feature index is used as the normalization benchmark.

[0088] The characteristic indicators of various hidden dangers, their normalization benchmarks, and risk weights are detailed in Table 1.

[0089] The risk score for multiple coupled hidden dangers is calculated using the following formula:

[0090] (3)

[0091] In the formula, The risk score is calculated based on the coupling of multiple potential hazards, on a 100-point scale. The number of types of hazards occurring simultaneously; The risk score for the i-th type of hazard is on a percentage basis. is the coupling matching factor for the i-th type of hidden danger.

[0092] The coupling matching factor of the potential hazard is calculated using the following formula:

[0093] (4)

[0094] In the formula, Let be the coupling matching factor for the i-th type of hidden danger; This represents the maximum risk score among all types of potential hazards, expressed as a percentage. , which is the coupling enhancement factor for the i-th type of hidden danger.

[0095] The coupling enhancement factor of the hidden danger is calculated by the following formula:

[0096] (5)

[0097] The calculation method for the risk score of multiple coupled hidden dangers is as follows:

[0098]

[0099] (6)

[0100] The above-mentioned multi-hazard coupling risk scoring algorithm ensures that:

[0101] (1) Risk scores for individual hidden dangers can be calculated;

[0102] (2) When a certain implicit risk score is 100 points, regardless of the geometric risk scores of other hidden risks, the coupled risk score is 100 points;

[0103] (3) When the types of hazards and the risk scores of other hazards remain unchanged, if the risk score of a certain hazard increases, the score of the coupled risk also increases;

[0104] (4) The most significant risk is the dominant risk, which also has the greatest impact on the coupled risk score;

[0105] (5) When the number of hidden dangers increases (other hidden dangers and risk scores remain unchanged), adding a hidden danger will increase the coupled risk score.

[0106] The specific steps of execution step S400 include:

[0107] (1) After jumping to the evaluation results, you can view the flashing icon and the interval sound alarm;

[0108] Specifically, after navigating to the assessment results interface, the location of the warning point is clearly marked on the electronic map and displayed intuitively with color icons corresponding to the warning level. Simultaneously, the warning icons are dynamically flashed at different time intervals according to the warning level to enhance visual alertness. The five warning levels—black, red, orange, yellow, and blue—correspond to flashes of 0.15s / time, 0.4s / time, 0.6s / time, 0.8s / time, and 0s / time, respectively. In the control center, audible alarms at different time intervals and volumes according to the warning level are also provided. The five warning levels—black, red, orange, yellow, and blue—correspond to flashes of 0.3s / time, 120dB, 0.8s / time, 100dB, 1.2s / time, 80dB, 1.6s / time, 60dB, and 0s / time, 0dB, respectively, ensuring that the alarm is perceived through multiple channels.

[0109] The specific steps of execution step S500 include:

[0110] (1) After jumping to the evaluation results, you can view the processing decision;

[0111] Specifically, when selecting a single hazard assessment and choosing "occupancy" as the hazard type, if the assessment result is a Level 4 warning, the following decision recommendations can be viewed: Level 4 warning, increase monitoring frequency. Detailed recommendations: 1. Increase monitoring frequency to twice a week; 2. Prepare emergency plans; 3. Notify relevant management personnel. Hazard-specific recommendations: Recommendation: Remove the obstruction within a specified time and strengthen monitoring of this pipeline section. When the assessment result is no warning, conduct normal inspections. Detailed recommendations: 1. Maintain normal inspection frequency; 2. Record monitoring data; 3. No special treatment required. Hazard-specific recommendations: Recommendation: Develop a specific treatment plan based on the site conditions. When the assessment result is a Level 1 warning, immediately shut down operations and activate the emergency plan! Detailed recommendations: 1. Immediately stop operation; 2. Evacuate surrounding personnel; 3. Activate the highest level emergency plan; 4. Notify government emergency departments; 5. Prepare for media notification. Hazard-specific recommendations: Immediately remove the obstruction, and conduct pipeline inspection if necessary. For other hazard types and levels, see other embodiments of the method.

[0112] Alternatively, select Coupled Hazard Assessment, choose "Occupation" as the first hazard type and "Third-Party Construction Damage" as the second hazard type. If the assessment result is a Level 2 warning, click on the handling decision to view the decision recommendations: Level 2 Warning, arrange immediate repairs, and shut down operations if necessary. Coupled Warning Recommendations: 1. Prioritize handling according to urgency: address "Third-Party Construction Damage" first, then "Occupation"; 2. The two hazards may have a coupling effect, requiring comprehensive analysis; 3. It is recommended to develop a joint handling plan; 4. Monitor the mutual influence of the two hazards during the handling process. Occupation-Specific Recommendations: Mark the occupation location and conduct regular inspections. Third-Party Construction Damage-Specific Recommendations: Strengthen patrols to ensure compliance with construction plans. Comprehensive Recommendations: 1. Immediately activate the emergency plan and handle both hazards simultaneously; 2. Prioritize resolving the "Third-Party Construction Damage" issue, then address "Occupation"; 3. Establish a joint command team to coordinate the handling work.

[0113] Select the coupled hazard assessment, choose "Landslide" as the first hazard type and "Pipeline Aging Corrosion" as the second hazard type. If the assessment result is a Level 1 warning, click "Handling Decision" to view the decision recommendations: Level 1 Warning, Immediate shutdown, activate the emergency plan! Coupled Warning Recommendations: 1. Prioritize handling: address "Landslide" first, then "Pipeline Aging Corrosion"; 2. The two hazards may have a coupling effect, requiring comprehensive analysis; 3. A joint handling plan is recommended; 4. Monitor the mutual influence of the two hazards during the handling process. Landslide-Specific Recommendations: Regular inspections, paying attention to rainy season changes. Pipeline Aging Corrosion-Specific Recommendations: Continue existing anti-corrosion measures, conduct regular inspections. Comprehensive Recommendations: 1. Immediately activate the emergency plan, handling both hazards simultaneously; 2. Prioritize resolving "Landslide," then address "Pipeline Aging Corrosion"; 3. Establish a joint command team to coordinate the handling work. See other examples of the method for other hazard types and levels.

[0114] The specific steps in performing step S600 include:

[0115] (1) Click on the processing operation to enter the processing time, the person handling the processing, the specific operation, and the processing result;

[0116] (2) Click "Processing Complete" to jump to the evaluation results page. The page will display a green checkmark and stop flashing and alarm sounds.

[0117] (3) Click on the processing operation history to view the past records of hidden danger processing time, processor, specific operation, processing result, etc.;

[0118] (4) Click Export Report to export hazard records and handling operation records in various formats.

[0119] Specifically, you can enter the processing time: 2026-01-19; the processor: user; the specific operation: handle it promptly and properly according to the processing decision suggestions; and the processing result: the hidden danger has been eliminated. After recording, click "Processing Complete" to jump to the evaluation result page, where a green checkmark will be displayed, and the flashing and alarm sounds will stop. Click on the processing operation history to view this processing record.

[0120] Specific Implementation Scheme 2: The present invention provides a system for hierarchical early warning and decision-making of gas system hazards. The system has program modules corresponding to the above steps and executes the steps in the above-mentioned method for hierarchical early warning and decision-making of gas system hazards when running.

[0121] The other combinations and connections in this implementation scheme are the same as in Specific Implementation Scheme 1.

[0122] Specific Implementation Scheme 3: The present invention provides a computer-readable storage medium storing a computer program configured to implement, when called by a processor, the steps of a method for graded early warning and decision-making regarding potential hazards in a gas system.

[0123] The other combinations and connections in this implementation scheme are the same as in Specific Implementation Scheme 1.

[0124] Example 1: This example illustrates a specific implementation method for a single hazard assessment.

[0125] After completing registration and login, select Single Hazard Assessment, choose "Occupation" as the hazard type, and enter the occupied area: 80m². 2 The parameters include: occupancy time: 30 days, pipe material: PE pipe, burial depth: 1.5m, etc., or imported from an Excel document. Clicking "Start Evaluation" will take you to the evaluation results interface, where you will get the following score: 29.3, indicating a Level 4 warning. The interface displays a yellow triangle icon with a flashing interval of 0.8 seconds per flash. The time interval for different volume sounds is 1.6 seconds per flash, at 60dB. Clicking "Handling Decision" will display the recommended action: Level 4 warning, increase monitoring frequency.

[0126] Detailed recommendations: 1. Increase monitoring frequency to twice a week; 2. Prepare emergency plans; 3. Notify relevant management personnel. Specific recommendations for potential hazards: Recommendation: Remove obstructions within a specified time and strengthen monitoring of this section of pipeline. Click on the action, enter the action time, person in charge, specific actions, and action results, then click "Action Complete." You will then be redirected to the assessment results page, which will display a green checkmark.

[0127] Example 2: This example illustrates a specific implementation method for coupled hazard assessment.

[0128] After completing registration and login, select Coupled Hazard Assessment, choose the first hazard type as "Occupation", and enter the occupied area: 100m². 2 The parameters are as follows: Occupancy time: 120 days; Pipe material: PE pipe; Burial depth: 1.5m, etc. Select the second hazard type as "Third-party construction damage" and enter the parameters such as construction distance: 8m; construction type: Level 4; protection measures: Level 4; duration: 20 days, etc., or import values ​​from an Excel document. Click "Start Assessment" to jump to the assessment results interface. The assessment results are: Hazard 1 score: 60, Hazard 2 score: 88.8, Overall score: 74.4, which is a Level 2 warning. The interface displays a red triangle icon with a flashing interval of 0.4s / time, and the time interval for different volume sounds is 0.8s / time, 100dB. Click "Handling Decision" to view the decision suggestion: Level 2 warning, arrange repair immediately, and shut down if necessary. Coupled hazard assessment results: 1. Hazard 1: Occupancy (score: 60.0); 2. Hazard 2: Third-party construction damage (score: 88.8); 3. Overall score: 74.4.

[0129] Coupling Warning Recommendations: 1. Prioritize handling according to urgency: address "third-party construction damage" first, then "occupancy"; 2. The two hazards may have a coupling effect, requiring comprehensive analysis; 3. It is recommended to develop a joint handling plan; 4. Monitor the mutual influence of the two hazards during the handling process. Occupancy-Specific Recommendations: Mark the occupancy location and conduct regular inspections. Third-Party Construction Damage-Specific Recommendations: Strengthen patrols to ensure compliance with construction plans. Comprehensive Recommendations: 1. Immediately activate the emergency plan and handle both hazards simultaneously; 2. Prioritize resolving the "third-party construction damage" issue, then address "occupancy"; 3. Establish a joint command team to coordinate the handling work. Click the handling operation, enter the handling time, handler, specific operation, and handling result, then click "Handling Complete." This will redirect you to the assessment results page, which will display a green checkmark.

[0130] While the present invention has been disclosed above, its scope of protection is not limited thereto. Those skilled in the art can make various changes and modifications without departing from the spirit and scope of the present invention, and all such changes and modifications will fall within the scope of protection of the present invention.

Claims

1. A method for graded early warning and decision-making regarding potential hazards in gas systems, characterized in that, Includes the following steps: S100. Provide users with registration and login functions by entering their username and password in the user management module; S200: Import the raw pipeline monitoring data from multiple sources into the data management module for data preprocessing to eliminate noise and outliers, and perform normalization. S300. Input the pipeline monitoring data preprocessed in step S200 into the risk assessment calculation module, calculate the risk score, and conduct an early warning level assessment. S400. The risk score and warning level obtained in step S300 are visualized through the visualization module. That is, the warning level is displayed graphically, and alarm prompts are given in combination with dynamic flashing lights and graded sounds. S500: After receiving the risk score and warning level obtained from the risk assessment module in step S300, S500 generates corresponding emergency response suggestions for different warning levels through the decision knowledge base in the decision support module. For single and coupled hazards, we provide single and comprehensive solutions respectively, and recommend appropriate emergency plans for commanders to refer to. The S600 incorporates a design feedback optimization mechanism that transmits real-time status information from the visualization module back to the data management model. The decision support module records the actual application effects of the processing solutions, which are then fed back to the risk assessment module as feedback data to drive the continuous iteration and optimization of the risk assessment calculation model.

2. The method for graded early warning and decision-making of potential hazards in gas systems according to claim 1, characterized in that: In step S200, when importing the original pipeline monitoring data, the data is imported according to the type of hidden danger, which includes encroachment, damage caused by third-party construction, ground subsidence, landslides, and pipeline aging and corrosion.

3. The method for graded early warning and decision-making of potential hazards in gas systems according to claim 2, characterized in that: When the hazard type is a single hazard, the corresponding parameters for this single hazard need to be imported; when the hazard type is a coupled hazard, the corresponding parameters for each type of hazard need to be imported separately.

4. The method for graded early warning and decision-making regarding potential hazards in a gas system according to claim 3, characterized in that: In step S300, the risk score is calculated as follows: Suppose that each type of hidden danger contains m characteristic indicators, which correspond to m risk weights respectively. Calculate the risk score based on the normalized characteristic indicators and the risk weights. When n types of hidden dangers occur simultaneously, the hidden danger coupling risk score is calculated based on the individual hidden danger risk score, coupling enhancement factor, and coupling matching factor. Based on the risk scores of coupled hazards, graded early warnings are issued, and the risk score of an individual hazard is calculated using the following formula: （1） In the formula, This represents the risk score for the i-th individual hidden danger. The number of characteristic indicators for a single hidden danger; This is the normalized value of the k-th feature index; The risk weight of the k-th feature indicator; The normalization method for feature indicators is as follows: （2） In the formula, The value of the k-th feature index; The maximum value of the kth feature index is used as the normalization benchmark. The risk score for multiple coupled hidden dangers is calculated using the following formula: （3） In the formula, A risk score for the coupling of multiple hidden dangers; The number of types of hazards occurring simultaneously; This represents the risk score for the i-th type of hazard. Let be the coupling matching factor for the i-th type of hidden danger; The coupling matching factor of the potential hazard is calculated using the following formula: （4） In the formula, Let be the coupling matching factor for the i-th type of hidden danger; This represents the maximum risk score among all types of potential hazards. This is the coupling enhancement factor for the i-th type of hidden danger; The coupling enhancement factor of the hidden danger is calculated by the following formula: （5） The calculation method for the risk score of multiple coupled hidden dangers is as follows: （6）。 5. The method for graded early warning and decision-making regarding potential hazards in a gas system according to claim 4, characterized in that: In step S300, the preset risk score warning levels are divided as follows: 0 ≤ risk score < 20, no warning; A score of 20 or less and less than 40 indicates a Level 4 warning. A score of 40 ≤ score < 60 indicates a Level 3 warning; a score of 60 ≤ score < 80 indicates a Level 2 warning; and a score of 80 ≤ score < 100 indicates a Level 1 warning.

6. The method for graded early warning and decision-making of potential hazards in gas systems according to claim 5, characterized in that: In step S400, the five warning levels are distinguished by the color of the light: black, red, orange, yellow, and blue. The flashing frequencies of the corresponding colors are 0.15s / time, 0.4s / time, 0.6s / time, 0.8s / time, and 0s / time, respectively.

7. The method for graded early warning and decision-making regarding potential hazards in a gas system according to claim 6, characterized in that: In step S400, five warning levels are distinguished by sound volume and frequency: 0.3s / time, 120dB, 0.8s / time, 100dB, 1.2s / time, 80dB, 1.6s / time, 60dB, and 0s / time, 0dB.

8. A system for graded early warning and decision-making regarding potential hazards in gas systems, characterized in that: The system has a program module corresponding to the steps of any one of the claims 1-7 above, and executes the steps in the above-described method for hierarchical early warning and decision-making of gas system hazards when it is run.

9. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program configured to, when invoked by a processor, implement the steps of any one of claims 1-7: a method for graded early warning and decision-making regarding potential hazards in a gas system.

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