Safety control method and system for underground pipe network based on multiple grating pressure sensors

Abstract

The invention discloses a safety management and control method and system for an underground pipe network based on multiple grating pressure sensors, and relates to the technical field of underground pipe networks. The safety coefficient of the underground pipe network is determined based on the internal load parameters of the pipe network areas, the ground load parameters corresponding to the pipe network areas and the forms of the pipe network areas, the accuracy of the safety coefficient of the underground pipe network is guaranteed, and the safety condition of the underground pipe network is managed and controlled. If the safety coefficient of the underground pipe network is lower than the preset safety coefficient, the multiple abnormal nodes are determined according to the safety coefficient of the underground pipe network, the real-time pressure data of the multiple grating pressure sensors and the damage coefficients of the inner side walls of the multiple pipe network areas, and abnormal management and control of the underground pipe network are guaranteed. Therefore, the corresponding safety management and control measures are determined based on the abnormal area defined by the multiple abnormal nodes, the safety coefficient of the underground pipe network and the safety logic system, and the effectiveness and rationality of the safety management and control measures are guaranteed.

Description

Technical Field

[0001] The present invention relates to the technical field of underground pipe networks, and in particular to a safety management and control method and system for underground pipe networks based on multiple grating pressure sensors. Background Art

[0002] With the development of science and technology, underground pipelines are gradually applied to people's lives. The underground pipelines are located underground and contain multiple grating pressure sensors. The corresponding pressure data is measured by the grating pressure sensors. In the existing technology, the underground pipelines are divided into regions, and multiple pipeline areas are introduced. The safety factor of the underground pipelines is estimated based on the shape of each pipeline area, and the internal load parameters of each pipeline area and the ground load parameters corresponding to each pipeline area are not fully considered, which affects the accuracy of the safety factor of the underground pipeline. Summary of the invention

[0003] The purpose of the present invention is to overcome the deficiencies of the prior art. The present invention provides a safety management method and system for an underground pipe network based on multiple grating pressure sensors.

[0004] The embodiment of the present invention provides a safety management method for an underground pipe network based on multiple grating pressure sensors, including: determining multiple pipe network areas based on the underground pipe network and corresponding ground loads; In each pipe network area, a plurality of pressure nodes are determined based on the length of the pipe network area, the depth of the pipe network area, and the previous water level of the pipe network area, and the pressure nodes are matched with grating pressure sensors; Determine the internal load parameters of each pipe network area according to the real-time pressure data of multiple grating pressure sensors, the detection space formed by the multiple grating pressure sensors and the corresponding liquid types; Determine the safety factor of the underground pipe network based on the internal load parameters of each pipe network area, the ground load parameters corresponding to each pipe network area, and the morphology of each pipe network area; If the safety factor of the underground pipe network is lower than the preset safety factor, multiple abnormal nodes are determined according to the safety factor of the underground pipe network, the real-time pressure data of multiple grating pressure sensors, and the damage factor of the inner wall of multiple pipe network areas; Corresponding safety management and control measures are determined based on the abnormal area enclosed by multiple abnormal nodes, the safety factor of the underground pipeline network, and the safety logic system.

[0005] An embodiment of the present invention provides a safety management and control system for an underground pipe network based on multiple grating pressure sensors, the safety management and control system for an underground pipe network based on multiple grating pressure sensors is applied to the above-mentioned safety management and control method for an underground pipe network based on multiple grating pressure sensors, and the safety management and control system for an underground pipe network based on multiple grating pressure sensors includes: A pipe network area module, used to determine multiple pipe network areas based on the underground pipe network and the corresponding ground load; A pressure node module is used to determine a plurality of pressure nodes in each pipe network area based on the length of the pipe network area, the depth of the pipe network area and the previous water level of the pipe network area, and the pressure node is matched with a grating pressure sensor; A load parameter module, used to determine the internal load parameters of each pipe network area according to the real-time pressure data of multiple grating pressure sensors, the detection space formed by the multiple grating pressure sensors and the corresponding liquid types; A safety factor module is used to determine the safety factor of the underground pipe network based on the internal load parameters of each pipe network area, the ground load parameters corresponding to each pipe network area, and the morphology of each pipe network area; An abnormal node module is used to determine multiple abnormal nodes according to the safety factor of the underground pipe network, the real-time pressure data of multiple grating pressure sensors and the damage factor of the inner wall of multiple pipe network areas if the safety factor of the underground pipe network is lower than the preset safety factor; The safety management and control module is used to determine corresponding safety management and control measures based on the abnormal area enclosed by multiple abnormal nodes, the safety factor of the underground pipeline network and the safety logic system.

[0006] In an embodiment of the present invention, through the method in the embodiment of the present invention, multiple pipeline areas are determined based on the underground pipeline network and the corresponding ground load; in each pipeline area, multiple pressure nodes are determined based on the length of the pipeline area, the depth of the pipeline area and the previous water level of the pipeline area, and the pressure nodes match the grating pressure sensor; the internal load parameters of each pipeline area are determined according to the real-time pressure data of the multiple grating pressure sensors, the detection space formed by the multiple grating pressure sensors and the corresponding liquid types; the safety factor of the underground pipeline is determined based on the internal load parameters of each pipeline area, the ground load parameters corresponding to each pipeline area and the shape of each pipeline area, which is compatible with the overall consideration of the internal load parameters of each pipeline area, the ground load parameters corresponding to each pipeline area and the shape of each pipeline area, thereby ensuring the accuracy of the safety factor of the underground pipeline and managing the safety of the underground pipeline.

[0007] Furthermore, if the safety factor of the underground pipeline network is lower than the preset safety factor, multiple abnormal nodes are determined based on the safety factor of the underground pipeline network, the real-time pressure data of multiple grating pressure sensors and the damage coefficient of the inner walls of multiple pipeline areas. Multiple abnormal nodes are introduced to further analyze the abnormal conditions of the underground pipeline network, thereby ensuring the abnormal control of the underground pipeline network.

[0008] Therefore, corresponding safety control measures are determined based on the abnormal area enclosed by multiple abnormal nodes, the safety factor of the underground pipeline network and the safety logic system, realizing multiple interactions of the abnormal area enclosed by multiple abnormal nodes, the safety factor of the underground pipeline network and the safety logic system, thereby ensuring the effectiveness and rationality of the safety control measures. BRIEF DESCRIPTION OF THE DRAWINGS

[0009] Figure 1 A schematic diagram of an application scenario of a method for safety control of an underground pipe network based on multiple grating pressure sensors in an embodiment; Figure 2 It is a flow chart of a safety control method for an underground pipe network based on multiple grating pressure sensors in an embodiment of the present invention; Figure 3 It is a schematic diagram of the structural composition of the safety management and control system of the underground pipe network based on multiple grating pressure sensors in an embodiment of the present invention; Figure 4 The figure is a hardware diagram of an electronic device according to an exemplary embodiment. DETAILED DESCRIPTION

[0010] The technical solutions in the embodiments of the present invention will be described clearly and completely below in conjunction with the accompanying drawings in the embodiments of the present invention. Embodiment 1

[0011] The underground pipe network safety control method based on multiple grating pressure sensors provided in this application is applied to Figure 1 In the application environment shown, the computer 102 communicates with the server 104 through the network. The terminal 102 is but not limited to various personal computers, servers, underground pipe networks, and the server 104 is implemented by an independent server or a server cluster composed of multiple servers. Embodiment 2

[0012] See also Figures 1 to 4 A safety control method for an underground pipe network based on multiple grating pressure sensors is applied to a safety control scenario of an underground pipe network based on multiple grating pressure sensors; the safety control method for an underground pipe network based on multiple grating pressure sensors includes: Step S11: determining a plurality of pipe network areas based on the underground pipe network and the corresponding ground load; Step S12: In each pipe network area, a plurality of pressure nodes are determined based on the length of the pipe network area, the depth of the pipe network area, and the previous water level of the pipe network area, and the pressure nodes are matched with grating pressure sensors; Step S13: determining the internal load parameters of each pipe network area according to the real-time pressure data of the multiple grating pressure sensors, the detection space formed by the multiple grating pressure sensors, and the corresponding liquid types; Step S14: determining the safety factor of the underground pipe network based on the internal load parameters of each pipe network area, the ground load parameters corresponding to each pipe network area, and the shape of each pipe network area; Step S15: if the safety factor of the underground pipe network is lower than the preset safety factor, multiple abnormal nodes are determined according to the safety factor of the underground pipe network, the real-time pressure data of multiple grating pressure sensors, and the damage factor of the inner wall of multiple pipe network areas; Step S16: Determine corresponding safety management and control measures based on the abnormal area enclosed by the multiple abnormal nodes, the safety factor of the underground pipeline network, and the safety logic system.

[0013] In step S11, a plurality of pipe network areas are determined based on the underground pipe network and the corresponding ground load; In the specific implementation process of the present invention, the specific steps are: S111: locate the underground pipe network and collect the underground path of the underground pipe network; S112: Determine a corresponding ground track according to the underground path of the underground pipe network; S113: determining a corresponding ground load area according to the ground track, and determining a corresponding ground load distribution according to detection of the ground load area; S114: Determine multiple pipe network areas based on the ground load distribution, the underground path of the underground pipe network, and the layout of the underground pipe network.

[0014] In an embodiment of the present application, the underground pipe network is located, and the underground path of the underground pipe network is collected; the corresponding ground track is determined according to the underground path of the underground pipe network, and the ground track is introduced to facilitate subsequent control of the ground.

[0015] Specifically, the positioning of underground pipelines is introduced. For the positioning of underground pipelines, underground pipelines are usually hidden below the ground, so geological radar detection technology is needed to determine their locations.

[0016] After determining the location of the underground pipeline network, its underground path information needs to be collected, which usually involves measuring key parameters such as the starting point, end point, turning point, and burial depth along the way.

[0017] Optionally, the location of the underground pipe network is first determined using geological radar detection technology. By moving the radar device on the ground and collecting the reflected electromagnetic wave signals, a two-dimensional image of the underground pipe network is drawn. Specialized measurement tools are used to collect underground path information of the pipe network, including the starting point, end point, turning point, and buried depth of the pipe network, and the underground path of the underground pipe network is formed through this information.

[0018] At the same time, after obtaining the underground path information of the underground pipeline network, it needs to be mapped to the ground, which usually involves using a geographic information system (GIS) or other related software to convert the location and direction of the underground pipeline network into a track on the ground. The ground track is a visual representation of the underground pipeline network on the ground.

[0019] Furthermore, a corresponding ground load area is determined according to the ground track, and a corresponding ground load distribution is determined according to the detection of the ground load area, thereby realizing the detection of the ground load area and ensuring the accuracy of the ground load distribution.

[0020] At this point, after obtaining the ground trajectory of the underground pipeline network, the ground is divided into different load areas based on this information. These areas are usually divided based on factors such as the distribution of buildings on the ground, road types, soil types, and expected ground activities.

[0021] In each load area, field inspections or reference to relevant data are required to determine the load type and intensity of the area. This includes understanding information such as the building weight, traffic flow, and soil type's load-bearing capacity in the area. Based on the above inspections and analysis, a ground load distribution diagram is drawn. The ground load distribution diagram shows the load type and intensity of different load areas.

[0022] Specifically, after determining the ground track of the underground pipeline network, the ground along the line was divided into several load areas. For example, the area close to a large commercial area is classified as a high-load area because there are a large number of high-rise buildings and dense traffic in this area; while the area close to the park is classified as a low-load area because this area is mainly green space and a small number of low-rise buildings. In each area, a field survey was conducted to measure data such as the weight of the building, traffic flow, and the bearing capacity of the soil type for the load was considered. Finally, a ground load distribution map was drawn, showing the load type and intensity in different areas.

[0023] At the same time, multiple pipeline network areas are determined based on the ground load distribution, the underground paths of the underground pipeline network, and the layout of the underground pipeline network, which is compatible with the overall consideration of the ground load distribution, the underground paths of the underground pipeline network, and the layout of the underground pipeline network, and ensures the accuracy of the division of multiple pipeline network areas.

[0024] Specifically, the ground load distribution, underground paths of underground pipe networks, and the layout of underground pipe networks are introduced. At this time, the ground load distribution refers to the distribution of load types and intensities borne by different areas on the ground. Load types include building weight, traffic flow, crowd density, etc., while load intensity refers to the pressure or weight these loads exert on the ground.

[0025] The underground path of the underground pipe network refers to the actual direction and location of the underground pipe network. It includes key information such as the starting point, end point, turning point, pipe diameter, material, etc. of the pipe network.

[0026] The layout of the underground pipe network refers to the relative position and connection relationship between the pipe networks in the underground pipe network system. It includes key information such as intersections, branch points, and connecting pipes between the pipe networks.

[0027] Optionally, when determining the pipeline network area, the underground pipeline network is divided into multiple relatively independent areas by comprehensively considering the ground load distribution, the underground path of the underground pipeline network and the layout of the pipeline network. The division of these areas is intended to ensure that the pipeline network in each area can be properly monitored and managed. At the same time, considering the impact of the ground load on the pipeline network, different management strategies are formulated for different areas after the pipeline network area is determined.

[0028] Specifically, we first integrated the ground load distribution map, underground pipe network path map and layout map. The ground load in the city center is high due to dense buildings and busy traffic, while the load in the city fringe is relatively low. The underground pipe network is divided into three main areas: High-load core areas: including high-rise buildings and bustling commercial areas in the city center. The pipeline network in this area requires more frequent monitoring and maintenance to ensure normal operation under high-load conditions.

[0029] Medium-load transition area: located between the high-load core area and the urban fringe area, including some medium-density residential and industrial areas. The pipeline maintenance frequency in this area is moderate.

[0030] Low-load edge areas: mainly green spaces and low-density residential areas on the edge of the city, where the demand for pipeline maintenance is relatively low.

[0031] In addition, the trained pipeline area model is used to predict the new ground load distribution, underground pipeline path and layout data. Based on the prediction results, combined with actual conditions and urban planning needs, the underground pipeline network is divided into regions, and each pipeline area should have clear boundaries and signs.

[0032] In addition, according to the ground load distribution, the underground path and layout of the underground pipeline network, a pipeline area matching table is designed. The pipeline area matching table should contain different ground load types, intensities, pipeline path characteristics, layout patterns, etc. as matching conditions. For each matching condition, the corresponding pipeline area division suggestions and maintenance strategies are listed. When it is necessary to divide the new underground pipeline network into regions, according to the ground load distribution, pipeline path and layout, the most matching entry is found in the matching table. According to the matching results, the actual pipeline area division work is carried out by referring to the pipeline area division suggestions and maintenance strategies given in the pipeline area matching table.

[0033] In step S12, in each pipe network area, a plurality of pressure nodes are determined based on the length of the pipe network area, the depth of the pipe network area, and the previous water level of the pipe network area, and the pressure nodes are matched with grating pressure sensors; In the specific implementation process of the present invention, the specific steps are: S121: Acquire multiple pipe network areas, and perform synchronous management and control on the multiple pipe network areas; S122: In each pipe network area, the length and depth of the pipe network area are collected based on the traversal of the pipe network area; S123: tracing back the data of the pipe network area, and determining the previous water level of the pipe network area according to the tracing back the data of the pipe network area; S124: multiple interactions are performed on the length of the pipe network area, the depth of the pipe network area, and the previous water level of the pipe network area; S125: determining a first node parameter according to the length of the pipe network area and the depth of the pipe network area, and determining a second node parameter according to the length of the pipe network area and the previous water level of the pipe network area; S126: Determine a plurality of pressure nodes according to the pipe network area, the first node parameter, and the second node parameter, and the pressure nodes match the grating pressure sensor.

[0034] In an embodiment of the present application, multiple pipeline network areas are acquired and the multiple pipeline network areas are synchronously managed and controlled; in each pipeline network area, the length of the pipeline network area and the depth of the pipeline network area are collected based on the traversal of the pipeline network area, and the length of the pipeline network area and the depth of the pipeline network area are introduced.

[0035] Among them, multiple pipeline network areas are obtained, and the multiple pipeline network areas are further processed. At the same time, the multiple pipeline network areas are synchronously managed and controlled to facilitate detailed management of each pipeline network area.

[0036] In each pipe network area, the pipe network area is traversed. The traversal of the pipe network area means checking the pipe network area one by one according to a certain path or method. At the same time, in the process of traversing the pipe network area, the length and depth data of the pipe network area need to be collected. The length data of the pipe network area is obtained by measuring the actual length of the pipe network area or consulting the design drawings. The depth data of the pipe network area usually needs to be determined by field measurement or the use of professional equipment to determine the buried depth of the pipe network area underground.

[0037] Optionally, a professional team will be organized to traverse each pipe network area first, using professional pipe detection equipment to measure the length and depth of the pipe. For example, in a certain area, a drainage pipe was found to have a total length of 500 meters and an average burial depth of 2 meters. These data will be recorded and used in subsequent pipe network maintenance and management work.

[0038] Furthermore, data tracing is performed on the pipe network area, and the previous water level of the pipe network area is determined based on the data tracing of the pipe network area, thereby realizing data tracing of the pipe network area and ensuring further control of the previous water level of the pipe network area.

[0039] Specifically, data tracing is an important part of pipe network management, which involves the collection, organization and analysis of historical data of the pipe network, including the construction time, material, maintenance records, water level changes, etc. The purpose of data tracing is to understand the historical status of the pipe network and provide basic data support for subsequent pipe network maintenance, repair and optimization.

[0040] In the process of data tracing in the pipeline area, some technical means are needed, such as GIS (geographic information system), database management system, etc. These technologies help to efficiently collect, store and analyze pipeline data, and improve the accuracy and efficiency of data tracing.

[0041] After collecting historical data of the pipe network area, it is necessary to analyze these data to determine the previous water level of the pipe network area. The previous water level data is of great significance for understanding the hydraulic characteristics of the pipe network area, predicting future water level changes, and formulating maintenance strategies for the pipe network area. Methods for determining previous water levels include statistical analysis, mathematical model prediction, etc. These methods use the historical data of the pipe network area and combine it with current environmental conditions (such as rainfall, temperature, etc.) to calculate the water level of the pipe network area in a certain period of time in the past.

[0042] Therefore, multiple interactions are performed on the length of the pipe network area, the depth of the pipe network area and the previous water level of the pipe network area; the first node parameter is determined according to the length of the pipe network area and the depth of the pipe network area, and the second node parameter is determined according to the length of the pipe network area and the previous water level of the pipe network area, and the first node parameter and the second node parameter are introduced.

[0043] At this point, the length of the pipeline area, the depth of the pipeline area and the previous water level of the pipeline area are introduced, and a comprehensive analysis of the three key parameters of the length, depth and previous water level of the pipeline area is required. Multiple interactions mean that it is necessary to examine the relationship between these parameters and their impact on the operation of the pipeline network, which usually involves complex data analysis and modeling processes to determine how these parameters work together on the hydraulic performance of the pipeline area.

[0044] The first node parameters usually refer to hydraulic parameters directly related to the length and depth of the pipe network area, such as flow, pressure, flow velocity, etc. These parameters are crucial for evaluating the hydraulic performance of the pipe network. When determining the first node parameters, it is necessary to consider the impact of the length and depth of the pipe network area on the water flow. For example, longer pipe network areas require greater pressure to overcome resistance, while deeper pipe network areas need to consider the pressure and support of the soil on the pipe network area.

[0045] Second node parameters refer to other hydraulic parameters or performance indicators related to the length of the network area and the previous water level of the network area, such as leakage risk, pipeline stability, etc. These parameters help to further understand the status and potential problems of the network area. When determining the second node parameters, it is necessary to consider the impact of the length of the network area on the water flow path and the impact of the previous water level on the internal state of the pipeline. For example, longer pipelines are more likely to leak, and changes in the previous water level reflect the deposition, corrosion or blockage inside the pipeline.

[0046] Optionally, the first node parameters, including the pressure, flow rate and velocity at the inlet and outlet of the pipe, are calculated based on the length and depth of the pipe network. These parameters provide an important basis for subsequent pipe network optimization and maintenance. Based on the length of the above-mentioned urban water supply network and previous water level data, the second node parameters, including the leakage risk and stability index of the pipe, are calculated. These parameters help identify potential problem areas and formulate corresponding maintenance plans. For example, it is decided to focus on the inspection and maintenance of pipes with higher leakage risks to ensure the safety and reliability of water supply.

[0047] Therefore, multiple pressure nodes are determined according to the pipeline area, the first node parameters and the second node parameters. The pressure nodes are matched with grating pressure sensors to perform multi-dimensional control on the pipeline area, the first node parameters and the second node parameters, thereby ensuring the rationality of the distribution of multiple pressure nodes.

[0048] At this point, the network area, first node parameters and second node parameters are introduced. Further, a comprehensive analysis of the network area is conducted, including network layout, pipeline material, pipe diameter, historical operation data, etc. This information helps to understand the overall condition of the network and potential pressure change points. Combined with the first node parameters (such as flow, pressure, flow velocity, etc.) and the second node parameters (such as leakage risk, pipeline stability, etc.), the pressure fluctuation areas or key nodes in the network are further identified. These nodes are usually the most sensitive locations to pressure changes in the network. Multiple potential pressure nodes are further determined, and these nodes will serve as candidate locations for installing grating pressure sensors.

[0049] At the same time, according to the characteristics of the pipeline area and the specific needs of the pressure node, the appropriate grating pressure sensor model should be selected. This requires consideration of factors such as the sensor's measurement range, accuracy, stability, and installation environment. At the determined pressure node, the specific installation location should be determined based on the actual site conditions and the sensor's installation requirements. This requires consideration of factors such as the direction of the pipeline, the setting of the bracket, and the convenience of subsequent maintenance.

[0050] Specifically, taking a city's water supply network as an example, the network area is complex, including multiple branch pipes and connection points. In order to monitor the pressure changes in the network, we decided to use grating pressure sensors for real-time monitoring.

[0051] First, a comprehensive analysis of the pipeline network area was conducted, and multiple potential pressure nodes were identified by combining the first node parameters (such as flow and pressure) and the second node parameters (such as leakage risk and pipeline stability). These nodes are mainly distributed at the key branches of the pipeline network, pipeline intersections, and areas with large pressure fluctuations in historical records.

[0052] Next, we selected a grating pressure sensor model suitable for the characteristics of the pipe network area, and determined the specific installation location based on the actual situation on site. During the installation process, we strictly followed the installation instructions of the sensor and carried out necessary debugging work. After the installation was completed, the grating pressure sensor began to monitor the pressure changes in the pipe network in real time.

[0053] Another method is to collect the preset pressure node model, input the actual operating parameters of the pipeline network (such as the flow rate and water pressure of the first node and the second node), and use the pressure node model to calculate the water pressure values ​​of multiple other nodes in the pipeline network. Based on the calculation results, the hydraulic state of the pipeline network is analyzed and evaluated, such as whether there is insufficient or excessive water pressure.

[0054] In step S13, the internal load parameters of each pipe network area are determined according to the real-time pressure data of the multiple grating pressure sensors, the detection space formed by the multiple grating pressure sensors, and the corresponding liquid types; In the specific implementation process of the present invention, the specific steps are: S131: In each pipe network area, collect real-time pressure data of multiple grating pressure sensors; S132: collecting spatial positions of multiple grating pressure sensors; S133: forming a detection space according to the spatial positions of the plurality of grating pressure sensors and the shape of the pipe network area. At this time, the detection space is a detection space formed by the plurality of grating pressure sensors; S134: collecting liquid passing through the pipe network area, and determining the corresponding liquid type according to the detection of the liquid; S135: Associating the real-time pressure data of multiple grating pressure sensors, the detection space, and the corresponding liquid types; S136: Determine the internal load parameters of the pipe network area according to the real-time pressure data of the plurality of grating pressure sensors, the detection space and the corresponding liquid type, so as to determine the internal load parameters of each pipe network area.

[0055] In an embodiment of the present application, in each pipe network area, real-time pressure data of multiple grating pressure sensors are collected, and the real-time pressure data of the multiple grating pressure sensors are subsequently managed and controlled.

[0056] At this time, each pipeline area is controlled and monitored by introducing multiple grating pressure sensors to collect real-time pressure data from multiple grating pressure sensors. At the same time, the grating pressure sensors are connected to the data acquisition system to collect pressure data in real time.

[0057] Specifically, taking a city water supply system as an example, the water supply system includes multiple water supply areas, each of which has its own independent pipe network system. In order to monitor the pressure of the pipe network, the water supply system decided to collect real-time pressure data from multiple grating pressure sensors in each pipe network area. First, the pipe network areas that need to be monitored are identified, including three water supply areas A, B, and C. According to the characteristics and requirements of the water supply system, grating pressure sensors that can withstand high water pressure and are corrosion-resistant are selected.

[0058] Grating pressure sensors are installed at key locations in the three water supply areas A, B and C, such as pump station outlets and pipe network branches. The grating pressure sensors are connected to specially designed data acquisition instruments to achieve real-time data collection.

[0059] Furthermore, the spatial positions of multiple grating pressure sensors are collected; a detection space is formed according to the spatial positions of the multiple grating pressure sensors and the morphology of the pipe network area. At this time, the detection space is the detection space formed by the multiple grating pressure sensors, which is compatible with the overall consideration of the spatial positions of the multiple grating pressure sensors and the morphology of the pipe network area, thereby ensuring precise control of the detection space.

[0060] At this point, determine a unified coordinate system to accurately record the position of each grating pressure sensor, which is a geographic coordinate system (such as WGS84) and a local coordinate system (such as relative coordinates based on a fixed point); use a GPS locator, laser rangefinder or other measurement tools to accurately measure the geographic location of each grating pressure sensor, including longitude, latitude (if a geographic coordinate system is used) and horizontal and vertical distances relative to a reference point (if a local coordinate system is used), and record the measured position data, either in paper form or more commonly using a dedicated application on an electronic device (such as a tablet or smartphone) for subsequent data processing and analysis.

[0061] Optionally, in order to monitor the pressure of the pipe network, the park management decided to install grating pressure sensors at each key location. When collecting the spatial positions of these sensors, the geographic coordinate system (WGS84) was first determined, and then professionals were sent to the site to accurately measure the position of each sensor using a GPS locator.

[0062] At the same time, the spatial position data of the collected grating pressure sensors are imported into the GIS (Geographic Information System) software. Using the modeling function of the software, a three-dimensional model of the pipeline network is constructed according to the actual layout and form of the pipeline network, which includes all key elements such as pipelines, valves, and pumping stations. In the pipeline network model, the location of each grating pressure sensor is marked, which is usually achieved by adding points or icons to the model. According to the pipeline network model and the location of the sensor, one or more detection spaces are automatically or manually divided. These detection spaces are the areas covered by the sensors in the pipeline network for subsequent data analysis and monitoring.

[0063] Specifically, after collecting the spatial location data of all grating pressure sensors, the park management imported these data into the GIS software. Then, using the modeling function of the software, a three-dimensional model of the pipeline network was constructed based on the actual layout and form of the pipeline network. In the model, the location of each sensor was marked, and multiple detection spaces were automatically divided according to these locations. These spaces cover all key areas in the pipeline network, including the main water supply pipelines, branch pipelines, and pumping stations.

[0064] Furthermore, liquid passing through the pipe network area is collected, and the corresponding liquid type is determined based on the detection of the liquid, thereby realizing the detection of the liquid and ensuring the accuracy of the liquid type of the liquid.

[0065] At this point, select sampling points at key locations in the pipe network area, which are usually places where the liquid flow is stable and can represent the characteristics of the entire pipe network area. Use appropriate sampling containers and tools to collect liquid samples from the selected sampling points. Ensure that no external contamination is introduced during the sampling process.

[0066] The collected liquid samples are sent to the laboratory or tested using on-site testing equipment for chemical composition, physical properties, etc. These tests include the determination of indicators such as pH value, conductivity, dissolved oxygen, turbidity, organic content, etc. Based on the test results, combined with the known liquid property database or professional knowledge, the type of liquid collected is determined, which is water, oil, chemical solvent, etc.

[0067] Therefore, the real-time pressure data, detection space and corresponding liquid types of multiple grating pressure sensors are associated; the internal load parameters of the pipeline area are determined according to the real-time pressure data, detection space and corresponding liquid types of multiple grating pressure sensors, so as to determine the internal load parameters of each pipeline area, thereby realizing multi-dimensional control of the real-time pressure data, detection space and corresponding liquid types of multiple grating pressure sensors, and ensuring the accurate control of the internal load parameters of the pipeline area.

[0068] At this point, the pressure data is collected in real time from the grating pressure sensor, and the accuracy and completeness of the data are ensured. The collected pressure data is integrated with the previously determined detection space information, which usually involves associating the pressure data with the spatial location (such as GPS coordinates). Matching the detected liquid type with the corresponding detection space and pressure data requires the establishment of a database or data table to quickly query and associate information from different sources.

[0069] Conduct in-depth analysis of the associated data, including trend analysis of pressure data, distribution of liquid types, etc. Based on the analysis results, calculate the internal load parameters of the pipe network area, including flow rate in the pipe, pressure fluctuation range, energy consumption, etc. Compare and verify the calculated load parameters with the actual operation conditions to ensure the accuracy and reliability of the parameters. If necessary, adjust and optimize the parameters.

[0070] Optionally, after determining the type of liquid transported in each pipeline, this information is associated with the previously collected real-time pressure data of the grating pressure sensor. The pressure data is matched with the spatial location of the pipeline using GIS software, and the type of liquid transported in each pipeline is recorded in the database, so that the type of liquid transported in a specific pipeline and its corresponding pressure data at any given time point or time period can be queried at any time.

[0071] After correlating the pressure data, detection space, and liquid type, the information was analyzed in depth using data analysis software. It was found that some pipelines had large pressure fluctuations and high energy consumption when transporting specific types of liquids. Based on these findings, the internal load parameters of the pipeline network area were calculated, including the flow rate, pressure fluctuation range, and energy consumption of each pipeline. The calculated load parameters were then compared and verified with the actual operation conditions, and the operation strategies of some pipelines were adjusted and optimized based on the verification results to reduce energy consumption and improve the overall efficiency of the pipeline network system.

[0072] In addition, it was decided to use the internal load parameter matching table method to determine the internal load parameters of the pipe network area. First, based on historical data and experience, an internal load parameter matching table containing different pressure, detection space and liquid type combinations and corresponding load parameters was established. When it is necessary to determine the internal load parameters of a pipe network area, the manager searches the internal load parameter matching table for the combination that best matches the current pressure data, detection space information and liquid type, and obtains the corresponding load parameter value.

[0073] In step S14, the safety factor of the underground pipe network is determined based on the internal load parameters of each pipe network area, the ground load parameters corresponding to each pipe network area, and the morphology of each pipe network area; In the specific implementation process of the present invention, the specific steps are: S141: Obtaining internal load parameters of each pipe network area; S142: Determine multiple load characteristics based on the ground load distribution corresponding to each pipe network area; S143: determining ground load parameters corresponding to each pipe network area according to the relative positions of the multiple load features, the areas of the multiple load features, and the types of the multiple load features; S144: collecting the inner contours of each pipe network area, and determining the shape of each pipe network area based on the identification of the inner contours of each pipe network area; S145: performing multiple interactions on internal load parameters of each pipe network area, ground load parameters corresponding to each pipe network area, and the morphology of each pipe network area; S146: Determine the safety factor of the underground pipe network based on multiple interactions of internal load parameters of each pipe network area, ground load parameters corresponding to each pipe network area, and the shape of each pipe network area.

[0074] At this time, multiple load characteristics are determined based on the ground load distribution corresponding to each pipeline network area; the ground load parameters corresponding to each pipeline network area are determined according to the relative positions of the multiple load characteristics, the areas of the multiple load characteristics and the types of the multiple load characteristics, and the relative positions of the multiple load characteristics, the areas of the multiple load characteristics and the types of the multiple load characteristics are comprehensively considered to ensure the accuracy of the ground load parameters corresponding to each pipeline network area.

[0075] Specifically, the ground load distribution data corresponding to each pipeline network area is collected, and the collected ground load distribution data is deeply analyzed to understand the distribution characteristics of loads in different areas, including load density, intensity, change trend, etc. Based on the load distribution analysis results, load features that have an important impact on pipeline network safety are extracted, including building weight, population density, traffic flow, soil type, groundwater level, etc. The extracted load features are classified and coded to facilitate subsequent data processing and analysis.

[0076] At the same time, determine the spatial distribution of each load feature in the pipe network area, including their location, shape, size and other information. For each load feature, calculate the area it occupies in the pipe network area, which helps to understand the overall impact of the load feature on the pipe network area. According to the type of load feature and its impact on the safety of the pipe network, assign a weight value to each feature. This weight value reflects the importance of the feature in determining the ground load parameters. Based on the relative position, area and weight value of the load feature, calculate the ground load parameters corresponding to each pipe network area. This is a comprehensive indicator used to describe the overall load situation above the pipe network area.

[0077] In addition, the location, shape and size of these features in the pipeline area are determined, and the area occupied by each feature is calculated. Then, a weight value is assigned to each feature according to the degree of impact of these features on the safety of the pipeline network. Finally, based on the location, area and weight values ​​of these features, a specific algorithm or model is used to calculate the ground load parameters of each pipeline area. This parameter is a comprehensive indicator used to describe the overall load situation above the pipeline area and help managers understand the safety and stability of the pipeline network under different load conditions.

[0078] Also, when determining the ground load parameters corresponding to each pipe network area, the relative positions, areas and types of multiple load characteristics are considered comprehensively, and weights and scores are used for calculation.

[0079] Ground load parameters for network area A First, the load characteristics above the pipe network area A are identified, including building B, building C, road D, and green space E. According to the relative position of the load characteristics in the pipe network area, its impact on the safety of the pipe network is evaluated. For example, buildings located in the central area exert greater pressure on the pipe network.

[0080] Use GIS to determine the area occupied by each load feature in the network area. According to the type of load feature (such as residential, commercial, main road, public green space, etc.), combined with its impact on the safety of the network, a weight value is assigned to each feature. The weight value is usually between 0 and 1, and the sum of the weight values ​​of all features is 1. For each load feature, the area is multiplied by the weight to get a score. The score reflects the contribution of the feature to the ground load parameters of the network area.

[0081] The scores of all load characteristics are added together to obtain the total score of the ground load parameters of the pipeline network area A. This total score is used to evaluate the safety and stability of the pipeline network area under different load conditions.

[0082] Furthermore, the inner contour of each pipe network area is collected, and the shape of each pipe network area is determined based on the identification of the inner contour of each pipe network area, thereby realizing the identification of the inner contour of each pipe network area and ensuring the accuracy of the shape of each pipe network area.

[0083] At this time, the inner contour data of each pipe network area is collected, which includes the geometric shape, length, width, curvature, etc. of the pipe network. The collected data is processed and analyzed to identify the inner contour of each pipe network area, and the form of each pipe network area is determined based on the identified inner contour. The forms include straight line, curved, branched, etc., which reflect the spatial layout and structural characteristics of the pipe network.

[0084] Specifically, the pipe network area is photographed to obtain high-definition images. Then, the image is processed using image processing software to identify the inner contour of the pipe network area. Through comparison and analysis, it is determined that the shape of a certain pipe network area is curved because the pipes in the pipe network area present a series of continuous bends.

[0085] Therefore, multiple interactions are carried out on the internal load parameters of each pipeline network area, the ground load parameters corresponding to each pipeline network area, and the morphology of each pipeline network area; the safety factor of the underground pipeline network is determined based on the multiple interactions of the internal load parameters of each pipeline network area, the ground load parameters corresponding to each pipeline network area, and the morphology of each pipeline network area, thereby realizing the multiple interactions of the internal load parameters of each pipeline network area, the ground load parameters corresponding to each pipeline network area, and the morphology of each pipeline network area, and ensuring the accuracy of the safety factor of the underground pipeline network.

[0086] At this point, the internal load parameters (such as flow and pressure), ground load parameters (such as building weight and population density) and morphological data of each pipeline network area are integrated together to form a comprehensive data set. Multiple interactive analyses are performed on the data set, considering the interactions and influences between the internal load parameters, ground load parameters and morphology. Through multiple interactive analyses, the potential relationships between the internal load parameters, ground load parameters and morphology are identified. These potential relationships reveal the behavioral characteristics of the pipeline network under different load and morphological conditions.

[0087] Optionally, previously collected internal load parameters (such as flow and pressure data), ground load parameters (such as building weight and population density data), and pipe network morphology data are integrated together. Then, multiple interactive analyses are performed on these data using data analysis software. Through analysis, it is found that areas with higher flow and pressure are often located in areas with dense buildings and large populations. At the same time, the pipe network morphology in these areas also shows more bends, which indicates that ground load and pipe network morphology have an important impact on internal loads.

[0088] At the same time, the internal load parameters of each pipeline network area, the ground load parameters corresponding to each pipeline network area, and the multiple interactions of the morphology of each pipeline network area are introduced. Based on the results of the multiple interaction analysis, a prediction model for evaluating the safety factor of the underground pipeline network is constructed. The internal load parameters, ground load parameters and morphological data of each pipeline network area are input into the prediction model of the safety factor of the underground pipeline network to calculate the safety factor of each pipeline network area. The safety factor is a comprehensive indicator used to evaluate the safety and stability of the pipeline network under different load and morphological conditions. The internal load parameters, ground load parameters and morphological data of each pipeline network area are input into the model to calculate the safety factor of each pipeline network area. The safety factor is a comprehensive indicator used to evaluate the safety and stability of the pipeline network under different load and morphological conditions.

[0089] In addition, when determining the safety factor of the underground pipeline network, a weight and score method is used to comprehensively consider the multiple interactive effects of the internal load parameters of each pipeline area, the ground load parameters, and the pipeline morphology.

[0090] Calculation table of safety factor of underground pipe network Internal load parameter: 0.4 (reflects the internal fluid state of the pipeline network, which has a direct impact on safety); Ground load parameter: 0.3 (reflects the external load of the pipeline network, such as buildings, population density, etc.); Pipeline network form: 0.3 (reflects the spatial layout and structural characteristics of the pipeline network, affecting the difficulty of maintenance and overhaul); For each pipe network area, a score is given based on the internal load parameters, ground load parameters and specific conditions of the pipe network morphology. The score is set with different standards and levels according to the actual situation, such as the stability of flow and pressure, the density of buildings and population, and the complexity of the pipe network morphology.

[0091] The weighted scores of the internal load parameters, the ground load parameters, and the network morphology of each network area are added together to obtain a total score. The total score is divided by the highest total score (in this case, 300, which is the sum of the highest scores for each parameter) to obtain the safety factor. The closer the safety factor is to 1, the safer the network area is.

[0092] Although Area A and Area B have the same total score, their safety factors are different due to different weight distribution. Area A has a higher score for the pipe network shape (straight line, easy to maintain), so its safety factor is higher than that of Area B with the same total score. Although Area C has a lower score for internal load parameters, its safety factor is still within an acceptable range because its pipe network shape is relatively stable and its ground load parameter score is moderate.

[0093] In step S15, if the safety factor of the underground pipe network is lower than the preset safety factor, multiple abnormal nodes are determined according to the safety factor of the underground pipe network, the real-time pressure data of multiple grating pressure sensors, and the damage factor of the inner wall of multiple pipe network areas; In the specific implementation process of the present invention, the specific steps are: S151: Collect the safety system matched by the underground pipe network, and collect the preset safety factor corresponding to the underground pipe network according to the traversal of the safety system; S152: Compare the safety factor of the underground pipe network with the preset safety factor; S153: If the safety factor of the underground pipe network is lower than the preset safety factor, triggering the online safety control of the underground pipe network; S154: In the online safety control of the underground pipe network, damage images of inner walls of multiple pipe network areas are collected, and the damaged areas are determined based on the recognition of the damage images; S155: determining damage coefficients of inner walls of multiple pipe network areas according to the location of each damaged area, the area of ​​each damaged area, and the damage state of the damaged area; S156: Determine multiple abnormal nodes based on the safety factor of the underground pipe network, the real-time pressure data of multiple grating pressure sensors, and the damage coefficient of the inner wall of multiple pipe network areas.

[0094] At this time, the safety system matched by the underground pipeline network is collected, and the preset safety factor corresponding to the underground pipeline network is collected based on the traversal of the safety system; the safety factor of the underground pipeline network is compared with the preset safety factor, thereby realizing the comparison between the safety factor of the underground pipeline network and the preset safety factor.

[0095] Specifically, the safety system matching the underground pipe network is collected. Traversing the entire safety system means checking and accessing all relevant safety components and subsystems, which involves accessing the database, checking the status of sensors, reading historical records, etc. In the process of traversing the safety system, it is necessary to find and record the preset safety factors related to the underground pipe network. These factors are usually derived according to standards, specifications or risk assessments when the pipe network is designed or installed. They exist in the form of numbers, charts, reports, etc. Integrate the collected preset safety factors into a centralized data warehouse or database for subsequent analysis and comparison.

[0096] Before comparing the safety factor of the underground pipeline network with the preset safety factor, it is first necessary to calculate the current real-time safety factor. This requires collecting various data during the operation of the pipeline network, such as pressure, flow, temperature, etc., and using a specific algorithm or model to calculate the safety factor.

[0097] Select an appropriate comparison method, such as using a threshold value. The purpose of the comparison is to determine whether the current safety status of the pipeline network is within the preset safety range. Based on the comparison results, analyze the safety status of the pipeline network and record any abnormal conditions or potential risks. If the real-time safety factor is lower than the preset safety factor, it means that there is a safety risk in the pipeline network and further measures need to be taken.

[0098] Furthermore, if the safety factor of the underground pipeline network is lower than a preset safety factor, the online safety control of the underground pipeline network is triggered, thereby realizing the online safety control of the underground pipeline network.

[0099] At this point, the actual safety factor of the underground pipeline network is compared with the preset safety factor, which is usually done through an automated monitoring system that collects pipeline network operation data in real time and calculates the safety factor of the pipeline network based on this data. When the actual safety factor is lower than the preset safety factor, the system will automatically determine whether the trigger condition is met, which usually means that the pipeline network is currently in an unsafe state and immediate measures need to be taken to prevent potential accidents. Once the trigger condition is met, the system will immediately start online safety management and control, which includes but is not limited to issuing alarms, starting emergency response procedures, adjusting the operation status of the pipeline network, etc. The purpose of online safety management and control is to intervene in the pipeline network in the shortest possible time to reduce the likelihood of accidents or mitigate the impact of accidents.

[0100] Furthermore, in the online safety management and control of the underground pipeline network, damage images of the inner walls of multiple pipeline network areas are collected, and the damaged areas are determined based on the recognition of the damage images; the damage coefficients of the inner walls of the multiple pipeline network areas are determined according to the positions of the damaged areas, the areas of the damaged areas and the damage states of the damaged areas, which is compatible with the overall consideration of the positions of the damaged areas, the areas of the damaged areas and the damage states of the damaged areas, thereby ensuring the accuracy of the damage coefficients of the inner walls of the multiple pipeline network areas.

[0101] At this point, after the online safety control of the underground pipeline network is triggered, it is first necessary to deploy detection equipment in the key or suspected damaged areas of the pipeline network. These devices include high-definition cameras, visual inspection systems carried by drones, or specialized pipeline inspection robots. Use the deployed inspection equipment to collect detailed images of the inner wall of the pipeline network, which includes taking high-definition photos or recording videos to capture the detailed condition of the inner wall of the pipeline network. The collected image data is uploaded to the image recognition system, which uses advanced image processing and machine learning algorithms to identify and analyze the damaged areas in the image. Based on the results of image recognition, the system accurately determines the damaged area of ​​the inner wall of the pipeline network, including the location, shape, and preliminary judgment of the degree of damage.

[0102] Analyze the location of each damaged area in the pipeline network and evaluate its impact on the overall pipeline network safety. For example, pipelines with damage located at key nodes or high-pressure areas have a higher risk level. Use image analysis software or manual measurement to determine the area of ​​each damaged area, which is one of the important parameters for assessing the severity of the damage. Conduct a detailed analysis of the damage status of each damaged area, including the depth of the damage, the width of the cracks, and whether there are signs of corrosion or erosion. This information helps to more accurately assess the impact of the damage on the safety of the pipeline network. Combining the analysis results of location, area, and damage status, a specific algorithm or model is used to calculate the damage coefficient of each pipeline network area. This coefficient is a comprehensive indicator that reflects the severity of the damage to the inner wall of the pipeline network and its impact on the safety of the pipeline network.

[0103] Therefore, multiple abnormal nodes are determined based on the safety factor of the underground pipeline network, the real-time pressure data of multiple grating pressure sensors, and the damage coefficient of the inner walls of multiple pipeline areas. Multiple interactions are performed on the safety factor of the underground pipeline network, the real-time pressure data of multiple grating pressure sensors, and the damage coefficient of the inner walls of multiple pipeline areas to ensure the rationality of the distribution of multiple abnormal nodes.

[0104] At this point, the safety factor of the underground pipe network, the real-time pressure data of the grating pressure sensor, and the inner wall damage factor of the pipe network area are integrated into a comprehensive data platform or system. Advanced anomaly detection algorithms or machine learning models are used to analyze the integrated data. These algorithms identify data points that deviate from the normal state, that is, abnormal nodes. Based on the analysis results of the algorithm, abnormal nodes in multiple pipe network areas are determined. These nodes are areas with serious damage, abnormal pressure, or high safety risks. Risk assessment is performed on each identified abnormal node, and corresponding response measures are formulated, including emergency repairs, enhanced monitoring, and adjustment of the operation status of the pipe network.

[0105] Specifically, suppose that in a city's water supply system, a certain section of the underground pipe network has multiple damages due to aging. After triggering the online safety control, the system deployed high-definition cameras and pipeline inspection robots to collect detailed images of the inner wall of the pipe network. The image recognition system successfully identified multiple damaged areas on the inner wall of the pipe network, including some tiny cracks and corrosion spots. The system also determined the location of each damaged area and the initial degree of damage based on the image data. A detailed location assessment, area measurement, and damage status analysis were performed for each damaged area. For example, a damaged area located at a key node of the pipe network was assessed as high risk because it was large in area and accompanied by severe signs of corrosion. Based on these analysis results, the system calculated the damage coefficient of each pipe network area. The safety factor of the underground pipe network, the real-time pressure data of the grating pressure sensor, and the damage coefficient of the inner wall of the pipe network area were integrated. By applying the anomaly detection algorithm, the system successfully identified multiple abnormal nodes, including those with severe damage, abnormal pressure, or high safety risks. Based on the risk assessment results provided by the system, managers quickly formulated repair plans and emergency response measures to ensure the safe operation of the water supply system.

[0106] In addition, when determining multiple abnormal nodes in the underground pipeline network, a weight and score method is used for comprehensive evaluation. This method combines the safety factor of the underground pipeline network, the real-time pressure data of multiple grating pressure sensors, and the damage coefficient of the inner wall of multiple pipeline areas, so as to more accurately identify potential risk areas.

[0107] According to the safety assessment standards and historical data of underground pipeline networks, the safety factor, real-time pressure data and damage factor are assigned corresponding weights, which reflect the importance of each factor in assessing the safety of the pipeline network. The safety factor, real-time pressure data and damage factor are standardized to ensure that they are compared on the same scale, which usually involves converting the data into dimensionless fractions or percentages.

[0108] For each network area, the following formula is used to calculate its comprehensive score: Comprehensive score = (safety factor × weight 1) + (real-time pressure data × weight 2) + (damage factor × weight 3); where weight 1, weight 2 and weight 3 are the weights of safety factor, real-time pressure data and damage factor respectively. Pipeline network areas are sorted according to the calculated comprehensive score. Areas with lower scores indicate higher safety risks and are therefore considered abnormal nodes.

[0109] Consider a hypothetical underground water network system with three distinct network areas (A, B, C). Below are the normalized scores (converted to percentages) for each area's safety factor, real-time pressure data, and damage factor, along with the weights assigned to each factor: Calculate the composite score for each region using the above formula: Region A: Comprehensive score = (85 × 0.3) + (90 × 0.4) + (70 × 0.3) = 25.5 + 36+ 21 = 82.5; Region B: Comprehensive score = (95 × 0.3) + (75 × 0.4) + (60 × 0.3) = 28.5 +30 + 18 = 76.5; Region C: Comprehensive score = (70 × 0.3) + (85 × 0.4) + (90 × 0.3) = 21+ 34 + 27 = 82; According to the calculated comprehensive scores, the pipeline network areas are ranked as follows: Region A (82.5 points); Region C (82 points); Region B (76.5 points).

[0110] In this example, although the comprehensive scores of area A and area C are similar, the score of area B is lower, indicating that it has a higher security risk. Therefore, area B is regarded as an abnormal node and further inspection and maintenance are carried out on it.

[0111] In step S16, corresponding safety control measures are determined based on the abnormal area surrounded by the multiple abnormal nodes, the safety factor of the underground pipe network, and the safety logic system; In the specific implementation process of the present invention, the specific steps are: S161: Collect multiple abnormal nodes; S162: Determine a corresponding enclosure mode based on the relative positions of the multiple abnormal nodes and the shape of the pipe network area; S163: determining a corresponding abnormal area according to the multiple abnormal nodes and the corresponding enclosing patterns, where the abnormal area is an abnormal area enclosed by the multiple abnormal nodes; S164: Real-time monitoring of the online safety control of the underground pipe network; S165: collecting a safety logic system according to the online safety control monitoring of the underground pipe network, where the safety logic system is formed based on a comprehensive analysis of past safety events of the underground pipe network; S166: Multiple interactions are performed on the safety factors of multiple abnormal areas, underground pipeline networks, and safety logic systems, and corresponding safety management and control measures are determined based on the multiple interactions of the safety factors of multiple abnormal areas, underground pipeline networks, and safety logic systems.

[0112] At this time, multiple abnormal nodes are collected; the corresponding enclosure mode is determined based on the relative positions of the multiple abnormal nodes and the morphology of the pipeline area, which is compatible with the comprehensive consideration of the relative positions of the multiple abnormal nodes and the morphology of the pipeline area, and ensures the accuracy of the enclosure mode.

[0113] Specifically, multiple abnormal nodes are collected to identify the specific coordinates of each abnormal node in the pipe network, which is usually obtained through precise measurement and positioning technology. The relative position relationship of these nodes, such as distance, direction, etc., is analyzed.

[0114] Consider the overall layout of the network, such as the direction of the pipeline, branching, intersections, etc. Assess the complexity of the network area, including factors such as the density, curvature, and burial depth of the pipeline. Select the most appropriate enclosure mode based on the relative position of the abnormal nodes and the shape of the network area. Enclosure modes include polygonal enclosure, circular enclosure, irregular shape enclosure, etc., depending on the actual situation. The goal is to ensure that all abnormal nodes are enclosed while minimizing interference with the surrounding normal areas.

[0115] Furthermore, according to the enclosure pattern, the boundaries of the abnormal area are clarified. Ensure that the abnormal area completely contains all abnormal nodes, and appropriately consider a certain buffer zone to deal with errors and uncertainties. In the abnormal area, further analyze the direction, material, service life and other information of the pipeline. Identify the existing risk points, such as severely aged pipeline sections and areas prone to corrosion. Based on the analysis results of the abnormal area, formulate a targeted management plan.

[0116] Specifically, suppose that in a city’s water supply network, three abnormal nodes A, B, and C are discovered through monitoring and data analysis. These three nodes are located at different positions in the network, and each has potential leakage risks.

[0117] Abnormal node A is located on a main water supply pipeline near a residential area. Abnormal node B is located at the branch of another pipeline, surrounded by some commercial buildings. Abnormal node C is located in an industrial park, near a chemical plant.

[0118] After determining the relative positions of these nodes, the morphology of the pipe network area was further analyzed. It was found that the pipe network layout in this area is relatively complex, with multiple pipes crossing and branching. Taking these factors into consideration, it was decided to adopt a polygon enclosure mode to enclose the three nodes A, B and C in a closed polygonal area, which ensures that all abnormal nodes are covered while minimizing the impact on the surrounding normal water supply areas. After determining the polygon enclosure mode, the information in the abnormal area was further refined. It was found that there were many old pipes in the abnormal area, and some of the pipes showed signs of corrosion and leakage. Especially near the abnormal nodes A and C, the condition of the pipelines is particularly worrying.

[0119] At the same time, the corresponding abnormal area is determined according to the multiple abnormal nodes and the corresponding enclosure patterns. The abnormal area is the abnormal area enclosed by the multiple abnormal nodes, which realizes the overall consideration of the multiple abnormal nodes and the corresponding enclosure patterns and ensures the enclosure accuracy of the abnormal area.

[0120] At this point, according to the selected enclosure mode, the geographic information system (GIS) is used to draw the boundaries of the abnormal area on the pipeline layout map. Ensure that the boundaries completely contain all identified abnormal nodes and take into account a certain safety margin to deal with errors or uncertainties. After determining the boundaries of the abnormal area, further refine the pipeline network information in the area, including the material, specifications, service life, historical maintenance records, etc. of the pipeline, as well as any external factors that affect the safety of the pipeline, such as geological conditions, groundwater levels, traffic conditions, etc.

[0121] Based on the information inside the abnormal area, the risk level of the area is assessed, which usually involves quantitative analysis of the probability and impact of potential risk events such as pipeline leakage and explosion to determine whether additional safety measures are needed in the area. According to the risk level of the abnormal area, a targeted management plan is formulated, which includes measures such as strengthening monitoring, regular inspections, repairing or replacing pipelines, and setting up emergency response teams and supplies.

[0122] Suppose that in a city’s underground natural gas pipeline system, three abnormal nodes D, E, and F were discovered through data analysis. These three nodes are located in different positions of the pipeline network and have potential leakage risks.

[0123] The abnormal node D is located on a main gas pipeline, near a residential area. The abnormal node E is located at the branch of another pipeline, surrounded by some commercial buildings. The abnormal node F is located in an industrial area, near some heavy industrial equipment. Based on the location relationship of these nodes, a polygon enclosure mode was selected. Using GIS software, a polygon boundary was drawn on the pipeline layout map, which completely included the three abnormal nodes D, E and F, and considered sufficient safety margin.

[0124] In the abnormal area, many old pipelines were found, and some of them showed signs of corrosion. In particular, in the areas near abnormal nodes D and E, the pipelines were in service for a long time, and historical maintenance records showed that these areas had experienced several small-scale leaks. After quantitative analysis, the risk level of the abnormal area was determined to be medium-high, mainly because the pipelines in the area were severely aged and corroded, and there were a large number of residential areas and commercial buildings around them.

[0125] Furthermore, the online safety control of the underground pipeline network is monitored in real time; a safety logic system is collected based on the monitoring of the online safety control of the underground pipeline network, and a safety logic system is introduced. The safety logic system is formed based on a comprehensive analysis of previous safety incidents of the underground pipeline network.

[0126] At this time, the online safety control of the underground pipeline network is monitored in real time, and the online safety control of the underground pipeline network is monitored. At the same time, the previous safety event data is collected and analyzed, including the event type, time of occurrence, location, cause, etc. The data sources include accident reports, maintenance records, safety inspection reports, etc. Based on the results of historical data analysis, a safety logic system is constructed. The safety logic system should include risk identification, risk assessment, risk control and other links.

[0127] Collect and analyze data from past safety incidents. It was found that leaks often occurred in old pipelines, areas with complex geological conditions or heavy traffic. Based on these findings, a safety logic system was built to identify high-risk areas in the pipeline network. The safety logic system includes considerations of multiple factors such as pipeline age, material, geological conditions, and traffic conditions.

[0128] Therefore, multiple interactions are carried out on the safety factors of multiple abnormal areas, underground pipeline networks, and safety logic systems, and corresponding safety management measures are determined based on the multiple interactions of the safety factors of multiple abnormal areas, underground pipeline networks, and safety logic systems, thus achieving multiple interactions of the safety factors of multiple abnormal areas, underground pipeline networks, and safety logic systems, and ensuring the accuracy of the safety management measures.

[0129] At this time, the abnormal areas, safety factors and safety logic system are integrated to comprehensively analyze the safety status of multiple abnormal areas, the overall safety factor of the pipeline network and the predicted results of the safety logic system. According to the analysis results, targeted safety control measures are formulated.

[0130] After building the safety logic system, the water supply network management department began to use multiple interactive platforms to conduct a comprehensive analysis of multiple abnormal areas, the safety factors of the network, and the safety logic system. It was found that the safety risks in some abnormal areas were high, which was consistent with the prediction results of the safety logic system. Based on these findings, a series of safety control measures were formulated, including strengthening monitoring, regular inspections, and repairing or replacing old pipes. These measures were then implemented and their implementation effects were monitored.

[0131] Specifically, according to the nature, scope of impact and potential consequences of the anomaly, the abnormal area is divided into three levels: high, medium and low, and weights are assigned to them respectively: 0.5, 0.3 and 0.2. According to factors such as the material, service life and maintenance status of the pipeline network, the safety factor of the pipeline network is comprehensively evaluated, and the safety factor is divided into three levels: high (0.9-1.0), medium (0.6-0.8) and low (0.3-0.5). The security logic system includes multiple aspects such as network security, physical security and management security. Each aspect is assigned different weights according to its implementation effect, coverage and other factors. For example, the weight of network security is 0.4, the weight of physical security is 0.3, and the weight of management security is 0.3.

[0132] According to the level and number of abnormal areas, calculate the total score of abnormal areas. For example, if a certain area has 2 high-level abnormal areas, 3 medium-level abnormal areas, and 1 low-level abnormal area, the score of the abnormal area is 2×0.5+3×0.3+1×0.2=2.3. According to the safety factor level and length (or number) of the pipeline network, calculate the total safety factor score of the pipeline network. For example, the total length of the underground pipeline network in a certain area is 1,000 meters, of which the high-safety factor pipeline network accounts for 40%, the medium-safety factor pipeline network accounts for 50%, and the low-safety factor pipeline network accounts for 10%. The pipeline network safety factor score is 0.4×0.9+0.5×0.7+0.1×0.4=0.79. According to the implementation and evaluation results of various aspects of the safety logic system, calculate the scores of each aspect, and add up the weighted sum to get the total score. For example, if the network security score is 0.8, the physical security score is 0.7, and the management security score is 0.6, then the security logic system score is 0.4×0.8+0.3×0.7+0.3×0.6=0.74.

[0133] The weighted sum of the abnormal area score, underground pipeline safety factor score and safety logic system score is used to obtain a comprehensive score. The weights are assigned according to the actual situation. For example, the weight of the abnormal area is 0.4, the weight of the underground pipeline safety factor is 0.3, and the weight of the safety logic system is 0.3. The comprehensive score is 0.4×2.3+0.3×0.79+0.3×0.74=1.387. According to the comprehensive score, the corresponding safety control measures are determined. The higher the score, the greater the safety risk in the area, and more stringent and comprehensive control measures need to be taken. For example, when the comprehensive score is higher than 1.5, emergency measures need to be taken for rectification and reinforcement; when the score is between 1.0 and 1.5, monitoring and maintenance need to be strengthened; when the score is lower than 1.0, the existing control measures are maintained, but vigilance is still required. Embodiment 3

[0134] See also Figure 3 , Figure 3 It is a schematic diagram of the structural composition of a safety management and control system for an underground pipe network based on multiple grating pressure sensors in an embodiment of the present invention.

[0135] like Figure 3 As shown, a safety management and control system for an underground pipe network based on multiple grating pressure sensors, the safety management and control system for an underground pipe network based on multiple grating pressure sensors includes: A pipe network area module 21, for determining a plurality of pipe network areas based on the underground pipe network and the corresponding ground load; A pressure node module 22 is used to determine a plurality of pressure nodes in each pipe network area based on the length of the pipe network area, the depth of the pipe network area and the previous water level of the pipe network area, and the pressure nodes are matched with grating pressure sensors; A load parameter module 23, for determining internal load parameters of each pipe network area according to real-time pressure data of multiple grating pressure sensors, a detection space formed by multiple grating pressure sensors, and corresponding liquid types; A safety factor module 24 is used to determine the safety factor of the underground pipe network based on the internal load parameters of each pipe network area, the ground load parameters corresponding to each pipe network area, and the morphology of each pipe network area; The abnormal node module 25 is used to determine multiple abnormal nodes according to the safety factor of the underground pipe network, the real-time pressure data of multiple grating pressure sensors and the damage coefficient of the inner wall of multiple pipe network areas if the safety factor of the underground pipe network is lower than the preset safety factor; The safety control module 26 is used to determine corresponding safety control measures based on the abnormal area surrounded by multiple abnormal nodes, the safety factor of the underground pipeline network and the safety logic system. Embodiment 4

[0136] In this embodiment, an electronic device is provided. The internal structure diagram is as follows: Figure 4 As shown, the electronic device includes a processor, a memory, a network interface, a display screen and an input device connected through a system bus. Among them, the processor of the electronic device is used to provide computing and control capabilities, the memory of the electronic device includes a non-volatile storage medium and an internal memory, the non-volatile storage medium stores an operating system and a computer program, and the non-volatile storage medium is deployed with a database, the database is used to store user behavior data and user portraits, the internal memory provides an environment for the operation of the operating system and computer program in the non-volatile storage medium, the network interface of the electronic device is used to communicate with other electronic devices that deploy application software, and the computer program is executed by the processor to implement a low-altitude patrol method of a drone, the display screen of the electronic device is a liquid crystal display screen or an electronic ink display screen, and the input device of the electronic device is a touch layer covered on the display screen, a key, a trackball or a touchpad set on the housing of the electronic device, or an external keyboard, touchpad or mouse, etc.

[0137] The technical features of the above embodiments are arbitrarily combined. In order to make the description concise, not all combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

Claims

1. A safety control method for underground pipe network based on multiple grating pressure sensors, characterized in that: include: Determine multiple pipe network areas based on the underground pipe network and the corresponding ground loads; In each pipe network area, a plurality of pressure nodes are determined based on the length of the pipe network area, the depth of the pipe network area, and the previous water level of the pipe network area, and the pressure nodes are matched with grating pressure sensors; Determine the internal load parameters of each pipe network area according to the real-time pressure data of multiple grating pressure sensors, the detection space formed by the multiple grating pressure sensors and the corresponding liquid types; Determine the safety factor of the underground pipe network based on the internal load parameters of each pipe network area, the ground load parameters corresponding to each pipe network area, and the morphology of each pipe network area; If the safety factor of the underground pipe network is lower than the preset safety factor, multiple abnormal nodes are determined according to the safety factor of the underground pipe network, the real-time pressure data of multiple grating pressure sensors, and the damage factor of the inner wall of multiple pipe network areas; Corresponding safety management and control measures are determined based on the abnormal area enclosed by multiple abnormal nodes, the safety factor of the underground pipeline network, and the safety logic system.

2. The safety control method for underground pipe network based on multiple grating pressure sensors according to claim 1 is characterized in that: The determining of a plurality of pipe network areas based on the underground pipe network and the corresponding ground loads includes: Locate underground pipe networks and collect underground paths of underground pipe networks; Determine the corresponding ground track according to the underground path of the underground pipe network; Determine a corresponding ground load area according to the ground track, and determine a corresponding ground load distribution according to detection of the ground load area; A plurality of pipe network areas are determined based on the ground load distribution, the underground paths of the underground pipe network, and the layout of the underground pipe network.

3. The underground pipe network safety control method based on multiple grating pressure sensors according to claim 2 is characterized in that: In each pipe network area, a plurality of pressure nodes are determined based on the length of the pipe network area, the depth of the pipe network area and the previous water level of the pipe network area, and the pressure nodes are matched with grating pressure sensors, including: Acquire multiple pipe network areas and conduct synchronous management and control of multiple pipe network areas; In each pipe network area, the length and depth of the pipe network area are collected based on the traversal of the pipe network area; Conduct data tracing of the pipe network area, and determine the previous water level of the pipe network area based on the data tracing of the pipe network area; Multiple interactions are performed on the length of the pipe network area, the depth of the pipe network area, and the previous water level of the pipe network area; Determine a first node parameter according to the length of the pipe network area and the depth of the pipe network area, and determine a second node parameter according to the length of the pipe network area and the previous water level of the pipe network area; A plurality of pressure nodes are determined according to the pipe network area, the first node parameter and the second node parameter, and the pressure nodes match the grating pressure sensor.

4. The safety control method for underground pipe network based on multiple grating pressure sensors according to claim 3 is characterized in that: The method of determining the internal load parameters of each pipe network area according to the real-time pressure data of the plurality of grating pressure sensors, the detection space formed by the plurality of grating pressure sensors and the corresponding liquid types includes: In each pipe network area, real-time pressure data from multiple grating pressure sensors is collected; Collect the spatial positions of multiple grating pressure sensors; A detection space is formed according to the spatial positions of the plurality of grating pressure sensors and the shape of the pipe network area. At this time, the detection space is a detection space formed by the plurality of grating pressure sensors; Collect liquid passing through the pipe network area and determine the corresponding liquid type based on the detection of the liquid; Correlate the real-time pressure data of multiple grating pressure sensors, the detection space and the corresponding liquid types; The internal load parameters of the pipe network area are determined according to the real-time pressure data of multiple grating pressure sensors, the detection space and the corresponding liquid types, so as to determine the internal load parameters of each pipe network area.

5. The safety control method for underground pipe network based on multiple grating pressure sensors according to any one of claims 1 to 4, characterized in that: The method of determining the safety factor of the underground pipe network based on the internal load parameters of each pipe network area, the ground load parameters corresponding to each pipe network area, and the shape of each pipe network area includes: Obtain internal load parameters of each pipe network area; Determine multiple load characteristics based on the ground load distribution corresponding to each pipe network area; Determine the ground load parameters corresponding to each pipe network area according to the relative positions of the multiple load features, the areas of the multiple load features, and the types of the multiple load features; Collect the inner contours of each pipe network area, and determine the shape of each pipe network area based on the identification of the inner contours of each pipe network area; Multiple interactions are performed on the internal load parameters of each pipe network area, the ground load parameters corresponding to each pipe network area, and the morphology of each pipe network area; The safety factor of the underground pipeline network is determined based on the multiple interactions of the internal load parameters of each pipeline network area, the ground load parameters corresponding to each pipeline network area, and the morphology of each pipeline network area.

6. The safety control method for underground pipe network based on multiple grating pressure sensors according to claim 5 is characterized in that: If the safety factor of the underground pipe network is lower than the preset safety factor, multiple abnormal nodes are determined according to the safety factor of the underground pipe network, the real-time pressure data of multiple grating pressure sensors, and the damage factor of the inner wall of multiple pipe network areas, including: Collect the safety system matched by the underground pipe network, and collect the preset safety factor corresponding to the underground pipe network according to the traversal of the safety system; Compare the safety factor of the underground pipe network with the preset safety factor; If the safety factor of the underground pipeline network is lower than the preset safety factor, the online safety control of the underground pipeline network will be triggered.

7. The safety control method for underground pipe network based on multiple grating pressure sensors according to claim 6 is characterized in that: If the safety factor of the underground pipe network is lower than the preset safety factor, multiple abnormal nodes are determined according to the safety factor of the underground pipe network, the real-time pressure data of multiple grating pressure sensors, and the damage factor of the inner wall of multiple pipe network areas, and further comprising: In the online safety control of the underground pipe network, the online safety control of the underground pipe network is collected; Collect damaged images of inner walls of multiple pipe network areas, and determine damaged areas based on recognition of the damaged images; Determine the damage coefficient of the inner wall of the plurality of pipe network areas according to the location of each damaged area, the area of ​​each damaged area and the damage state of the damaged area; Multiple abnormal nodes are determined based on the safety factor of the underground pipe network, the real-time pressure data of multiple grating pressure sensors, and the damage coefficient of the inner wall of multiple pipe network areas.

8. The safety control method for underground pipe network based on multiple grating pressure sensors according to claim 7 is characterized in that: The corresponding safety control measures are determined based on the abnormal area surrounded by multiple abnormal nodes, the safety factor of the underground pipe network and the safety logic system, including: Collect multiple abnormal nodes; Determine the corresponding enclosure mode based on the relative positions of multiple abnormal nodes and the shape of the pipe network area; A corresponding abnormal area is determined according to the multiple abnormal nodes and the corresponding enclosure mode, and the abnormal area is an abnormal area enclosed by the multiple abnormal nodes.

9. The underground pipe network safety management and control method based on multiple grating pressure sensors according to claim 8 is characterized in that: The determining of corresponding safety control measures based on the abnormal area surrounded by the multiple abnormal nodes, the safety factor of the underground pipe network and the safety logic system also includes: Real-time monitoring of the online safety management of the underground pipeline network; A safety logic system is collected based on the online safety control monitoring of the underground pipe network, and the safety logic system is formed based on a comprehensive analysis of previous safety incidents of the underground pipe network; Multiple interactions are performed on the safety factors of multiple abnormal areas, underground pipeline networks, and safety logic systems, and corresponding safety management and control measures are determined based on the safety factors of multiple abnormal areas, underground pipeline networks, and safety logic systems.

10. A safety management and control system for underground pipe network based on multiple grating pressure sensors, characterized in that: The underground pipe network safety management and control system based on multiple grating pressure sensors is applied to the underground pipe network safety management and control method based on multiple grating pressure sensors as claimed in any one of claims 1 to 9, and the underground pipe network safety management and control system based on multiple grating pressure sensors includes: A pipe network area module, used to determine multiple pipe network areas based on the underground pipe network and the corresponding ground load; A pressure node module is used to determine a plurality of pressure nodes in each pipe network area based on the length of the pipe network area, the depth of the pipe network area and the previous water level of the pipe network area, and the pressure node is matched with a grating pressure sensor; A load parameter module, used to determine the internal load parameters of each pipe network area according to the real-time pressure data of multiple grating pressure sensors, the detection space formed by the multiple grating pressure sensors and the corresponding liquid types; A safety factor module is used to determine the safety factor of the underground pipe network based on the internal load parameters of each pipe network area, the ground load parameters corresponding to each pipe network area, and the morphology of each pipe network area; An abnormal node module is used to determine multiple abnormal nodes according to the safety factor of the underground pipe network, the real-time pressure data of multiple grating pressure sensors and the damage factor of the inner wall of multiple pipe network areas if the safety factor of the underground pipe network is lower than the preset safety factor; The safety management and control module is used to determine corresponding safety management and control measures based on the abnormal area enclosed by multiple abnormal nodes, the safety factor of the underground pipeline network and the safety logic system.

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