Underground pipeline network safety control method and system based on multiple grating pressure sensors

Abstract

The present invention discloses a safety control method and system for underground pipe networks based on multiple grating pressure sensors. The present invention relates to the technical field of underground pipe networks. 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, ensuring the accuracy of the safety factor of the underground pipe network and controlling the safety situation of the underground pipe network. 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 coefficient of the inner side walls of multiple pipe network areas, ensuring the abnormal control of the underground pipe network. Therefore, corresponding safety control measures are determined based on the abnormal area enclosed by multiple abnormal nodes, the safety factor of the underground pipe network, and the safety logic system, ensuring the effectiveness and rationality of the safety control measures.

Description

Technical Field

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

[0002] With the development of technology, underground pipe networks have gradually been applied to people's lives. The underground pipe networks are underground and contain multiple grating pressure sensors. The corresponding pressure data is measured by the grating pressure sensors. In the prior art, the underground pipe networks are divided into regions, and multiple pipe network regions are introduced. The safety factor of the underground pipe networks is estimated based on the morphology of each pipe network region, without fully considering the internal load parameters of each pipe network region and the ground load parameters corresponding to each pipe network region, which affects the accuracy of the safety factor of the underground pipe networks. 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 control method and system for underground pipe networks based on multiple grating pressure sensors.

[0004] An embodiment of the present invention provides a safety control method for underground pipe networks based on multiple grating pressure sensors, including: determining multiple pipe network regions based on the underground pipe networks and the corresponding ground loads;

[0005] In each pipe network region, determining multiple pressure nodes based on the length, depth, and previous water level of the pipe network region, and the pressure nodes are matched with grating pressure sensors;

[0006] Determining the internal load parameters of each pipe network region according to the real-time pressure data of multiple grating pressure sensors, the detection space formed by multiple grating pressure sensors, and the corresponding liquid types;

[0007] Determining the safety factor of the underground pipe networks based on the internal load parameters of each pipe network region, the ground load parameters corresponding to each pipe network region, and the morphology of each pipe network region;

[0008] If the safety factor of the underground pipe networks is lower than the preset safety factor, determining multiple abnormal nodes according to the safety factor of the underground pipe networks, the real-time pressure data of multiple grating pressure sensors, and the damage coefficients of the inner side walls of multiple pipe network regions;

[0009] Determining corresponding safety control measures based on the abnormal region enclosed by multiple abnormal nodes, the safety factor of the underground pipe networks, and the safety logic system.

[0010] An embodiment of the present invention provides a safety control system for an underground pipe network based on multiple grating pressure sensors. The safety control system for the underground pipe network based on multiple grating pressure sensors is applied to the above-mentioned safety control method for the underground pipe network based on multiple grating pressure sensors. The safety control system for the underground pipe network based on multiple grating pressure sensors includes:

[0011] A pipe network area module, configured to determine multiple pipe network areas based on the underground pipe network and the corresponding ground load;

[0012] A pressure node module, configured to determine multiple pressure nodes in each pipe network area based on the length, depth, and previous water level of the pipe network area, and the pressure nodes are matched with grating pressure sensors;

[0013] A load parameter module, configured 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 multiple grating pressure sensors, and the corresponding liquid type;

[0014] A safety factor module, configured to determine the safety factor of the underground pipe network based on the internal load parameters of each pipe network area, the corresponding ground load parameters of each pipe network area, and the shape of each pipe network area;

[0015] An abnormal node module, configured to, if the safety factor of the underground pipe network is lower than a preset safety factor, 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 side walls of multiple pipe network areas;

[0016] A safety control module, configured to determine corresponding safety control measures based on the abnormal area enclosed by multiple abnormal nodes, the safety factor of the underground pipe network, and the safety logic system.

[0017] In the embodiment of the present invention, by the method in the embodiment of the present invention, multiple pipe network areas are determined based on the underground pipe network and the corresponding ground load; in each pipe network area, multiple pressure nodes are determined based on the length, depth, and previous water level of the pipe network area, and the pressure nodes are matched with grating pressure sensors; the internal load parameters of each pipe network area are determined according to the real-time pressure data of multiple grating pressure sensors, the detection space formed by multiple grating pressure sensors, and the corresponding liquid type; the safety factor of the underground pipe network is determined based on the internal load parameters of each pipe network area, the corresponding ground load parameters of each pipe network area, and the shape of each pipe network area, which comprehensively considers the internal load parameters of each pipe network area, the corresponding ground load parameters of each pipe network area, and the shape of each pipe network area, ensures the accuracy of the safety factor of the underground pipe network, and controls the safety condition of the underground pipe network.

[0018] Further, 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 side walls of multiple pipe network areas. The introduction of multiple abnormal nodes further analyzes the abnormal conditions of the underground pipe network, ensuring the abnormal control of the underground pipe network.

[0019] Therefore, corresponding safety control measures are determined based on the abnormal area enclosed by multiple abnormal nodes, the safety factor of the underground pipe network, and the safety logic system, realizing the multiple interactions of the abnormal area enclosed by multiple abnormal nodes, the safety factor of the underground pipe network, and the safety logic system, and ensuring the effectiveness and rationality of the safety control measures. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] Figure 1 FIG. is a schematic diagram of an application scenario of a safety control method for an underground pipe network based on multiple grating pressure sensors in an embodiment;

[0021] Figure 2 is a schematic flowchart of a safety control method for an underground pipe network based on multiple grating pressure sensors in an embodiment of the present invention;

[0022] Figure 3 is a schematic diagram of the structural composition of a safety control system for an underground pipe network based on multiple grating pressure sensors in an embodiment of the present invention;

[0023] Figure 4 is a hardware diagram of an electronic device shown according to an exemplary embodiment. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0024] The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention. Embodiment 1

[0025] The safety control method for an underground pipe network based on multiple grating pressure sensors provided by the present application is applied to an application environment as Figure 1 shown. Among them, the computer 102 communicates with the server 104 through the network. Among them, the terminal 102 is but not limited to various personal computers, servers, and underground pipe networks, and the server 104 is implemented by an independent server or a server cluster composed of multiple servers. Embodiment 2

[0026] Please refer to Figures 1 to 4 , a safety control method for an underground pipe network based on multiple grating pressure sensors, which 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:

[0027] Step S11: Determine multiple pipeline network regions based on the underground pipeline network and the corresponding ground loads;

[0028] Step S12: In each pipeline network region, determine multiple pressure nodes based on the length of the pipeline network region, the depth of the pipeline network region, and the previous water levels in the pipeline network region. The pressure nodes are matched with grating pressure sensors;

[0029] Step S13: Determine the internal load parameters of each pipeline network region according to the real-time pressure data of multiple grating pressure sensors, the detection space formed by multiple grating pressure sensors, and the corresponding liquid types;

[0030] Step S14: Determine the safety factor of the underground pipeline network based on the internal load parameters of each pipeline network region, the ground load parameters corresponding to each pipeline network region, and the morphology of each pipeline network region;

[0031] Step S15: If the safety factor of the underground pipeline network is lower than the preset safety factor, determine multiple abnormal nodes according to the safety factor of the underground pipeline network, the real-time pressure data of multiple grating pressure sensors, and the damage coefficients of the inner side walls of multiple pipeline network regions;

[0032] Step S16: Determine the corresponding safety control measures based on the abnormal region enclosed by multiple abnormal nodes, the safety factor of the underground pipeline network, and the safety logic system.

[0033] In step S11, determine multiple pipeline network regions based on the underground pipeline network and the corresponding ground loads;

[0034] In the specific implementation process of the present invention, the specific steps are as follows:

[0035] S111: Locate the underground pipeline network and collect the underground path of the underground pipeline network;

[0036] S112: Determine the corresponding ground trajectory according to the underground path of the underground pipeline network;

[0037] S113: Determine the corresponding ground load area according to the ground trajectory, and determine the corresponding ground load distribution according to the detection of the ground load area;

[0038] S114: Determine multiple pipeline network regions based on the ground load distribution, the underground path of the underground pipeline network, and the layout of the underground pipeline network.

[0039] In the embodiment of the present application, locate the underground pipeline network and collect the underground path of the underground pipeline network; determine the corresponding ground trajectory according to the underground path of the underground pipeline network, and introduce the ground trajectory to facilitate subsequent control of the ground.

[0040] Specifically, the positioning of underground pipe networks is introduced. For the positioning of underground pipe networks, since they are usually hidden underground, ground penetrating radar detection technology needs to be used to determine their positions.

[0041] After determining the positions of the underground pipe networks, it is necessary to collect their underground path information, which usually involves measuring key parameters such as the starting point, ending point, turning points of the pipe networks, and the burial depth along the way.

[0042] Optionally, first use ground penetrating radar detection technology to determine the positions of the underground pipe networks. By moving the radar device on the ground and collecting the reflected electromagnetic wave signals, a two-dimensional image of the underground pipe networks is drawn. Use specialized measuring tools to collect the underground path information of the pipe networks, including the starting point, ending point, turning points of the pipe networks, and the burial depth, etc. Based on this information, the underground path of the underground pipe networks is formed.

[0043] At the same time, after obtaining the underground path information of the underground pipe networks, it is necessary to map it onto the ground, which usually involves using a Geographic Information System (GIS) or other relevant software to convert the position and orientation of the underground pipe networks into a trajectory on the ground. The ground trajectory is an intuitive representation of the underground pipe networks on the ground.

[0044] Furthermore, based on this ground trajectory, the corresponding ground load area is determined, and based on the detection of the ground load area, the corresponding ground load distribution is determined, realizing the detection of the ground load area and ensuring the accuracy of the ground load distribution.

[0045] At this time, after obtaining the ground trajectory of the underground pipe networks, the ground is divided into different load areas based on this information. These areas are usually divided based on factors such as the building distribution on the ground, road type, soil type, and expected ground activities.

[0046] Within each load area, on-site detection or reference to relevant materials is required to determine the load type and intensity of this area, which includes understanding information such as the building weight, traffic flow, and load-bearing capacity of the soil type in the area. Based on the above detection and analysis, a ground load distribution map is drawn. The ground load distribution map shows the load type and intensity of different load areas.

[0047] Specifically, after determining the ground trajectory of the underground pipe network, the ground along the line is divided into several load areas. For example, the area near large commercial areas is divided into high-load areas because there are a large number of high-rise buildings and dense pedestrian flows in this area; while the area near parks is divided into low-load areas because this area is mainly green spaces and a small number of low-rise buildings. In each area, on-site investigations were carried out, and data such as the weight of buildings and traffic flow were measured, and the bearing capacity of the soil type for the load was considered. Finally, a ground load distribution map was drawn, showing the load types and intensities of different areas.

[0048] At the same time, based on the ground load distribution, the underground path of the underground pipe network, and the layout of the underground pipe network, multiple pipe network areas are determined, taking into account the overall situation of the ground load distribution, the underground path of the underground pipe network, and the layout of the underground pipe network, ensuring the accuracy of the division of multiple pipe network areas.

[0049] Specifically, the ground load distribution, the underground path of the underground pipe network, and the layout of the underground pipe network are introduced. At this time, the ground load distribution refers to the distribution of the load types and intensities borne by different areas on the ground. The load types include the weight of buildings, traffic flow, population density, etc., and the load intensity refers to the pressure or weight generated by these loads on the ground.

[0050] The underground path of the underground pipe network refers to the actual direction and position of the underground pipe network underground. It includes key information such as the starting point, ending point, turning points, pipe diameter, and material of the pipe network.

[0051] The layout of the underground pipe network refers to the relative positions and connection relationships between the pipe networks in the underground pipe network system. It includes key information such as the intersection points, branch points, and connecting pipes between the pipe networks.

[0052] Optionally, when determining the pipe network area, comprehensively considering the ground load distribution, the underground path of the underground pipe network, and the layout of the pipe network, the underground pipe network is divided into multiple relatively independent areas. The division of these areas aims to ensure that the pipe networks in each area can be properly monitored and managed. At the same time, considering the impact of the ground load on the pipe network, after determining the pipe network area, different management strategies are formulated for different areas.

[0053] Specifically, first, the ground load distribution map, the underground pipe network path map, and the layout map are integrated. The urban center area has a high ground load due to dense buildings and heavy traffic; while the urban fringe area has a relatively low load;

[0054] The underground pipe network is divided into three main areas:

[0055] High-load core area: It includes high-rise buildings and bustling commercial areas in the city center. The pipe networks in this area need to be monitored and maintained more frequently to ensure normal operation under high-load conditions.

[0056] Medium-load transition area: It is located between the high-load core area and the urban fringe area, including some medium-density residential areas and industrial areas. The pipe networks in this area are maintained at a moderate frequency.

[0057] Low-load fringe area: It is mainly green spaces and low-density residential areas on the urban fringe. The maintenance requirements for the pipe networks in this area are relatively low.

[0058] In addition, the trained pipe network area model is used to predict new ground load distribution, underground pipe network paths and layout data. According to the prediction results, combined with the actual situation and urban planning requirements, the underground pipe network is divided into regions, and each pipe network region should have clear boundaries and identifiers.

[0059] In addition, according to the ground load distribution, underground paths and layout of the underground pipe network, a pipe network area matching table is designed. The pipe network area matching table should include different ground load types, intensities, pipe network path characteristics, layout patterns, etc. as matching conditions. For each matching condition, corresponding pipe network area division suggestions and maintenance strategies are listed. When new underground pipe networks need to be divided into regions, according to the ground load distribution, pipe network paths and layout, the most matching entry is found in the matching table, and based on the matching results, referring to the pipe network area division suggestions and maintenance strategies given in the pipe network area matching table, the actual pipe network area division work is carried out.

[0060] In step S12, in each pipe network region, multiple pressure nodes are determined based on the length of the pipe network region, the depth of the pipe network region, and the previous water levels of the pipe network region, and the pressure nodes are matched with grating pressure sensors;

[0061] In the specific implementation process of the present invention, the specific steps are as follows:

[0062] S121: Obtain multiple pipe network regions and perform synchronous control on the multiple pipe network regions;

[0063] S122: In each pipe network region, collect the length of the pipe network region and the depth of the pipe network region based on the traversal of the pipe network region;

[0064] S123: Trace the data of the pipe network region and determine the previous water levels of the pipe network region according to the data tracing of the pipe network region;

[0065] S124: Perform multiple interactions on the length of the pipe network region, the depth of the pipe network region, and the previous water levels of the pipe network region;

[0066] S125: Determine the first node parameters according to the length and depth of the pipe network area, and determine the second node parameters according to the length of the pipe network area and the previous water level of the pipe network area;

[0067] S126: Determine multiple pressure nodes according to the pipe network area, the first node parameters, and the second node parameters, and the pressure nodes are matched with grating pressure sensors.

[0068] In the embodiments of the present application, multiple pipe network areas are obtained and synchronized control is performed on the multiple pipe network areas; in each pipe network area, based on the traversal of the pipe network area, the length and depth of the pipe network area are collected, and the length and depth of the pipe network area are introduced.

[0069] Among them, multiple pipe network areas are obtained, further processed, and at the same time, synchronized control is performed on the multiple pipe network areas to facilitate detailed control for each pipe network area.

[0070] In each pipe network area, the pipe network area is traversed. For the traversal of the pipe network area, that is, each pipe network area is checked one by one according to a certain path or method. At the same time, during 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 referring to the design drawings. The depth data of the pipe network area usually needs to be determined by on-site measurement or using professional equipment to determine the buried depth of the pipe network area underground.

[0071] Optionally, a professional team will first traverse each pipe network area and use professional pipeline detection equipment to measure the length and depth of the pipeline. For example, in a certain area, it is found that the total length of a drainage pipeline is 500 meters and the average buried depth is 2 meters. These data will be recorded and used for subsequent pipeline network maintenance and management work.

[0072] Furthermore, data tracing is performed on the pipe network area, and the previous water level of the pipe network area is determined according to the data tracing of the pipe network area, realizing data tracing of the pipe network area and ensuring further control of the previous water level of the pipe network area.

[0073] Specifically, data tracing is an important link in pipeline network management. It involves the collection, collation, and analysis of historical data of the pipeline network, including the construction time, material, previous maintenance records, water level changes, etc. of the pipeline network. The purpose of data tracing is to understand the historical state of the pipeline network and provide basic data support for subsequent pipeline network maintenance, repair, and optimization.

[0074] In the process of data traceability in the pipe network 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 pipe network data, improving the accuracy and efficiency of data traceability.

[0075] After collecting the historical data of the pipe network area, it is necessary to analyze this data to determine the past water levels in the pipe network area. The past 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 the past water levels include statistical analysis, mathematical model prediction, etc. These methods calculate the water levels in the pipe network area at a certain past time period based on the historical data of the pipe network area and combined with the current environmental conditions (such as rainfall, temperature, etc.).

[0076] Therefore, multiple interactions are carried out on the length of the pipe network area, the depth of the pipe network area, and the past water levels in the pipe network area; the first node parameters are determined according to the length and depth of the pipe network area, the second node parameters are determined according to the length and past water levels of the pipe network area, and the first node parameters and the second node parameters are introduced.

[0077] At this time, the length, depth, and past water levels of the pipe network area are introduced. It is required to comprehensively analyze these three key parameters of the length, depth, and past water levels of the pipe network area. Multiple interactions mean that it is necessary to examine the relationships between these parameters and their impacts on the operation of the pipe network. This usually involves complex data analysis and modeling processes to determine how these parameters jointly affect the hydraulic performance of the pipe network area.

[0078] The first node parameters usually refer to the hydraulic parameters directly related to the length and depth of the pipe network area, such as flow rate, pressure, flow velocity, etc. These parameters are crucial for evaluating the hydraulic performance of the pipe network. When determining the first node parameters, the impacts of the length and depth of the pipe network area on the water flow need to be considered. For example, a longer pipe network area requires greater pressure to overcome resistance, and a deeper pipe network area needs to consider the pressure and support of the soil on the pipe network area.

[0079] The second node parameters refer to other hydraulic parameters or performance indicators related to the length of the pipe network area and the past water levels in the pipe network area, such as leakage risk, pipeline stability, etc. These parameters help to further understand the state and potential problems of the pipe network area. When determining the second node parameters, the impact of the length of the pipe network area on the water flow path and the impact of the past water levels on the internal state of the pipeline need to be considered. For example, longer pipelines are more prone to leakage, and changes in past water levels reflect sedimentation, corrosion, or blockage inside the pipeline.

[0080] Optionally, the first node parameters are calculated based on the length and depth of the pipe network, including the pressure, flow rate, and flow velocity at the inlet and outlet of the pipeline. These parameters provide an important basis for subsequent pipe network optimization and maintenance. According to the length of the urban water supply pipe network and the previous water level data, the second node parameters are calculated, including the leakage risk and stability index of the pipeline. These parameters help identify potential problem areas and formulate corresponding maintenance plans. For example, it is decided to focus on inspecting and maintaining the pipelines with higher leakage risks to ensure the safety and reliability of water supply.

[0081] Therefore, multiple pressure nodes are determined based on the pipe network area, the first node parameters, and the second node parameters. The pressure nodes are matched with grating pressure sensors to control the pipe network area, the first node parameters, and the second node parameters in multiple dimensions, ensuring the reasonable distribution of multiple pressure nodes.

[0082] At this time, the pipe network area, the first node parameters, and the second node parameters are introduced. Further, a comprehensive analysis of the pipe network area is carried out, including pipe network layout, pipe material, pipe diameter size, historical operation data, etc. This information helps to understand the overall condition of the pipe network and potential pressure change points. Combining the first node parameters (such as flow rate, pressure, flow velocity, etc.) and the second node parameters (such as leakage risk, pipe stability, etc.), potential pressure fluctuation areas or key nodes in the pipe network are further identified. These nodes are usually the positions in the pipe network that are most sensitive to pressure changes. Further, multiple potential pressure nodes are determined, and these nodes will be used as candidate positions for installing grating pressure sensors.

[0083] At the same time, according to the characteristics of the pipe network area and the specific requirements of the pressure nodes, a suitable model of grating pressure sensor is selected. This requires considering factors such as the measurement range, accuracy, stability, and installation environment of the sensor. At the determined pressure nodes, according to the actual situation on site and the installation requirements of the sensor, the specific installation positions are determined. This requires considering factors such as the pipeline direction, the setting of brackets, and convenience for subsequent maintenance.

[0084] Specifically, taking the water supply pipe network of a certain city as an example, the pipe network area is complex, including multiple branch pipelines and connection points. In order to monitor the pressure changes in the pipe network, it is decided to use grating pressure sensors for real-time monitoring.

[0085] First, a comprehensive analysis of the pipe network area is carried out, and multiple potential pressure nodes are determined by combining the first node parameters (such as flow rate and pressure) and the second node parameters (such as leakage risk and pipe stability). These nodes are mainly distributed at the key branches of the pipe network, pipe intersections, and areas with large pressure fluctuations in historical records.

[0086] Next, a grating pressure sensor model suitable for the characteristics of the pipe network area was selected, and the specific installation location was determined according to the actual on-site situation. During the installation process, the operation was carried out strictly in accordance with the installation instructions of the sensor, and the necessary debugging work was carried out. After the installation was completed, the grating pressure sensor began to monitor the pressure changes in the pipe network in real time.

[0087] In addition, a preset pressure node model was collected, the actual operation parameters of the pipe network (such as the flow rate and water pressure of the first node and the second node, etc.) were input, and the water pressure values of multiple other nodes in the pipe network were calculated using the pressure node model. According to the calculation results, the hydraulic state of the pipe network was analyzed and evaluated, such as whether there was a situation of insufficient or excessive water pressure.

[0088] In step S13, according to the real-time pressure data of multiple grating pressure sensors, the detection space formed by multiple grating pressure sensors, and the corresponding liquid types, the internal load parameters of each pipe network area are determined;

[0089] In the specific implementation process of the present invention, the specific steps are as follows:

[0090] S131: In each pipe network area, collect the real-time pressure data of multiple grating pressure sensors;

[0091] S132: Collect the spatial positions of multiple grating pressure sensors;

[0092] S133: According to the spatial positions of multiple grating pressure sensors and the shape of the pipe network area, form a detection space. At this time, the detection space is the detection space formed by multiple grating pressure sensors;

[0093] S134: Collect the liquid passing through the pipe network area, and determine the corresponding liquid type according to the detection of the liquid;

[0094] S135: Associate the real-time pressure data of multiple grating pressure sensors, the detection space, and the corresponding liquid types;

[0095] S136: According to the real-time pressure data of multiple grating pressure sensors, the detection space, and the corresponding liquid types, determine the internal load parameters of the pipe network area to determine the internal load parameters of each pipe network area.

[0096] In the embodiment of the present application, in each pipe network area, collect the real-time pressure data of multiple grating pressure sensors, and perform subsequent control on the real-time pressure data of multiple grating pressure sensors.

[0097] At this time, control is carried out on each pipe network area, and the monitoring of multiple grating pressure sensors is introduced to collect the real-time pressure data of 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.

[0098] Specifically, taking a certain city's water supply system as an example, the water supply system includes multiple water supply areas, and each area has its own independent pipe network system. In order to monitor the pressure of the pipe network, the water supply system decides to collect the real-time pressure data of multiple grating pressure sensors in each pipe network area. First, the pipe network areas to be monitored are clarified, 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 have corrosion resistance are selected.

[0099] Grating pressure sensors are installed at key positions in the three water supply areas A, B, and C, such as the outlet of the pumping station and the branch of the pipe network. The grating pressure sensors are connected to a specially designed data acquisition instrument to achieve real-time data collection.

[0100] Furthermore, the spatial positions of multiple grating pressure sensors are collected; a detection space is formed based on the spatial positions of multiple grating pressure sensors and the morphology of the pipe network area. At this time, the detection space is the detection space formed by multiple grating pressure sensors, which takes into account the overall consideration of the spatial positions of multiple grating pressure sensors and the morphology of the pipe network area, ensuring the accurate control of the detection space.

[0101] At this time, a unified coordinate system is determined to accurately record the position of each grating pressure sensor. This is a geographic coordinate system (such as WGS84) and also a local coordinate system (such as relative coordinates based on a fixed point); a GPS locator, laser rangefinder or other measurement tools are used to accurately measure the geographical location of each grating pressure sensor, which includes longitude, latitude (if using a geographic coordinate system) and horizontal and vertical distances relative to a reference point (if using a local coordinate system). The measured position data is recorded, which is a paper record, but more commonly, a dedicated application on an electronic device (such as a tablet or smartphone) is used for recording for subsequent data processing and analysis.

[0102] Optionally, in order to monitor the pressure of the pipe network, the park management decides to install grating pressure sensors at each key position. When collecting the spatial positions of these sensors, a geographic coordinate system (WGS84) is first determined, and then professional personnel are dispatched to the site to accurately measure the position of each sensor using a GPS locator.

[0103] Meanwhile, the spatial position data of the collected grating pressure sensors are imported into GIS (Geographic Information System) software. Using the software's modeling function, a 3D model of the pipe network is constructed according to the actual layout and shape of the pipe network, which includes all key elements such as pipes, valves, and pump stations. In the pipe network model, the positions of each grating pressure sensor are marked, which is usually achieved by adding points or icons in the model. According to the pipe network model and the positions of the sensors, one or more detection spaces are automatically or manually divided. These detection spaces are the areas in the pipe network covered by the sensors and are used for subsequent data analysis and monitoring.

[0104] Specifically, after collecting the spatial position data of all grating pressure sensors, the park management party imported these data into GIS software. Then, using the software's modeling function, a 3D model of the pipe network was constructed according to the actual layout and shape of the pipe network. In the model, the positions of each sensor were marked, and multiple detection spaces were automatically divided according to these positions. These spaces cover all key areas in the pipe network, including main water supply pipes, branch pipes, and pump stations.

[0105] Furthermore, the liquid passing through the pipe network area is collected, and the corresponding liquid type is determined based on the detection of this liquid, realizing the detection of the liquid and ensuring the accuracy of the liquid type of the liquid.

[0106] At this time, sampling points are selected at key positions in the pipe network area. These positions are usually where the liquid flow is stable and can represent the characteristics of the entire pipe network area. Appropriate sampling containers and tools are used to collect liquid samples from the selected sampling points. Ensure that no external contamination is introduced during the sampling process.

[0107] The collected liquid samples are sent to a laboratory or on-site testing equipment for testing in terms of chemical composition, physical properties, etc. These tests include the determination of indicators such as pH value, conductivity, dissolved oxygen, turbidity, and organic matter content. According to the test results, combined with the known liquid property database or professional knowledge, the type of the collected liquid is determined, which is water, oil, chemical solvent, etc.

[0108] Therefore, the real-time pressure data, detection spaces, and corresponding liquid types of multiple grating pressure sensors are correlated; the internal load parameters of the pipe network area are determined based on the real-time pressure data, detection spaces, and corresponding liquid types of multiple grating pressure sensors to determine the internal load parameters of each pipe network area, realizing the multi-dimensional control of the real-time pressure data, detection spaces, and corresponding liquid types of multiple grating pressure sensors and ensuring the accurate control of the internal load parameters of the pipe network area.

[0109] At this time, pressure data is collected in real time from the grating pressure sensor, and the accuracy and integrity 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 spatial positions (such as GPS coordinates). The detected liquid types are matched with the corresponding detection spaces and pressure data, which requires establishing a database or data table to quickly query and associate information from different sources.

[0110] In-depth analysis is carried out on the associated data, including trend analysis of pressure data, distribution of liquid types, etc. Based on the analysis results, internal load parameters of the pipe network area are calculated, and these parameters include flow rate in the pipeline, pressure fluctuation range, energy consumption, etc. The calculated load parameters are compared and verified with the actual operating conditions to ensure the accuracy and reliability of the parameters. If necessary, the parameters are adjusted and optimized.

[0111] Optionally, after determining the liquid types transmitted in each pipeline, this information is associated with the real-time pressure data of the grating pressure sensor collected previously. The GIS software is used to match the pressure data with the spatial positions of the pipelines, and the liquid types transmitted in each pipeline are recorded in the database. In this way, it is possible to query at any given time point or time period the liquid types transmitted in a specific pipeline and their corresponding pressure data.

[0112] After associating the pressure data, detection space, and liquid types, in-depth analysis is carried out on this information using data analysis software. It is found that when certain pipelines transmit specific types of liquids, the pressure fluctuates greatly and the energy consumption is high. Based on these findings, internal load parameters of the pipe network area are calculated, including the flow rate, pressure fluctuation range, and energy consumption of each pipeline. Then, the calculated load parameters are compared and verified with the actual operating conditions, and the operating strategies of some pipelines are adjusted and optimized according to the verification results to reduce energy consumption and improve the overall efficiency of the pipe network system.

[0113] In addition, a method of using an internal load parameter matching table is decided 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 combinations of different pressures, detection spaces, and liquid types and their corresponding load parameters is established. When it is necessary to determine the internal load parameters of a certain pipe network area, the management personnel search in the internal load parameter matching table for the combination that best matches the current pressure data, detection space information, and liquid types, and obtain the corresponding load parameter values.

[0114] 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;

[0115] In the specific implementation process of the present invention, the specific steps are as follows:

[0116] S141: Obtain the internal load parameters of each pipe network area;

[0117] S142: Determine multiple load characteristics based on the ground load distribution corresponding to each pipe network area;

[0118] S143: Determine the ground load parameters corresponding to each pipe network area according to the relative positions, areas, and types of multiple load characteristics;

[0119] S144: Collect the inner contours of each pipe network area, and determine the morphology of each pipe network area based on the recognition of the inner contours of each pipe network area;

[0120] S145: Perform multiple interactions 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;

[0121] S146: Determine the safety factor of the underground pipe network according to the multiple interactions of 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.

[0122] At this time, 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, areas, and types of multiple load characteristics, and comprehensively consider the relative positions, areas, and types of multiple load characteristics, ensuring the accuracy of the ground load parameters corresponding to each pipe network area.

[0123] Specifically, collect the ground load distribution data corresponding to each pipe network area, conduct in-depth analysis on the collected ground load distribution data to understand the distribution characteristics of loads in different areas, including load density, intensity, change trend, etc. Based on the load distribution analysis results, extract load characteristics that have an important impact on the safety of the pipe network, including the weight of buildings, population density, traffic flow, soil type, groundwater level, etc. Classify and code the extracted load characteristics for subsequent data processing and analysis.

[0124] Meanwhile, determine the spatial distribution of each load feature in the pipe network area, which includes information such as their locations, shapes, sizes, etc. For each load feature, calculate the area it occupies in the pipe network area, which helps to understand the overall impact degree of the load feature on the pipe network area. According to the type of the load feature and its impact degree on the pipe network safety, assign a weight value to each feature, and this weight value reflects the importance of the feature when determining the ground load parameters. Based on the relative positions, areas, and weight values of the load features, calculate the ground load parameters corresponding to each pipe network area, which is a comprehensive index used to describe the overall load situation above the pipe network area.

[0125] In addition, the positions, shapes, and sizes of these features in the pipe network area are determined, and the area occupied by each feature is calculated. Then, according to the impact degree of these features on the pipe network safety, a weight value is assigned to each feature. Finally, based on the positions, areas, and weight values of these features, the ground load parameters of each pipe network area are calculated using a specific algorithm or model. This parameter is a comprehensive index used to describe the overall load situation above the pipe network area and helps the management personnel to understand the safety and stability of the pipe network under different load conditions.

[0126] Moreover, when determining the ground load parameters corresponding to each pipe network area, comprehensively consider the relative positions, areas, and types of multiple load features, and use weights and scores for calculation.

[0127] The ground load parameter of pipe network area A

[0128] First, clarify the load features above pipe network area A, including building B, building C, road D, green space E, etc. According to the relative positions of the load features in the pipe network area, evaluate their impacts on the pipe network safety. For example, a building located in the central area exerts greater pressure on the pipe network.

[0129] Use GIS to determine the area occupied by each load feature in the pipe network area. According to the type of the load feature (such as residential, commercial, main road, public green space, etc.), combined with its impact degree on the pipe network safety, assign a weight value 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, multiply the area by the weight to get the score. The score reflects the contribution degree of the feature to the ground load parameter of the pipe network area.

[0130] Add up the scores of all load features to obtain the total score of the ground load parameter of pipe network area A, and this total score is used to evaluate the safety and stability of the pipe network area under different load conditions.

[0131] 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.

[0132] 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.

[0133] 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.

[0134] 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.

[0135] 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.

[0136] 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.

[0137] Meanwhile, the multiple interactions of 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 are introduced. Based on the results of the multiple interaction analysis, a prediction model for evaluating the safety factor of the underground pipe network is constructed. The internal load parameters, ground load parameters, and morphological data of each pipe network area are input into the prediction model for the safety factor of the underground pipe network to calculate the safety factor of each pipe network area. The safety factor is a comprehensive index used to evaluate the safety and stability of the pipe network under different load and morphological conditions. The internal load parameters, ground load parameters, and morphological data of each pipe network area are input into the model to calculate the safety factor of each pipe network area. The safety factor is a comprehensive index used to evaluate the safety and stability of the pipe network under different load and morphological conditions.

[0138] In addition, when determining the safety factor of the underground pipe network, the method of weights and scores is adopted, comprehensively considering the multiple interaction effects of the internal load parameters, ground load parameters, and pipe network morphology of each pipe network area.

[0139] Underground Pipe Network Safety Factor Calculation Table

[0140] Internal load parameter: 0.4 (reflecting the internal fluid state of the pipe network, having a direct impact on safety); ground load parameter: 0.3 (reflecting the external load conditions of the pipe network, such as buildings, population density, etc.); pipe network morphology: 0.3 (reflecting the spatial layout and structural characteristics of the pipe network, affecting the difficulty of maintenance and repair);

[0141] For each pipe network area, scores are given according to the specific situations of the internal load parameter, ground load parameter, and pipe network morphology. The scoring sets different criteria and levels according to the actual situation, such as the stability of flow rate and pressure, the density of buildings and population, the complexity of the pipe network morphology, etc.

[0142] The weighted scores of the internal load parameter, ground load parameter, and pipe network morphology of each pipe network area are added together to obtain the total score. The total score is divided by the highest total score (in this example, it is 300, which is the sum when each parameter reaches the highest score) to obtain the safety factor. The closer the safety factor is to 1, the higher the safety of the pipe network area.

[0143] Although the total scores of Area A and Area B are the same, due to their different weight distributions, the safety factors are different. The pipe network morphology score of Area A is relatively high (linear, convenient for maintenance). Therefore, under the same total score, its safety factor is higher than that of Area B. Although the internal load parameter score of Area C is relatively low, due to its relatively stable pipe network morphology and moderate ground load parameter score, its safety factor is still within an acceptable range.

[0144] In step S15, if the safety factor of the underground pipe network is lower than the preset safety factor, 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 factor of the inner walls of multiple pipe network areas;

[0145] In the specific implementation process of the present invention, the specific steps are as follows:

[0146] 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;

[0147] S152: Compare the safety factor of the underground pipe network with the preset safety factor;

[0148] S153: If the safety factor of the underground pipe network is lower than the preset safety factor, trigger the online safety control of the underground pipe network;

[0149] S154: In the online safety control of the underground pipe network, collect the damaged images of the inner walls of multiple pipe network areas, and determine the damaged areas based on the recognition of the damaged images;

[0150] S155: Determine the damage factors of the inner walls of multiple pipe network areas according to the positions where each damaged area is located, the areas of each damaged area, and the damaged states of the damaged areas;

[0151] 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 factors of the inner walls of multiple pipe network areas.

[0152] At this time, 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, and the comparison between the safety factor of the underground pipe network and the preset safety factor is realized.

[0153] Specifically, collect the safety system matched by the underground pipe network. Traversing the entire safety system means checking and accessing all relevant safety components and subsystems, which involves accessing databases, checking sensor status, reading historical records, etc. During the traversal of the safety system, it is necessary to find and record the preset safety factors related to the underground pipe network. These factors are usually obtained based on standards, specifications, or risk assessments during the design or installation of the pipe network. 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.

[0154] Before comparing the safety factor of the underground pipe network with the preset safety factor, it is first necessary to calculate the current real-time safety factor, which requires collecting various data during the operation of the pipe network, such as pressure, flow rate, temperature, etc., and using specific algorithms or models to calculate the safety factor.

[0155] Select an appropriate comparison method, such as using threshold judgment, etc. The purpose of the comparison is to determine whether the current safety state of the pipe network is within the preset safety range. Based on the comparison results, analyze the safety state of the pipe network and record any abnormal situations or potential risks. If the real-time safety factor is lower than the preset safety factor, it means that there are safety risks in the pipe network and further measures need to be taken.

[0156] Furthermore, if the safety factor of the underground pipe network is lower than the preset safety factor, the online safety control of the underground pipe network is triggered, realizing the online safety control of the underground pipe network.

[0157] At this time, compare the actual safety factor of the underground pipe network with the preset safety factor, which is usually completed by an automated monitoring system. This system will collect the operation data of the pipe network in real time and calculate the safety factor of the pipe network based on these data. When the actual safety factor is lower than the preset safety factor, the system will automatically judge whether the trigger conditions are met, which usually means that the pipe network is currently in an unsafe state and immediate measures need to be taken to prevent potential accidents. Once the trigger conditions are met, the system will immediately start the online safety control, which includes but is not limited to issuing alarms, starting emergency response procedures, adjusting the operation state of the pipe network, etc. The purpose of the online safety control is to intervene in the pipe network in the shortest possible time to reduce the probability of accidents or mitigate the impact of accidents.

[0158] Furthermore, in the online safety control of the underground pipe network, collect the damaged images of the inner walls of multiple pipe network areas, and determine the damaged areas based on the recognition of the damaged images; determine the damage coefficients of the inner walls of multiple pipe network areas according to the positions of the damaged areas, the areas of the damaged areas, and the damage states of the damaged areas, taking into account the overall situation of the positions of the damaged areas, the areas of the damaged areas, and the damage states of the damaged areas, ensuring the accuracy of the damage coefficients of the inner walls of multiple pipe network areas.

[0159] At this time, after the online safety control of the underground pipe network is triggered, it is first necessary to deploy detection equipment in the critical or suspected damaged areas of the pipe network. These equipment include high-definition cameras, vision detection systems carried by drones, or specialized pipeline inspection robots. Use the deployed detection equipment to conduct detailed image acquisition of the inner wall of the pipe network, which includes taking high-definition photos or recording videos to capture the detailed condition of the inner wall of the pipe network. Upload the collected image data to the image recognition system, which uses advanced image processing and machine learning algorithms to identify and analyze the damaged areas in the images. Based on the results of image recognition, the system accurately determines the damaged areas of the inner wall of the pipe network, including the location, shape, and initially judged degree of damage.

[0160] Analyze the location of each damaged area in the pipe network and evaluate its impact on the overall safety of the pipe network. For example, the pipe network with damage located at critical nodes or high-pressure areas has 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 evaluating 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 crack, and whether there are signs of corrosion or erosion, etc. This information helps to more accurately evaluate the impact of the damage on the safety of the pipe network. Combine the analysis results of location, area, and damage status, and use specific algorithms or models to calculate the damage coefficient of each pipe network area. This coefficient is a comprehensive indicator that reflects the severity of the damage to the inner wall of the pipe network and its impact on the safety of the pipe network.

[0161] Therefore, based on the safety coefficient of the underground pipe network, the real-time pressure data of multiple grating pressure sensors, and the damage coefficients of the inner walls of multiple pipe network areas, multiple abnormal nodes are determined. The multiple interactions of the safety coefficient of the underground pipe network, the real-time pressure data of multiple grating pressure sensors, and the damage coefficients of the inner walls of multiple pipe network areas ensure the reasonable distribution of multiple abnormal nodes.

[0162] At this time, integrate the safety coefficient of the underground pipe network, the real-time pressure data of the grating pressure sensors, and the damage coefficients of the inner walls of the pipe network areas into a comprehensive data platform or system. Apply advanced anomaly detection algorithms or machine learning models 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 algorithms, determine the abnormal nodes in multiple pipe network areas. These nodes are areas with serious damage, abnormal pressure, or relatively high safety risks. Conduct a risk assessment for each determined abnormal node and formulate corresponding countermeasures, which include emergency repair, enhanced monitoring, adjustment of the pipe network operation status, etc.

[0163] Specifically, assume that in a city's water supply system, multiple breaks have occurred in a certain section of the underground pipe network due to aging. After triggering the online safety control, the system deployed high-definition cameras and pipeline inspection robots to conduct detailed image acquisition 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 initially judged degree of damage based on the image data. A detailed location assessment, area measurement, and damage status analysis were carried out for each damaged area. For example, a damaged area located at a key node of the pipe network was evaluated as high-risk because of its large area and severe corrosion signs. Based on these analysis results, the system calculated the damage coefficient for each pipe network area. The safety coefficient of the underground pipe network, the real-time pressure data of the grating pressure sensors, and the inner wall damage coefficient of the pipe network area were integrated. By applying anomaly detection algorithms, the system successfully identified multiple abnormal nodes, including those areas with severe damage, abnormal pressure, or high safety risks. According to the risk assessment results provided by the system, the management quickly developed repair plans and emergency response measures to ensure the safe operation of the water supply system.

[0164] In addition, when determining multiple abnormal nodes in the underground pipe network, a method of combining weights and scores is used for comprehensive evaluation. This method combines the safety coefficient of the underground pipe network, the real-time pressure data of multiple grating pressure sensors, and the inner wall damage coefficient of multiple pipe network areas, so as to more accurately identify potential risk areas.

[0165] According to the safety assessment criteria and historical data of the underground pipe network, corresponding weights are assigned to the safety coefficient, real-time pressure data, and damage coefficient. These weights reflect the importance of each factor in evaluating the safety of the pipe network. Standardization processing is carried out on the safety coefficient, real-time pressure data, and damage coefficient to ensure that they are compared on the same scale, which usually involves converting the data into dimensionless scores or percentages.

[0166] For each pipe network area, the following formula is used to calculate its comprehensive score:

[0167] Comprehensive score = (Safety coefficient × Weight 1) + (Real-time pressure data × Weight 2) + (Damage coefficient × Weight 3); where Weight 1, Weight 2, and Weight 3 are the weights of the safety coefficient, real-time pressure data, and damage coefficient respectively. According to the calculated comprehensive scores, the pipe network areas are sorted. Areas with lower scores indicate higher safety risks and are therefore regarded as abnormal nodes.

[0168] Suppose there is an underground pipe network system, which contains three different pipe network areas (A, B, and C). The following are the standardized scores (converted to percentage form) of the safety factor, real-time pressure data, and damage factor for each area, as well as the weights assigned to each factor:

[0169] Calculate the comprehensive score for each area using the above formula:

[0170] Area A: Comprehensive score = (85 × 0.3) + (90 × 0.4) + (70 × 0.3) = 25.5 + 36 + 21 = 82.5; Area B: Comprehensive score = (95 × 0.3) + (75 × 0.4) + (60 × 0.3) = 28.5 + 30 + 18 = 76.5; Area C: Comprehensive score = (70 × 0.3) + (85 × 0.4) + (90 × 0.3) = 21 + 34 + 27 = 82; According to the calculated comprehensive scores, sort the pipe network areas: Area A (82.5 points); Area C (82 points); Area B (76.5 points).

[0171] In this example, although the comprehensive scores of Area A and Area C are similar, the score of Area B is lower, indicating a higher safety risk. Therefore, Area B is regarded as an abnormal node and further inspection and maintenance are carried out on it.

[0172] In step S16, determine the corresponding safety control measures based on the abnormal area enclosed by multiple abnormal nodes, the safety factor of the underground pipe network, and the safety logic system;

[0173] In the specific implementation process of the present invention, the specific steps are as follows:

[0174] S161: Collect multiple abnormal nodes;

[0175] S162: Determine the corresponding enclosure mode based on the relative positions of multiple abnormal nodes and the shape of the pipe network area;

[0176] S163: Determine the corresponding abnormal area according to multiple abnormal nodes and the corresponding enclosure mode, and this abnormal area is the abnormal area enclosed by multiple abnormal nodes;

[0177] S164: Monitor the online safety control of the underground pipe network in real time;

[0178] S165: Collect the safety logic system according to the monitoring of the online safety control of the underground pipe network, and this safety logic system is formed based on the comprehensive analysis of past safety events of the underground pipe network;

[0179] S166: Perform multiple interactions on multiple abnormal areas, the safety factors of the underground pipe network, and the safety logic system, and determine corresponding safety control measures based on the multiple interactions of the multiple abnormal areas, the safety factors of the underground pipe network, and the safety logic system.

[0180] At this time, collect multiple abnormal nodes; determine the corresponding enclosure mode based on the relative positions of the multiple abnormal nodes and the shape of the pipe network area, which takes into account the relative positions of the multiple abnormal nodes and the shape of the pipe network area, and ensures the accuracy of the enclosure mode.

[0181] Specifically, collect multiple abnormal nodes, and clarify the specific coordinates of each abnormal node in the pipe network, which are usually obtained through precise measurement and positioning techniques. Analyze the relative position relationships of these nodes, such as distance, direction, etc.

[0182] Consider the overall layout of the pipe network, such as the pipeline direction, branch situation, intersection points, etc. Evaluate the complexity of the pipe network area, including factors such as pipeline density, bending degree, burial depth, etc. Based on the relative positions of the abnormal nodes and the shape of the pipe network area, select the most appropriate enclosure mode. The enclosure mode includes polygon 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 to the surrounding normal areas.

[0183] Furthermore, according to the enclosure mode, clarify the boundary of the abnormal area. Ensure that the abnormal area completely contains all abnormal nodes, and appropriately consider a certain buffer zone to cope with errors and uncertainties. Within the abnormal area, further analyze information such as the pipeline direction, material, service life, etc. Identify existing risk points, such as severely aged pipeline segments, easily corroded areas, etc. Based on the analysis results of the abnormal area, formulate a targeted management plan.

[0184] Specifically, assume that in a city's water supply pipe 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 pipe network and each has a potential leakage risk.

[0185] 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 within an industrial park, near a chemical plant.

[0186] 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 was relatively complex, with multiple pipelines crossing and branching. Considering these factors, it was decided to adopt a polygon enclosure mode to enclose nodes A, B, and C within a closed polygon area, which not only ensured that all abnormal nodes were covered but also minimized the impact on the surrounding normal water supply areas. After determining the polygon enclosure mode, the information within the abnormal area was further refined. It was found that there were multiple old pipelines within the abnormal area, and some pipelines showed signs of corrosion and leakage. Especially near abnormal nodes A and C, the condition of the pipelines was particularly worrying.

[0187] At the same time, the corresponding abnormal area was determined according to multiple abnormal nodes and the corresponding enclosure mode. This abnormal area was the abnormal area enclosed based on multiple abnormal nodes, achieving an overall consideration of multiple abnormal nodes and the corresponding enclosure mode, and ensuring the accuracy of the enclosure of the abnormal area.

[0188] At this time, according to the selected enclosure mode, using Geographic Information System (GIS), the boundary of the abnormal area was drawn on the pipe network layout map. Ensure that the boundary completely contains all the identified abnormal nodes and consider a certain safety margin to cope with errors or uncertainties. After determining the boundary of the abnormal area, the pipe network information within this area was further refined, which included the material, specifications, service life, historical maintenance records, etc. of the pipelines, as well as any external factors affecting the pipeline safety, such as geological conditions, groundwater level, traffic conditions, etc.

[0189] Based on the information within the abnormal area, the risk level of this area was evaluated. This usually involved a quantitative analysis of the probability and impact of potential risk events such as pipeline leakage and explosion to determine whether additional safety measures were required in this area. According to the risk level of the abnormal area, a targeted management plan was formulated, which included measures such as strengthening monitoring, regular inspections, repairing or replacing pipelines, setting up emergency response teams and materials.

[0190] Suppose in the underground natural gas pipe network system of a city, three abnormal nodes D, E, and F were discovered through data analysis. These three nodes were located at different positions in the pipe network and had potential leakage risks.

[0191] Abnormal node D was located on a main gas transmission pipeline, near a residential area. Abnormal node E was located at a branch of another pipeline, surrounded by some commercial buildings. Abnormal node F was located within an industrial area, near some heavy industrial equipment. Based on the positional relationships of these nodes, the polygon enclosure mode was selected. Using GIS software, a polygon boundary was drawn on the pipe network layout map, completely containing the three abnormal nodes D, E, and F, and considering a sufficient safety margin.

[0192] Within the abnormal area, multiple old pipelines were found, and some pipelines showed signs of corrosion. Especially in the areas near abnormal nodes D and E, the pipelines have been in use for a long time, and historical maintenance records indicate that small-scale leakage incidents have occurred in these areas multiple times. Through quantitative analysis, the risk level of the abnormal area was determined to be medium to high, mainly because the aging degree and corrosion condition of the pipelines in this area are relatively serious, and there are a large number of residential and commercial buildings in the vicinity.

[0193] Furthermore, real-time monitoring of the online safety control of this underground pipe network; collecting a safety logic system based on the monitoring of the online safety control of this underground pipe network, and introducing a safety logic system, which is formed based on the comprehensive analysis of past safety events of the underground pipe network.

[0194] At this time, real-time monitoring of the online safety control of this underground pipe network is achieved, and at the same time, data on past safety events are collected and analyzed, including event types, occurrence times, locations, causes, 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 links such as risk identification, risk assessment, and risk control.

[0195] Collect and analyze data on past safety events. It was found that leakage incidents often occur in areas with old pipelines, complex geological conditions, or heavy traffic. Based on these findings, a safety logic system was constructed to identify high-risk areas in the pipe network. The safety logic system takes into account multiple factors such as pipeline age, material, geological conditions, and traffic conditions.

[0196] Therefore, multiple interactions are carried out among multiple abnormal areas, the safety factor of the underground pipe network, and the safety logic system. Based on the multiple interactions among multiple abnormal areas, the safety factor of the underground pipe network, and the safety logic system, corresponding safety control measures are determined, realizing the multiple interactions among multiple abnormal areas, the safety factor of the underground pipe network, and the safety logic system, and ensuring the accuracy of the safety control measures.

[0197] At this time, the abnormal areas, safety factors, and safety logic system are integrated, and the safety conditions of multiple abnormal areas, the overall safety factor of the pipe network, and the prediction results of the safety logic system are comprehensively analyzed. According to the analysis results, targeted safety control measures are formulated.

[0198] After constructing the security logic system, the water supply network management department began to comprehensively analyze multiple abnormal areas, the safety factor of the pipe network, and the security logic system using a multi-interaction platform. It was found that the security risks in certain abnormal areas were relatively high and consistent with the prediction results of the security logic system. Based on these findings, a series of security control measures were formulated, including strengthening monitoring, regular inspections, repairing or replacing old pipelines, etc. Subsequently, these measures were implemented and their implementation effects were monitored.

[0199] Specifically, according to the nature, scope of influence, and potential consequences of the anomalies, the abnormal areas are divided into three levels: high, medium, and low, and weights of 0.5, 0.3, and 0.2 are assigned respectively. According to factors such as the material, service life, and maintenance status of the pipe network, the safety factor of the pipe 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 factors such as its implementation effect and coverage. 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.

[0200] According to the level and quantity of the abnormal areas, the total score of the abnormal areas is calculated. For example, if there are 2 high-level abnormal areas, 3 medium-level abnormal areas, and 1 low-level abnormal area in a certain area, then the score of the abnormal areas is 2×0.5 + 3×0.3 + 1×0.2 = 2.3. According to the safety factor level and length (or quantity) of the pipe network, the total score of the safety factor of the pipe network is calculated. For example, if the total length of the underground pipe network in a certain area is 1000 meters, with 40% of the pipe network having a high safety factor, 50% having a medium safety factor, and 10% having a low safety factor, then the score of the safety factor of the pipe network is 0.4×0.9 + 0.5×0.7 + 0.1×0.4 = 0.79. According to the implementation situation and evaluation results of each aspect of the security logic system, the scores of each aspect are calculated, and the weighted sum is obtained to get the total score. For example, if the score of network security is 0.8, the score of physical security is 0.7, and the score of management security is 0.6, then the score of the security logic system is 0.4×0.8 + 0.3×0.7 + 0.3×0.6 = 0.74.

[0201] The abnormal area score, the underground pipeline network safety coefficient score, and the safety logic system score are weighted and summed to obtain a comprehensive score. The weights are allocated according to the actual situation. For example, the weight of the abnormal area is 0.4, the weight of the underground pipeline network safety coefficient is 0.3, and the weight of the safety logic system is 0.3. Then the comprehensive score is 0.4×2.3 + 0.3×0.79 + 0.3×0.74 = 1.387. According to the level of the comprehensive score, the corresponding safety control measures are determined. The higher the score, the greater the safety risk in this area, and more strict 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 still need to be vigilant. Embodiment III

[0202] Please refer to Figure 3 , Figure 3 which is a schematic diagram of the structural composition of the safety control system for the underground pipeline network based on multiple grating pressure sensors in the embodiment of the present invention.

[0203] As Figure 3 shown, a safety control system for the underground pipeline network based on multiple grating pressure sensors, the safety control system for the underground pipeline network based on multiple grating pressure sensors includes:

[0204] A pipeline network area module 21, configured to determine a plurality of pipeline network areas based on the underground pipeline network and the corresponding ground load;

[0205] A pressure node module 22, configured to determine a plurality of pressure nodes in each pipeline network area based on the length, depth, and previous water level of the pipeline network area, and the pressure nodes are matched with grating pressure sensors;

[0206] A load parameter module 23, configured to determine the internal load parameters of each pipeline 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;

[0207] A safety coefficient module 24, configured to determine the safety coefficient of the underground pipeline network based on the internal load parameters of each pipeline network area, the corresponding ground load parameters of each pipeline network area, and the shape of each pipeline network area;

[0208] An abnormal node module 25, configured to determine a plurality of abnormal nodes according to the safety coefficient of the underground pipeline network, the real-time pressure data of the multiple grating pressure sensors, and the damage coefficient of the inner sidewalls of the multiple pipeline network areas if the safety coefficient of the underground pipeline network is lower than a preset safety coefficient;

[0209] The security control module 26 is configured to determine corresponding security control measures based on an abnormal area enclosed by multiple abnormal nodes, the safety factor of the underground pipe network, and the security logic system. Embodiment 4

[0210] In this embodiment, an electronic device is provided. The internal structure diagram thereof is as Figure 4 shown. This 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 this electronic device is used to provide computing and control capabilities. The memory of this 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 a database is deployed on the non-volatile storage medium. 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 the computer program in the non-volatile storage medium. The network interface of this electronic device is used to communicate with other electronic devices on which application software is deployed. When the computer program is executed by the processor, it implements a low-altitude patrol method for an unmanned aerial vehicle. The display screen of this electronic device is a liquid crystal display screen or an electronic ink display screen. The input device of this electronic device is a touch layer covering the display screen, and is also a button, a trackball, or a touchpad provided on the outer shell of the electronic device, or an external keyboard, touchpad, or mouse, etc.

[0211] For any combination of the technical features of the above embodiments, for the sake of brevity of description, not all combinations of the various technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, it should be considered as the scope described in 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: collect the liquid passing through the pipe network area, and determine the corresponding liquid type according to the detection of the liquid; Correlate the real-time pressure data of multiple grating pressure sensors, the detection space and the corresponding liquid types; Determine the internal load parameters of the pipe network area according to the real-time pressure data of multiple grating pressure sensors, the detection space and the corresponding liquid type, so as to determine the internal load parameters of each pipe network area; 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 shape of each pipe network area: determine the shape of each pipe network area based on the identification of the inner contour of each pipe network area; Perform multiple interactions 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; determine the safety factor of the underground pipe network based on the multiple interactions of 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.

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.

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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