Method, device, equipment and medium product for checking and diagnosing sewage pipe network deposition

Abstract

This invention relates to the field of wastewater pipe network detection technology, and discloses a method, apparatus, equipment, and media product for diagnosing and investigating sedimentation in wastewater pipe networks. The method includes: dividing the target area into multiple diagnostic zones based on the connection relationship between main and branch pipes; determining the inflow infiltration rate of external water based on water quality index concentration and flow monitoring data; determining the organic matter deposition degradation rate based on water quality index concentration and flow monitoring data; determining the target diagnostic zone based on the inflow infiltration rate of external water and the organic matter deposition degradation rate of each diagnostic zone; and determining the quantitative parameters of pipe sediments in the target diagnostic zone based on the three-dimensional model of the pipes in the target diagnostic zone, thereby conducting wastewater pipe network sedimentation diagnosis and investigation. This invention identifies severely deposited target diagnostic zones by using the inflow infiltration rate of external water and the organic matter deposition degradation rate, and then determines the quantitative parameters of sediments based on the three-dimensional model of the pipes, thus improving the accuracy of sediment parameter determination.

Description

Technical Field

[0001] This invention relates to the field of sewage pipe network detection technology, specifically to methods, devices, equipment, and media products for investigating and diagnosing sedimentation in sewage pipe networks. Background Technology

[0002] With the deepening of wastewater treatment efficiency improvement efforts, increasing the BOD5 (5-day Biochemical Oxygen Demand) concentration in wastewater treatment plant influent has become a key objective. However, urban wastewater pipe networks have long operated at high liquid levels and low flow rates, leading to severe pollutant deposition at the bottom of the pipes. This has become one of the core issues restricting the operational efficiency of the pipe network and resulting in low pollutant concentrations in the influent to wastewater treatment plants.

[0003] Currently, the diagnosis of sediment buildup in sewage pipes mainly relies on manual visual inspection from inside the manhole and closed-circuit television (CCTV) testing. Methods include Circuit Television Inspection (CT) or sonar detection. Manual inspection is limited by safety risks and toxic gas environments in wells, making it difficult to implement under high water levels. CCTV inspection relies on visible light imaging, typically requiring dewatering or pipe emptying; it cannot obtain clear images of the bottom sediment under high water levels and cannot quantify sediment volume. While sonar technology can detect the outline of the pipe underwater, large-scale, full-area detection is costly and inefficient. Furthermore, in the complex flow field of a full pipe filled with sewage, sonar equipment is susceptible to flow velocity disturbances and carrier movement, leading to inaccurate sediment location and large errors in volume calculation. Summary of the Invention

[0004] This invention provides a method, apparatus, equipment, and media product for investigating and diagnosing sediment deposits in sewage pipe networks, in order to solve the problems of inability to quantify volume and high investigation costs in the investigation and diagnosis of sediment deposits in sewage pipes in related technologies.

[0005] In a first aspect, the present invention provides a method for investigating and diagnosing sediment deposits in a sewage pipe network, comprising: dividing the target area into multiple diagnostic zones based on the topological relationship of the sewage pipes in the target area; acquiring water quality index concentration and flow monitoring data for each diagnostic zone; determining the external water inflow infiltration rate for each diagnostic zone based on the water quality index concentration and flow monitoring data; determining the organic matter deposition degradation rate for each diagnostic zone based on the water quality index concentration and flow monitoring data; determining the target diagnostic zone based on the external water inflow infiltration rate and organic matter deposition degradation rate for each diagnostic zone; and determining the pipe sediment quantification parameters of the sewage pipes in the target diagnostic zone based on the three-dimensional model of the pipes in the target diagnostic zone, so as to conduct sewage pipe network sediment investigation and diagnosis based on the pipe sediment quantification parameters.

[0006] The wastewater pipe network sedimentation investigation and diagnosis method of this invention divides the target area into multiple diagnostic zones based on the topological relationship of the wastewater pipes in the target area. This zone division is achieved by relying on the topological connection relationship between the main and branch pipes of the pipe network, avoiding direct full-scale testing of the entire large pipe network and narrowing down the spatial units for subsequent analysis. This invention acquires water quality index concentration and flow monitoring data for each diagnostic zone. Based on this data, it determines the external water inflow infiltration rate for each diagnostic zone. The external water inflow infiltration rate is a key external factor affecting pipe flow velocity and hydraulic conditions, thus influencing sediment deposition. It quantifies the interference of external water on the hydraulic environment of the pipe network in each diagnostic zone. Based on the water quality index concentration and flow monitoring data, this invention determines the organic matter deposition degradation rate for each diagnostic zone. The organic matter deposition degradation rate characterizes the comprehensive level of organic matter sedimentation and decomposition within the diagnostic zone, reflecting the intrinsic material source conditions for sediment formation in the diagnostic zone. This invention determines target diagnostic zones based on the inflow and infiltration rate of external water and the organic matter deposition and degradation rate of each diagnostic zone. It first performs a macroscopic screening of the diagnostic zones, then identifies target diagnostic zones with abnormal deposition degradation based on the inflow and infiltration rate of external water and the organic matter deposition and degradation rate. The volume of sediment in the target diagnostic zones is then quantified, improving the efficiency of sediment quantification. Compared with related technologies, this invention can be implemented under high water level conditions, enabling the quantification of sediment in target diagnostic zones. After selecting target diagnostic zones with abnormal deposition degradation, quantitative analysis of sediment is then performed, improving the accuracy and efficiency of sediment quantification analysis.

[0007] In one optional implementation, the target area is divided into multiple diagnostic zones based on the sewage pipe topology of the target area. This includes: extracting the intersection nodes of the main pipe and branch pipes based on the sewage pipe topology of the target area, using the intersection nodes as dividing nodes, and dividing along the main pipe to obtain multiple sub-diagnostic zones; each sub-diagnostic zone is an independent water collection and drainage unit; when the area of ​​a sub-diagnostic zone is greater than a preset area threshold, it is divided according to the intersection nodes between branch pipes to obtain multiple diagnostic zones; when the area of ​​a sub-diagnostic zone is less than or equal to the preset area threshold, the sub-diagnostic zone is used as a diagnostic zone.

[0008] In one optional implementation, water quality index concentration and flow monitoring data for each diagnostic area are acquired. Based on the water quality index concentration and flow monitoring data, the inflow infiltration rate of external water in each diagnostic area is determined, including: conducting water quality testing on each diagnostic area according to the pipeline network diagnostic monitoring nodes to obtain water quality index concentrations; conducting flow monitoring on each diagnostic area according to the pipeline network diagnostic monitoring nodes to obtain flow monitoring data; constructing water balance equations and pollutant mass balance equations based on the water quality index concentration and flow monitoring data; solving the water balance equations and pollutant mass balance equations to obtain the external water volume and wastewater volume generated in each diagnostic area; and obtaining the inflow infiltration rate of external water in each diagnostic area based on the quotient of the external water volume and the wastewater volume generated in the area.

[0009] In one optional implementation, the organic matter deposition degradation rate of each diagnostic area is determined based on water quality index concentration and flow monitoring data, including: constructing a pollutant mass balance equation for the chemical oxygen demand index based on water quality index concentration and flow monitoring data; and solving the pollutant mass balance equation to obtain the organic matter deposition degradation rate of each diagnostic area.

[0010] In one optional implementation, a target diagnostic area is determined based on the external water inflow infiltration rate and the organic matter deposition degradation rate of each diagnostic area, including: determining a diagnostic area where the external water inflow infiltration rate is less than or equal to a preset external water inflow infiltration rate threshold and the organic matter deposition degradation rate is greater than a preset organic matter deposition degradation rate threshold as a target diagnostic area; and determining a diagnostic area where the external water inflow infiltration rate is greater than a preset external water inflow infiltration rate threshold and the organic matter deposition degradation rate is greater than a preset organic matter deposition degradation rate threshold as a target diagnostic area.

[0011] In one optional implementation, based on the 3D model of the pipeline in the target diagnostic area, the pipeline sediment quantification parameters of the sewage pipeline in the target diagnostic area are determined, so as to conduct sewage pipeline network sediment investigation and diagnosis based on the pipeline sediment quantification parameters. This includes: controlling an underwater mobile device equipped with multiple sensors and sonar to conduct detection in the sewage pipeline network of the target diagnostic area, obtaining cross-sectional point cloud data containing sediment information and multi-source sensor data; correcting the cross-sectional point cloud data based on the multi-source sensor data to obtain target cross-sectional point cloud data; constructing a pipeline 3D model based on the target cross-sectional point cloud data; and obtaining the distance between two adjacent sediment cross-sections based on the pipeline 3D model. The following parameters are used to determine the total sediment volume in the pipe section: the cross-sectional area of ​​the first sediment and the cross-sectional area of ​​the second sediment; the total sediment volume in the pipe section is determined by multiplying the standard cross-sectional area of ​​the pipe by the length of the pipe section; the sedimentation rate is obtained by dividing the total sediment volume of the pipe section by the first product; the second product is obtained by multiplying the effective sediment width at the bottom of the pipe by the length of the pipe section; the average sediment thickness is obtained by dividing the total sediment volume of the pipe section by the second product; and the quantitative parameters of the pipe sediment are obtained based on the total sediment volume, sedimentation rate, and average sediment thickness.

[0012] This invention employs an underwater mobile device to enter the pipeline for operation, avoiding the safety risks of manual well entry. It directly acquires the original spatial information of the pipeline's inner wall and bottom sediments by collecting cross-sectional point cloud data and multi-source sensor data using a combination of sonar and multiple sensors. Data acquisition can be completed even in pipeline environments where sewage is full and turbidity makes visual observation impossible. The cross-sectional point cloud data is corrected using multi-source sensor data, which can compensate for point cloud distortion errors caused by sewage turbidity, impurities in the water, and sonar noise, and eliminate measurement deviations of the original point cloud. Based on the corrected high-precision point cloud, a three-dimensional model of the pipeline is constructed, restoring the true three-dimensional morphology of the pipeline's inner wall and sediments. This invention determines the total volume of sediment in a pipe section based on the distance between two adjacent sediment cross-sections, the area of ​​the first sediment cross-section, and the area of ​​the second sediment cross-section. This allows for a quantitative solution of the total sediment volume within the pipe section, directly reflecting the actual sediment stock. The sedimentation rate characterizes the proportion of sediment in the total flow space of the pipeline. The sedimentation rate allows for horizontal comparison of the severity of siltation in pipe sections of different diameters and lengths, eliminating the interference of pipe diameter. The average sediment thickness is calculated based on the effective area at the bottom of the pipe where sedimentation can occur, avoiding interference from non-depositional spaces above the pipe. The average sediment thickness directly reflects the thickness of the siltation layer at the bottom of the pipe and is directly related to the water flow capacity of the pipeline network and the actual operating conditions of dredging operations. This invention can determine not only the sediment stock but also the degree of flow occupancy and the thickness of siltation at the bottom of the pipe, achieving accurate quantitative analysis of sediment.

[0013] Secondly, the present invention provides a sewage pipe network deposition investigation and diagnosis device, comprising: a region division module, used to divide the target region into multiple diagnostic zones according to the topological relationship of the sewage pipes in the target region; an external water inflow infiltration rate determination module, used to acquire water quality index concentration and flow monitoring data for each diagnostic zone, and determine the external water inflow infiltration rate for each diagnostic zone based on the water quality index concentration and flow monitoring data; an organic matter deposition degradation rate determination module, used to determine the organic matter deposition degradation rate for each diagnostic zone based on the water quality index concentration and flow monitoring data; a target diagnostic zone determination module, used to determine the target diagnostic zone based on the external water inflow infiltration rate and organic matter deposition degradation rate for each diagnostic zone; and a sewage pipe network deposition investigation and diagnosis module, used to determine the pipe deposition quantification parameters of the sewage pipes in the target diagnostic zone based on the three-dimensional model of the pipes in the target diagnostic zone, so as to perform sewage pipe network deposition investigation and diagnosis based on the pipe deposition quantification parameters.

[0014] Thirdly, the present invention provides an electronic device, comprising: a memory and a processor, wherein the memory and the processor are communicatively connected to each other, the memory stores computer instructions, and the processor executes the computer instructions to perform the sewage pipe network sediment investigation and diagnosis method described in the first aspect or any corresponding embodiment.

[0015] Fourthly, the present invention provides a computer-readable storage medium storing computer instructions for causing a computer to execute the sewage pipe network sediment investigation and diagnosis method of the first aspect or any corresponding embodiment described above.

[0016] Fifthly, the present invention provides a computer program product, including computer instructions, which are used to cause a computer to execute the sewage pipe network sediment investigation and diagnosis method described in the first aspect or any corresponding embodiment. Attached Figure Description

[0017] To more clearly illustrate the specific embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the specific embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present invention. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.

[0018] Figure 1 This is a schematic diagram of an application scenario according to an embodiment of the present invention; Figure 2 This is a schematic diagram of the first process of the wastewater pipe network sediment investigation and diagnosis method according to an embodiment of the present invention; Figure 3This is a schematic diagram of the second process of the wastewater pipe network sediment investigation and diagnosis method according to an embodiment of the present invention; Figure 4 This is a schematic diagram illustrating the classification of sewage pumping stations according to an embodiment of the present invention when sewage pumping stations exist in the study area; Figure 5 This is a schematic diagram of the third process of the wastewater pipe network sediment investigation and diagnosis method according to an embodiment of the present invention; Figure 6 This is a schematic diagram of the fourth process of the wastewater pipe network sediment investigation and diagnosis method according to an embodiment of the present invention; Figure 7 This is a structural block diagram of a sewage pipe network sediment investigation and diagnosis device according to an embodiment of the present invention; Figure 8 This is a schematic diagram of the hardware structure of an electronic device according to an embodiment of the present invention. Detailed Implementation

[0019] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0020] It is understood that before using the technical solutions disclosed in the various embodiments of the present invention, users should be informed of the types, scope of use, and usage scenarios of the personal information involved in the present invention and their authorization should be obtained in accordance with relevant laws and regulations through appropriate means.

[0021] The terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of that feature. In the description of this invention, "a plurality of" means two or more, unless otherwise explicitly specified.

[0022] As an optional application scenario of this invention, such as Figure 1 As shown, the sewage pipe network sediment investigation and diagnosis system may include at least one terminal device and at least one server. Figure 1 The system is illustrated in the example, which includes a computer 101, a mobile terminal 102, and a server 103, and the terminal devices such as the computer 101 and the mobile terminal 102 are connected to the server 103 through a network 110.

[0023] Specifically, the terminal device can be a smartphone, tablet, laptop, PDA, desktop computer, game console, smart TV, smart wearable device, in-vehicle terminal, VR (Virtual Reality) device, AR (Augmented Reality) device, etc. Server 103 can be a standalone physical server, a server cluster, a distributed system, or a cloud server providing cloud services. Network 110 can be a wired or wireless network, examples of which include, but are not limited to, the Internet, corporate intranet, local area network, wide area network, mobile communication network, and combinations thereof.

[0024] This invention provides a method for investigating and diagnosing sedimentation in sewage pipe networks. By using the infiltration rate of external water inflow and the degradation rate of organic matter sedimentation, the method identifies target diagnostic areas with severe sedimentation. Based on the three-dimensional model of the pipeline, the method determines the quantitative parameters of sedimentation, thereby improving the accuracy of sedimentation parameter determination.

[0025] According to an embodiment of the present invention, a method for investigating and diagnosing sedimentation in sewage pipe networks is provided. It should be noted that the steps shown in the flowchart in the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions. Furthermore, although a logical order is shown in the flowchart, in some cases, the steps shown or described may be executed in a different order than that shown here.

[0026] This embodiment provides a method for investigating and diagnosing sediment deposits in sewage pipe networks, which can be used with computer equipment. Figure 2 This is a first flowchart of a sewage pipe network sediment investigation and diagnosis method according to an embodiment of the present invention, as follows: Figure 2 As shown, the process includes the following steps: Step S201: Based on the topological relationship of the sewage pipes in the target area, the target area is divided into multiple diagnostic zones.

[0027] The target area is the geographical range of the complete sewage pipe network for which the pipe network sediment analysis is to be carried out. The target area includes multiple main sewage pipes and branch pipes. In this embodiment of the invention, the sewage pipe network can be a high-full-water-level sewage pipe network.

[0028] In some optional implementations, the sewage pipeline topology is abstracted as a directed graph, with manholes, storm drains, or outlets as nodes and pipe segments as edges. The graph records the logical relationships between sewage pipes and manholes, including connections, adjacencies, upstream and downstream flow directions, and main-branch pipe hierarchies. The sewage pipeline topology includes main-branch pipe relationships, where the main pipe is a large-diameter water conveyance pipe that collects water from multiple branch pipes, and the branch pipes are small-diameter pipes that collect sewage from various plots and flow into the main pipe.

[0029] In some optional implementations, the diagnostic zone is a sub-assessment unit after being split. The sewage flow within each zone is relatively independent. The diagnostic zone has clear inlet and outlet nodes, and the water quality and flow rate within the diagnostic zone can be monitored independently.

[0030] Step S202: Obtain water quality index concentration and flow monitoring data for each diagnostic area, and determine the external water inflow infiltration rate for each diagnostic area based on the water quality index concentration and flow monitoring data.

[0031] The water quality index concentration refers to the concentration of water quality testing indicators collected at the effluent nodes of each diagnostic area. For example, the water quality testing indicators include hydrogen and oxygen isotopes (HNO3-O2). 2 H-H2O, 18 O-H2O), manganese ions (Mn) 2+ ), fluoride ions (F) - The water quality parameters include hardness, chlorophyll a, chemical oxygen demand (COD), and ammonia nitrogen (NH3-N). Among these, chlorophyll a can be used as an indicator to characterize the water quality of river water. 2+ F - Hardness can be used as a water quality indicator to characterize groundwater, while hydrogen and oxygen isotopes and NH3-N can be used as water quality indicators to characterize domestic sewage. Water quality indicator concentrations are collected using an automatic sampler at a frequency of 3 hours per sample, with 24-hour mixed samples taken for testing. Monitoring is conducted continuously for 3 days during dry weather.

[0032] In some alternative implementations, the flow monitoring data is continuous time-series flow data of the effluent nodes for each diagnostic area, which can be obtained using online flow monitoring equipment and continuously monitored for one week during dry weather.

[0033] In some alternative implementations, the water outlet nodes include outlet pipe network nodes, upstream water inlet nodes, sewage outlet well nodes of typical source dischargers, and potential external water (river water, groundwater, etc.) nodes.

[0034] In some alternative implementations, the external water inflow infiltration rate is used to characterize the extent to which external groundwater or rainwater infiltrates the pipe network in the diagnostic area.

[0035] Step S203: Determine the organic matter deposition degradation rate for each diagnostic area based on water quality index concentration and flow monitoring data.

[0036] Among them, the organic matter deposition degradation rate is used to characterize the overall rate at which organic matter in the wastewater of the diagnostic area settles into pipeline sediments and is consumed by biodegradation within the pipelines; the organic matter deposition degradation rate is used to reflect the potential capacity of the diagnostic area to generate organic sediments.

[0037] Step S204: Determine the target diagnostic area based on the inflow and infiltration rate of external water and the degradation rate of organic matter deposition in each diagnostic area.

[0038] Among them, the target diagnostic area is the area with high siltation risk that has been screened out, and it is the target area for subsequent detailed internal inspection of the pipeline.

[0039] In some alternative implementations, a target diagnostic zone is selected from multiple diagnostic zones based on the inflow and infiltration rate of external water and the degradation rate of organic matter deposition in each diagnostic zone.

[0040] Step S205: Based on the three-dimensional model of the pipeline in the target diagnostic area, determine the quantitative parameters of pipeline sediment in the sewage pipeline in the target diagnostic area, so as to carry out sewage pipeline network sediment investigation and diagnosis based on the quantitative parameters of pipeline sediment.

[0041] Among them, the three-dimensional model of the pipeline is a model that realistically restores the three-dimensional morphology of the inner wall space of the pipeline and the sediment at the bottom of the pipe, including the pipeline diameter and the spatial geometry of the sediment at the bottom of the pipe.

[0042] In some alternative implementations, pipeline sediment quantification parameters are parameters that quantitatively describe the pipeline siltation state, including the total volume of sediment in the pipe section, sedimentation rate, and average sediment thickness.

[0043] The wastewater pipe network sediment investigation and diagnosis method provided in this embodiment divides the target area into multiple diagnostic zones based on the topological relationship of the wastewater pipes in the target area. This zone division relies on the topological connection relationship between the main and branch pipes of the pipe network, avoiding direct full-scale testing of the entire large pipe network and narrowing down the spatial units for subsequent analysis. This embodiment acquires water quality index concentration and flow monitoring data for each diagnostic zone. Based on this data, it determines the external water inflow infiltration rate for each diagnostic zone. The external water inflow infiltration rate is a key external factor affecting pipe flow velocity and hydraulic conditions, thus influencing sediment deposition. It quantifies the interference of external water on the hydraulic environment of the pipe network in each diagnostic zone. Based on the water quality index concentration and flow monitoring data, this embodiment determines the organic matter deposition degradation rate for each diagnostic zone. The organic matter deposition degradation rate characterizes the comprehensive level of organic matter sedimentation and decomposition within the diagnostic zone, reflecting the intrinsic material source conditions for sediment formation in the diagnostic zone. This invention determines target diagnostic zones based on the inflow and infiltration rate of external water and the organic matter deposition and degradation rate of each diagnostic zone. It first performs macroscopic screening within the diagnostic zones, then identifies target diagnostic zones with abnormal deposition degradation based on the inflow and infiltration rate of external water and the organic matter deposition and degradation rate. The volume of sediment in these target diagnostic zones is then quantified, improving the efficiency of sediment quantification. Compared with related technologies, this invention can be implemented under high water level conditions, enabling the quantification of sediment in target diagnostic zones. By selecting target diagnostic zones with abnormal deposition degradation and then performing quantitative analysis of the sediments, the accuracy and efficiency of sediment quantification analysis are improved.

[0044] This embodiment provides a method for investigating and diagnosing sediment deposits in sewage pipe networks, which can be used with computer equipment. Figure 3 This is a second flowchart of the wastewater pipe network sediment investigation and diagnosis method according to an embodiment of the present invention, as follows: Figure 3 As shown, the process includes the following steps: Step S301: Based on the topological relationship of the sewage pipes in the target area, the target area is divided into multiple diagnostic zones.

[0045] Specifically, step S301 includes: Step S3011: Based on the topological relationship of the sewage pipeline in the target area, extract the intersection nodes of the main pipe and branch pipe, use the intersection nodes as dividing nodes, divide along the main pipe to obtain multiple sub-diagnostic areas; each sub-diagnostic area is an independent water catchment and drainage unit.

[0046] Among them, the junction of the main pipe and the branch pipe can be a junction inspection well, which is the well where the end of the branch pipe connects to the main pipe, and the location where the water from the branch pipe flows into the main pipe; In some alternative implementations, the segmentation node is a check well used for cutting the boundary of the area, serving as the start and end boundaries of the diagnostic area.

[0047] In some alternative implementations, the sub-diagnostic area is the area unit output from the first coarse division, obtained by dividing the main pipe into branch manifolds.

[0048] Step S3012: When the area of ​​the sub-diagnostic area is greater than the preset area threshold, it is divided according to the intersection nodes between the branches to obtain multiple diagnostic areas.

[0049] The preset area threshold is a pre-set area critical value that can be set according to actual conditions.

[0050] In some alternative implementations, the junction nodes between branches are inspection wells where branches intersect, without involving the main pipe. The wells where multiple branches converge are the confluence nodes within the branch network.

[0051] Step S3013: When the area of ​​the sub-diagnostic area is less than or equal to the preset area threshold, the sub-diagnostic area is used as the diagnostic area.

[0052] In some optional implementations, the complex sewage network is divided into several diagnostic zones based on the sewage network topology, sewage pumping stations, service areas of sewage treatment plants, and catchment boundaries. Specifically, the sewage network grid can be divided step-by-step according to the order of main pipes first, followed by branch pipes, forming different diagnostic zones and assigning them numbers. The dividing nodes are located at the junctions of main and branch pipes. For example, a sewage treatment plant has a service area of ​​4.8 km. 2 Based on the connection relationship between the main and branch pipes of the sewage pipe network, the total area is divided into 7 diagnostic zones, covering an area of ​​approximately 0.17 km². 2 ~2.02km 2 Among them, the upstream area of ​​location A can be further extended by 2.02 km as needed for diagnosis. 2 It is divided into more detailed diagnostic zones.

[0053] In some alternative implementations, when there are sewage pumping stations in the target area, the sewage network is divided into several diagnostic zones and the pumping stations are classified into different levels, with the sewage intermediate booster pumping stations as nodes. Figure 4 This is a schematic diagram of the classification of sewage pumping stations when there are sewage pumping stations in the study area according to an embodiment of the present invention. The sewage discharged by the upstream drainage user is first pumped to the sewage pumping station involved in the downstream pipeline during the pipeline transportation process, which is called the Class I pumping station. There are three Class I pumping stations. By analogy, a Class II pumping station, a Class III pumping station, and so on, can be obtained, up to a Class N pumping station, and finally the sewage is transported to the sewage treatment plant.

[0054] Step S302: Obtain water quality index concentration and flow monitoring data for each diagnostic area, and determine the external water inflow infiltration rate for each diagnostic area based on the water quality index concentration and flow monitoring data.

[0055] Specifically, step S302 includes: Step S3021: Based on the pipeline network diagnostic monitoring nodes of each diagnostic area, water quality is tested in each diagnostic area to obtain water quality index concentrations. Based on the pipeline network diagnostic monitoring nodes, flow rate is tested in each diagnostic area to obtain flow rate monitoring data.

[0056] Among them, pipeline diagnostic monitoring nodes are set up at the outlet pipeline nodes, upstream water inlet nodes, sewage outlet well nodes of typical source drainage users, and potential external water (river water, groundwater, etc.) nodes in the diagnostic area. Water quality is tested in each diagnostic area based on the pipeline diagnostic monitoring nodes to obtain the concentration of water quality indicators. Flow rate is also tested in each diagnostic area based on the pipeline diagnostic monitoring nodes to obtain flow monitoring data.

[0057] Step S3022: Based on the water quality index concentration and flow monitoring data, construct the water balance equation and the pollutant mass balance equation.

[0058] Among them, the water balance equation is the mathematical equation for the conservation of water matter in the diagnostic area, which is used to describe the conservation relationship of all water inputs and outputs in the area.

[0059] For example, the water balance equation can be expressed as: ; in, The external water volume for the diagnostic area is measured in cubic meters (m³). 3 / d, The amount of wastewater generated in the diagnostic area is expressed in cubic meters (m³). 3 / d, To diagnose the upstream water inflow volume of the area, the unit is m³. 3 / d, The effluent volume of the diagnostic area is measured in cubic meters (m³). 3 / d.

[0060] In some alternative implementations, the pollutant mass balance equation is a mathematical equation for the conservation of substances in the wastewater of the diagnostic area.

[0061] For example, the pollutant mass balance equation can be expressed as: ; in, The external water volume for the diagnostic area is measured in cubic meters (m³). 3 / d, For foreign water The index concentration is expressed in mg / L. The amount of wastewater generated in the diagnostic area is expressed in cubic meters (m³). 3 / d, In sewage The index concentration is expressed in mg / L. To diagnose the upstream water inflow volume of the area, the unit is m³. 3 / d, To diagnose the upstream water flow in the area The index concentration is expressed in mg / L. The effluent volume of the diagnostic area is measured in cubic meters (m³). 3 / d, To diagnose the water in the outlet of the area Indicator concentration.

[0062] Specifically, The indicators can be relatively stable dissolved water quality indicators such as hydrogen and oxygen isotopes, manganese ions, fluoride ions, ammonia nitrogen, hardness, and chlorophyll a.

[0063] Step S3023: Solve the water balance equation and the pollutant mass balance equation to obtain the amount of external water and the amount of wastewater generated in each diagnostic area.

[0064] The flow monitoring data includes the upstream water inflow of the diagnostic area. and the outflow of water from the diagnostic area The concentration of water quality indicators includes that from external water sources. index concentration sewage index concentration Diagnostic area upstream water index concentration and the water at the outlet of the diagnostic area index concentration Substituting the above data into the water balance equation and the pollutant mass balance equation, and solving the simultaneous water balance equation and pollutant mass balance equation, the amount of external water entering the diagnostic area can be obtained. Wastewater generated in the diagnostic area .

[0065] Step S3024: Based on the quotient of the external water inflow and the wastewater generated in the area, obtain the external water inflow infiltration rate for each diagnostic area.

[0066] The external water inflow infiltration rate represents the proportion of external water to the total amount of wastewater generated in the area. The formula for determining the external water inflow infiltration rate for each diagnostic area can be: ; in, The infiltration rate of external water inflow. To diagnose the amount of external water entering the area, To diagnose the amount of wastewater generated in the area.

[0067] In some alternative implementations, it is generally permissible that It is 10% to 15%.

[0068] Step S303: Determine the organic matter deposition degradation rate for each diagnostic area based on water quality index concentration and flow monitoring data.

[0069] Specifically, step S303 includes: Step S3031: Based on the water quality index concentration and flow monitoring data, construct the pollutant mass balance equation for the chemical oxygen demand index.

[0070] In particular, given that the decrease in the concentration of chemical oxygen demand (COD) is affected by the combined effects of infiltration and dilution from external water inflow and deposition and degradation within the pipeline, a pollutant mass balance equation based on COD is further constructed to solve for the deposition and degradation of pollutants in the area.

[0071] For example, the pollutant mass balance equation for the chemical oxygen demand index can be expressed as: ; in, To diagnose the amount of external water entering the area, This refers to the chemical oxygen demand (COD) concentration in imported water. To diagnose the amount of wastewater generated in the area, The concentration of chemical oxygen demand (COD) in wastewater. To diagnose the upstream water volume in the area, To diagnose the chemical oxygen demand (COD) concentration in the upstream water flowing into the area, To diagnose the outflow volume of the area, To diagnose the chemical oxygen demand (COD) concentration in the effluent water of the area, To diagnose the degradation rate of organic matter deposits in the pipe network of the affected area.

[0072] Step S3032: Solve the pollutant mass balance equation to obtain the organic matter deposition degradation rate of each diagnostic area.

[0073] Among them, the amount of external water in the diagnostic area will be... The amount of wastewater generated in the diagnostic area Substituting other known quantities into the pollutant mass balance equation and solving it, the organic matter deposition degradation rate of the pipe network in the diagnostic area is obtained. .

[0074] In some alternative implementations, the organic matter deposition degradation rate is used to characterize the degree of degradation of organic matter during the pipeline deposition process.

[0075] Step S304: Determine the target diagnostic area based on the inflow and infiltration rate of external water and the degradation rate of organic matter deposition in each diagnostic area.

[0076] Specifically, step S304 includes: Step S3041: The diagnostic area where the external water inflow infiltration rate is less than or equal to the preset external water inflow infiltration rate threshold and the organic matter deposition degradation rate is greater than the preset organic matter deposition degradation rate threshold is identified as the target diagnostic area.

[0077] The preset external water inflow infiltration rate threshold can be set according to the actual situation. For example, the preset external water inflow infiltration rate threshold can be any value between 10% and 15%.

[0078] In some optional implementations, the preset organic matter deposition degradation rate threshold can be set according to the actual situation. For example, the preset organic matter deposition degradation rate threshold can be 15%.

[0079] In some optional implementations, when the inflow infiltration rate of external water is less than or equal to a preset threshold for external water inflow infiltration rate, and the organic matter deposition degradation rate is greater than a preset threshold for organic matter deposition degradation rate, it indicates that the low pollutant concentration is more likely to be affected by the deposition degradation of organic matter in the pipeline network, and fine-grained detection and dredging of sediments should be prioritized.

[0080] Step S3042: The diagnostic area where the external water inflow infiltration rate is greater than the preset external water inflow infiltration rate threshold and the organic matter deposition degradation rate is greater than the preset organic matter deposition degradation rate threshold is identified as the target diagnostic area.

[0081] In some optional implementations, when the inflow and infiltration rate of external water is greater than a preset threshold for external water inflow and infiltration rate, and the organic matter deposition and degradation rate is greater than a preset threshold for organic matter deposition and degradation rate, it indicates that the effects of external water dilution and deposition degradation are significant, and external water investigation and sediment detection should be carried out simultaneously.

[0082] In some optional implementations, when the inflow rate of external water is greater than the preset threshold for external water inflow rate and the organic matter deposition degradation rate is less than or equal to the preset threshold for organic matter deposition degradation rate, it indicates that the low concentration of pollutants is mainly affected by the dilution of external water, and inflow investigation and external water stripping projects should be carried out first.

[0083] In some optional implementations, when the inflow infiltration rate of external water is less than or equal to a preset threshold for external water inflow infiltration rate, and the organic matter deposition degradation rate is greater than a preset threshold for organic matter deposition degradation rate, and the concentration of wastewater at the source in the area is less than or equal to a wastewater concentration threshold (the wastewater concentration threshold can be 260 mg / L), it indicates that it may be related to the characteristics of the source discharge, and a water quality survey of the dischargers should be carried out.

[0084] Step S305: Based on the 3D model of the pipelines in the target diagnostic area, determine the quantitative parameters of pipeline sediment in the sewage pipelines of the target diagnostic area, so as to conduct sewage pipeline network sediment investigation and diagnosis based on the quantitative parameters of pipeline sediment. For details, please refer to... Figure 2Step S205 of the illustrated embodiment will not be described again here.

[0085] The wastewater pipe network sediment investigation and diagnosis method provided in this embodiment constructs a water quantity and mass balance model through the regional water quality characteristic factor method. It can quickly isolate the influence of external water dilution and sediment degradation, accurately screen out key investigation areas with sediment problems, and avoid the high cost of blindly probing the entire pipe network.

[0086] This embodiment provides a method for investigating and diagnosing sediment deposits in sewage pipe networks, which can be used with computer equipment. Figure 5 This is a third flowchart of the wastewater pipe network sediment investigation and diagnosis method according to an embodiment of the present invention, as follows: Figure 5 As shown, the process includes the following steps: Step S501: Based on the sewage pipe topology of the target area, the target area is divided into multiple diagnostic zones. For details, please refer to [link to relevant documentation]. Figure 3 Step S101 of the illustrated embodiment will not be described again here.

[0087] Step S502: Obtain water quality indicator concentration and flow monitoring data for each diagnostic area. Based on the water quality indicator concentration and flow monitoring data, determine the external water inflow infiltration rate for each diagnostic area. For details, please refer to [link to relevant documentation]. Figure 3 Step S302 of the illustrated embodiment will not be described again here.

[0088] Step S503: Based on water quality index concentration and flow monitoring data, determine the organic matter deposition degradation rate for each diagnostic area. For details, please refer to [link to relevant documentation]. Figure 3 Step S303 of the illustrated embodiment will not be described again here.

[0089] Step S504: Determine the target diagnostic area based on the external water inflow infiltration rate and organic matter deposition degradation rate of each diagnostic area. For details, please refer to [link to relevant documentation]. Figure 3 Step S304 of the illustrated embodiment will not be described again here.

[0090] Step S505: Based on the three-dimensional model of the pipeline in the target diagnostic area, determine the quantitative parameters of pipeline sediment in the sewage pipeline in the target diagnostic area, so as to carry out sewage pipeline network sediment investigation and diagnosis based on the quantitative parameters of pipeline sediment.

[0091] Specifically, step S505 includes: Step S5051: Control the underwater mobile device equipped with multiple sensors and sonar to conduct detection in the sewage pipe network of the target diagnostic area, and obtain cross-sectional point cloud data containing sediment information and multi-source sensor data.

[0092] The underwater mobile device can be an underwater remotely operated robot or a floating inspection platform; the sonar can be a rotating sonar fixed on the underwater mobile device to scan the internal contour of the sewage pipe, including the inner wall of the pipe, the sewage-sediment interface and the sediment boundary. The location or distribution of the sediment is determined by the point cloud data collected by the sonar (based on the sonar coordinate system). The maximum measurement range from the center of the sonar probe is 0.15m to 6m.

[0093] In some alternative implementations, multiple sensors include gyroscopes, accelerometers, odometers, etc.; the gyroscopes are fixed to the underwater mobile device and are used to collect the attitude angles (roll angle, pitch angle, yaw angle, and quaternion) of the underwater mobile device; the accelerometers are fixed to the underwater mobile device and are used to collect the three-axis acceleration of the underwater mobile device; the odometers are used to collect the distance the underwater mobile device moves along the pipe direction with an accuracy of 1 mm.

[0094] In some optional implementations, the underwater mobile device also includes a data acquisition and time synchronization module, a communication and power supply module, etc. The data acquisition and time synchronization module is used to synchronously acquire and unify the timestamps of each sensor to ensure the spatiotemporal consistency of data fusion. The communication and power supply module is responsible for communicating with the ground control terminal and supplying power to the device.

[0095] In some alternative implementations, an underwater mobile device is deployed inside the pipe and controlled to move axially along the pipe. A rotating sonar continuously scans the pipe's cross-section, acquiring a series of cross-sectional point cloud data containing sediment information. Simultaneously, gyroscopes, accelerometers, and odometry collect real-time attitude and motion information of the detection device in the absence of GPS (Global Positioning System) signals. In this process, the sonar overcomes its dependence on illumination and low water levels, enabling effective detection even in a full-pipe state. The multi-sensor data provides a basis for eliminating dynamic errors.

[0096] Step S5052: Correct the cross-sectional point cloud data based on the multi-source sensor data to obtain the target cross-sectional point cloud data, and construct a three-dimensional model of the pipeline based on the target cross-sectional point cloud data.

[0097] In some optional implementations, unscented Kalman filtering and smoothing algorithms are used to fuse multi-source sensor data from gyroscopes, accelerometers, and odometry to accurately estimate the real-time position and attitude (roll, pitch, yaw) of the underwater mobile device in a GPS-free environment. Using the fused high-precision attitude data, the original point cloud data based on the sonar coordinate system is transformed to a fixed global coordinate system of the pipeline, eliminating point cloud data offsets and distortions caused by sewage flow interference and robot motion jitter.

[0098] Specifically, the fixed coordinate system of the pipeline is set as (X...s Y s Z s The sonar body coordinate system is ( , , At a certain moment, the coordinates of the center of the sonar body coordinate system in the fixed coordinate system of the pipeline are ( , , The coordinates of a point in the sonar point cloud in the sonar body coordinate system are ( , , The attitude angle of the underwater mobile device was detected. , , Point cloud correction can be performed according to the following steps: Based on the attitude angle of the underwater mobile device, determine the transformation matrix, which can be expressed as: ; in, For the transformation matrix, The yaw angle is the attitude angle of the underwater mobile device. The pitch angle represents the attitude angle of the underwater mobile device. The roll angle is the attitude angle of the underwater mobile device.

[0099] In some alternative implementations, the coordinates of a point in the sonar body coordinate system are initially transformed according to the transformation matrix: ; in,( , , ( ) represents the point cloud coordinates after the initial transformation. For the transformation matrix, ( , , () represents the coordinates of a point in the point cloud within the sonar body coordinate system.

[0100] In some alternative implementations, the formula for correcting the cross-sectional point cloud data based on multi-source sensor data is as follows: ; in,( , , () represents the coordinates of the point cloud after the initial transformation. , , ) represents the coordinates of the center of the sonar body coordinate system in the fixed coordinate system of the pipeline. , , ( ) is the target cross-sectional point cloud data.

[0101] In some alternative implementations, a push-broom modeling method is used to reconstruct a 3D model of the pipeline's interior based on the corrected target cross-sectional point cloud data. The reconstructed model is then compared with the pipeline design model or a standard circular pipe model to accurately identify sediment areas. Push-broom modeling uses the pipeline axis as its trajectory. As the underwater mobile device moves along the axis, sonar scans the pipeline cross-section. Point cloud data from each cross-section is used to generate a measurement model of the pipeline's interior. Depending on the acquisition frequency of the acquisition device, interpolation can be used to generate a complete 3D model of the pipeline's interior from sparse point cloud data.

[0102] Step S5053: Based on the three-dimensional model of the pipeline, obtain the distance between two adjacent sediment cross sections, the area of ​​the first sediment cross section, and the area of ​​the second sediment cross section.

[0103] Among them, two adjacent sediment cross sections are two vertical cut sections that are one in front of the other and next to each other along the pipe axis; the area of ​​the first sediment cross section is the cross-sectional area occupied by the sediment in the first of the two adjacent cross sections; the area of ​​the second sediment cross section is the cross-sectional area occupied by the sediment in the second of the two adjacent cross sections.

[0104] Step S5054: Determine the total volume of sediment in the pipe section based on the distance between two adjacent sediment cross sections, the area of ​​the first sediment cross section, and the area of ​​the second sediment cross section.

[0105] The formula for determining the total volume of sediment in the pipe section is as follows: ; in, This represents the total volume of sediment in the pipe section. The cross-sectional area of ​​the first sediment is... This represents the cross-sectional area of ​​the second sediment. This represents the distance between two adjacent sediment cross sections.

[0106] Step S5055: Determine the first product result based on the product of the standard cross-sectional area of ​​the pipeline and the length of the pipeline segment; obtain the deposition rate based on the quotient of the total volume of sediment in the pipeline segment and the first product result.

[0107] The formula for determining the deposition rate is: ; in, For sedimentation rate, This represents the total volume of sediment in the pipe section. This refers to the standard cross-sectional area of ​​the pipeline. This refers to the length of the pipe section.

[0108] Step S5056: Based on the product of the effective deposition width at the bottom of the pipe and the length of the pipe section, a second product result is obtained. Based on the quotient of the total volume of the pipe section sediment and the second product result, the average thickness of the sediment is obtained.

[0109] The formula for determining the average thickness of sediments is as follows: ; in, The average thickness of the sediment. This represents the total volume of sediment in the pipe section. The effective deposition width at the bottom of the pipe. This refers to the length of the pipe section.

[0110] Step S5057: Based on the total volume of sediment in the pipe section, the sedimentation rate, and the average thickness of the sediment, obtain the quantitative parameters of the pipe sediment.

[0111] The quantitative parameters of pipeline sediments are obtained from the total volume of sediments in the pipe section, the sedimentation rate, and the average thickness of sediments.

[0112] In some alternative implementations, sediment quantification parameters are used to conduct sediment investigation and diagnosis of the sewage pipe network to determine the actual situation of sedimentation in the sewage pipe network.

[0113] The wastewater pipeline sediment investigation and diagnosis method provided in this embodiment uses an underwater mobile device to enter the pipeline for operation, avoiding the safety risks of manual entry into wells. It directly obtains the original spatial information of sediments on the inner wall and bottom of the pipeline by collecting cross-sectional point cloud data and multi-source sensor data based on sonar and multi-sensor combination. Data collection can be completed in pipeline environments where the sewage is full and the turbidity is too high to be seen visually. The cross-sectional point cloud data is corrected using multi-source sensor data, which can compensate for the point cloud distortion errors caused by sewage turbidity, impurities in the water and sonar noise, and eliminate the measurement deviation of the original point cloud. Based on the corrected high-precision point cloud, a three-dimensional model of the pipeline is constructed to restore the true three-dimensional morphology of the inner wall and sediments of the pipeline. This invention determines the total volume of sediment in a pipe section based on the distance between two adjacent sediment cross-sections, the area of ​​the first sediment cross-section, and the area of ​​the second sediment cross-section. This allows for a quantitative solution to the total amount of sediment within the pipe section, directly reflecting the actual sediment stock. The sedimentation rate characterizes the proportion of sediment in the total flow space of the pipeline. The sedimentation rate allows for horizontal comparison of the severity of siltation in pipe sections of different diameters and lengths, eliminating the interference of pipe diameter. The average sediment thickness is calculated based on the effective area at the bottom of the pipe where sedimentation can occur, avoiding interference from non-depositional spaces above the pipe. The average sediment thickness directly reflects the thickness of the siltation layer at the bottom of the pipe and is directly related to the water flow capacity of the pipeline network and the actual working conditions of dredging operations. This invention can determine not only the sediment stock but also the degree of flow occupancy and the thickness of siltation at the bottom of the pipe, achieving accurate quantitative analysis of sediment.

[0114] This embodiment provides a method for investigating and diagnosing sediment deposits in sewage pipe networks, which can be used with computer equipment. Figure 6 This is a fourth flowchart of the wastewater pipe network sediment investigation and diagnosis method according to an embodiment of the present invention, as follows: Figure 6 As shown, the process includes the following steps: The project involves screening key areas for wastewater pipeline sedimentation and refining the detection of sedimentation conditions in key areas. Screening key areas for wastewater pipeline sedimentation includes: diagnostic area delineation; water quality and quantity testing; calculation of external water inflow and infiltration rates; calculation of organic matter deposition degradation rates; and screening and classification of key areas based on external water inflow and infiltration rates and organic matter deposition degradation rates. Refined detection of sedimentation conditions in key areas includes: construction of an underwater mobile device with multi-sensor fusion; high-level water level pipeline sedimentation detection; multi-sensor data fusion; and sediment volume calculation and assessment.

[0115] This embodiment also provides a sewage pipe network sediment investigation and diagnosis device, which is used to implement the above embodiments and preferred embodiments, and will not be repeated as already described. As used below, the term "module" can be a combination of software and / or hardware that implements a predetermined function. Although the device described in the following embodiments is preferably implemented in software, hardware implementation, or a combination of software and hardware, is also possible and contemplated.

[0116] This embodiment provides a device for investigating and diagnosing sediment deposits in sewage pipe networks, such as... Figure 7 As shown, it includes: The region division module 701 is used to divide the target region into multiple diagnostic zones based on the topological relationship of the sewage pipeline in the target region.

[0117] The external water inflow infiltration rate determination module 702 is used to acquire water quality index concentration and flow monitoring data for each diagnostic area, and determine the external water inflow infiltration rate for each diagnostic area based on the water quality index concentration and flow monitoring data.

[0118] The organic matter deposition degradation rate determination module 703 is used to determine the organic matter deposition degradation rate of each diagnostic area based on water quality index concentration and flow monitoring data.

[0119] The target diagnostic area determination module 704 is used to determine the target diagnostic area based on the inflow and infiltration rate of external water and the degradation rate of organic matter deposition in each diagnostic area.

[0120] The wastewater pipe network sediment investigation and diagnosis module 705 is used to determine the quantitative parameters of pipe sediments in the target diagnosis area based on the three-dimensional model of the pipes in the target diagnosis area, so as to carry out wastewater pipe network sediment investigation and diagnosis based on the quantitative parameters of pipe sediments.

[0121] In some alternative implementations, the region partitioning module 701 includes: The first division unit is used to extract the intersection nodes of the main pipe and branch pipes according to the sewage pipe topology of the target area, and use the intersection nodes as dividing nodes to divide along the main pipe to obtain multiple sub-diagnostic areas; each sub-diagnostic area is an independent water catchment and drainage unit.

[0122] The second division unit is used to divide the sub-diagnostic area into multiple diagnostic areas based on the intersection nodes between branches when the area of ​​the sub-diagnostic area is greater than a preset area threshold.

[0123] The third division unit is used to treat a sub-diagnostic area as a diagnostic area when the area of ​​the sub-diagnostic area is less than or equal to a preset area threshold.

[0124] In some alternative implementations, the external water inflow infiltration rate determination module 702 includes: The data monitoring unit is used to detect the water quality of each diagnostic area based on the pipeline network diagnostic monitoring nodes to obtain the concentration of water quality indicators, and to detect the flow rate of each diagnostic area based on the pipeline network diagnostic monitoring nodes to obtain flow monitoring data.

[0125] The equation building unit is used to construct water balance equations and pollutant mass balance equations based on water quality index concentration and flow monitoring data.

[0126] The water quantity calculation unit is used to solve the water balance equation and the pollutant mass balance equation to obtain the amount of external water and the amount of wastewater generated in each diagnostic area.

[0127] The external water inflow infiltration rate determination unit is used to obtain the external water inflow infiltration rate of each diagnostic area based on the quotient of the external water volume and the sewage volume generated in the area.

[0128] In some optional embodiments, the organic matter deposition degradation rate determination module 703 includes; The equation building unit is used to construct the pollutant mass balance equation for the chemical oxygen demand (COD) index based on water quality index concentration and flow monitoring data.

[0129] The degradation rate solution unit is used to solve the pollutant mass balance equation to obtain the organic matter deposition degradation rate of each diagnostic area.

[0130] In some optional implementations, the target diagnostic region determination module 704 includes: The first area determination unit is used to determine the diagnostic areas where the external water inflow infiltration rate is less than or equal to a preset external water inflow infiltration rate threshold and the organic matter deposition degradation rate is greater than a preset organic matter deposition degradation rate threshold, as target diagnostic areas.

[0131] The second area determination unit is used to determine the diagnostic areas where the external water inflow infiltration rate is greater than a preset external water inflow infiltration rate threshold and the organic matter deposition degradation rate is greater than a preset organic matter deposition degradation rate threshold, as target diagnostic areas.

[0132] In some optional implementations, the wastewater network sediment investigation and diagnosis module 705 includes: The data detection unit is used to control an underwater mobile device equipped with multiple sensors and sonar to conduct detection in the sewage pipe network of the target diagnostic area, and obtain cross-sectional point cloud data containing sediment information and multi-source sensor data.

[0133] The model building unit is used to correct the cross-sectional point cloud data based on multi-source sensor data to obtain the target cross-sectional point cloud data, and to build a three-dimensional model of the pipeline based on the target cross-sectional point cloud data.

[0134] The data acquisition unit is used to obtain the distance between two adjacent sediment cross sections, the area of ​​the first sediment cross section, and the area of ​​the second sediment cross section based on the three-dimensional model of the pipeline.

[0135] The sediment volume determination unit is used to determine the total sediment volume of the pipe section based on the distance between two adjacent sediment sections, the area of ​​the first sediment section, and the area of ​​the second sediment section.

[0136] The sedimentation rate determination unit is used to determine the first product result based on the product of the standard cross-sectional area of ​​the pipeline and the length of the pipeline segment, and to obtain the sedimentation rate based on the quotient of the total volume of sediment in the pipeline segment and the first product result.

[0137] The sediment thickness determination unit is used to obtain a second product result based on the product of the effective sediment width at the bottom of the pipe and the pipe segment length, and to obtain the average sediment thickness based on the quotient of the total sediment volume of the pipe segment and the second product result.

[0138] The quantification parameter determination unit is used to obtain the quantification parameters of pipeline sediments based on the total volume of sediments in the pipe section, the sedimentation rate, and the average thickness of sediments.

[0139] The wastewater pipe network sediment investigation and diagnosis device provided in this embodiment of the invention can execute the wastewater pipe network sediment investigation and diagnosis method provided in any embodiment of the invention, and has the corresponding functional modules and beneficial effects of the method. Further functional descriptions of the above modules and units are the same as in the corresponding embodiments described above, and will not be repeated here.

[0140] Figure 8 This is a schematic diagram of the structure of an electronic device provided in an embodiment of the present invention.

[0141] The following is a detailed reference. Figure 8This diagram illustrates a suitable structural schematic for implementing an electronic device according to embodiments of the present invention. The electronic device may include a processor (e.g., a central processing unit, graphics processor, etc.) 801, which can perform various appropriate actions and processes based on a program stored in read-only memory (ROM) 802 or a program loaded from memory 808 into random access memory (RAM) 803. The RAM 803 also stores various programs and data required for the operation of the electronic device. The processor 801, ROM 802, and RAM 803 are interconnected via a bus 804. An input / output (I / O) interface 805 is also connected to the bus 804.

[0142] Typically, the following devices can be connected to I / O interface 805: input devices 806 including, for example, touchscreens, touchpads, keyboards, mice, cameras, microphones, accelerometers, gyroscopes, etc.; output devices 807 including, for example, liquid crystal displays (LCDs), speakers, vibrators, etc.; memory devices 808 including, for example, magnetic tapes, hard disks, etc.; and communication devices 809. Communication device 809 allows electronic devices to communicate wirelessly or wiredly with other devices to exchange data. Although Figure 8 Electronic devices with various devices are shown, but it should be understood that it is not required to implement or have all of the devices shown, and more or fewer devices may be implemented or have instead.

[0143] In particular, according to embodiments of the present invention, the processes described above with reference to the flowcharts can be implemented as computer software programs. For example, embodiments of the present invention include a computer program product comprising a computer program carried on a non-transitory computer-readable medium, the computer program containing program code for performing the methods shown in the flowcharts. In such embodiments, the computer program can be downloaded and installed from a network via a communication device 809, or installed from a memory 808, or installed from a ROM 802. When the computer program is executed by the processor 801, it performs the functions defined in the wastewater pipe network sediment investigation and diagnosis method of the embodiments of the present invention.

[0144] Figure 8 The electronic device shown is merely an example and should not be construed as limiting the functionality and scope of use of the embodiments of the present invention.

[0145] This invention also provides a computer-readable storage medium. The methods described above according to embodiments of the invention can be implemented in hardware or firmware, or implemented as computer code that can be recorded on a storage medium, or implemented as computer code downloaded via a network and originally stored on a remote storage medium or a non-transitory machine-readable storage medium and then stored on a local storage medium. Thus, the methods described herein can be processed by software stored on a storage medium using a general-purpose computer, a dedicated processor, or programmable or dedicated hardware. The storage medium can be a magnetic disk, optical disk, read-only memory, random access memory, flash memory, hard disk, or solid-state drive, etc.; further, the storage medium can also include combinations of the above types of memory. It is understood that computers, processors, microprocessor controllers, or programmable hardware include storage components capable of storing or receiving software or computer code. When the software or computer code is accessed and executed by the computer, processor, or hardware, the wastewater pipe network sediment investigation and diagnosis method shown in the above embodiments is implemented.

[0146] A portion of this invention can be applied as a computer program product, such as computer program instructions, which, when executed by a computer, can invoke or provide the methods and / or technical solutions according to the invention through the operation of the computer. Those skilled in the art will understand that the forms in which computer program instructions exist in a computer-readable medium include, but are not limited to, source files, executable files, installation package files, etc. Correspondingly, the ways in which computer program instructions are executed by a computer include, but are not limited to: the computer directly executing the instructions, or the computer compiling the instructions and then executing the corresponding compiled program, or the computer reading and executing the instructions, or the computer reading and installing the instructions and then executing the corresponding installed program. Here, the computer-readable medium can be any available computer-readable storage medium or communication medium accessible to a computer.

[0147] Although embodiments of the invention have been described in conjunction with the accompanying drawings, those skilled in the art can make various modifications and variations without departing from the spirit and scope of the invention, and all such modifications and variations fall within the scope defined by the appended claims.

Claims

1. A method for investigating and diagnosing sediment deposits in sewage pipe networks, characterized in that, The method includes: Based on the topological relationship of the sewage pipes in the target area, the target area is divided into multiple diagnostic zones; Acquire water quality index concentration and flow monitoring data for each diagnostic area, and determine the external water inflow infiltration rate for each diagnostic area based on the water quality index concentration and flow monitoring data; Based on the water quality index concentration and the flow monitoring data, the organic matter deposition degradation rate of each diagnostic area is determined; The target diagnostic area is determined based on the external water inflow infiltration rate and the organic matter deposition degradation rate of each diagnostic area; Based on the three-dimensional model of the pipeline in the target diagnostic area, the pipeline sediment quantification parameters of the sewage pipeline in the target diagnostic area are determined, so as to carry out sewage pipeline network sediment investigation and diagnosis based on the pipeline sediment quantification parameters.

2. The method according to claim 1, characterized in that, The target area is divided into multiple diagnostic zones based on the topological relationship of the sewage pipes in the target area, including: Based on the sewage pipeline topology of the target area, the intersection nodes of the main pipe and branch pipes are extracted, and the intersection nodes are used as dividing nodes to divide the main pipe into multiple sub-diagnostic areas; each sub-diagnostic area is an independent water catchment and drainage unit. When the area of ​​the sub-diagnostic area is greater than a preset area threshold, it is divided according to the intersection nodes between the branches to obtain multiple diagnostic areas; When the area of ​​the sub-diagnostic region is less than or equal to the preset area threshold, the sub-diagnostic region is used as the diagnostic region.

3. The method according to claim 1 or 2, characterized in that, The step of acquiring water quality index concentration and flow monitoring data for each diagnostic area, and determining the external water inflow infiltration rate for each diagnostic area based on the water quality index concentration and flow monitoring data, includes: Based on the pipeline network diagnostic monitoring nodes of each diagnostic area, water quality is tested in each diagnostic area to obtain the concentration of the water quality index. Based on the pipeline network diagnostic monitoring nodes, the flow rate of each diagnostic area is tested to obtain the flow rate monitoring data. Based on the water quality index concentrations and the flow monitoring data, water balance equations and pollutant mass balance equations are constructed. Solve the water balance equation and the pollutant mass balance equation to obtain the amount of external water and the amount of wastewater generated in each diagnostic area; The external water inflow infiltration rate for each diagnostic area is obtained by quotient of the external water inflow and the wastewater generated in the area.

4. The method according to claim 1 or 2, characterized in that, The determination of the organic matter deposition degradation rate for each diagnostic zone based on the water quality index concentration and the flow monitoring data includes: Based on the water quality index concentration and the flow monitoring data, a pollutant mass balance equation for the chemical oxygen demand index is constructed. The pollutant mass balance equation is solved to obtain the organic matter deposition degradation rate of each diagnostic area.

5. The method according to claim 1 or 2, characterized in that, The step of determining the target diagnostic area based on the external water inflow infiltration rate and the organic matter deposition degradation rate of each diagnostic area includes: The diagnostic area where the external water inflow infiltration rate is less than or equal to a preset external water inflow infiltration rate threshold and the organic matter deposition degradation rate is greater than a preset organic matter deposition degradation rate threshold is determined as the target diagnostic area. The diagnostic area where the external water inflow infiltration rate is greater than the preset external water inflow infiltration rate threshold and the organic matter deposition degradation rate is greater than the preset organic matter deposition degradation rate threshold is determined as the target diagnostic area.

6. The method according to claim 1 or 2, characterized in that, The step of determining the pipeline sediment quantification parameters of the sewage pipelines in the target diagnostic area based on the three-dimensional model of the pipelines in the target diagnostic area, and then conducting sewage pipeline network sediment investigation and diagnosis based on the pipeline sediment quantification parameters, includes: The underwater mobile device equipped with multiple sensors and sonar is controlled to conduct detection in the sewage pipe network of the target diagnostic area to obtain cross-sectional point cloud data containing sediment information and multi-source sensor data. The cross-sectional point cloud data is corrected based on the multi-source sensor data to obtain the target cross-sectional point cloud data, and the three-dimensional model of the pipeline is constructed based on the target cross-sectional point cloud data. Based on the three-dimensional model of the pipeline, the distance between two adjacent sediment cross sections, the area of ​​the first sediment cross section, and the area of ​​the second sediment cross section are obtained; The total volume of sediment in the pipe section is determined based on the distance between two adjacent sediment cross sections, the area of ​​the first sediment cross section, and the area of ​​the second sediment cross section. The first product result is determined by multiplying the standard cross-sectional area of ​​the pipeline by the length of the pipeline segment. The deposition rate is obtained by dividing the total volume of sediment in the pipeline segment by the first product result. The second product result is obtained by multiplying the effective deposition width at the bottom of the pipe by the length of the pipe segment. The average thickness of the deposit is obtained by dividing the total volume of the deposit in the pipe segment by the second product result. The quantitative parameters of the pipeline sediments are obtained based on the total volume of sediments in the pipe section, the sedimentation rate, and the average thickness of the sediments.

7. A device for investigating and diagnosing sediment deposits in sewage pipe networks, characterized in that, The device includes: The region division module is used to divide the target region into multiple diagnostic zones based on the topological relationship of the sewage pipelines in the target region. The external water inflow infiltration rate determination module is used to acquire water quality index concentration and flow monitoring data for each of the diagnostic areas, and determine the external water inflow infiltration rate for each of the diagnostic areas based on the water quality index concentration and the flow monitoring data. An organic matter deposition degradation rate determination module is used to determine the organic matter deposition degradation rate of each diagnostic area based on the water quality index concentration and the flow monitoring data. The target diagnostic area determination module is used to determine the target diagnostic area based on the external water inflow infiltration rate and the organic matter deposition degradation rate of each diagnostic area; The sewage pipe network deposition investigation and diagnosis module is used to determine the quantitative parameters of pipe deposits in the sewage pipes of the target diagnosis area based on the three-dimensional model of the pipes in the target diagnosis area, so as to carry out sewage pipe network deposition investigation and diagnosis based on the quantitative parameters of pipe deposits.

8. An electronic device, characterized in that, include: The system includes a memory and a processor, which are interconnected. The memory stores computer instructions, and the processor executes the computer instructions to perform the sewage pipe network sediment investigation and diagnosis method according to any one of claims 1 to 6.

9. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer instructions for causing the computer to execute the sewage pipe network sediment investigation and diagnosis method according to any one of claims 1 to 6.

10. A computer program product, characterized in that, It includes computer instructions for causing a computer to execute the sewage pipe network sediment investigation and diagnosis method according to any one of claims 1 to 6.

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