A method and system for investigating the topology of drainage pipe networks

Abstract

This invention relates to the field of drainage management technology and discloses a method and system for investigating the topological relationships of drainage pipe networks. The method includes: acquiring target drainage pipe network information from a data backend and transmitting the target drainage pipe network information to a tracer gas injection device; the tracer gas injection device injecting a mixed gas into a target manhole of the upstream drainage pipe network based on the target drainage pipe network information; an unmanned aerial vehicle (UAV)-borne spectral detection device performing cyclic scanning of the tracer gas spectral characteristics of the manhole at a given spatial coordinate along the mixed gas transmission direction to obtain measured tracer gas data; the data backend simulating the tracer gas diffusion process under various misconnection paths to obtain simulated tracer gas data, and identifying misconnection points based on the measured and simulated tracer gas data to obtain the drainage pipe network misconnection investigation results. This invention can determine pipe misconnection problems without entering the pipe interior, significantly reducing implementation costs and difficulty.

Description

Technical Field

[0001] This invention relates to the field of drainage management technology, specifically to a method and system for investigating the topology of drainage pipe networks. Background Technology

[0002] After the construction of urban drainage pipe networks, there are common problems of misconnection and incorrect connection, resulting in direct discharge of sewage during dry weather and overflow pollution during rainy weather, which seriously threatens the health of urban water ecological environment and urgently requires investigation and treatment.

[0003] The methods for investigating misconnections in related drainage pipe networks require entering the pipes, which significantly increases implementation costs and time. Summary of the Invention

[0004] In view of this, the present invention provides a method and system for investigating the topology of drainage pipe networks, so as to solve the problem of significantly increased implementation cost and cycle of the method for investigating misconnections in drainage pipe networks.

[0005] In a first aspect, the present invention provides a method for investigating the topological relationships of drainage pipe networks, applied to a drainage pipe network misconnection investigation system. The system includes a data backend, a tracer gas injection device, and an UAV-borne spectral detection device; the data backend is connected to both the tracer gas injection device and the UAV-borne spectral detection device; the method includes:

[0006] The data backend obtains the target drainage network information and transmits it to the tracer gas injection device.

[0007] The tracer gas injection device injects a mixed gas into the target inspection well of the upstream drainage network based on the target drainage network information; wherein the mixed gas is tracer gas and carrier gas with a preset mixing ratio;

[0008] The UAV-borne spectral detection device performs a cyclic scan of the tracer gas spectral characteristics of the inspection well at a given spatial coordinate along the direction of gas mixture transport, and obtains the measured data of the tracer gas.

[0009] The data backend simulates the diffusion process of tracer gas under various mixed connection paths to obtain tracer gas simulation data.

[0010] The data backend identifies the locations of misconnections based on the actual and simulated data of tracer gas, and obtains the results of the investigation of misconnections in the drainage network.

[0011] This embodiment provides a method for investigating the topology of a drainage pipe network. A tracer gas injection device injects a mixed gas into the target manhole of the upstream drainage pipe network. An unmanned aerial vehicle (UAV)-borne spectral detection device automatically cruises and detects the gas characteristic information at the manhole. The data backend then identifies misconnection points based on measured and simulated tracer gas data, obtaining the investigation results for misconnections in the drainage pipe network. This method allows for the determination of misconnection problems without entering the pipes, significantly reducing implementation costs and difficulty. Furthermore, by diagnosing all erroneous connections in the storm and sewage pipes, it achieves a comprehensive investigation of misconnections in the drainage pipe network.

[0012] In one optional embodiment, the tracer gas injection device includes: a high-pressure gas source storage module, a flow control module, and a gas injection module; the tracer gas injection device injects a mixed gas into a target inspection well in the upstream drainage network based on target drainage network information, including:

[0013] The gas injection module determines the amount and timing of mixed gas injection based on the target drainage network information.

[0014] Based on the mixed gas injection volume and injection time, the gas injection module injects the tracer gas and carrier gas stored in the high-pressure gas source storage module into the target inspection well of the upstream drainage network by controlling the flow control module.

[0015] This embodiment provides a method for investigating the topology of a drainage pipe network. By controlling the flow control module, the tracer gas and carrier gas stored in the high-pressure gas source storage module are injected into the target inspection well of the upstream drainage pipe network. The method utilizes the transmission process of the tracer gas in the pipeline to locate the misconnection of the drainage pipe network. The problem of misconnection can be determined without entering the pipeline, which significantly reduces the implementation cost and difficulty.

[0016] In one optional implementation, the gas injection module determines the mixed gas injection volume and injection time based on the target drainage network information, including:

[0017] The gas injection module obtains the detection limit of the UAV-borne spectral detection device, determines the pipe volume based on the target drainage network information, and calculates the total amount of tracer gas injected based on the detection limit of the UAV-borne spectral detection device and the pipe volume.

[0018] The gas injection module obtains the volume ratio of tracer gas to carrier gas, and calculates the total volume of carrier gas injected based on the total volume of tracer gas injected and the volume ratio of tracer gas to carrier gas.

[0019] The gas injection module determines the amount of mixed gas to be injected based on the total amount of tracer gas injected and the total amount of carrier gas injected;

[0020] The gas injection module acquires the tracer gas injection flow rate and the carrier gas injection flow rate, and determines the mixed gas injection time based on the total tracer gas injection volume and the tracer gas injection flow rate, or the total carrier gas injection volume and the carrier gas injection flow rate.

[0021] This embodiment provides a method for investigating the topology of drainage pipe networks. By calculating the amount and time of mixed gas injection, it ensures the efficient diffusion of mixed gas in the pipeline, making the detection results of the UAV-borne spectral detection device more accurate and ensuring the accuracy of the investigation of misconnections in drainage pipe networks.

[0022] In one optional implementation, the gas injection module obtains the detection limit of the UAV-borne spectral detection device, determines the pipe volume based on the target drainage network information, and calculates the total amount of tracer gas injected based on the detection limit of the UAV-borne spectral detection device and the pipe volume; wherein, the formula for calculating the total amount of tracer gas injected is as follows:

[0023]

[0024] in, This represents the total amount of tracer gas injected. The detection limit of the UAV-borne spectral detection device. For the volume of the pipe, For compensation coefficient, This is to ensure that the tracer gas actually achieves a uniform mixing degree within the pipeline.

[0025] In one optional implementation, the gas injection module obtains the volume ratio of tracer gas to carrier gas, and calculates the total carrier gas injection amount based on the total tracer gas injection amount and the volume ratio of tracer gas to carrier gas; wherein, the formula for calculating the total carrier gas injection amount is as follows:

[0026]

[0027] in, This represents the total amount of carrier gas injected. This represents the volume ratio of the tracer gas to the carrier gas.

[0028] In one optional implementation, the gas injection module acquires the tracer gas injection flow rate and the carrier gas injection flow rate, and determines the mixed gas injection time based on the total tracer gas injection volume and the tracer gas injection flow rate, or the total carrier gas injection volume and the carrier gas injection flow rate; wherein, the formula for calculating the mixed gas injection time is as follows:

[0029]

[0030] in, For the injection time of the mixed gas, For the tracer gas injection flow rate, Inject the carrier gas flow rate.

[0031] In one optional implementation, the data backend simulates the tracer gas diffusion process under various mixed connection paths to obtain tracer gas simulation data, including:

[0032] The data backend determines the topology of the drainage pipeline based on the target drainage network information, and establishes a pipeline transport model for the tracer gas based on the drainage pipeline topology.

[0033] The data backend uses a pipeline transport model for tracer gas to simulate the time, location, and detected gas data of tracer gas diffusion to each inspection well under various mixed connection paths, thus obtaining tracer gas simulation data.

[0034] This embodiment provides a method for investigating the topology of drainage pipe networks. By establishing a pipeline transport model for tracer gas, the method simulates the time, location, and detected gas data of tracer gas diffusion to each inspection well under various mixed and incorrect connection paths. This achieves accurate simulation of the tracer gas diffusion process under various mixed and incorrect connection paths, laying the foundation for the subsequent identification and location of mixed and incorrect connections in drainage pipe networks.

[0035] In one optional implementation, the data backend identifies misconnection points based on measured tracer gas data and simulated tracer gas data, obtaining the results of the drainage network misconnection investigation, including:

[0036] The measured data and simulated data of tracer gas are matched, and the misconnection points are located and identified based on the matching results to obtain the investigation results of misconnections in the drainage pipe network.

[0037] This embodiment provides a method for investigating the topology of drainage pipe networks. It uses an unmanned aerial vehicle (UAV)-borne spectral detection system to automatically cruise and scan tracer gases. Combined with the pipeline transmission model of the tracer gases, it can achieve intelligent, accurate, and efficient inversion of misconnection points and accurately locate misconnections in drainage pipe networks.

[0038] In one optional implementation, the data backend acquires target drainage network information and transmits the target drainage network information to the tracer gas injection device, including:

[0039] The data backend divides the target drainage network into grids based on the target drainage network information, and then transmits the divided drainage network information to the tracer gas injection device.

[0040] This embodiment provides a method for investigating the topology of a drainage pipe network. By dividing the target drainage pipe network into grid-like partitions, the method can investigate the misconnection of drainage pipe networks in each of the grid-like partitions, thus achieving a comprehensive and accurate investigation of the misconnection problem in the drainage pipe network.

[0041] Secondly, the present invention provides a drainage pipe network misconnection investigation system, which includes a data backend, a tracer gas injection device and an UAV-borne spectral detection device; the data backend is connected to the tracer gas injection device and the UAV-borne spectral detection device respectively.

[0042] The data backend is used to acquire target drainage network information and transmit the target drainage network information to the tracer gas injection device.

[0043] A tracer gas injection device is used to inject a mixed gas into the target inspection well of the upstream drainage network based on the target drainage network information; wherein the mixed gas is a tracer gas and a carrier gas with a preset mixing ratio;

[0044] The UAV-borne spectral detection device is used to perform cyclic scanning of the tracer gas spectral characteristics of a manhole at a given spatial coordinate along the direction of gas mixture transport, and obtain actual measured data of the tracer gas.

[0045] The data backend is also used to simulate the diffusion process of tracer gas under various mixed connection paths to obtain tracer gas simulation data;

[0046] The data backend is also used to identify misconnection points based on actual tracer gas measurement data and tracer gas simulation data, and to obtain the results of the investigation of misconnections in the drainage pipe network. Attached Figure Description

[0047] 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.

[0048] Figure 1 This is a structural block diagram of a drainage pipe network misconnection investigation system according to an embodiment of the present invention;

[0049] Figure 2 This is a structural block diagram of a tracer gas injection device according to an embodiment of the present invention;

[0050] Figure 3 This is a flowchart illustrating a method for investigating the topology of a drainage pipe network according to an embodiment of the present invention.

[0051] Figure 4 This is a flowchart illustrating another method for investigating the topology of a drainage network according to an embodiment of the present invention;

[0052] Figure 5This is a flowchart illustrating another method for investigating the topology of a drainage network according to an embodiment of the present invention;

[0053] Figure 6 This is a schematic diagram showing the spatial distribution and types of inspection wells and the spatial distribution of storm drain grates within a street block, according to an embodiment of the present invention.

[0054] Figure 7 This is a schematic diagram of the pipe connection relationship and route based on drainage pipe network survey data according to an embodiment of the present invention;

[0055] Figure 8 This is a schematic diagram showing the detection status, location, and time of the tracer gas in an embodiment of the present invention;

[0056] Figure 9 This is a schematic diagram of possible misconnection paths in an embodiment of the present invention (generally occurring between adjacent storm and sewage pipe inspection wells). Detailed Implementation

[0057] 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.

[0058] Geophysical detection methods based on video images, such as closed-circuit television and periscopes, can identify misconnections by filming the internal connections of pipelines one manhole at a time. However, when the water level inside the pipeline is deep or there is a lot of sediment, resulting in poor filming conditions or the pipeline robot being unable to crawl, it is necessary to carry out necessary pipeline sealing and water cut-off and sediment removal, which significantly increases the implementation cost and time.

[0059] Non-invasive water-based diagnostic technologies, such as water balance analysis and water tracer analysis, effectively avoid the need for rainwater dredging operations and significantly improve inspection efficiency. However, these methods must be implemented during the period of mixed water discharge in pipelines, and the problems diagnosed are limited to the aforementioned incidents, failing to achieve the goal of comprehensive inspection.

[0060] The essence of misconnection in the pipeline network is that rainwater and sewage pipes are incorrectly connected, resulting in cross-contamination of the pipeline space. As a low-density, compressible, and easily diffused fluid, gas can achieve efficient diffusion and propagation in the pipeline space through pressure.

[0061] Therefore, this invention proposes a method for investigating the topological relationships of drainage pipe networks. By injecting tracer gas into the pipes and automatically patrolling and detecting the gas characteristic information at the pipe inspection wells based on the UAV-borne spectral detection system, combined with gas fingerprint information comparison, the pipe network connection relationship is analyzed to determine the problem of misconnection.

[0062] This invention provides a method for investigating the topology of drainage pipe networks, applicable to a drainage pipe network misconnection investigation system, such as... Figure 1 As shown, the system includes a data backend 101, a tracer gas injection device 102, and an UAV-borne spectral detection device 103; the data backend 101 is connected to the tracer gas injection device 102 and the UAV-borne spectral detection device 103 respectively.

[0063] like Figure 2 As shown, the tracer gas injection device 102 includes: a high-pressure gas source storage module 1021, a flow control module 1022, and a gas injection module 1023. The high-pressure gas source storage module 1021 is used for the safe storage of high-pressure gas (tracer gas and carrier gas), and also has a temperature control function to ensure stable gas supply under extreme environments and avoid pressure fluctuations caused by phase change. The flow control module 1022 is used to maintain a constant inlet pressure, ensure that the flow rate is controlled only by the valve opening, and measure the gas flow rate in real time in conjunction with a mass flow meter. The gas injection module 1023 is used to control the high-pressure gas source storage module 1021 and the flow control module 1022 to inject a specific mixing ratio of tracer gas and carrier gas into the drainage pipe, and to control the injection volume and time according to the pipe space size and the mixed gas flow rate.

[0064] The gas injection module consists of an injection volume calculation unit, a pressurization device (such as a booster pump or compressor), a manhole sealing plug, and a gas connection pipeline. The injection volume calculation unit calculates the required volume of tracer gas and carrier gas to be injected for a given pipeline length and diameter, ensuring that injecting this dosage of tracer gas will not cause safety or environmental problems. The pressurization device increases the pressure of the mixed gas, thereby driving the tracer gas to be rapidly transported along the pipeline connection path. The manhole sealing plug tightly seals the manhole opening, preventing tracer gas leakage and affecting the tracing effect, while also helping to maintain the pressure provided by the pressurization device, promoting efficient transport of the mixed gas within the pipeline. The gas connection pipeline connects the pressurization device and the manhole sealing plug, efficiently delivering the tracer gas and carrier gas to the manhole at a given flow rate.

[0065] According to an embodiment of the present invention, a method for investigating the topology of a drainage pipe network 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.

[0066] This embodiment provides a method for investigating the topology of a drainage pipe network, which can be used in the aforementioned drainage pipe network misconnection investigation system. Figure 3 This is a flowchart of a drainage pipe network topology investigation method according to an embodiment of the present invention, such as... Figure 3 As shown, the process includes the following steps:

[0067] Step S301: The data backend obtains the target drainage network information and transmits the target drainage network information to the tracer gas injection device.

[0068] Specifically, the data backend divides the target drainage network into grid-like partitions based on the target drainage network information, and then transmits the partitioned drainage network information to the tracer gas injection device.

[0069] In step S302, the tracer gas injection device injects the mixed gas into the target inspection well of the upstream drainage network based on the target drainage network information; wherein, the mixed gas is tracer gas and carrier gas with a preset mixing ratio.

[0070] Specifically, tracer gases are screened based on a multi-dimensional evaluation system, with the following requirements: Safety: non-toxic, non-flammable, and with a density close to that of air to avoid asphyxiation risk; Chemical stability: highly inert, resistant to biodegradation, and with low adsorption to ensure controllable underground diffusion; Low environmental interference: atmospheric background concentration <1 ppb, absorption spectrum similar to common gases (such as water vapor, etc.). No overlap; High detectability: Strong absorption cross-section and low detection limit; Environmental compliance: Zero ozone depletion potential, global warming potential complies with emission regulations; Economically feasible: Low-cost storage and transportation, non-regulated chemicals, and no special operating qualifications required; Tracer gases that meet the above multi-dimensional evaluation system include: hexafluoroethane, octafluoropropane, fluorinated ethers, etc.

[0071] In step S303, the UAV-borne spectral detection device performs a cyclic scan of the tracer gas spectral characteristics of the inspection well at a given spatial coordinate along the mixed gas transmission direction to obtain the measured data of the tracer gas.

[0072] Specifically, starting from the rainwater pipe inspection well where tracer gas is injected, while the mixed gas is being injected, a spectral detection system equipped with a drone is used to perform high-frequency cyclic scanning of the tracer gas spectral characteristics of the sewage pipe inspection well at a given spatial coordinate along the direction of tracer gas transmission, thereby obtaining the tracer gas detection status, location, and time.

[0073] Step S304: The data backend simulates the diffusion process of tracer gas under various mixed connection paths to obtain tracer gas simulation data.

[0074] In step S305, the data backend identifies the mixed and incorrect connection points based on the actual and simulated tracer gas data, and obtains the results of the investigation of mixed and incorrect connections in the drainage network.

[0075] Specifically, the measured data and simulated data of tracer gas are matched, and the misconnection points are located and identified based on the matching results to obtain the investigation results of misconnections in the drainage pipe network.

[0076] Furthermore, the simulated detection of tracer gas (e.g., the amount of tracer gas detected), location and time are compared and matched with the actual detection of tracer gas, location and time. The solution with the best matching effect is the most realistic misconnection result, thereby realizing intelligent and efficient positioning of the misconnection location.

[0077] Furthermore, the diagnosis of misconnection issues in drainage pipe networks within other grid partitions is repeated until the diagnosis of misconnection issues in drainage pipe networks within all grid partitions is completed. Then, the locations of misconnections in the drainage pipe network topology are investigated and rectified to address the misconnection issues.

[0078] This embodiment provides a method for investigating the topology of a drainage pipe network. A tracer gas injection device injects a mixed gas into the target manhole of the upstream drainage pipe network. An unmanned aerial vehicle (UAV)-borne spectral detection device automatically cruises and detects the gas characteristic information at the manhole. The data backend then identifies misconnection points based on measured and simulated tracer gas data, obtaining the investigation results for misconnections in the drainage pipe network. This method allows for the determination of misconnection problems without entering the pipes, significantly reducing implementation costs and difficulty. Furthermore, by diagnosing all erroneous connections in the storm and sewage pipes, it achieves a comprehensive investigation of misconnections in the drainage pipe network.

[0079] This embodiment provides a method for investigating the topology of a drainage pipe network, which can be used in the aforementioned drainage pipe network misconnection investigation system. Figure 4 This is a flowchart of a drainage pipe network topology investigation method according to an embodiment of the present invention, such as... Figure 4 As shown, the process includes the following steps:

[0080] Step S401: The data backend obtains the target drainage network information and transmits it to the tracer gas injection device. For details, please refer to [link to relevant documentation]. Figure 3 Step S301 of the illustrated embodiment will not be described again here.

[0081] In step S402, the tracer gas injection device injects the mixed gas into the target inspection well of the upstream drainage network based on the target drainage network information; wherein, the mixed gas is tracer gas and carrier gas with a preset mixing ratio.

[0082] Specifically, step S402 includes:

[0083] In step S4021, the gas injection module determines the amount of mixed gas to be injected and the time of injection based on the target drainage network information.

[0084] Specifically, the injection volume calculation unit in the gas injection module can determine the gas injection volume and time based on the pipe length and diameter, the detection limit of the tracer gas spectrometer, and the gas flow rate.

[0085] In some optional implementations, step S4021 above includes:

[0086] Step a1: The gas injection module obtains the detection limit of the UAV-borne spectral detection device, determines the pipe volume based on the target drainage network information, and calculates the total amount of tracer gas injected based on the detection limit of the UAV-borne spectral detection device and the pipe volume.

[0087] The formula for calculating the total amount of tracer gas injected is as follows:

[0088]

[0089] in, Total amount of tracer gas injected ( ), The detection limit (ppb) for UAV-borne spectral detection devices. For the pipe volume ( ), This is a compensation factor to compensate for tracer gas losses caused by leakage, adsorption, etc. The degree to which the tracer gas actually achieves uniform mixing within the pipe is determined by the turbulence intensity.

[0090] Step a2: The gas injection module obtains the volume ratio of tracer gas to carrier gas, and calculates the total volume of carrier gas injected based on the total volume of tracer gas injected and the volume ratio of tracer gas to carrier gas.

[0091] The formula for calculating the total carrier gas injection volume is as follows:

[0092]

[0093] in, This represents the total amount of carrier gas injected. It is the volume ratio of the tracer gas to the carrier gas, i.e., the dilution factor by the carrier gas.

[0094] Step a3: The gas injection module determines the amount of mixed gas to be injected based on the total amount of tracer gas injected and the total amount of carrier gas injected.

[0095] Step a4: The gas injection module acquires the tracer gas injection flow rate and the carrier gas injection flow rate, and determines the mixed gas injection time based on the total tracer gas injection volume and the tracer gas injection flow rate, or the total carrier gas injection volume and the carrier gas injection flow rate.

[0096] The formula for calculating the gas mixture injection time is as follows:

[0097]

[0098] in, For the injection time of the mixed gas, For the tracer gas injection flow rate, Inject the carrier gas flow rate.

[0099] In step S4022, the gas injection module, based on the mixed gas injection volume and the mixed gas injection time, injects the tracer gas and carrier gas stored in the high-pressure gas source storage module into the target inspection well of the upstream drainage network by controlling the flow control module.

[0100] Specifically, for any area of ​​the drainage network, starting from the upstream stormwater pipe network inspection well, a tracer gas injection device is used to inject tracer gas and carrier gas with a specific mixing ratio into the inspection well according to the above-mentioned mixed gas injection time.

[0101] Step S403: The UAV-borne spectral detection device performs a cyclic scan of the tracer gas spectral characteristics of the inspection well at a given spatial coordinate along the gas mixture transport direction, obtaining measured tracer gas data. For details, please refer to [link to relevant documentation]. Figure 3 Step S303 of the illustrated embodiment will not be described again here.

[0102] Step S404: The data backend simulates the tracer gas diffusion process under various mixed connection paths to obtain tracer gas simulation data. For details, please refer to [link to relevant documentation]. Figure 3 Step S304 of the illustrated embodiment will not be described again here.

[0103] Step S405: The data backend identifies the locations of misconnections based on the measured and simulated tracer gas data, obtaining the results of the drainage network misconnection investigation. For details, please refer to... Figure 3Step S305 of the illustrated embodiment will not be described again here.

[0104] This embodiment provides a method for investigating the topology of a drainage pipe network. By controlling the flow control module, the tracer gas and carrier gas stored in the high-pressure gas source storage module are injected into the target inspection well of the upstream drainage pipe network. The method utilizes the transmission process of the tracer gas in the pipeline to locate the misconnection of the drainage pipe network. The problem of misconnection can be determined without entering the pipeline, which significantly reduces the implementation cost and difficulty.

[0105] This embodiment provides a method for investigating the topology of a drainage pipe network, which can be used in the aforementioned drainage pipe network misconnection investigation system. Figure 5 This is a flowchart of a drainage pipe network topology investigation method according to an embodiment of the present invention, such as... Figure 5 As shown, the process includes the following steps:

[0106] Step S501: The data backend obtains the target drainage network information and transmits it to the tracer gas injection device. For details, please refer to [link to relevant documentation]. Figure 4 Step S401 of the illustrated embodiment will not be described again here.

[0107] Step S502: Based on the target drainage network information, the tracer gas injection device injects the mixed gas into the target inspection well of the upstream drainage network; wherein the mixed gas is a tracer gas and a carrier gas with a preset mixing ratio. For details, please refer to... Figure 4 Step S402 of the illustrated embodiment will not be described again here.

[0108] Step S503: The UAV-borne spectral detection device performs a cyclic scan of the tracer gas spectral characteristics of the inspection well at a given spatial coordinate along the gas mixture transport direction, obtaining measured tracer gas data. For details, please refer to [link to relevant documentation]. Figure 4 Step S403 of the illustrated embodiment will not be described again here.

[0109] In step S504, the data backend simulates the diffusion process of tracer gas under various mixed connection paths to obtain tracer gas simulation data.

[0110] Specifically, step S504 includes:

[0111] Step S5041: The data backend determines the topology of the drainage pipeline based on the target drainage network information, and establishes a pipeline transport model for the tracer gas based on the drainage pipeline topology.

[0112] Specifically, based on the topology of the drainage pipeline system and the principle of material transport and diffusion, a mathematical model for the transport of tracer gas in the pipeline is established, namely, the pipeline transport model of tracer gas. This model should take into account factors such as the pipe diameter, slope, roughness, and diffusion coefficient of the tracer gas.

[0113] In step S5042, the data backend uses the pipeline transport model of tracer gas to simulate the time, location and detected gas data of tracer gas diffusion to each inspection well under various mixed connection paths, and obtains tracer gas simulation data.

[0114] Specifically, using the tracer gas detection status, location, and time data as fitting targets, the matching of the tracer gas detection status, location, and time simulated under different mixed connection paths with the above fitting targets is analyzed.

[0115] Step S505: The data backend identifies the locations of misconnections based on the measured and simulated tracer gas data, obtaining the results of the drainage network misconnection investigation. For details, please refer to... Figure 4 Step S405 of the illustrated embodiment will not be described again here.

[0116] This embodiment provides a method for investigating the topology of drainage pipe networks. By establishing a pipeline transport model for tracer gas, the method simulates the time, location, and detected gas data of tracer gas diffusion to each inspection well under various mixed and incorrect connection paths. This achieves accurate simulation of the tracer gas diffusion process under various mixed and incorrect connection paths, laying the foundation for the subsequent identification and location of mixed and incorrect connections in drainage pipe networks.

[0117] The following specific example illustrates the steps of a method for investigating the topology of a drainage pipe network.

[0118] Example 1:

[0119] Taking a sewage pipe network with misconnected rainwater pipes as an example, in the demonstration area, such as... Figure 6 As shown, based on previous observations, sewage overflow occurred in manhole W3 during the heavy rainfall, raising suspicion of a misconnection of rainwater in the upstream sewage pipe. The spatial distribution and types of manholes and the spatial distribution of rainwater grates within the block are shown in the figure. Figure 6 As shown; the specific steps of the method for investigating misconnections in underground pipe networks based on an unmanned aerial vehicle (UAV) spectral detection system include:

[0120] Step 1: Data collection and analysis of pipeline network survey:

[0121] Collect comprehensive data on the drainage network of this neighborhood, including manhole numbers, coordinates, ground and bottom elevations, storm and sewage pipe diameters (800mm), lengths (160m), and connection information, and outline the drainage network's route and service area. Figure 7 As shown, the sewage pipe network misconnection problem was investigated as an independent grid zone.

[0122] Step 2, tracer gas screening:

[0123] Based on safety, chemical stability, low environmental interference, high detectability, environmental compliance, and economic feasibility, octafluorocyclobutane (density 8.2 kg / m³) was selected as the tracer gas. ), with a lower density (density of 1.25 kg / Nitrogen, which has no significant absorption peak and does not affect the detection of octafluorocyclobutane, can be used as a carrier gas. The density of the mixed gas can be adjusted to be close to that of air to improve the diffusion uniformity. Tunable laser absorption spectroscopy is used to detect octafluorocyclobutane, with a detection limit of 5 ppb and an absorption peak of 9.2 μm.

[0124] Step 3: Inject tracer gas into the pipeline using a tracer gas injection device:

[0125] A gas injection module was used to continuously and stably inject mixed gas into the upstream inspection well Y1 of the rainwater pipe. The injection flow rate was 0.001 L / min, the compensation coefficient k was set to 1.5, the mixing efficiency was set to 0.6, the volume ratio of octafluorocyclobutane to carrier nitrogen was set to 1:100, and the density of the mixed gas was 1.32 kg / min. It is close to the density of air (1.29 kg / m³). This satisfies the requirement for efficient gas diffusion.

[0126] Based on the above parameters, the injection volume and injection time are calculated, and the tracer gas injection volume is:

[0127]

[0128] The carrier gas injection volume is:

[0129] 0.001 × 100 = 0.1 L

[0130] The injection time for the mixed gas is:

[0131] 0.001 / 0.001 = 1.0 min

[0132] Step 4: High-frequency detection of tracer gas and intelligent identification of misconnection points:

[0133] Starting from the rainwater pipe inspection well Y1 where tracer gas was injected, a tunable laser absorption spectroscopy detection system equipped with an unmanned aerial vehicle (UAV) was used simultaneously with the tracer gas injection to perform high-frequency cyclic scanning of the tracer gas spectral characteristics of the sewage pipe inspection well at a given spatial coordinate along the tracer gas transmission direction. The detection wavelength was 9.2 μm. The tracer gas detection status, location, and time are as follows: Figure 8 As shown.

[0134] COMSOL simulation software was used to simulate different mixed connection scenarios (such as...). Figure 9 The time it takes for the tracer gas to first diffuse into each sewage inspection well is shown in Table 1 below. The simulated values ​​of the time for the tracer gas to diffuse into the sewage inspection well under different mixed connection conditions are shown in Table 1 below.

[0135] Table 1:

[0136]

[0137] By comparing the simulated time with the measured time, it was found that when there was only a connection (misconnection) between inspection wells Y1-W1, the simulated value and the measured value of the time when the tracer gas first diffused into the sewage inspection well were closest.

[0138] Further, a periscope was used to take pictures of the downstream pipeline from inspection well Y1. The pictures confirmed that there was indeed a problem of rainwater pipes being misconnected to sewage pipes. The above results verified that by actively diffusing tracer gas and combining it with a UAV-borne spectral detection system for fixed-point cruise scanning, misconnection problems in drainage pipe networks can be identified efficiently and accurately.

[0139] The above-described embodiment 1 has the following advantages:

[0140] 1) Employs non-invasive and efficient diagnostic methods: Compared with geophysical detection technology, it can determine pipeline misconnection problems without entering the pipeline, significantly reducing implementation costs and difficulty.

[0141] 2) Comprehensive investigation: Compared with numerical diagnostic methods based on water quantity and quality monitoring, this method achieves a comprehensive investigation of misconnection problems by diagnosing all incorrect connections in rainwater and sewage pipes.

[0142] 3) Intelligent and precise positioning: The UAV-borne spectral detection system automatically cruises and scans the tracer gas, which has the advantages of wide coverage, no terrain limitation, and low cost. Combined with the mixed misconnection inversion positioning technology based on the drainage pipe network topology and air diffusion and transmission model, it can realize intelligent, precise and efficient inversion of mixed misconnection points.

[0143] This embodiment also provides a drainage pipe network misconnection investigation system. This device is used to implement the above embodiments and preferred embodiments, and will not be repeated for details already described. As used below, the term "module" can be a combination of software and / or hardware that performs 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.

[0144] This embodiment provides a drainage pipe network misconnection detection system, such as... Figure 1As shown, it includes: a data backend 101, a tracer gas injection device 102, and an UAV-borne spectral detection device 103; the data backend 101 is connected to the tracer gas injection device 102 and the UAV-borne spectral detection device 103 respectively.

[0145] The data backend 101 is used to obtain the target drainage network information and transmit the target drainage network information to the tracer gas injection device 102;

[0146] The tracer gas injection device 102 is used to inject a mixed gas into the target inspection well of the upstream drainage network based on the target drainage network information; wherein the mixed gas is a tracer gas and a carrier gas with a preset mixing ratio.

[0147] The UAV-borne spectral detection device 103 is used to perform cyclic scanning of the tracer gas spectral characteristics of the inspection well at a given spatial coordinate along the direction of gas mixture transmission, so as to obtain the actual measured data of the tracer gas.

[0148] Data backend 101 is also used to simulate the diffusion process of tracer gas under various mixed connection paths to obtain tracer gas simulation data;

[0149] Data backend 101 is also used to identify misconnection points based on tracer gas measured data and tracer gas simulated data, and to obtain the results of the investigation of misconnections in the drainage pipe network.

[0150] In some alternative implementations, such as Figure 2 As shown, the tracer gas injection device 102 includes: a high-pressure gas source storage module 1021, a flow control module 1022, and a gas injection module 1023.

[0151] Further functional descriptions of the above modules and units are the same as those in the corresponding embodiments described above, and will not be repeated here.

[0152] Those skilled in the art will recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of the embodiments of this application.

[0153] Those skilled in the art will understand that, for the sake of convenience and brevity, the specific working processes of the systems, devices, and units described above can be referred to the corresponding processes in the foregoing method embodiments, and will not be repeated here.

[0154] In the embodiments provided in this application, it should be understood that the disclosed systems, apparatuses, and methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; for instance, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the displayed or discussed mutual couplings, direct couplings, or communication connections may be through some interfaces; indirect couplings or communication connections between devices or units may be electrical, mechanical, or other forms.

[0155] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0156] In addition, the functional units in the various embodiments of this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit.

[0157] If a function is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solutions of this application, essentially, or the parts that contribute to the prior art, or parts of the technical solutions, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods in the various embodiments of this application. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0158] 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 such modifications and variations all fall within the scope defined by the appended claims.

Claims

1. A method for investigating the topology of a drainage pipe network, characterized in that, An application to a system for investigating misconnections in drainage pipe networks, the system includes a data backend, a tracer gas injection device, and an unmanned aerial vehicle (UAV)-borne spectral detection device; The data backend is connected to both the tracer gas injection device and the UAV-borne spectral detection device; the method includes: The data backend acquires the target drainage network information and transmits the target drainage network information to the tracer gas injection device; The tracer gas injection device injects a mixed gas into the target inspection well of the upstream drainage network based on the target drainage network information; wherein the mixed gas is a tracer gas and a carrier gas with a preset mixing ratio. The UAV-borne spectral detection device performs a cyclic scan of the tracer gas spectral characteristics of the inspection well at a given spatial coordinate along the mixed gas transmission direction to obtain the actual measured data of the tracer gas. The data backend simulates the diffusion process of tracer gas under various mixed connection paths to obtain tracer gas simulation data. The data backend identifies the mixed and incorrect connection points based on the actual measured data and simulated data of the tracer gas, and obtains the results of the investigation of mixed and incorrect connections in the drainage pipe network.

2. The method according to claim 1, characterized in that, The tracer gas injection device includes: a high-pressure gas source storage module, a flow control module, and a gas injection module; the tracer gas injection device, based on the target drainage network information, injects the mixed gas into the target inspection well of the upstream drainage network, including: The gas injection module determines the amount and time of mixed gas injection based on the target drainage network information. The gas injection module, based on the mixed gas injection volume and the mixed gas injection time, controls the flow control module to inject the tracer gas and the carrier gas stored in the high-pressure gas source storage module into the target inspection well of the upstream drainage network.

3. The method according to claim 2, characterized in that, The gas injection module determines the mixed gas injection volume and injection time based on the target drainage network information, including: The gas injection module obtains the detection limit of the UAV-borne spectral detection device, determines the pipe volume based on the target drainage network information, and calculates the total amount of tracer gas injected based on the detection limit of the UAV-borne spectral detection device and the pipe volume. The gas injection module obtains the volume ratio of tracer gas to carrier gas, and calculates the total volume of carrier gas injected based on the total volume of tracer gas injected and the volume ratio of tracer gas to carrier gas. The gas injection module determines the amount of mixed gas injected based on the total amount of tracer gas injected and the total amount of carrier gas injected; The gas injection module acquires the tracer gas injection flow rate and the carrier gas injection flow rate, and determines the mixed gas injection time based on the total tracer gas injection volume and the tracer gas injection flow rate, or the total carrier gas injection volume and the carrier gas injection flow rate.

4. The method according to claim 3, characterized in that, The gas injection module acquires the detection limit of the UAV-borne spectral detection device, determines the pipe volume based on the target drainage network information, and calculates the total amount of tracer gas injected based on the detection limit of the UAV-borne spectral detection device and the pipe volume; wherein, the formula for calculating the total amount of tracer gas injected is as follows: in, This represents the total amount of tracer gas injected. The detection limit of the UAV-borne spectral detection device. For the pipe volume, For compensation coefficient, This is to ensure that the tracer gas actually achieves a uniform mixing degree within the pipeline.

5. The method according to claim 3, characterized in that, The gas injection module obtains the volume ratio of tracer gas to carrier gas, and calculates the total carrier gas injection volume based on the total injected tracer gas volume and the volume ratio of tracer gas to carrier gas; wherein, the formula for calculating the total injected carrier gas volume is as follows: in, This represents the total amount of carrier gas injected. This represents the volume ratio of the tracer gas to the carrier gas.

6. The method according to claim 3, characterized in that, The gas injection module acquires the tracer gas injection flow rate and the carrier gas injection flow rate, and determines the mixed gas injection time based on the total tracer gas injection volume and the tracer gas injection flow rate, or the total carrier gas injection volume and the carrier gas injection flow rate; wherein, the calculation formula for the mixed gas injection time is as follows: in, For the injection time of the mixed gas, For the tracer gas injection flow rate, Inject the carrier gas flow rate.

7. The method according to claim 1, characterized in that, The data backend simulates the diffusion process of tracer gas under various mixed connection paths to obtain tracer gas simulation data, including: The data backend determines the topology of the drainage pipeline based on the target drainage network information, and establishes a pipeline transport model for the tracer gas based on the drainage pipeline topology. The data backend uses the pipeline transport model of the tracer gas to simulate the time, location, and detected gas data of the tracer gas diffusion to each inspection well under various mixed connection paths, and obtains the tracer gas simulation data.

8. The method according to claim 1, characterized in that, The data backend identifies misconnection points based on the measured data and simulated data of the tracer gas, and obtains the results of the drainage network misconnection investigation, including: The measured data and simulated data of the tracer gas are matched, and the misconnection points are located and identified based on the matching results to obtain the investigation results of the misconnection of the drainage pipe network.

9. The method according to claim 1, characterized in that, The data backend acquires target drainage network information and transmits the target drainage network information to the tracer gas injection device, including: The data backend divides the target drainage network into grids based on the target drainage network information, and transmits the divided drainage network information to the tracer gas injection device.

10. A drainage pipe network misconnection detection system, characterized in that, The system includes a data backend, a tracer gas injection device, and an UAV-borne spectral detection device; the data backend is connected to the tracer gas injection device and the UAV-borne spectral detection device respectively. The data backend is used to acquire target drainage network information and transmit the target drainage network information to the tracer gas injection device. The tracer gas injection device is used to inject a mixed gas into the target inspection well of the upstream drainage network based on the target drainage network information; wherein the mixed gas is a tracer gas and a carrier gas with a preset mixing ratio. The UAV-borne spectral detection device is used to perform cyclic scanning of the tracer gas spectral characteristics of the inspection well at a given spatial coordinate along the mixed gas transport direction, so as to obtain the actual measured data of the tracer gas. The data backend is also used to simulate the diffusion process of tracer gas under various mixed connection paths to obtain tracer gas simulation data. The data backend is also used to identify misconnection points based on the measured data and simulated data of the tracer gas, and to obtain the results of the investigation of misconnections in the drainage network.

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