Method and device for detecting the health of a sewer network

Abstract

The present disclosure relates to a method and device for detecting the health of a sewer network. The method comprises: judging water level measurement results and / or water quality index measurement results corresponding to a target pipe in the sewer network; in the case that the water level measurement results corresponding to the target pipe do not satisfy preset water level conditions, determining whether the sewer network has a health problem by using a first method; in the case that the water level measurement results corresponding to the target pipe satisfy the preset water level conditions and the water quality index measurement results satisfy preset water quality conditions, determining whether the sewer network has a health problem by using a second method; and in the case that the water level measurement results corresponding to the target pipe satisfy the preset water level conditions and the water quality index measurement results do not satisfy the preset water quality conditions, determining whether the sewer network has a health problem by using a third method. According to the embodiments of the present disclosure, the health problem of the sewer network can be quickly, efficiently, conveniently and accurately investigated, and the safety and reliability of the operation of the sewer network can be improved.

Description

Technical Field

[0001] This disclosure relates to the field of water environment information processing technology, and in particular to a method and apparatus for health detection of drainage pipe networks. Background Technology

[0002] Currently, the investigation of health problems in drainage pipe networks mainly relies on manual inspections, but this method suffers from low source tracing efficiency. During the investigation from upstream to downstream, the large number of upstream nodes to be tested and the complex pipe network topology often make the work difficult to advance or even interrupted. Although some scenarios have introduced water quality testing equipment for online monitoring, limitations in energy supply and communication methods prevent existing equipment from achieving comprehensive, real-time monitoring, resulting in limitations in assessing the health status of the pipe network. Therefore, there is an urgent need for a fast, efficient, convenient, and accurate method for monitoring the health of drainage pipe networks to improve investigation efficiency and ensure the stability and safety of drainage pipe network operation. Summary of the Invention

[0003] In view of this, this disclosure proposes a method and apparatus for health detection of drainage pipe networks.

[0004] According to one aspect of this disclosure, a method for health monitoring of a drainage pipe network is provided. The method includes:

[0005] Determine the water level measurement results and / or the water quality index measurement results corresponding to the target pipe in the drainage network;

[0006] If the water level measurement results corresponding to the target pipeline do not meet the preset water level conditions, the first method is used to determine whether there are health problems in the drainage network.

[0007] If the water level measurement results corresponding to the target pipeline meet the preset water level conditions and the water quality index measurement results corresponding to the target pipeline meet the preset water quality conditions, the second method is used to determine whether there are health problems in the drainage network.

[0008] If the water level measurement results for the target pipeline meet the preset water level conditions, but the water quality index measurement results for the target pipeline do not meet the preset water quality conditions, a third method is used to determine whether there are health problems in the drainage network.

[0009] The method of using a third approach to determine whether there are health problems in the drainage network includes: determining the inflow and infiltration ratio of each inflow source based on the time series data of water quality indicators of each inflow source corresponding to the drainage network, the time series data of water quality indicators of the monitoring points of the target pipeline, and a global optimization algorithm; and determining whether there are inflow and infiltration problems in the drainage network based on the inflow and infiltration ratio.

[0010] In one possible implementation, the first method is used to determine whether there are health problems in the drainage network, including:

[0011] When the drainage network is a rainwater network and the rainfall in the area where the rainwater network is located does not meet the preset rainfall threshold within a preset time period, determine the measurement result of the first water quality index at the end unit of the target pipeline.

[0012] If the first water quality index measurement result meets the first preset condition, the first water level measurement result of the target pipeline is determined; otherwise, the second water level measurement result is determined after the water level in the target pipeline is lowered.

[0013] If either the first or second water level measurement result meets the second preset condition, it is determined that there are no health problems in the drainage network; otherwise,

[0014] If the detection results of the detection equipment at the end unit meet the third preset condition, it is determined that there is a problem of rainwater and sewage mixing in the drainage network; or, if the measurement results of the second water quality index at the measurement point upstream of the end unit meet the fourth preset condition, it is determined that there is a problem of external water inflow and infiltration in the drainage network.

[0015] In one possible implementation, the first method is used to determine whether there are health problems in the drainage network, including:

[0016] When the drainage network is a sewage network and the rainfall in the area where the sewage network is located does not meet the preset rainfall threshold within a preset time period, the flow rate of the liquid transport device in the target pipeline is compared between the rainfall in the area where the sewage network is located not meeting the preset rainfall threshold within a preset time period and the rainfall in the area where the sewage network is located in the past preset time period meeting the preset rainfall threshold, and / or the measurement results of the first water quality index are compared.

[0017] If the flow rate comparison and / or the first water quality index measurement result comparison meet the fifth preset condition, determine the second water quality index measurement result comparison between the upstream and downstream measurement points of the target pipeline;

[0018] If the comparison of the second water quality index measurement results meets the sixth preset condition, determine whether the third water level measurement result of the target pipeline meets the seventh preset condition.

[0019] If the third water level measurement results meet the seventh preset condition, it is determined that there is an inflow and infiltration problem of external water into the drainage network;

[0020] If the flow rate comparison and / or the comparison of the first water quality index measurement results do not meet the fifth preset condition, the comparison of the second water quality index measurement results does not meet the sixth preset condition, or the third water level measurement results do not meet the seventh preset condition, it is determined that there are no health problems in the drainage network.

[0021] In one possible implementation, the first method is used to determine whether there are health problems in the drainage network, including:

[0022] If the drainage network is a sewage network and the rainfall in the area where the sewage network is located meets the preset rainfall threshold within a preset time period, determine the water level comparison between the liquid conveying device in the target pipeline when the rainfall in the area where the sewage network is located meets the preset rainfall threshold within a preset time period and when the rainfall in the area where the sewage network is located does not meet the preset rainfall threshold within a historical preset time period.

[0023] If the water level comparison does not meet the eighth preset condition, it is determined that there are no health problems in the drainage network; otherwise...

[0024] If the measurement results of the third water quality index at the measurement point upstream of the terminal unit meet the ninth preset condition, it is determined that there is a problem of mixed connection between rainwater and sewage in the drainage network.

[0025] In one possible implementation, the second method is used to determine whether there are health problems in the drainage network, including:

[0026] When the drainage network is a rainwater network and the rainfall in the area where the rainwater network is located does not meet the preset rainfall threshold within a preset time period, determine the time series data of the first water quality index and the time series data of the first water level at the monitoring point in the target pipeline.

[0027] If the time series data of the first water level meets the tenth preset condition and the time series data of the first water quality index meets the eleventh preset condition, it is determined that there is a problem of rainwater and sewage mixing in the drainage network; or if the time series data of the first water level meets the tenth preset condition but the time series data of the first water quality index does not meet the eleventh preset condition, it is determined that there is a problem of external water inflow and infiltration in the drainage network.

[0028] When the drainage network is a rainwater network and the rainfall in the area where the rainwater network is located meets the preset rainfall threshold within a preset time period, the second water quality index time series data of the monitoring point is determined. The second water quality index time series data includes the time series data of two water quality indicators that are related. The related water quality indicators are water quality indicators that have complementary properties in the monitoring of the drainage network and reflect water quality characteristics from multiple perspectives.

[0029] If the time series data of the second water quality indicator meet the thirteenth preset condition, it is determined that there is initial rainwater pollution in the drainage network.

[0030] In one possible implementation, the second method is used to determine whether there are health problems in the drainage network, including:

[0031] When the drainage network is a sewage network and the rainfall in the area where the sewage network is located meets the preset rainfall threshold within a preset time period, the time series data of the third water quality index of the monitoring point in the target pipeline is determined. The time series data of the third water quality index includes the time series data of at least two water quality indicators that are related. The water quality indicators that are related indicate that they have complementary properties in the monitoring of the drainage network and reflect the water quality characteristics from multiple perspectives.

[0032] If the time series data of the third water quality indicator meets the fourteenth preset condition, it is determined that there is a problem of mixed connection between rainwater and sewage in the drainage pipe network;

[0033] When the drainage network is a sewage network and the rainfall in the area where the sewage network is located does not meet the preset rainfall threshold within a preset time period, determine one or more of the following: the fourth water quality index time series data, the second water level time series data, and the first flow time series data of the monitoring point.

[0034] If any one or more of the fourth water quality index time series data, the second water level time series data, and the first flow rate time series data meet the fifteenth preset condition, it is determined that there is an inflow and infiltration problem of external water into the drainage network.

[0035] In one possible implementation, a third method is used to determine whether there are health problems in the drainage network, including:

[0036] Obtain the original water quality index time series data corresponding to the drainage pipe network. The original water quality index time series data includes the water quality index time series data of each inflow source corresponding to the drainage pipe network, as well as the water quality index time series data at the monitoring points of the drainage pipe network.

[0037] The original water quality index time series data are processed to obtain the target water quality index time series data;

[0038] Based on the time series data of the target water quality indicators and the global optimization algorithm, the inflow and infiltration ratio of each inflow source corresponding to the drainage pipe network is determined;

[0039] Based on the inflow-infiltration ratio, determine whether there is an inflow-infiltration problem in the drainage network.

[0040] In one possible implementation, the inflow and infiltration ratios of each inflow source corresponding to the drainage network are determined based on time-series data of the target water quality indicators and a global optimization algorithm, including:

[0041] Based on the time series data of the target water quality indicators, calculate the initial inflow and infiltration ratio of each inflow source corresponding to the drainage network;

[0042] In response to the fact that the initial inflow and infiltration ratio of each inflow source does not meet the sixteenth preset condition, the time series data of the target water quality index are optimized using a global optimization algorithm to obtain optimized water quality index time series data. The optimization process includes mutation operation, crossover operation and selection operation.

[0043] The optimized water quality index time series data is used as the new target water quality index time series data. The process is iteratively executed to calculate the initial inflow and infiltration ratio of each inflow source corresponding to the drainage network based on the target water quality index time series data, and then proceeds until the initial inflow and infiltration ratio of each inflow source meets the sixteenth preset condition. The calculated initial inflow and infiltration ratio is then used as the inflow and infiltration ratio of each inflow source.

[0044] In one possible implementation, the original water quality index time series data is processed to obtain the target water quality index time series data, including:

[0045] Identify and remove abnormal data in the original water quality index time series data, and add normal data to obtain denoised water quality index time series data;

[0046] By aligning the time series data of the denoised water quality indicators along the time dimension, the time series data of the target water quality indicators are obtained.

[0047] According to another aspect of this disclosure, a health monitoring device for a drainage network is provided. The device includes:

[0048] The judgment module is used to judge the water level measurement results and / or the water quality index measurement results corresponding to the target pipe in the drainage network;

[0049] The first determining module is used to determine whether there is a health problem in the drainage network when the water level measurement result corresponding to the target pipeline does not meet the preset water level conditions, using the first method.

[0050] The second determination module is used to determine whether there is a health problem in the drainage network by using the second method, provided that the water level measurement result corresponding to the target pipeline meets the preset water level conditions and the water quality index measurement result corresponding to the target pipeline meets the preset water quality conditions.

[0051] The third determination module is used to determine whether there are health problems in the drainage network when the water level measurement results corresponding to the target pipeline meet the preset water level conditions but the water quality index measurement results corresponding to the target pipeline do not meet the preset water quality conditions.

[0052] The method of using a third approach to determine whether there are health problems in the drainage network includes: determining the inflow and infiltration ratio of each inflow source based on the time series data of water quality indicators of each inflow source corresponding to the drainage network, the time series data of water quality indicators of the monitoring points of the target pipeline, and a global optimization algorithm; and determining whether there are inflow and infiltration problems in the drainage network based on the inflow and infiltration ratio.

[0053] According to the embodiments of this disclosure, a diagnostic solution for the health problems of the drainage pipe network can be flexibly decided and accurately selected based on specific application scenarios and different actual conditions, thereby achieving rapid, efficient, convenient and accurate investigation of health problems of the drainage pipe network and improving the safety and reliability of the drainage pipe network operation.

[0054] Other features and aspects of this disclosure will become clear from the following detailed description of exemplary embodiments with reference to the accompanying drawings. Attached Figure Description

[0055] The accompanying drawings, which are included in and form part of this specification, illustrate exemplary embodiments, features, and aspects of this disclosure together with the specification and serve to explain the principles of this disclosure.

[0056] Figure 1 A schematic diagram illustrating an application scenario according to an embodiment of this disclosure is shown.

[0057] Figure 2 A flowchart illustrating a method for health monitoring of a drainage network according to an embodiment of this disclosure is provided.

[0058] Figure 3 A schematic diagram illustrating cross-operation according to an embodiment of the present disclosure is shown.

[0059] Figure 4 A structural diagram of a health detection device for a drainage network according to an embodiment of the present disclosure is shown. Detailed Implementation

[0060] Various exemplary embodiments, features, and aspects of this disclosure will now be described in detail with reference to the accompanying drawings. The same reference numerals in the drawings denote elements that have the same or similar functions. Although various aspects of the embodiments are shown in the drawings, they are not necessarily drawn to scale unless specifically indicated otherwise.

[0061] As used herein, the terms “comprising,” “including,” “having,” or variations thereof are open-ended and include one or more of the stated features, integrals, elements, steps, components, or functions, but do not exclude the presence or addition of one or more other features, integrals, elements, steps, components, functions, or groups thereof.

[0062] When an element is referred to as “connected,” “coupled,” “responding,” or a variation thereof relative to another element, it may be directly connected, coupled, or responding to another element, or there may be an intermediate element present.

[0063] Although the terms first, second, third, etc., may be used herein to describe various elements / operations, these elements / operations should not be limited by these terms. These terms are only used to distinguish one element / operation from another. Therefore, without departing from the teachings of the inventive concept, a first element / operation in some embodiments may be referred to as a second element / operation in other embodiments.

[0064] The term “exemplary” as used herein means “serving as an example, embodiment, or illustration.” Any embodiment illustrated herein as “exemplary” is not necessarily to be construed as superior to or better than other embodiments.

[0065] Furthermore, to better illustrate this disclosure, numerous specific details are set forth in the following detailed description. Those skilled in the art will understand that this disclosure can be practiced without certain specific details. In some instances, methods, means, components, and circuits well known to those skilled in the art have not been described in detail in order to highlight the main points of this disclosure.

[0066] Currently, the investigation of health problems in drainage pipe networks mainly relies on manual inspections, but this method suffers from low source tracing efficiency. During the investigation from upstream to downstream, the large number of upstream nodes to be tested and the complex pipe network topology often make the work difficult to advance or even interrupted. Although some scenarios have introduced water quality testing equipment for online monitoring, limitations in energy supply and communication methods prevent existing equipment from achieving comprehensive, real-time monitoring, resulting in limitations in assessing the health status of the pipe network. Therefore, there is an urgent need for a fast, efficient, convenient, and accurate method for monitoring the health of drainage pipe networks to improve investigation efficiency and ensure the stability and safety of drainage pipe network operation.

[0067] In view of this, this disclosure provides a method, apparatus, and storage medium for health detection of drainage pipe networks. The method of this disclosure determines whether there is a health problem in the drainage pipe network by judging the water level measurement result and / or the water quality index measurement result corresponding to the target pipe in the drainage pipe network; when the water level measurement result corresponding to the target pipe does not meet the preset water level conditions, a first method is used to determine whether there is a health problem in the drainage pipe network, enabling rapid troubleshooting of drainage pipe network problems when the target pipe is not full of water; and by determining whether there is a health problem in the drainage pipe network by using a second method when the water level measurement result corresponding to the target pipe meets the preset water level conditions and the water quality index measurement result corresponding to the target pipe meets the preset water quality conditions, enabling health detection when the target pipe is full of water and the water in the target pipe is not flowing. This method allows for rapid troubleshooting of drainage pipe networks. When the water level measurement results in the target pipe meet preset water level conditions but the water quality index measurement results do not, a third method is used to determine if a health problem exists in the drainage pipe network. This includes: determining the inflow / infiltration ratio of each inflow source based on time-series data of water quality indices from the drainage pipe network's inflow sources, time-series data of water quality indices from monitoring points in the target pipe, and a global optimization algorithm; and determining whether an inflow / infiltration problem exists in the drainage pipe network based on the inflow / infiltration ratio. This method can accurately identify and quantify inflow / infiltration problems in the drainage pipe network even when the target pipe is full and water is flowing within it. The method in this embodiment can flexibly decide and accurately select a diagnostic scheme for drainage pipe network health problems based on specific application scenarios and different actual conditions, thereby achieving rapid, efficient, convenient, and accurate troubleshooting of drainage pipe network health problems and improving the safety and reliability of drainage pipe network operation.

[0068] Figure 1 A schematic diagram illustrating an application scenario according to an embodiment of this disclosure is shown. For example... Figure 1 As shown, the health detection system for the drainage pipe network in this embodiment of the present disclosure can be deployed on terminal devices or servers. By selecting different methods (the first method, the second method, and the third method shown in the figure) based on the full water status of the target pipe and the water flow in the target pipe during the operation of the drainage pipe network, it can determine whether there are health problems in the drainage pipe network. Thus, it can issue an alarm when there are health problems, thereby improving the safety and reliability of the operation of the drainage pipe network.

[0069] The terminal devices involved in the embodiments of this disclosure can be any one or more of the following: mobile phones, foldable electronic devices, tablet computers, desktop computers, laptop computers, handheld computers, laptops, ultra-mobile personal computers (UMPCs), netbooks, cellular phones, personal digital assistants (PDAs), and in-vehicle devices. The embodiments of this disclosure do not impose any special limitations on the specific type of terminal device, which can have wired or wireless communication capabilities.

[0070] The server disclosed in this embodiment can be located locally or in the cloud, and can be a physical device or a virtual device, such as a virtual machine or container. It has wireless communication capabilities, which can be configured in the server's chip (system) or other components. The wireless communication capabilities can be implemented through mobile communication technologies such as 2G / 3G / 4G / 5G, as well as Wi-Fi, Bluetooth, frequency modulation (FM), data radio, and satellite communication. It can also communicate via a wired connection to enable interaction with other devices.

[0071] Figure 2 A flowchart illustrating a method for detecting the health of a drainage network according to an embodiment of this disclosure is provided. This method can be used in the aforementioned drainage network health detection system, such as... Figure 2 As shown, the method may include:

[0072] Step S201: Determine the water level measurement result and / or the water quality index measurement result corresponding to the target pipe in the drainage network.

[0073] A drainage network is a pipeline system used to collect, transport, and discharge rainwater, sewage, or combined sewer systems. A drainage network may include pipes (including main pipes and branch pipes), measuring points (such as manholes), liquid transport devices (such as pumping stations), gates, discharge outlets, and other facilities. Based on their function, drainage networks can be categorized into sewage networks, rainwater networks, and combined sewer networks. Sewage networks are used to collect and transport sewage (e.g., domestic sewage and industrial wastewater); rainwater networks are used to collect and discharge natural rainfall (e.g., rainwater); and combined sewer networks are used to collect and transport a mixture of sewage and rainwater.

[0074] In this embodiment of the disclosure, the target pipeline can be any trunk pipe in the drainage network. A trunk pipe can refer to a pipe that starts from a water source or main water collection point and is laid along the main water transmission route, responsible for collecting sewage or rainwater from various branch pipes and transporting it to treatment facilities or discharge outlets. Health problems can be checked on each trunk pipe in the drainage network individually (e.g., from upstream to downstream / downstream to upstream), or a section of the drainage network (e.g., including some or all of the trunk pipes) can be checked for health problems. This embodiment of the disclosure does not limit this approach.

[0075] Health problems in drainage networks can include one or more of the following: combined sewer overflows, infiltration of external water, and initial rainwater contamination. Combined sewer overflows refer to incorrect connections or damage between pipes in the rainwater and sewage systems of a separate drainage network (e.g., a sewage network or a rainwater network), causing rainwater and sewage to mix. Infiltration of external water refers to the seepage of clean water sources (such as groundwater, river or lake water, construction rainfall, etc.) into the sewage network through pipe damage or leaky connections, or the seepage of sewage sources (such as domestic sewage or industrial wastewater) into the rainwater network through pipe damage or leaky connections.

[0076] Initial rain pollution refers to the phenomenon where, at the beginning of rainfall, rainwater washes pollutants (such as dust, oil, and heavy metals) from surfaces like the ground and buildings into the drainage network, resulting in higher concentrations of pollutants in the water and a decline in water quality. This phenomenon is particularly pronounced in urbanized areas because the surface is often made of impermeable materials, making it easier for rainwater to carry away pollutants.

[0077] Detecting and addressing issues such as combined sewer overflows, infiltration of external water, and initial rainwater pollution in drainage networks is crucial for ensuring urban water quality and the efficient operation of drainage systems. For example, combined sewer overflows and infiltration of external water can lead to sewage entering the stormwater network, resulting in untreated sewage being discharged directly into rivers, lakes, or oceans, polluting water bodies; or rainwater entering the sewage network, increasing the load on sewage treatment plants and affecting their normal operation. Furthermore, initial rainwater pollution carries large amounts of pollutants, which, if left uncontrolled, can severely impact water bodies. Therefore, timely detection and remediation of these problems help improve the reliability of drainage network systems and protect water resources and the ecological environment.

[0078] In this embodiment of the disclosure, the water level measurement results of the target pipe during the operation of the drainage network are first determined to determine whether there is a full water situation, and the water quality index measurement results of the target pipe are determined to determine the water flow in the target pipe, and different methods are selected to determine whether there are health problems in the drainage network.

[0079] One method to determine the water level status of a target pipe in a drainage network is to check the water level of each main pipe in the network separately. If any one or more main pipes are full, the target pipe is considered full. Alternatively, the fullness of the target pipe can be determined by checking if the water level measurement results for the target pipe (i.e., any one or more main pipes in the drainage network) meet preset water level conditions. If the water level measurement results for the target pipe meet the preset conditions, it is considered full; otherwise, it is considered not full. For example, the water level in the main pipe can be measured using a water level sensor (such as a level gauge) or directly using a probe with a scale. The preset water level conditions can be that the water level reaches a preset threshold (such as the water level reaching the pipe height).

[0080] The method for determining whether water is flowing in a target pipeline can be based on whether the measured results of the corresponding water quality indicators meet the preset water quality conditions. If the measured results meet the preset conditions, the water in the target pipeline is considered to be in a non-flowing state; if the measured results do not meet the preset conditions, the water in the target pipeline is considered to be flowing. In this case, two or more consecutive measurements of water quality indicators (such as water temperature, conductivity, and turbidity) can be taken at the end unit of the target pipeline. Water temperature is the simplest and most direct indicator, as different water sources result in different temperatures; conductivity reflects the total dissolved solids content in the water and is very sensitive to the water source; a significant change in the two measured values ​​indicates the inflow of water of different qualities; turbidity can be used because flow can stir up bottom sediment or bring in water containing silt, causing a sharp increase in turbidity. When the changes in the two or more water quality indicators are less than a threshold, the preset water quality conditions are considered met, and the water in the target pipeline is considered to be in a non-flowing state.

[0081] In other implementations, the flow of water can be determined using methods such as leaves or flow direction meters. For example, leaves or other floating objects can be placed at an upstream measurement point (such as an upstream manhole) of the target pipe, and their appearance at a downstream measurement point (such as a downstream manhole) can be observed. If the leaves drift smoothly from upstream to downstream, it indicates continuous water flow within the target pipe, meaning the water in the target pipe is flowing; otherwise, the water in the target pipe is not flowing. Alternatively, a flow direction meter can be deployed within the target pipe to monitor whether the water is flowing. Of course, the accuracy of the determination can be improved by combining the above water quality indicator measurement results with observations of leaves and flow direction meters.

[0082] Step S202: If the water level measurement result corresponding to the target pipeline does not meet the preset water level conditions, the first method is used to determine whether there is a health problem in the drainage network.

[0083] If the water level measurement result corresponding to the target pipeline does not meet the preset water level conditions, it can be indicated that there is no full water in the target pipeline.

[0084] Step S202 may include: determining whether there is a problem of rainwater and sewage mixing or external water inflow and infiltration in the drainage pipe network based on the detection results of the detection equipment, the water quality index measurement results, or the water level measurement results.

[0085] When the target pipe is not full of water, the situation in the target pipe can be directly observed. In this embodiment of the disclosure, the first method is adopted. By measuring the water quality index and / or water level, the problem of rainwater and sewage mixing or external water inflow and infiltration in the drainage network can be quickly investigated when the target pipe is not full of water, which is more efficient.

[0086] In the first method, the presence of health problems in the drainage network can be determined based on different types of drainage networks and / or environmental conditions. For example, different indicators are used to detect health problems depending on whether the drainage network is a stormwater network, a sewage network (or a combined sewer system), and whether there is a rainfall event, thereby making the detection results more accurate. The first method of this disclosure is described below according to different types of drainage networks and / or environmental conditions.

[0087] In one possible implementation, the process of determining whether there are health problems in the drainage network using the first method may include:

[0088] If the drainage network is a rainwater network and the rainfall in the area where the rainwater network is located does not meet the preset rainfall threshold within a preset time period, determine the first water quality index measurement result at the end unit of the target pipeline; if the first water quality index measurement result meets the first preset condition, determine the first water level measurement result of the target pipeline; otherwise, proceed to: determine the second water level measurement result after lowering the water level in the target pipeline; if the first water level measurement result or the second water level measurement result meets the second preset condition, determine that the drainage network has no health problems; otherwise, proceed to: determine that the drainage network has a rainwater and sewage mixing problem if the measurement result of the detection device at the end unit meets the third preset condition, or proceed to: determine that the drainage network has an external water inflow and infiltration problem if the second water quality index measurement result at the measurement point upstream of the end unit meets the fourth preset condition.

[0089] Therefore, by using the first water quality indicator for preliminary screening, accurate test data can be obtained without external rainfall interference. When the first water quality indicator does not meet the preset conditions, the deviation caused by abnormal water level can be eliminated by lowering the water level in the pipe and re-measuring. Based on the preset conditions of water level and water quality measurement results, it can be determined whether there is a problem of rainwater and sewage mixing or external water inflow and infiltration in the rainwater pipe network, so as to accurately distinguish the abnormal types of the drainage pipe network. Thus, it is possible to accurately judge the health status of the rainwater pipe network under non-rainfall conditions.

[0090] Specifically, a non-rainfall event is defined as an area where the rainwater drainage network is located experiences rainfall that does not meet a preset rainfall threshold within a preset duration. The preset duration can be set based on actual application conditions, such as 3 days, 5 days, etc. The preset rainfall threshold can also be set based on actual application conditions, such as any value between 0-1mm, etc.

[0091] The terminal units of the target pipeline can include either a direct discharge outlet at the end of a main pipe (i.e., an outlet directly discharging into a natural water body) or an interface connecting to a pumping station or a manhole (e.g., the manhole preceding the direct discharge outlet). Terminal units can be identified and marked in advance based on a topology map of the drainage network. This topology map can be obtained from a third party, such as a municipal management department. Water quality indicators can be measured at the terminal units of the target pipeline using water quality sensors or test strips. These indicators can include one or more of the following: Chemical Oxygen Demand (COD), ammonia nitrogen, conductivity, and water temperature (i.e., temperature-related water quality indicators). Water level measurement results can be determined using the methods described above. The measurement results of water quality indicators and water level can be either time-series data or individual measurement values; there are no restrictions on this.

[0092] The first water quality indicator measurement result may include the measurement results of COD and / or ammonia nitrogen at the end unit of the target pipeline. The first preset condition may be that the COD in the water quality indicator measurement result is not less than the threshold (e.g., COD≥100mg / L) and / or ammonia nitrogen is not less than the threshold (e.g., ammonia nitrogen≥5mg / L).

[0093] If the first water quality indicator measurement result meets the first preset condition, the water level in the target pipeline can be measured (i.e., the first water level measurement result is obtained), and it can be verified whether the first water level measurement result meets the second preset condition. If the first water quality indicator measurement result does not meet the first preset condition, the water level in the target pipeline can be lowered by pumping water from the pumping station at the end of the main pipeline (for example, at night), and then the water level in the target pipeline can be measured again (i.e., the second water level measurement result is obtained), and it can be verified whether the second water level measurement result meets the second preset condition. The second preset condition may include the fullness (i.e., the ratio of the water level in the water level measurement result to the height of the target pipeline) being less than a threshold (e.g., 0.3).

[0094] If the first or second water level measurement result does not meet the second preset condition, it can be determined whether there is an inflow of external water by judging whether the second water quality index measurement result at the measurement point (such as the inspection well) upstream of the terminal unit meets the fourth preset condition. If the measurement result of any of the detection devices in the terminal unit, such as probes, video shooting devices, or image shooting devices, meets the third preset condition, it can be determined that there is a problem of rainwater and sewage mixing in the drainage network.

[0095] The topology diagram of the drainage network shows the pipes and their connections. When the pipes are not full of water, by using probes or video / image equipment to capture images of the pipe connections, it's possible to determine if there are any pipe intersections. This allows for quick and easy identification of any extra sewage pipes connected to the network. If a pipe intersection is identified, and the intersection is not explicitly shown in the drainage network's topology, then a sewage pipe is confirmed to be connected to the stormwater network.

[0096] The second water quality indicator measurement result can include conductivity measured by a conductivity measuring instrument. For example, if the characteristic conductivity value of local domestic sewage is approximately 1400 μs / cm, the fourth preset condition can include the measured conductivity matching the characteristic value of local domestic sewage (e.g., 1400 μs / cm), thereby determining that sewage exists in the target pipeline and indicating the presence of a sewage pipeline connection. Other methods can also be used to determine the presence of a sewage pipeline connection. For example, a probe can be used to detect whether there are pipe intersections in the target pipeline; if a pipe intersection is found, it is determined that a sewage pipeline connection exists.

[0097] The third preset condition may include the detection of a sewage pipe connection by a probe or the capture of an image by an image-capturing device.

[0098] The fourth preset condition may include COD being less than the threshold (e.g., COD < 100 mg / L) and / or ammonia nitrogen being less than the threshold (e.g., ammonia nitrogen < 5 mg / L) in the water quality index measurement results.

[0099] In the absence of sewage pipe connections, the drainage network can be considered to be free of health problems.

[0100] In one possible implementation, the process of determining whether there are health problems in the drainage network using the first method may include:

[0101] If the drainage network is a sewage network and the rainfall in the area where the sewage network is located does not meet the preset rainfall threshold within a preset time period, determine the flow transport comparison and / or the comparison of the first water quality index measurement results between the liquid transport device in the target pipeline when the rainfall in the area where the sewage network is located does not meet the preset rainfall threshold and when the rainfall in the area where the sewage network is located meets the preset rainfall threshold in the past preset time period; if the flow transport comparison and / or the comparison of the first water quality index measurement results meet the fifth preset condition, determine the relationship between the upstream and downstream measurement points of the target pipeline. The comparison results of the second water quality index measurement are compared; if the comparison results of the second water quality index measurement meet the sixth preset condition, it is determined whether the third water level measurement result of the target pipeline meets the seventh preset condition; if the third water level measurement result of the target pipeline meets the seventh preset condition, it is determined that there is an inflow and infiltration problem of external water in the drainage network; if the flow transport comparison and / or the comparison results of the first water quality index measurement do not meet the fifth preset condition, the comparison results of the second water quality index measurement do not meet the sixth preset condition, or the third water level measurement result of the target pipeline does not meet the seventh preset condition, it is determined that there is no health problem in the drainage network.

[0102] Therefore, by comparing the flow rate and / or water quality measurement results of the liquid conveying device between non-rainfall events and historical rainfall events, the health status of the drainage network can be preliminarily determined. When the above comparison data meets the fifth preset condition, by comparing the water quality measurement results between upstream measurement points and whether the comparison meets the sixth preset condition, and further considering whether the water level in the target pipeline meets the seventh preset condition, the type of health problem can be accurately distinguished. The above can be performed during non-rainfall events, thus enabling accurate judgment of the health status of the sewage network during non-rainfall periods, significantly improving the accuracy and efficiency of health problem detection.

[0103] Among them, if the rainfall in the area where the sewage pipe network is located does not meet the preset rainfall threshold within a preset time period, it is considered a non-rainfall event; if the rainfall in the area where the sewage pipe network is located meets the preset rainfall threshold within a preset historical time period, it is considered a historical rainfall event.

[0104] The liquid transport device can be any pump station in the target pipeline. The flow rate transport between non-rainfall events and historical rainfall events can be determined based on the average daily flow rate transported by the pump station during non-rainfall events and historical rainfall events. The flow rate transported by the pump station can be measured by means of flow meters, etc. Based on the daily average water quality index concentrations of the pumping station's sump during non-rainfall events and historical rainfall events, the comparison of the first water quality index measurement results between non-rainfall events and historical rainfall events can be determined. This water quality index concentration can refer to the concentration of any water quality index, such as COD, conductivity, ammonia nitrogen, five-day biochemical oxygen demand, total phosphorus, total nitrogen, suspended solids, total dissolved solids, petroleum hydrocarbons, pH value, anionic surfactants, cyanide, sulfide, fluoride, chloride, organophosphorus compounds, sulfate, mercury, chromium, cadmium, arsenic, lead, nickel, beryllium, silver, selenium, copper, zinc, manganese, iron, volatile phenols, benzene series compounds, aniline compounds, and nitrobenzene. This disclosure does not impose any limitations on this. The concentration of water quality indexes can be measured using water quality detection sensors or by using test strips.

[0105] The fifth preset condition may include that the average daily flow rate of the pumping station during historical rainfall events is greater than the average daily flow rate during non-rainfall events, and / or that the average daily water quality index concentration of the pumping station's sump during historical rainfall events is less than the average daily water quality index concentration during rainfall events.

[0106] The upstream and downstream measurement points can be any two adjacent inspection wells. The comparison of the measurement results of the second water quality index between the upstream and downstream measurement points can be determined based on the water quality index measured by the upstream inspection well (which can be any one or more of COD, ammonia nitrogen, and conductivity) and the water quality index measured by the downstream inspection well.

[0107] The sixth preset condition may include the increase in water quality indicators measured at upstream measurement points compared to those measured at downstream measurement points being greater than a threshold (e.g., 10%).

[0108] The seventh preset condition may include the water level in the target pipe being greater than a threshold (e.g., 3m) or equal to the height of the target pipe.

[0109] In one possible implementation, the process of determining whether there are health problems in the drainage network using the first method may include:

[0110] If the drainage network is a sewage network and the rainfall in the area where the sewage network is located meets the preset rainfall threshold within a preset time period, determine the water level comparison between the liquid transport device in the target pipeline when the rainfall in the area where the sewage network is located meets the preset rainfall threshold within a preset time period and when the rainfall in the area where the sewage network is located does not meet the preset rainfall threshold within a historical preset time period. If the water level comparison does not meet the eighth preset condition, determine that there is no health problem in the drainage network; otherwise, execute: if the measurement result of the third water quality index at the measurement point upstream of the terminal unit meets the ninth preset condition, determine that there is a problem of rainwater and sewage mixing in the drainage network.

[0111] Therefore, in the case of a sewage drainage network during rainfall events, a comprehensive analysis of water level and flow rate / water quality measurement results in the target pipeline's liquid transport devices during rainfall events and historical non-rainfall events can accurately determine whether there is a problem of combined sewer overflows in the drainage network. This can be performed during rainfall events, thus enabling accurate judgment of whether there is a problem of combined sewer overflows in the sewage network during rainfall, significantly improving the accuracy and efficiency of health problem detection.

[0112] Among them, a rainfall event is defined as the amount of rainfall in the area where the sewage pipe network is located within a preset time period that meets the preset rainfall threshold, and a historical non-rainfall event is defined as the amount of rainfall in the area where the sewage pipe network is located within a preset time period that does not meet the preset rainfall threshold.

[0113] Even when the pumping station is not operating, the water level comparison between rainfall events and historical non-rainfall events can be determined based on the water level at the pumping station during rainfall events and historical non-rainfall events.

[0114] The eighth preset condition may include the ratio of the water level at the pumping station during a rainfall event to the water level during a historical non-rainfall event being greater than a threshold (e.g., 1.4).

[0115] If the water level comparison does not meet the eighth preset condition, it can be determined whether there is a rainwater pipe connection by judging whether the measurement result of the third water quality index at the measurement point (such as the inspection well) upstream of the terminal unit meets the ninth preset condition. When the measurement result of the third water quality index meets the ninth preset condition, it can be considered that there is a rainwater pipe connection. At this time, it can be determined that there is a problem of rainwater and sewage mixing in the drainage network.

[0116] The third water quality index measurement results at the measurement point upstream of the end unit of the target pipeline may include the measurement results of COD and / or ammonia nitrogen at the inspection well upstream of the end of the target pipeline. The ninth preset condition may be that COD is less than the threshold (e.g., COD < 100 mg / L) and / or ammonia nitrogen is less than the threshold (e.g., ammonia nitrogen < 5 mg / L) in the water quality index measurement results.

[0117] If the measurement result of the third water quality index at the end unit of the target pipeline does not meet the ninth preset condition, it can be considered that there is no problem of rainwater and sewage mixing in the sewage network.

[0118] When the target pipe is full of water, since the situation in the target pipe cannot be directly observed, in this embodiment of the disclosure, a second method or a third method is selected to detect health problems based on whether the water in the target pipe is flowing.

[0119] Step S203: If the water level measurement result corresponding to the target pipeline meets the preset water level conditions and the water quality index measurement result corresponding to the target pipeline meets the preset water quality conditions, the second method is used to determine whether there are health problems in the drainage network.

[0120] Among them, if the water level measurement result of the target pipeline meets the preset water level conditions, it can be said that the target pipeline is full of water, and if the water quality index measurement result of the target pipeline meets the preset water quality conditions, it can be said that the water in the target pipeline is in a non-flowing state.

[0121] Step S203 may include: performing multi-dimensional data analysis based on the time series data of at least one water quality indicator corresponding to the monitoring point in the target pipeline, as well as the corresponding water level time series data and / or flow time series data, to determine whether the drainage network has one of the following problems: initial rainwater pollution, rainwater and sewage mixing, or external water inflow and infiltration.

[0122] When the target pipeline is full of water and the water in the pipeline is not flowing, a second method can be used to determine whether there are health problems in the drainage network by measuring time series data such as water quality indicators, water level, and flow rate. This method is more efficient. Compared with existing methods, which fail to effectively couple different types of water quality and quantity data, resulting in one-sided monitoring results and insufficient accuracy, and where the correlation between various data is not fully explored, making it difficult to accurately determine the root cause of health problems, this embodiment of the disclosure utilizes the second method to simultaneously collect and process multiple types of time series data for multi-dimensional data analysis. This achieves effective coupling of different types of time series data to gain a more comprehensive understanding of the pipeline system's operating status.

[0123] In the second method, the presence of health problems in the drainage network can also be determined based on different types of drainage networks and / or environmental conditions. For example, health problems can be detected using different types of time series data, depending on whether the drainage network is a stormwater network, a sewage network (or a combined sewer system), and whether there is a rainfall event, thereby making the detection results more accurate. The second method of this disclosure is described below according to different types of drainage networks and / or environmental conditions.

[0124] In using the second method to determine whether there are health problems in the drainage network, it is possible to:

[0125] When the drainage network is a rainwater network and the rainfall in the area where the rainwater network is located does not meet the preset rainfall threshold within a preset time period, determine the time series data of the first water quality index and the time series data of the first water level at the monitoring point in the target pipeline.

[0126] If the time series data of the first water level meets the tenth preset condition and the time series data of the first water quality index meets the eleventh preset condition, it is determined that there is a problem of mixed rainwater and sewage connection in the drainage pipe network; or

[0127] If the time series data of the first water level meets the tenth preset condition, and the time series data of the first water quality index does not meet the eleventh preset condition, it is determined that there is an inflow and infiltration problem of external water in the drainage network.

[0128] If the drainage network is a rainwater network and the rainfall in the area where the rainwater network is located meets the preset rainfall threshold within a preset time period, determine the time series data of the second water quality indicator for the monitoring point.

[0129] If the time series data of the second water quality indicator meet the thirteenth preset condition, it is determined that there is initial rainwater pollution in the drainage network.

[0130] Therefore, this solution enables multi-dimensional data analysis based on various time series data for target pipes in stormwater pipe networks that are full of water and have no water flow, under both non-rainfall and rainfall events. It achieves accurate identification and classification of health problems in stormwater pipe networks under different environmental conditions, providing scientific and reliable technical support for real-time monitoring and early warning of anomalies in the health status of drainage pipe networks.

[0131] Among them, if the rainfall in the area where the rainwater pipe network is located does not meet the preset rainfall threshold within a preset time period, it is considered a non-rainfall event; if the rainfall in the area where the rainwater pipe network is located meets the preset rainfall threshold within a preset time period, it is considered a rainfall event.

[0132] For time series data of the primary water quality index, water quality monitoring equipment can be used to collect monitoring values ​​of the primary water quality index, thereby forming time series data of the primary water quality index. For example, data can be collected using water quality monitoring equipment that includes a spectral sensor. Monitoring equipment with a spectral sensor can achieve online, in-situ, high-frequency, and real-time acquisition of water quality index monitoring values. For example, the acquisition frequency can be increased from once a day to once every 3-60 minutes, preferably 5-30 minutes, particularly preferably 8-20 minutes, and most preferably 10-15 minutes, which is far higher than the traditional detection method of sampling water quality and then conducting laboratory tests. Therefore, water quality data can be obtained at a higher frequency to effectively capture the water quality characteristics of drainage pipe networks.

[0133] The first water quality indicator time series data may include multiple COD concentration data monitored in chronological order within a preset time period at the monitoring point. The first water level time series data may include multiple water level data monitored in chronological order within a preset time period at the monitoring point. The monitoring point may be a location on the target pipeline where water quality monitoring sensors, level sensors, and flow sensors are deployed based on the drainage network topology. The tenth preset condition may include the median water level in the first water level time series data exceeding a preset water level threshold; the eleventh preset condition may include the median COD concentration in the first water quality indicator time series data exceeding a preset COD concentration threshold.

[0134] Since the stormwater drainage network should be dry during non-rainfall periods, if the first water level time series data meets the tenth preset condition, it can be determined that there is an abnormality in the drainage network. Furthermore, if the first water quality index time series data meets the eleventh preset condition, it can be determined that there is a problem of rainwater and sewage mixing in the drainage network, indicating that there is a problem of rainwater and sewage mixing upstream of the monitoring point in the stormwater network. However, if the first water level time series data meets the tenth preset condition but the first water quality index time series data does not meet the eleventh preset condition, it can be considered that there is no problem of rainwater and sewage mixing in the stormwater network, but rather that there is a problem of external water infiltration in the stormwater network.

[0135] The second water quality indicator time series data can include time series data of two water quality indicators that are related. The related water quality indicators are those that complement each other in the monitoring of drainage pipe networks and reflect water quality characteristics from multiple perspectives.

[0136] In the field of water quality monitoring technology, no single water quality indicator can independently and comprehensively reflect the quality of a water body. Generally, different water quality indicators can reflect the characteristics and pollution status of a water body from different angles and levels. Only by combining, verifying, and complementing different water quality indicators can a complete and accurate reflection of water quality be achieved. This characteristic between different water quality indicators is called their complementary nature.

[0137] For example, the second water quality indicator time series data may include COD concentration and conductivity concentration monitored in chronological order at the monitoring points within a preset time period.

[0138] The thirteenth preset condition may include an increase in COD concentration and a decrease in conductivity concentration in the time series data of the second water quality indicator. The determination of an increase in COD concentration may include: in the time series data corresponding to COD concentration, if the ratio of the difference between the COD concentration value at each later time point and the COD concentration value at the previous time point to the COD concentration value at the previous time point (this ratio can also be considered as the rate of change of COD concentration) is greater than a preset positive threshold, then the COD concentration is considered to have increased; or, comparing each concentration value in the time series data corresponding to COD concentration with the median of the time series data corresponding to COD concentration, if there is a time point before the time point corresponding to the median where the difference between the COD concentration value and the median is less than a preset negative threshold, and there is a time point after the time point corresponding to the median where the difference between the COD concentration value and the median is greater than a preset positive threshold, then the COD concentration is considered to have increased.

[0139] The determination of a decrease in conductivity concentration may include: in the time series data corresponding to the conductivity concentration, if the ratio of the difference between the conductivity concentration value at a later time point and the conductivity concentration value at the previous time point to the conductivity concentration value at the previous time point is less than a preset negative threshold, then the conductivity concentration is considered to have decreased; or, comparing each conductivity concentration value in the time series data corresponding to the conductivity concentration with the median of the time series data corresponding to the conductivity concentration, if there is a time point before the time point corresponding to the median where the difference between the conductivity concentration value and the median is greater than a preset positive threshold, and there is a time point after the time point corresponding to the median where the difference between the conductivity concentration value and the median is less than a preset negative threshold, then the conductivity concentration is considered to have decreased.

[0140] It should be noted that the embodiments of this disclosure do not limit the methods for determining the increase in COD concentration and the decrease in conductivity concentration as described above. Other methods may also be used to determine these concentrations in addition to the examples given in the embodiments of this disclosure.

[0141] If the time series data of the second water quality indicator meets the thirteenth preset condition, it can be determined that there is an initial rainwater pollution problem in the drainage pipe network, which means that there is an initial rainwater pollution problem upstream of the monitoring point in the rainwater pipe network.

[0142] If the time series data of the second water quality indicator does not meet the thirteenth preset condition, it can be considered that there is no initial rainwater pollution problem in the rainwater pipe network.

[0143] In using the second method to determine whether there are health problems in the drainage network, it is possible to:

[0144] Under the condition that the drainage network is a sewage network and the rainfall in the area where the sewage network is located meets the preset rainfall threshold within a preset time period, the time series data of the third water quality index of the monitoring point in the target pipeline are determined.

[0145] If the time series data of the third water quality indicator meets the fourteenth preset condition, it is determined that there is a problem of mixed connection between rainwater and sewage in the drainage pipe network;

[0146] When the drainage network is a sewage network and the rainfall in the area where the sewage network is located does not meet the preset rainfall threshold within a preset time period, determine one or more of the following: the fourth water quality index time series data, the second water level time series data, and the first flow time series data of the monitoring point.

[0147] If any one or more of the fourth water quality index time series data, the second water level time series data, and the first flow rate time series data meet the fifteenth preset condition, it is determined that there is an inflow and infiltration problem of external water into the drainage network.

[0148] Therefore, this solution enables multi-dimensional data analysis based on various time series data for target pipes in sewage pipe networks that are full of water and have no water flow, under both non-rainfall and rainfall conditions. It achieves accurate identification and classification of health problems in sewage pipe networks under different environmental conditions, thereby significantly improving the accuracy and response speed of early warning of health problems in sewage pipe networks. This provides scientific and reliable technical support for real-time monitoring and early warning of anomalies in the health status of drainage pipe networks.

[0149] Among them, a rainfall event is defined as the amount of rainfall in the area where the sewage pipe network is located within a preset time period meeting a preset rainfall threshold, and a non-rainfall event is defined as the amount of rainfall in the area where the sewage pipe network is located within a preset time period not meeting the preset rainfall threshold.

[0150] It should be noted that the second method described above for determining whether there is external water inflow or seepage in the sewage pipe network can also be applied to combined sewer systems.

[0151] The third water quality indicator time series data may include time series data of at least two water quality indicators that are related. The related water quality indicators are those that have complementary properties in drainage network monitoring and reflect water quality characteristics from multiple perspectives.

[0152] For example, the time series data for the third water quality indicator may include one or more of the following: COD concentration, ammonia nitrogen concentration, and water temperature (i.e., temperature-related water quality indicator) monitored at a monitoring point within a preset time period, as well as conductivity concentration. This monitoring point can be any location on the target pipeline where water quality monitoring sensors, level gauges, and thermometers are arranged. In other words, the third water quality indicator must include at least two water quality indicators, and conductivity must be present. Based on the presence of conductivity, one or more of the following indicators can be selected: COD, ammonia nitrogen, and water temperature.

[0153] The fourteenth preset condition may include any one or more of the following: a decrease in COD concentration, an initial increase followed by a decrease in COD concentration, a decrease in ammonia nitrogen concentration, a decrease in water temperature, and a decrease in conductivity concentration.

[0154] The determination of a decrease in COD concentration may include: in the time series data corresponding to COD concentration, if the ratio of the difference between the COD concentration value at a later time point and the COD concentration value at the previous time point to the COD concentration value at the previous time point (this ratio can also be considered as the rate of change of COD concentration value) is less than a preset negative threshold, then the COD concentration is considered to have decreased; or, comparing each concentration value in the time series data corresponding to COD concentration with the median of the time series data corresponding to COD concentration, if there is a time point before the time point corresponding to the median where the difference between the COD concentration value and the median is greater than a preset positive threshold, and there is a time point after the time point corresponding to the median where the difference between the COD concentration value and the median is less than a preset negative threshold, then the COD concentration is considered to have decreased.

[0155] The method for determining whether COD concentration first rises and then falls can include: in the time series data corresponding to COD concentration, if there is a continuous period of time where the difference in COD concentration between adjacent time points is greater than a preset positive threshold, forming a COD concentration rising phase, and then there is a continuous period of time where the difference in COD concentration between adjacent time points is less than a preset negative threshold, forming a COD concentration falling phase, then the COD concentration can be considered to have risen first and then fallen.

[0156] The method for determining the decrease in conductivity concentration can be the same as the method for determining the decrease in conductivity concentration in the thirteenth preset condition mentioned above. The methods for determining the decrease in water temperature and the decrease in ammonia nitrogen concentration can be achieved by referring to the method for determining the decrease in conductivity concentration.

[0157] It should be noted that the embodiments of this disclosure do not limit the methods for determining the decrease in COD concentration, the initial increase followed by a decrease in COD concentration, the decrease in ammonia nitrogen concentration, the decrease in water temperature, and the decrease in conductivity concentration. Other methods may be used besides the examples given in the embodiments of this disclosure.

[0158] If the time series data of the third water quality indicator meets the fourteenth preset condition, it can be determined that there is a problem of rainwater and sewage mixing in the drainage pipe network. This means that there is a problem of rainwater and sewage mixing upstream of the monitoring point in the sewage pipe network.

[0159] If the time series data of the third water quality indicator does not meet the fourteenth preset condition, it can be considered that there is no problem of rainwater and sewage mixing in the sewage pipe network.

[0160] The fourth water quality indicator time series data may include water temperature monitored at the monitoring point within a preset time period. The second water level time series data may include water level monitored at the monitoring point within a preset time period. The first flow rate time series data may include water flow rate monitored at the monitoring point within a preset time period.

[0161] The twelfth preset condition may include any one or more of the following: a significant decrease in water temperature, a significant increase in water level, and a significant increase in water flow. The method for determining a significant decrease in water temperature can be similar to the method described above, except that the negative threshold set for determining a significant decrease in water temperature is smaller than the negative threshold set for determining a significant decrease in water temperature, and the positive threshold set for determining a significant decrease in water temperature is greater than the positive threshold set for determining a significant decrease in water temperature.

[0162] Methods for determining a significant rise in water level may include: comparing the water level value at each time point in the time series data corresponding to the water level with a preset threshold (which can be set to a relatively large water level value); when the water level value exceeds the preset threshold for a consecutive preset time period, the water level is considered to have risen significantly; or, when the ratio of the difference between the water level value at a later time point and the water level value at the previous time point to the water level value at the previous time point (this ratio can also be considered as the rate of change of the water level value) in the time series data corresponding to the water level is greater than a preset positive threshold (which can be set to a relatively large value), the water level is considered to have risen significantly. The method for determining a significant rise in water flow can be implemented in the same way as the method for determining a significant rise in water level.

[0163] It should be noted that the embodiments of this disclosure do not limit the methods for determining a significant decrease in water temperature, a significant increase in water level, and a significant increase in water flow rate. Other methods may also be used to determine these conditions in addition to the examples given in the embodiments of this disclosure.

[0164] If any one or more of the fourth water quality index time series data, the second water level time series data, and the first flow rate time series data meet the fifteenth preset condition, it can be determined that there is an inflow and infiltration problem of external water in the drainage network, which means that there is an inflow and infiltration problem of external water upstream of the monitoring point in the sewage network.

[0165] If the time series data of the fourth water quality indicator, the second water level, and the first flow rate do not meet the fifteenth preset condition, it can be considered that there is no problem of external water inflow and infiltration in the sewage pipe network.

[0166] In this embodiment of the disclosure, when it is determined that there is a health problem upstream of a monitoring point in the drainage pipe network, the above method can be used to further investigate the upstream of the monitoring point in order to determine the specific location of the health problem.

[0167] Step S204: If the water level measurement result corresponding to the target pipeline meets the preset water level conditions but the water quality index measurement result corresponding to the target pipeline does not meet the preset water quality conditions, the third method is used to determine whether there is a health problem in the drainage network.

[0168] If the water level measurement result of the target pipeline meets the preset water level conditions, it indicates that the target pipeline is full of water. If the water quality index measurement result of the target pipeline does not meet the preset water quality conditions, it indicates that the water in the target pipeline is in a flowing state.

[0169] Step S204 may include: determining the inflow and infiltration ratio of each inflow source based on the time series data of water quality indicators of each inflow source corresponding to the drainage pipe network, the time series data of water quality indicators at the monitoring points of the target pipeline, and the global optimization algorithm; and determining whether there is an inflow and infiltration problem in the drainage pipe network based on the inflow and infiltration ratio.

[0170] The inflow and outflow water quality of drainage networks follows the principle of mass balance. Existing technologies mostly employ chemical sampling methods for water quality data collection, but this method itself has inherent errors. Because it is manual sampling, it is prone to asynchronous observation of water quality concentrations at multiple sampling points from the same inflow source, leading to errors in the monitored water quality values. Therefore, directly using a chemical mass balance model would reduce the accuracy of identifying inflow and infiltration units. Thus, we use water quality monitoring equipment to acquire water quality time-series data in situ, online, and at high frequency. However, even with in-situ and high-frequency data acquisition, it is impossible to completely avoid spatial differences and asynchronous monitoring among inflow sources, all of which contribute to errors in the collected water quality values. Therefore, combining the chemical mass balance principle with a global optimization algorithm can improve the accuracy of calculating the inflow and infiltration ratios of each inflow source, thereby improving the accuracy of determining whether inflow and infiltration problems exist in the drainage network.

[0171] According to the embodiments of this disclosure, it is possible to flexibly decide and accurately select diagnostic solutions for health problems of drainage pipe networks based on specific application scenarios and different actual conditions, thereby achieving rapid, efficient, convenient and accurate investigation of health problems of drainage pipe networks and improving the safety and reliability of drainage pipe network operation.

[0172] The following describes the process of determining the existence of health problems in a drainage network using a third method. First, water quality indicators corresponding to different inflow sources can be selected and determined to subsequently determine the inflow and infiltration ratio of each source. This method may include:

[0173] Obtain water quality characteristic data from different inflow sources; calculate the collinearity among different water quality indicators in the water quality characteristic data; and determine the water quality indicators corresponding to each inflow source based on the collinearity.

[0174] Inflow sources can include water bodies before the wastewater user connects to the pipeline and / or external clean water bodies. Wastewater users can be residential communities, commercial plazas, industrial enterprises, etc., and the water bodies before the wastewater user connects to the pipeline can be different types of wastewater, such as domestic sewage, municipal sewage, and industrial wastewater. External clean water bodies can include any one or more of groundwater, river water, lake water, and construction precipitation.

[0175] In this embodiment of the disclosure, water quality characteristic data of different inflow sources can be obtained through methods such as data collection and online monitoring (e.g., online water quality monitoring of the gate manholes before different types of drainage users connect to municipal pipelines to collect water quality characteristic data of different sewage water bodies, or online water quality monitoring of different external clean water bodies to collect water quality characteristic data of different external clean water bodies). This embodiment of the disclosure does not limit this. Water quality characteristic data may include the above-mentioned water quality index values ​​in the water body, such as any one or more of the following water quality index values: COD, conductivity, ammonia nitrogen, total phosphorus, total nitrogen, and hardness.

[0176] In calculating the collinearity among different water quality indicators in water quality characteristic data, the water quality characteristic data can first be divided according to the monitoring points of different inflow sources. These monitoring points can be the locations where water quality testing equipment is installed on pipelines. The water quality indicators can be any one of the indicators in the water quality characteristic data, such as COD or ammonia nitrogen.

[0177] For each inflow source monitoring point, collinearity among different water quality indicators in the water quality characteristic data can be calculated based on relevant technologies (such as calculating a correlation matrix). This collinearity can represent the degree of linear correlation between different water quality indicators. Water quality indicators with a higher degree of linear correlation (i.e., strong collinearity) can be labeled as the same category (for example, ammonia nitrogen and total nitrogen in municipal sewage water quality characteristic data can be labeled as the same category of water quality indicators), forming multiple categories of water quality indicators corresponding to each inflow source monitoring point.

[0178] Therefore, by combining the various water quality indicators corresponding to the monitoring points of each inflow source, the water quality indicator with the highest difference can be selected as the water quality indicator corresponding to each different inflow source. For example, monitoring point 1 corresponds to domestic sewage, and its corresponding water quality indicators include ammonia nitrogen and pH value. Ammonia nitrogen, which has the highest difference, can be selected as the water quality indicator corresponding to domestic sewage. Monitoring point 2 corresponds to groundwater, and its corresponding water quality indicators include hardness and pH value. Hardness, which has the highest difference, can be selected as the water quality indicator corresponding to groundwater.

[0179] The embodiments disclosed herein may also use other related technologies besides those described above to determine the water quality indicators corresponding to each inflow source, and the embodiments disclosed herein are not limited thereto.

[0180] After determining the water quality indicators corresponding to each inflow source, health problem detection can be performed on the time series data of water quality indicators in the drainage network. In step S204, the following can be done:

[0181] Obtain the original water quality index time series data corresponding to the drainage pipe network; obtain the target water quality index time series data from the original water quality index time series data; determine the inflow and infiltration ratio of each inflow source corresponding to the drainage pipe network based on the target water quality index time series data and the global optimization algorithm; determine whether there is an inflow and infiltration problem in the drainage pipe network based on the inflow and infiltration ratio.

[0182] This allows for the accurate identification and quantification of inflow and infiltration issues in drainage networks, even when water is flowing through the target pipe.

[0183] The original water quality index time series data can be data collected by water quality testing equipment within a preset time period. The water quality testing equipment can include equipment used to detect water quality (such as water quality testing sensors). The original water quality index time series data can include water quality index time series data of each inflow source corresponding to the drainage pipe network, as well as water quality index time series data at monitoring points of the drainage pipe network (such as the detection point at the end unit of the drainage pipe network).

[0184] The inflow infiltration ratio of each inflow source can represent the relative proportion of different inflow sources in the total inflow infiltration volume of the drainage network. For sewage networks, when the inflow infiltration ratio corresponding to external clean water bodies is not 0, it can be considered that the sewage network has an external water inflow infiltration problem; for stormwater networks, when the inflow infiltration ratio corresponding to the water bodies before each drainage user connects to the pipe is not 0, it can be considered that the stormwater network has an external water inflow infiltration problem.

[0185] In this embodiment of the disclosure, flow data at the monitoring point of the end unit of the drainage pipe network can also be obtained. When it is determined that there is an inflow infiltration problem in the drainage pipe network, the inflow infiltration ratio of each inflow source can be multiplied by the flow data to obtain the inflow infiltration volume corresponding to each inflow source.

[0186] This allows for a combination of qualitative and quantitative analysis, making the detection of health problems more accurate and reliable.

[0187] To ensure the accuracy of subsequently determining the inflow and infiltration ratios of each inflow source, real-time outlier removal and time correction can be performed on the original water quality indicator time series data. During the processing of the original water quality indicator time series data to obtain the target water quality indicator time series data, the following can be done:

[0188] Identify and remove abnormal data from the original water quality index time series data, and add normal data to obtain denoised water quality index time series data; align the denoised water quality index time series data in the time dimension to obtain the target water quality index time series data.

[0189] In the process of identifying and removing outlier data from the original water quality index time series data and adding normal data to obtain denoised water quality index time series data, the following can be done:

[0190] The original water quality index time series data is obtained by removing data collected by water quality testing equipment in an out-of-water state. Abnormal data in the out-of-water water quality index time series data is then removed to obtain filtered water quality index time series data. Normal data is then added to the filtered water quality index time series data to obtain denoised water quality index time series data.

[0191] Normal data can be obtained and supplemented through time series forecasting, interpolation, and other methods. When removing data collected in the water-out state, it can be determined whether the water quality testing equipment is in the water body of the target pipe. If it is determined that the water quality testing equipment is not in the water body of the target pipe, the data collected by the water quality testing equipment at this time can be regarded as the data collected in the water-out state (as air value) and discarded.

[0192] Outliers in non-aqueous water quality index time series data can be caused by non-environmental factors, such as obstruction by debris or contamination of the monitoring optical window. Outliers can include any one or more of the following: abnormal noise data, jittery data, baseline offset data, and abnormal jump data.

[0193] Abnormal noise data can refer to data in the time series data of non-disconnected water quality indicators that shows abrupt changes at a certain point in time. For example, abnormal noise data can be identified by considering the data at a certain point in the time series data of non-disconnected water quality indicators as abnormal noise data if the data value at that point is greater than a preset threshold (this threshold can be set relatively large).

[0194] Jittery data can represent multiple adjacent data points in non-disconnected water quality indicator time series data where the average relative difference exceeds a preset threshold. For example, jittery data can be identified as follows: if the average relative difference between the data values ​​corresponding to three adjacent time points in the non-disconnected water quality indicator time series data exceeds a preset threshold (e.g., 0.1), then the data corresponding to these three adjacent time points can be considered jittery data. The average relative difference can be calculated as: abs(y3-y1) / y2, where y1, y2, and y3 can refer to any three adjacent time points in the non-disconnected water quality indicator time series data.

[0195] Baseline offset data can be caused by zero-point drift, temperature drift, etc., and can represent data in non-detached water quality indicator time series data where the difference from the reference value changes linearly over time. For example, the method to identify baseline offset data is as follows: for non-detached water quality indicator time series data at a certain time point, the 90th quantile of the data within a preset time period (e.g., 24 hours) before that time point is recorded as x1, and the 10th quantile of the data within a preset time period (e.g., 24 hours) after that time point is recorded as x2. If (x2-x1) / x1 is within a preset range (e.g., 5%-50%), and the median slope of the data within the preset time period before and after that time point (which can be determined based on relevant technologies) is greater than a preset threshold (e.g., 0.01), then the data within the preset time period before that time point, the data at that time point, and the data within the preset time period after that time point can be identified as baseline offset data.

[0196] Abnormal jump data can represent data in non-detached water quality indicator time series data that is a preset multiple of the reference value. For example, an abnormal jump data identification method can be to calculate the hourly median of the non-detached water quality indicator time series data at each time point, calculate the increase ratio of the current time data to the median of the past x hours, and if the increase ratio exceeds a threshold, and the data of the period after the current time also meets the increase ratio threshold compared to the median of the aforementioned X hours, then the jump condition is considered met, and the data of the current time and the period after the adjacent time are identified as abnormal jump data. It should be noted that the embodiments of this disclosure do not limit the above-described method of identifying abnormal data, and abnormal data can also be identified by other methods besides the examples given in the embodiments of this disclosure.

[0197] Since the filtered water quality index time series data obtained after removing water-related data and outlier data may contain missing data at one or more time points, this embodiment of the disclosure can also utilize relevant technologies to fill in the missing data. For example, the missing data in the filtered water quality index time series data can be filled in using the Autoregressive Integrated Moving Average (ARIMA) prediction model, smoothing algorithms, interpolation algorithms (such as averaging the data before and after the missing data to obtain the missing data value), etc., to obtain denoised water quality index time series data.

[0198] Since the original water quality index time series data come from monitoring points of various upstream inflow sources and downstream terminal units, in order to ensure the comparability and temporal and spatial consistency of the upstream and downstream water quality index time series data, the denoised water quality index time series data can be time-aligned so that the upstream and downstream water quality index time series data are synchronized according to a unified time benchmark, so as to accurately analyze the inflow and infiltration ratio of each inflow source in the subsequent process.

[0199] In the process of aligning the time series data of denoised water quality indicators along the time dimension to obtain the time series data of the target water quality indicator, the following can be done:

[0200] Based on the cross-correlation function values ​​of upstream and downstream water quality index time series data in the denoised water quality index time series data, the phase difference between upstream and downstream monitoring points is obtained; based on the phase difference between upstream and downstream monitoring points, time correction is performed on the downstream water quality index time series data to obtain the target water quality index time series data.

[0201] Among them, the upstream water quality index time series data and the downstream water quality index time series data can correspond to the monitoring points of the upstream inflow source and the monitoring points of the downstream drainage network terminal unit, respectively. The phase difference between the upstream and downstream monitoring points can be the phase difference between the monitoring points of the inflow source and the monitoring points of the drainage network terminal unit.

[0202] The cross-correlation function values ​​of upstream and downstream water quality index time series data can be calculated as follows: Where x can represent upstream water quality index time series data, y can represent downstream water quality index time series data, k can represent the data index, and m is the total data volume. The above can be... Substitute into the formula To calculate the phase difference between upstream and downstream monitoring points. ,in, , .in, , .

[0203] The time correction of downstream water quality index time series data based on the phase difference between upstream and downstream monitoring points can be achieved using relevant technologies. For example, the time difference between upstream and downstream monitoring points can be calculated based on the phase difference between the upstream and downstream monitoring points (e.g., for example, the time difference between upstream and downstream monitoring points). The time series data of downstream water quality indicators are time-corrected based on the time difference to obtain the time series data of the target water quality indicators.

[0204] In determining the inflow and infiltration ratios of each inflow source corresponding to the drainage network based on time series data of the target water quality indicators and a global optimization algorithm, it is possible to:

[0205] Based on the time series data of the target water quality indicators, the initial inflow and infiltration ratio of each inflow source corresponding to the drainage network is calculated.

[0206] Specifically, the chemical mass balance equation can be input from the time series data of water quality indicators for each inflow source in the target water quality indicator time series data, as well as the time series data of water quality indicators at monitoring points in the drainage network. The equations are then solved simultaneously to calculate the initial inflow-infiltration ratio for each inflow source corresponding to the drainage network. The chemical mass balance equation can be expressed as: For multiple water quality indicators (i.e., multiple inflow sources), the above system of equations can be established separately and solved simultaneously. Here, n represents the number of inflow sources, j is the identifier of each inflow source, and i is the type identifier of the water quality indicator. This can represent the time series data of water quality index i corresponding to inflow source j. This can represent the time series data of water quality indicator i at monitoring points in the drainage pipe network. It can represent the initial inflow-infiltration ratio of inflow source j.

[0207] In response to the initial inflow-infiltration ratio of each inflow source satisfying the sixteenth preset condition, this initial inflow-infiltration ratio can be used as the inflow-infiltration ratio of each inflow source. The sixteenth preset condition may include the sum of the initial inflow-infiltration ratios of each inflow source being 1. For example, if the initial inflow-infiltration ratios of each inflow source satisfy the formula... Therefore, the sum of the initial inflow and infiltration ratios of each inflow source can be considered to be 1.

[0208] In response to the fact that the initial inflow and infiltration ratio of each inflow source does not meet the sixteenth preset condition, the time series data of the target water quality index are optimized using a global optimization algorithm to obtain the optimized water quality index time series data.

[0209] Among them, the global optimization algorithm is more objective and stable than the Monte Carlo method used in the prior art. The global optimization algorithm that can be used includes, but is not limited to, one of the following: differential evolution algorithm, genetic algorithm, simulated annealing algorithm, gradient descent algorithm, particle swarm optimization algorithm, etc. Differential evolution algorithm is preferred. The superior performance of this method comes from its effective use of parent individuals. By using the differences between parent individuals, the algorithm can generate a diverse population of offspring and grandchildren. Compared with the Monte Carlo method, this process not only ensures the objectivity of the algorithm in the optimization process, but also makes it more targeted and stable in solving problems, thus showing significant advantages in continuous optimization.

[0210] Differential evolutionary algorithms can be implemented using relevant technologies. This algorithm iteratively evolves individuals within a population, seeking the global optimum through optimization processes. Compared to other optimization methods, it offers advantages such as fewer input parameters, faster convergence, and better robustness. Optimization processes can include mutation, crossover, and selection operations.

[0211] You can start with the above. and As the initial population (each individual in the population, i.e., each...) and (This can represent a candidate solution in the problem space), and the scaling factor F and crossover probability CR are set to preset values ​​(e.g., F is set to 0.5 and CR is set to 0.2). The above optimization process is iteratively executed until a preset convergence threshold is met (e.g., set to 10). -2 Alternatively, by reaching the maximum number of iterations (e.g., set to 200), the optimized result can be obtained. and As optimized water quality index time series data.

[0212] During the optimization process, each individual in the initial population can undergo a mutation operation. This mutation operation can include: from the parent individual (corresponding to the above) and Four individuals are selected, and their vectors are subtracted twice to generate a difference vector. The current globally optimal individual is then summed with the two difference vectors scaled by F to generate the mutated individual. The calculation formula can be expressed as:

[0213]

[0214] in, It can represent the p-th mutated individual obtained in the g-th iteration; It can represent the current globally optimal individual obtained in the g-th iteration (i.e., the individual with the highest fitness value among the individuals). It can represent basis vectors; , These can be represented as the difference vectors obtained by subtracting the vectors twice from the four parent individuals. By obtaining two difference vectors, the optimization process can be made more robust to disturbances, with better randomization and global search capabilities.

[0215] Optionally, F can be adjusted during the optimization process to make its value decrease linearly or non-linearly with the number of iterations. One way to adjust the value of F is shown in the following formula: Where g is the current generation, G is the maximum number of iterations, and F is the maximum number of iterations. max and F min These are the preset maximum and minimum values ​​of F.

[0216] The above formula allows for a larger F value in the early stages of the optimization process iteration, which is beneficial for expanding the search space and maintaining population diversity. Furthermore, a smaller F value is adopted in the later stages of the optimization process iteration when convergence occurs, which is beneficial for searching around the optimal region, thereby improving the convergence rate and search accuracy.

[0217] Next, a crossover operation can be performed between the parent individual and the corresponding mutated individual to generate new offspring individuals. The crossover operation process can be represented as follows:

[0218]

[0219] Here, rand can represent a random number between 0 and 1, and this random process can satisfy a uniform distribution. CR, the crossover probability mentioned above, can represent the new offspring individuals. A certain gene in the sample comes from a mutated individual. The probability of. In order to ensure At least one gene in it comes from Therefore, qrand It can be a randomly generated integer between 1 and D, where D can represent the individual gene dimension (i.e., the vector dimension, the maximum value of q), thus requiring the q-th gene to come from V.

[0220] Figure 3 A schematic diagram illustrating cross-operation according to an embodiment of this disclosure is shown. For example... Figure 3 As shown, for The q-th gene in the graph (e.g., the gene dimension of an individual in the graph is 10), when it satisfies or This can be replaced with a mutated individual. (i.e., the solid black square in the image), otherwise, retain the parent individual. (i.e., the hollow square in the picture).

[0221] Optionally, the CR value can be adjusted during the optimization process to increase linearly or non-linearly with the number of iterations. One method for adjusting the CR value is shown in the following formula: Among them, CR max and CR min The maximum and minimum values ​​of CR are preset. By making CR increase with the number of iterations, the optimization process of this embodiment can maintain the diversity of the population in the early stage of iteration and have a larger convergence rate in the later stage of iteration.

[0222] Finally, a selection operation can be performed between the parent individual and the aforementioned child individuals. This selection can be based on the fitness values ​​of both the parent and child individuals. If the fitness value of the child individual is greater than that of the parent individual, then the child individual replaces the parent individual as the new parent individual in the next iteration; otherwise, the current parent individual can be included in the next iteration. This process can be represented as:

[0223]

[0224] in, It can represent the parent individual in g iterations. This can represent the offspring individuals obtained through the above mutation and crossover operations. This can represent the parent individual selected for the next iteration. and They can be represented separately and The fitness value can be calculated based on relevant technologies.

[0225] Through the above iterative optimization process, optimized water quality index time series data can be obtained. This optimized water quality index time series data can be used as the new target water quality index time series data, and the steps described above—calculating the initial inflow and infiltration ratio of each inflow source corresponding to the drainage network based on the target water quality index time series data, and subsequent steps—can be iteratively executed until the initial inflow and infiltration ratio of each inflow source meets the sixteenth preset condition. The calculated initial inflow and infiltration ratio is then used as the inflow and infiltration ratio of each inflow source. In this embodiment, a health problem can be alerted when one exists. This allows for timely detection of pipeline abnormalities, reminding relevant personnel to conduct inspections and maintenance, avoiding environmental pollution and drainage problems caused by pipeline damage or malfunction, and improving the operational safety and reliability of the drainage network.

[0226] Figure 4 A structural diagram of a health monitoring device for a drainage network according to an embodiment of this disclosure is shown. Figure 4 As shown, the device includes:

[0227] The judgment module 401 is used to judge the water level measurement result and / or the water quality index measurement result corresponding to the target pipe in the drainage pipe network;

[0228] The first determining module 402 is used to determine whether there is a health problem in the drainage network by using the first method when the water level measurement result corresponding to the target pipeline does not meet the preset water level conditions.

[0229] The second determining module 403 is used to determine whether there is a health problem in the drainage network by using the second method when the water level measurement result corresponding to the target pipeline meets the water level preset condition and the water quality index measurement result corresponding to the target pipeline meets the water quality preset condition.

[0230] The third determining module 404 is used to determine whether there is a health problem in the drainage network when the water level measurement result corresponding to the target pipeline meets the preset water level conditions but the water quality index measurement result corresponding to the target pipeline does not meet the preset water quality conditions.

[0231] The method of using a third approach to determine whether there are health problems in the drainage network includes: determining the inflow and infiltration ratio of each inflow source based on the time series data of water quality indicators of each inflow source corresponding to the drainage network, the time series data of water quality indicators of the monitoring points of the target pipeline, and a global optimization algorithm; and determining whether there are inflow and infiltration problems in the drainage network based on the inflow and infiltration ratio.

[0232] According to the embodiments of this disclosure, a diagnostic solution for the health problems of the drainage pipe network can be flexibly decided and accurately selected based on specific application scenarios and different actual conditions, thereby achieving rapid, efficient, convenient and accurate investigation of health problems of the drainage pipe network and improving the safety and reliability of the drainage pipe network operation.

[0233] The flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments of the present disclosure. In this regard, each block in a flowchart or block diagram may represent a module, segment, or portion of an instruction containing one or more executable instructions for implementing a specified logical function. In some alternative implementations, the functions marked in the blocks may occur in a different order than those shown in the drawings. For example, two consecutive blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each block in the block diagrams and / or flowcharts, and combinations of blocks in the block diagrams and / or flowcharts, may be implemented using a dedicated hardware-based system that performs the specified function or action, or using a combination of dedicated hardware and computer instructions.

[0234] The various embodiments of this disclosure have been described above. These descriptions are exemplary and not exhaustive, nor are they limited to the disclosed embodiments. Many modifications and variations will be apparent to those skilled in the art without departing from the scope and spirit of the described embodiments. The terminology used herein is chosen to best explain the principles, practical application, or technical improvements to the embodiments in the market, or to enable others skilled in the art to understand the embodiments disclosed herein.

Claims

1. A method for health detection of a drainage pipe network, characterized in that, The method includes: Determine the water level measurement results and / or the water quality index measurement results corresponding to the target pipe in the drainage network; If the water level measurement result corresponding to the target pipeline does not meet the preset water level conditions, the first method is used to determine whether there is a health problem in the drainage network; If the water level measurement result corresponding to the target pipeline meets the preset water level condition and the water quality index measurement result corresponding to the target pipeline meets the preset water quality condition, the second method is used to determine whether there is a health problem in the drainage network. If the water level measurement result corresponding to the target pipeline meets the preset water level condition but the water quality index measurement result corresponding to the target pipeline does not meet the preset water quality condition, a third method is used to determine whether there is a health problem in the drainage network. The water level preset condition is the condition for determining that the target pipe is full of water, and the water quality preset condition is the condition for determining that the water in the target pipe is not flowing. The method of determining whether the drainage network has health problems using a third method includes: Obtain the original water quality index time series data corresponding to the drainage pipe network. The original water quality index time series data includes the water quality index time series data of each inflow source corresponding to the drainage pipe network, as well as the water quality index time series data at the monitoring points of the drainage pipe network. The original water quality index time series data are processed to obtain the target water quality index time series data; Based on the time series data of the target water quality indicators and the global optimization algorithm, the inflow and infiltration ratio of each inflow source corresponding to the drainage network is determined; Based on the inflow and infiltration ratio, determine whether there is an inflow and infiltration problem in the drainage network; The step of determining the inflow and infiltration ratio of each inflow source corresponding to the drainage network based on the time series data of the target water quality index and the global optimization algorithm includes: Based on the time series data of the target water quality index, calculate the initial inflow and infiltration ratio of each inflow source corresponding to the drainage network; In response to the fact that the initial inflow and infiltration ratio of each inflow source does not meet the sixteenth preset condition, the global optimization algorithm is used to optimize the time series data of the target water quality index to obtain optimized water quality index time series data. The optimization process includes mutation operation, crossover operation and selection operation. The optimized water quality index time series data is used as the new target water quality index time series data, and the steps of calculating the initial inflow and infiltration ratio of each inflow source corresponding to the drainage network based on the target water quality index time series data and subsequent steps are executed iteratively until the initial inflow and infiltration ratio of each inflow source meets the sixteenth preset condition. The calculated initial inflow and infiltration ratio is then used as the inflow and infiltration ratio of each inflow source.

2. The method according to claim 1, characterized in that, The method of determining whether the drainage network has health problems includes: If the drainage network is a rainwater network and the rainfall in the area where the rainwater network is located does not meet the preset rainfall threshold within a preset time period, determine the measurement result of the first water quality index at the end unit of the target pipeline. If the first water quality index measurement result meets the first preset condition, the first water level measurement result of the target pipeline is determined; otherwise, the second water level measurement result is determined after the water level in the target pipeline is lowered. If either the first water level measurement result or the second water level measurement result meets the second preset condition, it is determined that the drainage network has no health problems; otherwise... If the detection result of the detection equipment of the terminal unit meets the third preset condition, it is determined that there is a problem of rainwater and sewage mixing in the drainage network; or, if the measurement result of the second water quality index at the measurement point upstream of the terminal unit meets the fourth preset condition, it is determined that there is a problem of external water inflow and infiltration in the drainage network.

3. The method according to claim 1, characterized in that, The method of determining whether the drainage network has health problems includes: When the drainage network is a sewage network and the rainfall in the area where the sewage network is located does not meet the preset rainfall threshold within a preset time period, the flow rate of the liquid conveying device in the target pipeline is compared between the rainfall in the area where the sewage network is located not meeting the preset rainfall threshold within a preset time period and the rainfall in the area where the sewage network is located in the past preset time period meeting the preset rainfall threshold, and / or the measurement results of the first water quality index are compared. If the flow rate comparison and / or the first water quality index measurement result comparison meet the fifth preset condition, determine the second water quality index measurement result comparison between the upstream and downstream measurement points of the target pipeline; If the comparison of the second water quality index measurement results meets the sixth preset condition, determine whether the third water level measurement result of the target pipeline meets the seventh preset condition. If the third water level measurement result meets the seventh preset condition, it is determined that there is an inflow and seepage problem of external water into the drainage network; If the flow rate comparison and / or the first water quality index measurement result comparison do not meet the fifth preset condition, the second water quality index measurement result comparison do not meet the sixth preset condition, or the third water level measurement result does not meet the seventh preset condition, it is determined that the drainage network has no health problems.

4. The method according to claim 1, characterized in that, The method of determining whether the drainage network has health problems includes: If the drainage network is a sewage network and the rainfall in the area where the sewage network is located meets a preset rainfall threshold within a preset time period, determine the water level comparison between the liquid conveying device in the target pipeline when the rainfall in the area where the sewage network is located meets the preset rainfall threshold within a preset time period and when the rainfall in the area where the sewage network is located does not meet the preset rainfall threshold within a historical preset time period. If the water level comparison does not meet the eighth preset condition, it is determined that the drainage network has no health problems; otherwise, If the measurement result of the third water quality index at the measurement point upstream of the terminal unit meets the ninth preset condition, it is determined that there is a problem of rainwater and sewage mixing in the drainage network.

5. The method according to claim 1, characterized in that, The method of determining whether the drainage network has health problems using the second method includes: If the drainage network is a rainwater network and the rainfall in the area where the rainwater network is located does not meet the preset rainfall threshold within a preset time period, determine the time series data of the first water quality index and the time series data of the first water level at the monitoring point in the target pipeline. If the first water level time series data meets the tenth preset condition and the first water quality index time series data meets the eleventh preset condition, it is determined that the drainage network has a problem of mixed rainwater and sewage; or if the first water level time series data meets the tenth preset condition and the first water quality index time series data does not meet the eleventh preset condition, it is determined that the drainage network has a problem of external water inflow and infiltration. When the drainage network is a rainwater network and the rainfall in the area where the rainwater network is located meets the preset rainfall threshold within a preset time period, the second water quality index time series data of the monitoring point is determined. The second water quality index time series data includes the time series data of two water quality indicators that are related. The related water quality indicators are water quality indicators that have complementary properties in the monitoring of the drainage network and reflect water quality characteristics from multiple perspectives. If the time series data of the second water quality indicator meets the thirteenth preset condition, it is determined that the drainage network has a problem with initial rainwater pollution.

6. The method according to claim 1, characterized in that, The method of determining whether the drainage network has health problems using the second method includes: When the drainage network is a sewage network and the rainfall in the area where the sewage network is located meets a preset rainfall threshold within a preset time period, the time series data of the third water quality index of the monitoring point in the target pipeline is determined. The time series data of the third water quality index includes the time series data of at least two water quality indicators that are related. The related water quality indicators are water quality indicators that have complementary properties in the monitoring of the drainage network and reflect water quality characteristics from multiple perspectives. If the time series data of the third water quality indicator meets the fourteenth preset condition, it is determined that there is a problem of mixed rainwater and sewage in the drainage network; If the drainage network is a sewage network and the rainfall in the area where the sewage network is located does not meet the preset rainfall threshold within a preset time period, determine one or more of the time series data of the fourth water quality index, the second water level, and the first flow rate of the monitoring point. If any one or more of the fourth water quality index time series data, the second water level time series data, and the first flow rate time series data meet the fifteenth preset condition, it is determined that there is an inflow and infiltration problem of external water into the drainage network.

7. The method according to claim 1, characterized in that, The process of processing the original water quality index time series data to obtain the target water quality index time series data includes: Abnormal data in the original water quality index time series data are identified and removed, and normal data is added to obtain denoised water quality index time series data; The time series data of the denoised water quality indicators are aligned in the time dimension to obtain the time series data of the target water quality indicators.

8. A health monitoring device for drainage pipe networks, characterized in that, The device includes: The judgment module is used to judge the water level measurement result and / or the water quality index measurement result corresponding to the target pipe in the drainage pipe network; The first determining module is used to determine whether there is a health problem in the drainage network when the water level measurement result corresponding to the target pipeline does not meet the preset water level conditions, using the first method. The second determining module is used to determine whether there is a health problem in the drainage network by using a second method when the water level measurement result corresponding to the target pipeline meets the water level preset condition and the water quality index measurement result corresponding to the target pipeline meets the water quality preset condition. The third determining module is used to determine whether there is a health problem in the drainage network when the water level measurement result corresponding to the target pipeline meets the water level preset condition and the water quality index measurement result corresponding to the target pipeline does not meet the water quality preset condition. The water level preset condition is the condition for determining that the target pipe is full of water, and the water quality preset condition is the condition for determining that the water in the target pipe is not flowing. The third determining module is further used for: Obtain the original water quality index time series data corresponding to the drainage pipe network. The original water quality index time series data includes the water quality index time series data of each inflow source corresponding to the drainage pipe network, as well as the water quality index time series data at the monitoring points of the drainage pipe network. The original water quality index time series data are processed to obtain the target water quality index time series data. Based on the time series data of the target water quality index, calculate the initial inflow and infiltration ratio of each inflow source corresponding to the drainage network; In response to the fact that the initial inflow and infiltration ratio of each inflow source does not meet the sixteenth preset condition, the time series data of the target water quality index is optimized using a global optimization algorithm to obtain optimized water quality index time series data. The optimization process includes mutation operation, crossover operation and selection operation. The optimized water quality index time series data is used as the new target water quality index time series data, and the steps of calculating the initial inflow and infiltration ratio of each inflow source corresponding to the drainage network based on the target water quality index time series data and subsequent steps are executed iteratively until the initial inflow and infiltration ratio of each inflow source meets the sixteenth preset condition. The calculated initial inflow and infiltration ratio is then used as the inflow and infiltration ratio of each inflow source. Based on the inflow-infiltration ratio, it is determined whether there is an inflow-infiltration problem in the drainage network.

Images