Health detection method and device for drainage pipe network

Abstract

The invention relates to a health detection method and device for a drainage pipe network. The method comprises the following steps: judging a water level measurement result and / or a water quality index measurement result corresponding to a target pipeline in the drainage pipe network; under the condition that the water level measurement result corresponding to the target pipeline does not meet the water level preset condition, whether the drainage pipe network has a health problem or not is determined through a first method; under the condition that the water level measurement result corresponding to the target pipeline meets the water level preset condition and the water quality index measurement result meets the water quality preset condition, whether the drainage pipe network has a health problem or not is determined through a second method; and when the water level measurement result corresponding to the target pipeline meets the water level preset condition and the water quality index measurement result does not meet the water quality preset condition, determining whether the drainage pipe network has a health problem or not by using a third method. According to the embodiment of the invention, the health problem of the drainage pipe network can be quickly, efficiently, conveniently and accurately checked, and the safety and reliability of the operation of the drainage pipe network are improved.

Description

TECHNICAL FIELD

[0001] The present disclosure relates to the technical field of water environment information processing, and particularly relates to a health detection method and device for a drainage pipe network. BACKGROUND

[0002] At present, the health problem of the drainage pipe network is mainly investigated by manual inspection, but this method has the problem of low traceability efficiency. In the process of investigation from upstream to downstream, due to the large number of nodes to be detected in the upstream and the complex topology relationship of the pipe network, the investigation work is often difficult to advance or even interrupted. Although water quality detection devices have been introduced in some scenarios for online monitoring, due to the limitation of energy supply and communication mode, the existing devices are difficult to achieve comprehensive and real-time monitoring, resulting in limitations in judging the health condition of the pipe network. Therefore, there is an urgent need for a fast, efficient, convenient and accurate health monitoring method for the drainage pipe network to improve the investigation efficiency and ensure the stability and safety of the operation of the drainage pipe network. SUMMARY

[0003] In view of this, the present disclosure provides a health detection method and device for a drainage pipe network.

[0004] According to an aspect of the present disclosure, a health detection method for a drainage pipe network is provided. The method comprises:

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

[0006] in a case where the water level measurement result corresponding to the target pipe does not satisfy a water level preset condition, determining whether the drainage pipe network has a health problem by using a first method;

[0007] in a case where the water level measurement result corresponding to the target pipe satisfies the water level preset condition and the water quality index measurement result corresponding to the target pipe satisfies a water quality preset condition, determining whether the drainage pipe network has a health problem by using a second method;

[0008] in a case where the water level measurement result corresponding to the target pipe satisfies the water level preset condition and the water quality index measurement result corresponding to the target pipe does not satisfy the water quality preset condition, determining whether the drainage pipe network has a health problem by using a third method,

[0009] wherein determining whether the drainage pipe network has a health problem by using the third method comprises: determining an inflow infiltration ratio of each inflow source according to water quality index time series data of each inflow source corresponding to the drainage pipe network, water quality index time series data of a monitoring point of the target pipe, and a global optimization algorithm; and determining whether the drainage pipe network has an inflow infiltration problem according to the inflow infiltration ratio.

[0010] In a possible implementation, the first method for determining whether the drainage pipe network has a health problem comprises:

[0011] In a case where the type of the drainage pipe network is a rainwater pipe network and the rainfall in the area where the rainwater pipe network is located in a preset time length does not satisfy a preset rainfall threshold, determining a first water quality index measurement result at the end unit of the target pipe;

[0012] In a case where the first water quality index measurement result satisfies a first preset condition, determining a first water level measurement result of the target pipe, or otherwise, determining a second water level measurement result after reducing the water level in the target pipe;

[0013] In a case where the first water level measurement result or the second water level measurement result satisfies a second preset condition, determining that the drainage pipe network does not have a health problem, or otherwise,

[0014] In a case where the detection result of the detection device of the end unit satisfies a third preset condition, determining that the drainage pipe network has a rain sewage mixing problem, or in a case where the second water quality index measurement result at the measurement point upstream of the end unit satisfies a fourth preset condition, determining that the drainage pipe network has an external water inflow infiltration problem.

[0015] In a possible implementation, the first method for determining whether the drainage pipe network has a health problem comprises:

[0016] In a case where the type of the drainage pipe network is a sewage pipe network and the rainfall in the area where the sewage pipe network is located in a preset time length does not satisfy a preset rainfall threshold, determining a flow delivery comparison condition and / or a first water quality index measurement result comparison condition of a liquid delivery device in the target pipe between a case where the rainfall in the area where the sewage pipe network is located in the preset time length does not satisfy the preset rainfall threshold and a case where the rainfall in the area where the sewage pipe network is located in a historical preset time length satisfies the preset rainfall threshold;

[0017] In a case where the flow delivery comparison condition and / or the first water quality index measurement result comparison condition satisfies a fifth preset condition, determining a second water quality index measurement result comparison condition between an upstream measurement point and a downstream measurement point of the target pipe;

[0018] In a case where the second water quality index measurement result comparison condition satisfies a sixth preset condition, determining whether a third water level measurement result of the target pipe satisfies a seventh preset condition;

[0019] In a case where the third water level measurement result satisfies the seventh preset condition, determining that the drainage pipe network has an external water inflow infiltration problem;

[0020] In a case where the flow delivery comparison condition and / or the first water quality index measurement result comparison condition does not satisfy the fifth preset condition, the second water quality index measurement result comparison condition does not satisfy the sixth preset condition, or the third water level measurement result does not satisfy the seventh preset condition, it is determined that the drainage pipe network does not have a health problem.

[0021] In a possible implementation, the first method is used to determine whether the drainage pipe network has a health problem, including:

[0022] In a case where the type of the drainage pipe network is a sewage pipe network and the rainfall in the area where the sewage pipe network is located within a preset time length satisfies a preset rainfall threshold, a water level comparison condition between a case where the rainfall in the area where the sewage pipe network is located within a preset time length satisfies the preset rainfall threshold and a case where the rainfall in the area where the sewage pipe network is located within a historical preset time length does not satisfy the preset rainfall threshold is determined.

[0023] In a case where the water level comparison condition does not satisfy an eighth preset condition, it is determined that the drainage pipe network does not have a health problem, otherwise,

[0024] In a case where the third water quality index measurement result of the measurement point upstream of the terminal unit satisfies a ninth preset condition, it is determined that the drainage pipe network has a rain and sewage mixing problem.

[0025] In a possible implementation, the second method is used to determine whether the drainage pipe network has a health problem, including:

[0026] In a case where the type of the drainage pipe network is a rainwater pipe network and the rainfall in the area where the sewage pipe network is located within a preset time length does not satisfy a preset rainfall threshold, first water quality index time series data and first water level time series data of the monitoring point in the target pipe are determined.

[0027] In a case where the first water level time series data satisfies a tenth preset condition and the first water quality index time series data satisfies an eleventh preset condition, it is determined that the drainage pipe network has a rain and sewage mixing problem; or in a case where the first water level time series data satisfies the tenth preset condition and the first water quality index time series data does not satisfy the eleventh preset condition, it is determined that the drainage pipe network has an external water inflow infiltration problem.

[0028] In a case where the type of the drainage pipe network is a rainwater pipe network and the rainfall in the area where the sewage pipe network is located within a preset time length satisfies a preset rainfall threshold, second water quality index time series data of the monitoring point are determined, wherein the second water quality index time series data include time series data of two water quality indexes having a correlation relationship, the water quality indexes having the correlation relationship represent water quality indexes having mutually complementary properties and reflecting water quality characteristics from multiple angles in drainage pipe network monitoring.

[0029] In a case where the second water quality index time series data meets a thirteenth preset condition, it is determined that the drainage pipe network has a preliminary rain pollution problem.

[0030] In a possible implementation, the second method for determining whether the drainage pipe network has a health problem includes:

[0031] In a case where the type of the drainage pipe network is a sewage pipe network and the rainfall in the area where the sewage pipe network is located within a preset time length meets a preset rainfall threshold, third water quality index time series data of the monitoring point in the target pipe are determined, wherein the third water quality index time series data include time series data of at least two water quality indexes having a correlation relationship, the water quality indexes having the correlation relationship represent water quality indexes having complementary properties to each other in drainage pipe network monitoring and reflecting water quality characteristics from multiple angles.

[0032] In a case where the third water quality index time series data meet a fourteenth preset condition, it is determined that the drainage pipe network has a rain and sewage mixing problem.

[0033] In a case where the type of the drainage pipe network is a sewage pipe network and the rainfall in the area where the sewage pipe network is located within a preset time length does not meet a preset rainfall threshold, any one or more of fourth water quality index time series data, second water level time series data and first flow time series data of the monitoring point are determined.

[0034] In a case where any one or more of the fourth water quality index time series data, the second water level time series data and the first flow time series data meet a fifteenth preset condition, it is determined that the drainage pipe network has an external water inflow infiltration problem.

[0035] In a possible implementation, the third method for determining whether the drainage pipe network has a health problem includes:

[0036] Original water quality index time series data corresponding to the drainage pipe network are acquired, the original water quality index time series data including water quality index time series data of each inflow source corresponding to the drainage pipe network and time series data of a water quality index at a monitoring point of the drainage pipe network.

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

[0038] According to the target water quality index time series data and a global optimization algorithm, inflow infiltration ratios of each inflow source corresponding to the drainage pipe network are determined.

[0039] According to the inflow infiltration ratios, it is determined whether the drainage pipe network has an inflow infiltration problem.

[0040] In a possible implementation, the initial infiltration ratio of each inflow source corresponding to the drainage pipe network is determined according to the target water quality index time series data and a global optimization algorithm, including:

[0041] The initial infiltration ratio of each inflow source corresponding to the drainage pipe network is calculated according to the target water quality index time series data;

[0042] In response to the initial infiltration ratio of each inflow source not satisfying the sixteenth preset condition, the global optimization algorithm is used to optimize the target water quality index time series data to obtain optimized water quality index time series data, and the optimization process includes mutation operation, crossover operation and selection operation.

[0043] The optimized water quality index time series data is taken as new target water quality index time series data, and the initial infiltration ratio of each inflow source corresponding to the drainage pipe network is calculated according to the new target water quality index time series data, and the subsequent steps are iteratively executed until the initial infiltration ratio of each inflow source satisfies the sixteenth preset condition, and the calculated initial infiltration ratio is taken as the infiltration ratio of each inflow source.

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

[0045] Abnormal data in the original water quality index time series data is identified and removed, and normal data is supplemented to obtain denoised water quality index time series data;

[0046] The denoised water quality index time series data is aligned in the time dimension to obtain the target water quality index time series data.

[0047] According to another aspect of the present disclosure, a health detection device for a drainage pipe network is provided. The device includes:

[0048] A judgment module is configured to judge the water level measurement result corresponding to a target pipe and / or the water quality index measurement result corresponding to the target pipe in the drainage pipe network.

[0049] A first determination module is configured to determine whether the drainage pipe network has a health problem by using a first method when the water level measurement result corresponding to the target pipe does not satisfy a water level preset condition.

[0050] A second determination module is configured to determine whether the drainage pipe network has a health problem by using a second method when the water level measurement result corresponding to the target pipe satisfies the water level preset condition and the water quality index measurement result corresponding to the target pipe satisfies a water quality preset condition.

[0051] The third determination module is configured to determine, by using a third method, whether the drainage pipe network has a health problem in a case where the water level measurement result corresponding to the target pipe meets the water level preset condition and the water quality index measurement result corresponding to the target pipe does not meet the water quality preset condition,

[0052] The third method includes: determining, according to the water quality index time series data of each inflow source corresponding to the drainage pipe network, the water quality index time series data of the monitoring point of the target pipe, and a global optimization algorithm, an inflow infiltration ratio of each inflow source; and determining, according to the inflow infiltration ratio, whether the drainage pipe network has an inflow infiltration problem.

[0053] According to the embodiments of the present disclosure, the diagnosis scheme of the health problem of the drainage pipe network can be flexibly decided and accurately selected according to specific application scenarios and different actual situations, so that the health problem of the drainage pipe network can be quickly, efficiently, conveniently and accurately checked, and the safety and reliability of the operation of the drainage pipe network are improved.

[0054] Other features and aspects of the present disclosure will become apparent from the following detailed description of the exemplary embodiments with reference to the drawings. BRIEF DESCRIPTION OF DRAWINGS

[0055] The accompanying drawings, which are incorporated in and constitute a part of the specification, illustrate exemplary embodiments, features, and aspects of the present disclosure and serve to explain the principles of the present disclosure.

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

[0057] Figure 2 A flowchart of a health detection method of a drainage pipe network according to an embodiment of the present disclosure is shown.

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

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

[0060] Various exemplary embodiments, features and aspects of the present disclosure will be described in detail below with reference to the accompanying drawings. The same reference signs in the drawings represent functionally identical or similar elements. Although various aspects of the embodiments are shown in the drawings, the drawings are not necessarily drawn to scale unless specifically indicated.

[0061] As used herein, the terms “comprise”, “comprising”, “have”, “having”, “include”, “including”, “contain”, “containing”, “provide”, “providing”, or variants thereof, are open-ended, and include one or more stated features, integers, elements, steps, components, or functions but do not preclude the presence or addition of one or more other features, integers, elements, steps, components, functions, or groups thereof.

[0062] When an element is referred to as being “connected”, “coupled”, “responsive”, or “in communication” with, to or with one or more other elements, it can be directly connected, coupled, responsive, or in communication with the one or more other elements or intervening elements can be present.

[0063] Although the terms first, second, third, etc. can 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 element / operation. Thus, a first element / operation in some embodiments could be termed a second element / operation in other embodiments without departing from the teachings of the present inventive concept.

[0064] The word “exemplary” is used herein to mean “serving as an example, instance, or illustration.” Any implementation described herein as “exemplary” is not necessarily to be construed as preferred or advantageous over other implementations.

[0065] In addition, for the purpose of convenience and brevity, detailed descriptions of well-known functions and structures incorporated in the present disclosure can be omitted. It will be appreciated that those skilled in the art, with the benefit of this disclosure, can practice the present disclosure without adding a feature unrelated to the core feature of the present disclosure.

[0066] At present, the health problem investigation of the drainage pipe network mainly relies on manual inspection, but this method has the problem of low traceability efficiency. In the process of investigation from upstream to downstream, due to the large number of nodes to be detected in the upstream and the complex pipe network topology relationship, the investigation work is often difficult to advance or even interrupted. Although water quality detection devices have been introduced in some scenarios for online monitoring, due to the limitations of energy supply and communication methods, existing devices are difficult to achieve comprehensive and real-time monitoring, resulting in limitations in judging the health status of the pipe network. Therefore, there is an urgent need for a fast, efficient, convenient and accurate health monitoring method for the drainage pipe network to improve the investigation efficiency and ensure the stability and safety of the operation of the drainage pipe network.

[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 device involved in the embodiments of the present disclosure can be any one or more of a mobile phone, a foldable electronic device, a tablet computer, a desktop computer, a laptop computer, a handheld computer, a notebook computer, an ultra-mobile personal computer (UMPC), a netbook, a cellular phone, a personal digital assistant (PDA), and a vehicle-mounted device. The embodiments of the present disclosure do not have special restrictions on the specific type of the terminal device, and the terminal device can have wired or wireless communication functions.

[0070] The server involved in the embodiments of the present disclosure can be located locally or in the cloud, and can be a physical device or a virtual device such as a virtual machine, a container, etc., and has a wireless communication function. The wireless communication function can be provided in a chip (system) or other components or assemblies of the server. The wireless communication function can be implemented by, for example, 2G / 3G / 4G / 5G mobile communication technology, Wi-Fi, Bluetooth, frequency modulation (FM), data radio, satellite communication, etc. The server can also communicate through wired connections to interact with other devices.

[0071] Figure 2 A flowchart of a method for detecting the health of a drainage pipe network according to an embodiment of the present disclosure is shown. The method can be used in the drainage pipe network health detection system described above, and as shown in the flowchart, the method can include: Figure 2

[0072] In step S201, the water level measurement result corresponding to the target pipe in the drainage pipe network and / or the water quality index measurement result corresponding to the target pipe is determined.

[0073] The drainage pipe network can be a pipe system for collecting, transporting, and discharging rainwater, sewage, or combined wastewater. The drainage pipe network can include pipes (including trunk pipes and branch pipes), measurement points (such as inspection wells, etc.), liquid transport devices (such as pump stations, etc.), gates, discharge outlets, and other facilities. According to the function of the drainage pipe network, the types of the drainage pipe network can include a sewage pipe network, a rainwater pipe network, and a combined pipe network. The sewage pipe network can be used to collect and transport sewage (such as domestic sewage and industrial wastewater). The rainwater pipe network is used to collect and discharge natural rainfall (such as rainwater). The combined pipe network can be used to collect and transport mixed sewage and rainwater.

[0074] ​In the embodiments of the present disclosure, the target pipe can be any main pipe in the drainage pipe network. The main pipe can refer to a pipe laid along a main water conveying route from a water source or a main water collection point, which is responsible for collecting and conveying sewage or rainwater from various branch pipes to a treatment facility or a discharge outlet. The health problems of each main pipe in the drainage pipe network can be checked one by one (for example, from upstream to downstream or from downstream to upstream), or the health problems of a certain section of the drainage pipe network (for example, including part or all of the main pipes) can be checked, and the embodiments of the present disclosure do not limit this.

[0075] The health problems of the drainage pipe network can include any one or more of rainwater and sewage mixing, external water inflow and seepage, and initial rain pollution. Among them, rainwater and sewage mixing can refer to an error connection or damage between a pipe in the rainwater pipe network and a pipe in the sewage pipe network in a drainage pipe network (for example, a sewage pipe network or a rainwater pipe network), causing rainwater and sewage to mix with each other. External water inflow and seepage can refer to external clean water sources (such as groundwater, river and lake water, construction rainfall, etc.) seeping into the sewage pipe network through pipe damage, interface tightness, etc., or external sewage sources (such as domestic sewage, industrial sewage, etc.) seeping into the rainwater pipe network through pipe damage, interface tightness, etc.

[0076] Initial rain pollution can refer to the phenomenon that at the beginning of rainfall, rainwater washes the pollutants (such as dust, oil stains, heavy metals, etc.) on the surface of the ground, buildings, etc. into the drainage pipe network, causing a high concentration of pollutants in the water and a decrease in water quality. This phenomenon is particularly evident in urban areas, where the ground is mostly impervious, and pollutants are more easily carried away by rainwater.

[0077] Detecting problems such as rainwater and sewage mixing, external water inflow and seepage, and initial rain pollution in the drainage pipe network is of great significance to the protection of urban water environment quality and the efficient operation of the drainage system. For example, rainwater and sewage mixing and external water inflow and seepage problems can cause sewage to flow into the rainwater pipe network, allowing untreated sewage to be directly discharged into rivers, lakes or oceans, polluting the water body; or allowing rainwater to enter the sewage pipe network, increasing the load of the sewage treatment plant and affecting its normal operation. For another example, initial rain pollution carries a large amount of pollutants, which can have a serious impact on the water body if not controlled. Therefore, timely detection and treatment of these problems can help improve the reliability of the drainage pipe network system and protect water resources and the ecological environment.

[0078] In the embodiments of the present disclosure, the water level measurement result corresponding to the target pipe during the operation of the drainage pipe network is first determined, so as to determine whether there is a full water condition, and the water quality index measurement result corresponding to the target pipe is determined, so as to determine the flow condition of the water in the target pipe, and different methods are selected to determine whether there is a health problem in the drainage pipe network.

[0079] The manner of judging whether the target pipe in the drainage pipe network is full of water can be judging whether each main pipe in the drainage pipe network is full of water. When any one or more main pipes are full of water, it can be considered that the target pipe is full of water. Whether the target pipe is full of water can be judged by judging whether the water level measurement result corresponding to the target pipe (i.e. any one or more main pipes in the drainage pipe network) satisfies the water level preset condition. When the water level measurement result corresponding to the target pipe satisfies the water level preset condition, it is considered that the target pipe is full of water. When the water level measurement result corresponding to the target pipe does not satisfy the water level preset condition, it is considered that the target pipe is not full of water. For example, the water level in the main pipe can be measured by a water level sensor (such as a liquid level meter) or directly by a probe rod with a scale. The water level preset condition can be that the water level reaches a preset water level threshold (such as the water level reaching the height of the pipe).

[0080] The manner of judging whether the water in the target pipe is flowing can be judging whether the water quality index measurement result corresponding to the target pipe satisfies the water quality preset condition. When the water quality index measurement result corresponding to the target pipe satisfies the water quality preset condition, it is considered that the water in the target pipe is in a non-flowing state. When the water quality index measurement result corresponding to the target pipe does not satisfy the water quality preset condition, it is considered that the water in the target pipe is in a flowing state. At this time, the water quality index (for example, water temperature, conductivity, turbidity, etc.) can be measured continuously twice or more at the end unit of the target pipe. The water temperature is the simplest and most direct water quality index, as the water temperature is different for different sources of water. The conductivity reflects the content of total dissolved solids in water and is very sensitive to the source of water. Significant changes in the two detection values indicate that water of different quality has flowed in. The turbidity index can be used because flowing can stir up sediment or bring in silt-laden water, causing turbidity to rise sharply. When the change value of the water quality index is less than a threshold value, it is considered that the water quality preset condition is satisfied, and it is considered that the water in the target pipe is in a non-flowing state.

[0081] In other embodiments, whether the water is flowing can also be judged by using leaves, flow direction meters, etc. For example, leaves or other floating objects can be thrown into a measurement point upstream of the target pipe (such as an upstream inspection well), and the appearance of the leaves at a measurement point downstream of the target pipe (such as a downstream inspection well) can be observed. If the leaves successfully drift from the upstream to the downstream, it indicates that there is continuous water flow in the target pipe, i.e. the water in the target pipe is in a flowing state. Otherwise, the water in the target pipe is in a non-flowing state. For another example, a flow direction meter can be deployed in the target pipe to monitor whether the water in the target pipe is in a flowing state. Of course, a comprehensive judgment based on the water quality index measurement result combined with leaves, flow direction meters, etc. can also be used to improve the accuracy of the judgment.

[0082] In step S202, when the water level measurement result corresponding to the target pipe does not satisfy the water level preset condition, the first method is used to determine whether the drainage pipe network has a health problem.

[0083] The water level measurement result corresponding to the target pipeline not satisfying the water level preset condition can represent that there is no full water condition in the target pipeline.

[0084] The step S202 can include determining whether the rainwater and sewage mixing problem or the external water inflow seepage problem exists in the drainage pipe network according to the detection result of the detection device or the water quality index measurement result or the water level measurement result.

[0085] In the case that there is no full water condition in the target pipeline, the first method is used in the embodiment of the present disclosure at this time, and the rainwater and sewage mixing problem or the external water inflow seepage problem of the drainage pipe network can be quickly investigated when there is no full water condition in the target pipeline by using the water quality index measurement result and / or the water level measurement result, which is more efficient.

[0086] In the first method, whether the drainage pipe network has a health problem can be determined according to different types of drainage pipe networks and / or environmental conditions. For example, according to whether the drainage pipe network is a rainwater pipe network, a sewage pipe network (or a combined pipe network), and whether there is a rainfall event at present, different indexes are used to detect the health problem, so that the detection result is more accurate. The first method of the embodiment of the present disclosure is introduced below according to different types of drainage pipe networks and / or environmental conditions.

[0087] In one possible implementation, in the process of determining whether the drainage pipe network has a health problem by using the first method, the following can be included:

[0088] In the case that the type of the drainage pipe network is a rainwater pipe network and the rainfall amount in the area where the rainwater pipe network is located within a preset time length does not satisfy a preset rainfall amount threshold, the first water quality index measurement result at the end unit of the target pipeline is determined; in the case that the first water quality index measurement result satisfies a first preset condition, the first water level measurement result of the target pipeline is determined, otherwise, the following is performed: the second water level measurement result is determined after the water level in the target pipeline is lowered; in the case that the first water level measurement result or the second water level measurement result satisfies a second preset condition, it is determined that the drainage pipe network does not have a health problem, otherwise, the following is performed: in the case that the measurement result of the detection device of the end unit satisfies a third preset condition, it is determined that the drainage pipe network has a rainwater and sewage mixing problem, or the following is performed: in the case that the second water quality index measurement result at a measurement point upstream of the end unit satisfies a fourth preset condition, it is determined that the drainage pipe network has an external water inflow seepage problem.

[0089] Thus, by using the first water quality index for preliminary screening, accurate detection data can be ensured without external rainfall interference. When the first water quality index does not meet the preset condition, the deviation caused by abnormal water level can be eliminated by re-measuring after reducing the water level in the pipeline. By determining whether the rainwater pipe network has rain and sewage mixing or external water inflow seepage problem according to the preset condition of the water level and water quality measurement results, the accurate differentiation of the abnormal type of the drainage pipe network can be realized, so that the accurate judgment of the health status of the rainwater pipe network under non-rainfall conditions can be realized.

[0090] The rainfall in the area where the rainwater pipe network is located within a preset time period does not meet a preset rainfall threshold, which is a non-rainfall event. The preset time period 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 0-1 mm, etc.

[0091] The end unit of the target pipeline can include a direct discharge outlet of the dry pipe end (i.e., an outlet directly discharging into a natural water body) and any one of an interface connected to a pump station, a manhole (e.g., a manhole before the direct discharge outlet). The end unit can be identified and labeled in advance based on the topological relationship diagram of the drainage pipe network. The topological relationship diagram can be obtained from a third party such as a municipal management department. The water quality index can be measured at the end unit of the target pipeline by a water quality detection sensor or test paper, etc. The water quality index can include any one or more of chemical oxygen demand (COD), ammonia nitrogen, conductivity, water temperature (i.e., temperature water quality index). The water level measurement result can be determined by the above-mentioned water level measurement method. The measurement result of the water quality index and the water level measurement result can be time series data of the water quality index or a single measurement value, which is not limited in this regard.

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

[0093] In a case where the first water quality index measurement result meets the first preset condition, the water level of the target pipeline can be measured (i.e., a first water level measurement result is obtained), and it is verified whether the first water level measurement result meets a second preset condition. In a case where the first water quality index measurement result does not meet the first preset condition, the manner in which the water level in the target pipeline is reduced can be to perform water pumping at the pump station at the end of the trunk (e.g., which can be performed at night), and then the water level of the target pipeline is measured again (i.e., a second water level measurement result is obtained), and it is verified whether the second water level measurement result meets the second preset condition. The second preset condition can include that the fullness (i.e., the ratio of the water level in the water level measurement result to the height of the target pipeline) is less than a threshold value (e.g., 0.3).

[0094] In a case where the first water level measurement result or the second water level measurement result does not meet the second preset condition, it can be determined whether there is an external water inflow infiltration problem by judging whether a second water quality index measurement result at a measurement point (such as a manhole) upstream of the end unit meets a fourth preset condition. In a case where any one of the detection devices such as a probe rod, a video shooting device, or an image shooting device at the end unit has a measurement result that meets a third preset condition, it can be determined that there is a rain and sewage mixing problem in the drainage pipe network.

[0095] The topological structure diagram of the drainage pipe network will have the pipelines of the pipe network and the connection relationship between the pipelines. In a case where the pipelines are not full of water, the connection of the pipelines is detected by the probe rod or shot by the video or image device, so as to determine whether there is a pipeline intersection point, and it can be determined whether there is an extra sewage pipe connected to the pipe network. In a case where it is determined that there is a pipeline intersection point and the intersection point does not exist in the topological structure of the drainage pipe network, it is determined that there is a sewage pipe connected to the rainwater pipe network.

[0096] The second water quality index measurement result can include the conductivity measured by a conductivity measuring instrument. For example, if the characteristic value of the local domestic sewage is about 1400 μs / cm, the fourth preset condition can include that the measured conductivity meets the characteristic value (e.g., 1400 μs / cm) of the local domestic sewage, so as to determine that there is sewage in the target pipeline and that there is a sewage pipeline connected. Other ways can also be used to determine whether there is a sewage pipeline connected, for example, the probe rod can be used to detect whether there is a pipeline intersection point in the target pipeline, and when there is a pipeline intersection point, it is determined that there is a sewage pipeline connected.

[0097] The third preset condition can include that the probe rod detects or the image shooting device shoots that there is a sewage pipe connected.

[0098] The fourth preset condition can include that the COD in the water quality index measurement result is less than a threshold value (such as COD < 100 mg / L) and / or the ammonia nitrogen is less than a threshold value (such as ammonia nitrogen < 5 mg / L).

[0099] In the absence of sewer access, it can be considered that the sewer network does not have health problems.

[0100] In one possible implementation, in the process of determining whether the sewer network has health problems by using the first method, the following can be included:

[0101] In the case that the type of the sewer network is a sewer network and the rainfall in the area where the sewer network is located within a preset time length does not satisfy a preset rainfall threshold, the flow delivery comparison and / or the first water quality index measurement comparison between when the rainfall in the area where the sewer network is located within a preset time length does not satisfy a preset rainfall threshold and when the rainfall in the area where the sewer network is located within a historical preset time length satisfies a preset rainfall threshold is determined; in the case that the flow delivery comparison and / or the first water quality index measurement comparison satisfies a fifth preset condition, the second water quality index measurement comparison between the upstream measurement point and the downstream measurement point of the target pipe is determined; in the case that the second water quality index measurement comparison satisfies a sixth preset condition, whether the third water level measurement result of the target pipe satisfies a seventh preset condition is determined; in the case that the third water level measurement result of the target pipe satisfies the seventh preset condition, it is determined that the sewer network has an external water inflow infiltration problem; in the case that the flow delivery comparison and / or the first water quality index measurement comparison does not satisfy the fifth preset condition, the second water quality index measurement comparison does not satisfy the sixth preset condition, or the third water level measurement result of the target pipe does not satisfy the seventh preset condition, it is determined that the sewer network does not have health problems.

[0102] Therefore, by comparing the flow delivery and / or the water quality index measurement result of the liquid delivery device between the non-rainfall event and the historical rainfall event, the health status of the sewer network can be preliminarily judged; when the above comparison data satisfies the fifth preset condition, by comparing the water quality index measurement result between the upstream measurement point and the downstream measurement point, and according to whether the comparison satisfies the sixth preset condition, and further combined with whether the water level of the target pipe satisfies the seventh preset condition, the accurate distinction of the health problem type is further realized. The above can be executed during the non-rainfall event, so that the accurate judgment of the health status of the sewer network during the non-rainfall period can be realized, and the accuracy and efficiency of the health problem detection are significantly improved.

[0103] In the case that the rainfall in the area where the sewer network is located within a preset time length does not satisfy a preset rainfall threshold is a non-rainfall event, and the rainfall in the area where the sewer network is located within a historical preset time length satisfies a preset rainfall threshold is a historical rainfall event.

[0104] The liquid delivery device can be any pump station in the target pipeline, and the comparison of the flow delivery between the non-rainfall event and the historical rainfall event can be determined according to the daily average flow delivered by the pump station during the non-rainfall event and the daily average flow delivered by the pump station during the historical rainfall event, where the flow delivered by the pump station can be measured by a flow meter or the like.

[0105] The fifth preset condition can include that the daily average flow delivered by the pump station during the historical rainfall event is greater than the daily average flow delivered by the pump station during the non-rainfall event, and / or the daily average concentration of the water quality index of the catch basin of the pump station during the historical rainfall event is less than the daily average concentration of the water quality index of the catch basin of the pump station during the rainfall event.

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

[0107] The sixth preset condition can include that the rising amplitude of the water quality index measured by the upstream measurement point compared with the water quality index measured by the downstream measurement point is greater than a threshold value (for example, 10%).

[0108] The seventh preset condition can include that the water level of the target pipeline is greater than a threshold value (for example, 3m) or is equal to the height of the target pipeline.

[0109] In one possible implementation, in the process of determining whether the drainage pipe network has a health problem by using the first method, the following can be included:

[0110] In a case where the type of the drainage pipe network is a sewage pipe network and the rainfall in the area where the sewage pipe network is located within a preset time length satisfies a preset rainfall threshold, the water level comparison between the liquid conveying device in the target pipe in a case where the rainfall in the area where the sewage pipe network is located within a preset time length satisfies a preset rainfall threshold and a case where the rainfall in the area where the sewage pipe network is located within a historical preset time length does not satisfy a preset rainfall threshold is determined; in a case where the water level comparison does not satisfy an eighth preset condition, it is determined that the drainage pipe network does not have a health problem, otherwise, the following is performed: the third water quality index measurement result of the measurement point upstream of the terminal unit satisfies a ninth preset condition, and it is determined that the drainage pipe network has a rain and sewage mixing problem.

[0111] Thus, in a case where the type of the drainage pipe network is a sewage pipe network and in a rainfall event, by comprehensively analyzing the water level comparison and the flow and water quality index measurement result comparison of the liquid conveying device in the target pipe between the rainfall event and the historical non-rainfall event, accurate judgment can be made on whether the drainage pipe network has a rain and sewage mixing problem. The above can be performed during a rainfall event, so that accurate judgment can be made on whether the sewage pipe network has a rain and sewage mixing problem during a rainfall period, and the accuracy and efficiency of health problem detection are significantly improved.

[0112] The rainfall in the area where the sewage pipe network is located within a preset time length satisfying a preset rainfall threshold is a rainfall event, and the rainfall in the area where the sewage pipe network is located within a historical preset time length not satisfying a preset rainfall threshold is a historical non-rainfall event.

[0113] In a case where the pump station does not work, the water level comparison between the rainfall event and the historical non-rainfall event can be determined according to the water level of the pump station in the rainfall event and in the historical non-rainfall event.

[0114] The eighth preset condition can include that the ratio of the water level of the pump station in the rainfall event to the water level in the historical non-rainfall event is greater than a threshold value (for example, 1.4).

[0115] In a case where the water level comparison does not satisfy the eighth preset condition, whether there is a rainwater pipe access can be determined by judging whether the third water quality index measurement result at the measurement point (such as a manhole) upstream of the terminal unit satisfies a ninth preset condition. When the third water quality index measurement result satisfies the ninth preset condition, it can be considered that there is a rainwater pipe access, and at this time, it can be determined that the drainage pipe network has a rain and sewage mixing problem.

[0116] The third water quality index measurement result of the measurement point upstream of the terminal unit of the target pipe can include the measurement result of COD and / or ammonia nitrogen at the manhole upstream of the terminal. The ninth preset condition can be that the COD in the water quality index measurement result is less than a threshold value (such as COD<100 mg / L) and / or the ammonia nitrogen is less than a threshold value (such as ammonia nitrogen<5 mg / L).

[0117] In a case where the third water quality index measurement result at the end unit of the target pipeline does not satisfy the ninth preset condition, it can be considered that the sewage pipe network does not have the rain and sewage mixing problem.

[0118] In a case where the target pipeline has the full water condition, at this time, since the situation in the target pipeline cannot be directly observed, in the embodiment of the disclosure, the second method or the third method is selected according to whether the water in the target pipeline flows to detect the health problem.

[0119] In a case where the water level measurement result corresponding to the target pipeline satisfies the water level preset condition and the water quality index measurement result corresponding to the target pipeline satisfies the water quality preset condition, the second method is used to determine whether the drainage pipe network has a health problem.

[0120] In a case where the water level measurement result corresponding to the target pipeline satisfies the water level preset condition and the water quality index measurement result corresponding to the target pipeline satisfies the water quality preset condition, the second method is used to determine whether the drainage pipe network has a health problem.

[0121] This step S203 can include: according to the time series data of at least one water quality index corresponding to the monitoring point of the target pipeline, and the corresponding water level time series data and / or flow time series data, multi-dimensional data analysis is performed to determine whether the drainage pipe network has one of the initial rain pollution problem, the rain and sewage mixing problem, and the external water inflow and infiltration problem.

[0122] In a case where the target pipeline has the full water condition and the water in the target pipeline is in a non-flowing state, the second method can be used to determine whether the drainage pipe network has a health problem by measuring the time series data of water quality index, water level, flow, etc. It is more efficient. Compared with the existing method, different types of water quality and quantity data are not effectively coupled, resulting in one-sided monitoring results and insufficient accuracy, and the correlation between each data is not fully explored, making it difficult to accurately determine the root cause of the health problem. The embodiment of the disclosure can simultaneously collect and process multiple types of time series data for multi-dimensional data analysis by using the second method, thereby realizing effective coupling of different types of time series data to better understand the operation state of the pipeline system.

[0123] In the second method, whether the drainage pipe network has a health problem can also be determined according to different types of drainage pipe networks and / or environmental conditions. For example, according to whether the drainage pipe network is a rainwater pipe network, a sewage pipe network (or a combined pipe network), and whether there is a rainfall event at present, different types of time series data are used to detect the health problem, thereby making the detection result more accurate. The second method of the embodiment of the disclosure is introduced below according to different types of drainage pipe networks and / or environmental conditions.

[0124] In the process of determining whether the sewer network has a health problem by using the second method, the following can be performed:

[0125] In a case where the type of the sewer network is a rainwater pipe network and the rainfall in the area where the sewer network is located within a preset time length does not satisfy a preset rainfall threshold, the first water quality index time series data and the first water level time series data of the monitoring point in the target pipe are determined.

[0126] In a case where the first water level time series data satisfies the tenth preset condition and the first water quality index time series data satisfies the eleventh preset condition, it is determined that the sewer network has a rain sewage mixing problem; or

[0127] In a case where the first water level time series data satisfies the tenth preset condition and the first water quality index time series data does not satisfy the eleventh preset condition, it is determined that there is an external water inflow infiltration problem in the sewer network.

[0128] In a case where the type of the sewer network is a rainwater pipe network and the rainfall in the area where the sewer network is located within a preset time length satisfies a preset rainfall threshold, the second water quality index time series data of the monitoring point is determined.

[0129] In a case where the second water quality index time series data satisfies the thirteenth preset condition, it is determined that the sewer network has a first-rain pollution problem.

[0130] Therefore, in the case of a non-rainfall event and a rainfall event, the present scheme respectively realizes multi-dimensional data analysis based on various time series data for the target pipe in the rainwater pipe network which is full of water and in which water does not flow, and realizes accurate identification and classification of the health problem of the rainwater pipe network under different environmental conditions, thereby providing scientific and reliable technical support for real-time monitoring and abnormal early warning of the health status of the sewer network.

[0131] The rainfall in the area where the sewer network is located within a preset time length not satisfying a preset rainfall threshold is a non-rainfall event, and the rainfall in the area where the sewer network is located within a preset time length satisfying a preset rainfall threshold is a rainfall event.

[0132] The first water quality index time series data can be obtained by using a water quality monitoring device to collect monitoring values of the first water quality index. For example, the monitoring values of the water quality index can be collected by a water quality monitoring device comprising a spectrum sensor. The monitoring device comprising the spectrum sensor can realize online, in-situ, high-frequency, real-time collection of the monitoring values of the water quality index, for example, the collection frequency can be increased from 1 day / time to 3-60 minutes / time, preferably 5-30 minutes / time, particularly preferably 8-20 minutes / time, and most preferably 10-15 minutes / time, which is much higher than the traditional detection method of sampling water quality and then testing in a laboratory, so that water quality data can be obtained at a higher frequency to effectively capture the water quality characteristics of the sewer network.

[0133] The first water quality index time series data can include a plurality of COD concentration data monitored in a preset time period in time sequence at the monitoring point. The first water level time series data can include a plurality of water level data monitored in a preset time period in time sequence at the monitoring point. The monitoring point can be a position on the target pipeline where a water quality monitoring sensor device, a liquid level sensor, and a flow sensor are arranged based on the topological structure of the drainage pipe network. The tenth preset condition can include that the median of the water level in the first water level time series data exceeds a preset water level threshold. The eleventh preset condition can include that the median of the COD concentration in the first water quality index time series data exceeds a preset COD concentration threshold.

[0134] Since the rainwater pipe network should be waterless in the normal pipeline during non-rainfall time, in the case where the first water level time series data satisfies the tenth preset condition, it can be determined that the drainage pipe network has an abnormal problem. Further, in the case where the first water quality index time series data satisfies the eleventh preset condition, it is determined that the drainage pipe network has a rain and sewage mixing problem, which can indicate that there is a rain and sewage mixing problem upstream of the monitoring point in the rainwater pipe network. In the case where the first water level time series data satisfies the tenth preset condition and the first water quality index time series data does not satisfy the eleventh preset condition, it can be considered that the rainwater pipe network does not have a rain and sewage mixing problem but has an external water inflow and infiltration problem.

[0135] The second water quality index time series data can include time series data of two water quality indexes having a correlation relationship. The water quality indexes having a correlation relationship represent water quality indexes having a mutual complementary property and reflecting water quality characteristics from multiple angles in drainage pipe network monitoring.

[0136] In the field of water quality monitoring technology, no single water quality index can independently and comprehensively reflect the quality of the water body. Under normal circumstances, different water quality indexes can reflect the characteristics and pollution status of the water body from different angles and different levels. By combining, verifying, and complementing different water quality indexes, the quality of the water quality can be completely and accurately reflected. This characteristic between different water quality indexes is called mutual complementary property.

[0137] For example, the second water quality index time series data can include COD concentration and conductivity concentration monitored in a preset time period in time sequence at the monitoring point.

[0138] The thirteenth preset condition can include that the COD concentration in the second water quality index time sequence data increases and the conductivity concentration decreases. The determination manner of the COD concentration increasing can include: in the time sequence data corresponding to the COD concentration, the ratio of the difference between the COD concentration value at each subsequent time point and the COD concentration value at the previous time point and the COD concentration value at the previous time point (the ratio can also be regarded as the change rate of the COD concentration value) is greater than a preset positive threshold value, and then it is considered that the COD concentration increases; or, the COD concentration values in the time sequence data corresponding to the COD concentration are compared with the median of the time sequence data corresponding to the COD concentration, if the difference between the COD concentration value at any time point before the time point corresponding to the median and the median is less than a preset negative threshold value, and the difference between the COD concentration value at any time point after the time point corresponding to the median and the median is greater than a preset positive threshold value, then it is considered that the COD concentration increases.

[0139] The determination manner of the conductivity concentration decreasing can include: in the time sequence data corresponding to the conductivity concentration, the ratio of the difference between the conductivity concentration value at each subsequent time point and the conductivity concentration value at the previous time point and the conductivity concentration value at the previous time point is less than a preset negative threshold value, and then it is considered that the conductivity concentration decreases; or, the conductivity concentration values in the time sequence data corresponding to the conductivity concentration are compared with the median of the time sequence data corresponding to the conductivity concentration, if the difference between the conductivity concentration value at any time point before the time point corresponding to the median and the median is greater than a preset positive threshold value, and the difference between the conductivity concentration value at any time point after the time point corresponding to the median and the median is less than a preset negative threshold value, then it is considered that the conductivity concentration decreases.

[0140] It should be noted that the present embodiment is not limited to the above-mentioned determination manners of the COD concentration increasing and the conductivity concentration decreasing, and other determination manners can also be used in addition to the examples given in the present embodiment.

[0141] In the case where the second water quality index time sequence data satisfies the thirteenth preset condition, it is determined that the drainage pipe network has a primary rain pollution problem, which can mean that it is determined that the upstream of the monitoring point in the rainwater pipe network has a primary rain pollution problem.

[0142] In the case where the second water quality index time sequence data does not satisfy the thirteenth preset condition, it can be considered that the rainwater pipe network does not have a primary rain pollution problem.

[0143] In the process of determining whether the drainage pipe network has a health problem by using the second method, the following can be performed:

[0144] In a case where the type of the drainage pipe network is a sewage pipe network and rainfall in a region where the sewage pipe network is located within a preset time length satisfies a preset rainfall threshold, third water quality index time series data of the monitoring point in the target pipe are determined;

[0145] In a case where the third water quality index time series data satisfy a fourteenth preset condition, it is determined that the drainage pipe network has a rain and sewage mixing problem;

[0146] In a case where the type of the drainage pipe network is a sewage pipe network and rainfall in a region where the sewage pipe network is located within a preset time length does not satisfy a preset rainfall threshold, any one or more of fourth water quality index time series data, second water level time series data and first flow time series data of the monitoring point are determined;

[0147] In a case where any one or more of the fourth water quality index time series data, the second water level time series data and the first flow time series data satisfy a fifteenth preset condition, it is determined that the drainage pipe network has an external water inflow and infiltration problem.

[0148] Therefore, the present scheme realizes multi-dimensional data analysis based on various time series data for the target pipe full of water and not flowing in the sewage pipe network in the case of non-rainfall events and rainfall events, and realizes accurate identification and classification of health problems of the sewage pipe network in different environmental conditions, thereby significantly improving the accuracy and response speed of the health problem warning of the sewage pipe network, and providing scientific and reliable technical support for real-time monitoring and abnormal warning of the health state of the drainage pipe network.

[0149] In a case where the type of the drainage pipe network is a sewage pipe network and rainfall in a region where the sewage pipe network is located within a preset time length satisfies a preset rainfall threshold, third water quality index time series data of the monitoring point in the target pipe are determined;

[0150] It should be noted that the second method for determining whether the sewage pipe network has an external water inflow and infiltration problem can also be applicable to the combined pipe network.

[0151] The third water quality index time series data can include time series data of at least two water quality indexes having a correlation relationship, the water quality indexes having a correlation relationship representing water quality indexes having complementary properties in drainage pipe network monitoring and reflecting water quality characteristics from multiple angles;

[0152] For example, the third water quality index time series data can include any one or more of the COD concentration, the ammonia nitrogen concentration, the water temperature (i.e., the temperature water quality index), and the conductivity concentration monitored at the monitoring point within a preset time length. The monitoring point can be any position on the target pipeline at which a water quality monitoring sensor, a liquid level meter, and a thermometer are arranged. That is, the third water quality index includes at least two water quality indexes, one of which is conductivity, and on the basis of the conductivity, any one or more of the COD, the ammonia nitrogen, and the water temperature can be selected.

[0153] The fourteenth preset condition can include any one or more of a COD concentration decrease, a COD concentration first increase and then decrease, an ammonia nitrogen concentration decrease, a water temperature decrease, and a conductivity concentration decrease.

[0154] The determination manner of the COD concentration decrease can include: in the time series data corresponding to the COD concentration, the difference between the COD concentration value at each subsequent time point and the COD concentration value at the previous time point, and the ratio of the difference to the COD concentration value at the previous time point (the ratio can also be regarded as the change rate of the COD concentration value), are all less than a preset negative threshold value, and it is considered that the COD concentration decreases; or, the concentration values in the time series data corresponding to the COD concentration are compared with the median of the time series data corresponding to the COD concentration, if the difference between the COD concentration value at any time point before the time point corresponding to the median and the median is greater than a preset positive threshold value, and the difference between the COD concentration value at any time point after the time point corresponding to the median and the median is less than a preset negative threshold value, it is considered that the COD concentration decreases.

[0155] The determination manner of the COD concentration first increase and then decrease can include: in the time series data corresponding to the COD concentration, if there is a continuous time point interval, the difference between the COD concentration values at adjacent time points in the interval is greater than a preset positive threshold value, forming a COD concentration increase stage, and then there is another continuous time point interval, the difference between the COD concentration values at adjacent time points in the interval is less than a preset negative threshold value, forming a COD concentration decrease stage, it is considered that the COD concentration first increases and then decreases.

[0156] The determination manner of the conductivity concentration decrease can be the same as the determination manner of the conductivity concentration decrease in the thirteenth preset condition, and the determination manners of the water temperature decrease and the ammonia nitrogen concentration decrease can be implemented by referring to the manner of determining the conductivity concentration decrease.

[0157] It should be noted that the embodiments of the present disclosure are not limited to the above-mentioned determination manners of the COD concentration decrease, the COD concentration first increase and then decrease, the ammonia nitrogen concentration decrease, the water temperature decrease, and the conductivity concentration decrease, and other determination manners can also be used in addition to the examples given in the embodiments of the present disclosure.

[0158] In a case where the third water quality index time series data meets the fourteenth preset condition, it is determined that the rainwater and sewage are mixed in the drainage pipe network, which means that it is determined that the rainwater and sewage are mixed in the upstream of the monitoring point in the sewage pipe network.

[0159] In a case where the third water quality index time series data does not meet the fourteenth preset condition, it is considered that the rainwater and sewage are not mixed in the sewage pipe network.

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

[0161] The twelfth preset condition can include any one or more of a significant decrease in water temperature, a significant increase in water level, and a significant increase in water flow. The determination of a significant decrease in water temperature can be achieved by referring to the above-mentioned method of determining a decrease in water temperature, with the difference being that the negative threshold value set when determining a significant decrease in water temperature is smaller than the negative threshold value set when determining a decrease in water temperature, and the positive threshold value set when determining a significant decrease in water temperature is larger than the positive threshold value set when determining a decrease in water temperature.

[0162] The method of determining a significant increase in water level can include: in the time series data corresponding to the water level, comparing the water level values at each time point with a preset threshold value (which can be set to a relatively large water level value), and when the water level values within a continuous preset time period all exceed the preset threshold value, it is considered that the water level has increased significantly; or, when the ratio of the difference between the water level value at each subsequent time point and the water level value at the previous time point to the water level value at the previous time point (which can also be considered as the change rate of the water level value) in the time series data corresponding to the water level is greater than a preset positive threshold value (which can be set to a relatively large value), it is considered that the water level has increased significantly. The determination of a significant increase in water flow can be achieved by referring to the method of determining a significant increase in water level.

[0163] It should be noted that the present embodiment does not limit the above-mentioned methods of determining a significant decrease in water temperature, a significant increase in water level, and a significant increase in water flow, and other methods can also be used in addition to the examples given in the present embodiment.

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

[0165] In a case where the fourth water quality index time series data, the second water level time series data, and the first flow time series data all do not satisfy the fifteenth preset condition, it can be considered that the sewerage network does not have the inflow infiltration problem.

[0166] In the embodiments of the present disclosure, when it is determined that there is a health problem upstream of the monitoring point in the sewerage network, the upstream of the monitoring point can be further investigated by using the above method to determine the specific location of the health problem.

[0167] Step S204: In a case where the water level measurement result corresponding to the target pipe satisfies the water level preset condition and the water quality index measurement result corresponding to the target pipe does not satisfy the water quality preset condition, a third method is used to determine whether the sewerage network has a health problem.

[0168] The water level measurement result corresponding to the target pipe satisfying the water level preset condition can indicate that the target pipe has a full water condition, and the water quality index measurement result corresponding to the target pipe not satisfying the water quality preset condition can indicate that the water in the target pipe is in a flowing state.

[0169] This step S204 can include: determining the inflow infiltration proportion of each inflow source according to the water quality index time series data of each inflow source corresponding to the sewerage network, the water quality index time series data at the monitoring point of the target pipe, and a global optimization algorithm; and determining whether the sewerage network has an inflow infiltration problem according to the inflow infiltration proportion.

[0170] The inflow water quality and the outflow water quality of the sewerage network follow the mass balance principle, and most of the existing technologies use the chemical sampling method to sample water quality data. This method itself has errors. Since it is manual sampling, it is easy to cause non-synchronization of water quality concentration observations of multiple sampling points of the same inflow source, and thus errors in the monitoring values of the water quality indicators. Then, directly using the chemical mass balance model will reduce the accuracy of identifying the inflow infiltration unit. Therefore, we use water quality detection equipment to obtain water quality time series data in situ, online, and high frequency. However, even if the data is obtained in situ and high frequency, it is still impossible to completely avoid the spatial differences and non-synchronization of monitoring of each inflow source, which will cause errors in the monitoring values of the collected water quality indicators. Therefore, the chemical mass balance principle and the global optimization algorithm are combined, which can improve the accuracy of calculating the inflow infiltration proportion of each inflow source, and thus improve the accuracy of determining whether the sewerage network has an inflow infiltration problem.

[0171] According to the embodiments of the present disclosure, the diagnosis scheme of the health problem of the sewerage network can be flexibly decided and accurately selected according to specific application scenarios and different actual situations, so as to realize rapid, efficient, convenient, and accurate investigation of the health problem of the sewerage network, and improve the safety and reliability of the operation of the sewerage network.

[0172] The following introduces the process of determining whether the sewer network has a health problem by using the third method. First, the water quality indicators corresponding to different inflow sources can be selected and determined in order to subsequently determine the inflow infiltration ratios of the inflow sources. The method can include:

[0173] obtaining water quality characteristic data of different inflow sources; calculating the collinearity between different water quality indicators in the water quality characteristic data; determining water quality indicators corresponding to each inflow source based on the collinearity.

[0174] The inflow source can include water bodies before the access pipes of drainage users and / or external clean water bodies. The drainage users can be residential communities, commercial complexes, industrial enterprises, etc., and the water bodies before the access pipes of the drainage users can be different sewage water bodies, such as domestic sewage, municipal sewage, industrial sewage, etc. The external clean water bodies can include any one or more of groundwater, river water, lake water, and construction dewatering.

[0175] In the embodiments of the present disclosure, the water quality characteristic data of different inflow sources can be obtained by collecting data, online monitoring (for example, online water quality monitoring of the outlet wells before the municipal pipes of different types of drainage users are accessed, collecting water quality characteristic data of different sewage water bodies, or online water quality monitoring of different external clean water bodies, collecting water quality characteristic data of different external clean water bodies), etc., which is not limited in the embodiments of the present disclosure. The water quality characteristic data can include the above-mentioned water quality indicator values in the water body, for example, including water quality indicator values of any one or more of COD, conductivity, ammonia nitrogen, total phosphorus, total nitrogen, and hardness.

[0176] In the process of calculating the collinearity between different water quality indicators in the water quality characteristic data, the water quality characteristic data can be first divided according to the monitoring points of different inflow sources. The monitoring points can be the positions where water quality detection devices are arranged on the pipes. The water quality indicators can be any water quality indicators in the water quality characteristic data, for example, COD, ammonia nitrogen, etc.

[0177] The collinearity between different water quality indicators in the water quality characteristic data can be calculated based on related technologies (for example, by calculating the correlation matrix, etc.) for the monitoring points of each inflow source. The 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 marked as the same class (for example, ammonia nitrogen and total nitrogen in the water quality characteristic data of municipal sewage are marked as the same class of water quality indicators), forming multiple classes of water quality indicators corresponding to the monitoring points of each inflow source.

[0178] Therefore, the water quality indicators corresponding to different inflow sources can be selected by combining the monitoring points of different inflow sources and selecting the water quality indicators with the highest difference. For example, the monitoring point 1 corresponds to domestic sewage, and the corresponding water quality indicators include ammonia nitrogen, PH value, etc. The ammonia nitrogen with the highest difference can be selected as the water quality indicator corresponding to domestic sewage. The monitoring point 2 corresponds to groundwater, and the corresponding water quality indicators include hardness, PH value, etc. The hardness with the highest difference can be selected as the water quality indicator corresponding to groundwater.

[0179] The embodiments of the present disclosure can also determine the water quality indicators corresponding to different inflow sources by other related technologies other than the above, and the embodiments of the present disclosure are not limited.

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

[0181] obtaining the original water quality indicator time series data corresponding to the drainage pipe network; obtaining target water quality indicator time series data from the original water quality indicator time series data; determining the inflow infiltration ratios of different inflow sources corresponding to the drainage pipe network according to the target water quality indicator time series data and a global optimization algorithm; and determining whether the drainage pipe network has an inflow infiltration problem according to the inflow infiltration ratios.

[0182] Therefore, the inflow infiltration problem of the drainage pipe network can be accurately identified and quantified in the case of water flow in the target pipe.

[0183] The original water quality indicator time series data can be data collected by a water quality detection device within a preset time length. The water quality detection device can include a device for detecting water quality (such as a water quality detection sensor, etc.). The original water quality indicator time series data can include water quality indicator time series data of different inflow sources corresponding to the drainage pipe network, and time series data of water quality indicators at the monitoring points of the drainage pipe network (such as at the detection points of the end units 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 water amount of the drainage pipe network. For a sewage pipe network, when the inflow infiltration ratio of the external clean water body is not 0, it can be considered that the sewage pipe network has an external water inflow infiltration problem. For a rainwater pipe network, when the inflow infiltration ratio of the water body before the connection of each drainage pipe is not 0, it can be considered that the rainwater pipe network has an external water inflow infiltration problem.

[0185] In the embodiments of the present disclosure, the flow data at the monitoring points of the end units of the drainage pipe network can also be acquired, and when it is determined that there is an inflow infiltration problem in the drainage pipe network, the inflow infiltration water quantity corresponding to each inflow source can be obtained by multiplying the inflow infiltration proportion of each inflow source with the flow data.

[0186] In this way, qualitative analysis and quantitative analysis are combined, so that the detection of health problems is more accurate and reliable.

[0187] In order to ensure the accuracy of subsequent determination of the inflow infiltration proportion of each inflow source, the original water quality index time series data can be first subjected to real-time abnormal data elimination and time correction. In the process of processing the original water quality index time series data to obtain the target water quality index time series data, the following can be performed:

[0188] abnormal data in the original water quality index time series data are identified and removed, and normal data is supplemented to obtain denoised water quality index time series data; and the denoised water quality index time series data are aligned in the time dimension to obtain the target water quality index time series data.

[0189] In the process of identifying and removing abnormal data in the original water quality index time series data and supplementing normal data to obtain denoised water quality index time series data, the following can be performed:

[0190] abnormal data in the original water quality index time series data are identified and removed, and normal data is supplemented to obtain denoised water quality index time series data; and the denoised water quality index time series data are aligned in the time dimension to obtain the target water quality index time series data.

[0191] The normal data can be obtained by time series prediction, interpolation method or the like and then supplemented. When removing the data collected in the off-water state, it can be determined whether the water quality detection device is in the water body of the target pipeline to be detected, such as determining that the water quality detection device is not in the water body of the target pipeline to be detected, the data collected by the water quality detection device at this time can be regarded as the data collected in the off-water state (as air value) and removed.

[0192] The abnormal data in the non-off-water water quality index time series data can be caused by non-environmental factors, such as being caused by foreign matter shielding or being caused by monitoring optical window pollution. The abnormal data can include any one or more of abnormal noise data, jitter data, baseline offset data and abnormal jump data.

[0193] The abnormal noise data can represent data that is a sudden value at a moment in the non-off-line water quality index time series data. For example, the manner of identifying the abnormal noise data can be that if there is data at a time point in the non-off-line water quality index time series data that is greater than a preset threshold (which can be set to be relatively large), it is considered that the data corresponding to the time point is abnormal noise data.

[0194] The jitter data can represent a plurality of adjacent data in the non-off-line water quality index time series data that has an average relative difference greater than a preset threshold. For example, the manner of identifying the jitter data can be that if there are three adjacent time points in the non-off-line water quality index time series data that have data values with an average relative difference greater than a preset threshold (for example, 0.1), the data corresponding to the three adjacent time points can be considered as jitter data. The manner of calculating the average relative difference can be abs(y3-y1) / y2, where y1, y2, and y3 can refer to data of any three adjacent time points in the non-off-line water quality index time series data.

[0195] The baseline offset data can be caused by zero drift, temperature drift, etc., and can represent data that has a difference from a reference value that changes linearly over time in the non-off-line water quality index time series data. For example, the manner of identifying the baseline offset data can be that for non-off-line water quality index time series data at a time point, 90% quantile of data within a preset time length (for example, 24 hours) before the time point in the non-off-line water quality index time series data is recorded as x1, and 10% quantile of data within a preset time length (for example, 24 hours) after the time point in the non-off-line water quality index time series data is recorded as x2, if (x2-x1) / x1 is in a preset range (for example, 5%-50%), and the median slope (which can be determined based on related technologies) of data within the preset time length before the time point and data within the preset time length after the time point is greater than a preset threshold (for example, 0.01), the data within the preset time length before the time point, the data at the time point, and the data within the preset time length after the time point can be identified as baseline offset data.

[0196] The abnormal jump data can represent data that is a preset multiple of a reference value in the non-offstream water quality index time series data. For example, the manner of identifying the abnormal jump data can be that, for each time point of the non-offstream water quality index time series data, the median value of each hour is calculated, the rising ratio of the current time data to the median value of the past x hours is calculated, if the rising ratio exceeds a threshold value, and the data of a period of time after the adjacent time of the time point also satisfies the rising ratio threshold value compared with the median value of the X hours, it is considered that the jump condition is met, and the data of the time point and the period of time after the adjacent time thereof is determined as the abnormal jump data. It should be noted that the embodiments of the present disclosure do not limit the manner of identifying the abnormal data, and the abnormal data can also be identified by other manners in addition to the examples given in the embodiments of the present disclosure.

[0197] Since there can be missing data at one or more time points in the screened water quality index time series data obtained after removing the offstream data and the abnormal data, the missing data in the screened water quality index time series data can also be filled in by using related technologies in the embodiments of the present disclosure. For example, the missing data in the screened water quality index time series data can be filled in by using an AutoRegressive Integrated Moving Average (ARIMA) prediction model, a smoothing algorithm, an interpolation algorithm (such as taking the average of the data of the time points before and after the missing data to obtain the missing data value), etc., to obtain the denoised water quality index time series data.

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

[0199] In the process of aligning the denoised water quality index time series data in the time dimension to obtain the target water quality index time series data, the following can be performed:

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

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

[0202] The calculation method of the cross-correlation function value of the upstream water quality index time series data and the downstream water quality index time series data can be: wherein x can represent the upstream water quality index time series data, y can represent the downstream water quality index time series data, k can represent a data index, and m is the total amount of data. The above formula can be substituted into the formula to calculate the phase difference between the upstream and downstream monitoring points wherein wherein

[0203] Based on the phase difference between the upstream and downstream monitoring points, the time correction of the downstream water quality index time series data can be implemented based on related technologies, for example, the time difference between the upstream and downstream monitoring points can be calculated based on the phase difference between the upstream and downstream monitoring points (for example, the time difference is ), and the downstream water quality index time series data is time-corrected according to the time difference, thereby obtaining the target water quality index time series data.

[0204] In the process of determining the inflow infiltration ratio of each inflow source corresponding to the drainage pipe network according to the target water quality index time series data and the global optimization algorithm, the following can be performed:

[0205] According to the target water quality index time series data, the initial inflow infiltration ratio of each inflow source corresponding to the drainage pipe network is calculated.

[0206] wherein the chemical mass balance equation can be inputted according to the water quality index time series data of each inflow source in the target water quality index time series data and the time series data of the water quality index at the monitoring point of the drainage pipe network, and the equations are solved simultaneously to calculate the initial inflow infiltration ratio of each inflow source corresponding to the drainage pipe network. The chemical mass balance equation can be represented as: For multiple water quality indexes (i.e., multiple inflow sources), the above equation set can be established and solved simultaneously. Wherein n can represent the number of inflow sources, j is the identification of each inflow source, i is the type identification of the water quality index, can represent the time series data of the water quality index i corresponding to the inflow source j, can represent the time series data of the water quality index i at the monitoring point of the drainage pipe network, ​​​​The initial inflow infiltration ratio of the inflow source j can be represented.

[0207] In response to the initial inflow infiltration ratio of each inflow source satisfying a sixteenth preset condition, the initial inflow infiltration ratio can be taken as the inflow infiltration ratio of each inflow source. The sixteenth preset condition can include that the sum of the initial inflow infiltration ratios of each inflow source is 1, for example, if the initial inflow infiltration ratio of each inflow source satisfies the formula , it can be considered that the sum of the initial inflow infiltration ratios of each inflow source is 1.

[0208] In response to the initial inflow infiltration ratio of each inflow source not satisfying the sixteenth preset condition, the global optimization algorithm is used to optimize the target water quality index time series data to obtain the optimized water quality index time series data.

[0209] The global optimization algorithm is more objective and stable than the Monte Carlo method used in the prior art, and the global optimization algorithm that can be used includes but is not limited to one of a differential evolution algorithm, a genetic algorithm, a simulated annealing algorithm, a gradient descent algorithm, and a particle swarm optimization algorithm, and the differential evolution algorithm is preferably used. The outstanding performance of the method comes from the effective use of the parent individuals. Through the difference between the 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 has more pertinence and stability when solving problems, thereby showing significant advantages in continuous optimization.

[0210] The differential evolution algorithm can be implemented based on related technologies. The algorithm iteratively evolves based on individuals in the population, and finds the global optimal solution through optimization processing. Compared with other optimization methods, the differential evolution algorithm has the advantages of fewer input parameters, faster convergence, and good robustness. The optimization processing can include mutation operation, crossover operation, and selection operation.

[0211] First, the above-mentioned and can be used as the initial population (each individual in the population (i.e., each and ) can represent a candidate solution in the problem space), and the scaling factor F and the crossover probability CR are set to preset values (for example, F is set to 0.5 and CR is set to 0.2), and the above-mentioned optimization processing process is iteratively executed until a preset convergence threshold (for example, 10 -2 ) is met or the maximum number of iterations (for example, 200 times) is reached, to obtain the optimized and as the optimized water quality index time series data.

[0212] In the process of optimization, mutation operation can be performed on each individual in the initialized population, which can include: selecting 4 individuals from the parent individuals (corresponding to the above and ) to perform 2 vector differences to generate difference vectors. The current global optimal individual and the 2 difference vectors scaled by F are summed to generate a mutated individual. The calculation formula can be represented as:

[0213]

[0214] Wherein, represents the pth mutated individual obtained in the gth iteration; represents the current global optimal individual (i.e. the individual with the highest fitness value among the individuals) obtained in the gth iteration, represents the base vector; , represents the difference vector obtained by performing 2 vector differences on the 4 parent individuals. By calculating 2 difference vectors, the anti-disturbance, randomization ability and global search ability in the optimization process can be better.

[0215] Optionally, F can also be adjusted in the optimization process, so that the value of F decreases linearly or non-linearly with the number of iterations. One way to adjust the value of F can be seen from the following formula: F = (F max -F min ) × (G-g) / G + F min . Wherein, g is the current evolution generation, G is the maximum number of iterations, F max and F min are the maximum and minimum values of F preset.

[0216] Through the above formula, F can take a larger value in the early stage of optimization iteration, which is beneficial to expand the search space and maintain the diversity of the population; and in the case of convergence in the later stage of optimization iteration, F takes a smaller value, which is beneficial to search around the best region, thereby improving the convergence rate and search accuracy.

[0217] Then, the parent individuals and the corresponding mutated individuals can be subjected to crossover operation to generate new offspring individuals. The process of crossover operation can be represented as:

[0218]

[0219] Wherein, rand can represent a random number between 0 and 1, the random process can satisfy uniform distribution, CR is the above-mentioned crossover probability, which can represent the probability that a certain gene in the new offspring individual comes from the mutated individual . In order to ensure at least one gene is from so q rand may be an integer randomly generated between 1 and D, D may represent the individual gene dimension (i.e. vector dimension, the maximum value of q), so that the qth gene must be from V.

[0220] Figure 3 A schematic diagram showing the crossover operation according to an embodiment of the present disclosure. As Figure 3 shown, for the qth gene (e.g. individual gene dimension is 10 in the figure) in , when or , the based on the replacement can be replaced by the mutated individual (i.e. black solid block in the figure), otherwise, the parent individual (i.e. hollow block in the figure) is retained.

[0221] Optionally, the above CR can also be adjusted during the optimization process, so that the value of CR increases linearly or non-linearly with the number of iterations. One way to adjust the value of CR can be seen from the following formula: CR = CR min +(CR max -CR min )×g / G. Wherein, CR max and CR min are the maximum and minimum values of the preset CR. By making CR increase with the number of iterations, the optimization process of the present embodiment can maintain the diversity of the population in the early iterations, and have a larger convergence rate in the later iterations.

[0222] Finally, a selection operation can be performed between the parent individual and the above offspring individual, wherein the selection can be performed according to the fitness value of the parent individual and the fitness value of the offspring individual, when the fitness value of the offspring individual is greater than the fitness value of the parent individual, then the offspring individual is used to replace the parent individual as the new parent individual in the next iteration, otherwise, the current parent individual can be included in the next iteration. The process can be represented as:

[0223]

[0224] Wherein, may represent the parent individual in the gth iteration, may represent the offspring individual obtained by the above mutation operation and crossover operation, may represent the parent individual obtained by selection for the next iteration. and may represent the fitness values of and , respectively. The fitness value can be calculated based on the related art.

[0225] Through the above iterative optimization process, the optimized water quality index time series data can be obtained. The optimized water quality index time series data can be used as new target water quality index time series data, and the above steps of calculating the initial inflow infiltration ratio of each inflow source corresponding to the drainage pipe network according to the target water quality index time series data and the subsequent steps can be iteratively performed until the initial inflow infiltration ratio of each inflow source meets the sixteenth preset condition, and the calculated initial inflow infiltration ratio is used as the inflow infiltration ratio of each inflow source. In the embodiment of the present disclosure, the health problem can be alarmed when the health problem exists. Thus, the abnormal situation of the pipeline can be found in time, the relevant personnel can be reminded to check and maintain, the environmental pollution, poor drainage and other problems caused by pipeline damage or functional failure can be avoided, and the operation safety and reliability of the drainage pipe network can be improved.

[0226] Figure 4 A structural diagram of a health detection device of a drainage pipe network according to an embodiment of the present disclosure is shown. As shown in the figure, the device includes: Figure 4

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

[0228] The first determination module 402 is configured to determine whether the drainage pipe network has a health problem by using a first method when the water level measurement result corresponding to the target pipe does not meet the water level preset condition.

[0229] The second determination module 403 is configured to determine whether the drainage pipe network has a health problem by using a second method when the water level measurement result corresponding to the target pipe meets the water level preset condition and the water quality index measurement result corresponding to the target pipe meets the water quality preset condition.

[0230] The third determination module 404 is configured to determine whether the drainage pipe network has a health problem by using a third method when the water level measurement result corresponding to the target pipe meets the water level preset condition and the water quality index measurement result corresponding to the target pipe does not meet the water quality preset condition.

[0231] The third method for determining whether the drainage pipe network has a health problem includes: determining the inflow infiltration ratio of each inflow source according to the water quality index time series data of each inflow source corresponding to the drainage pipe network, the water quality index time series data of the monitoring point of the target pipe and a global optimization algorithm; and determining whether the drainage pipe network has an inflow infiltration problem according to the inflow infiltration ratio.

[0232] ​According to the embodiments of the present disclosure, the diagnosis scheme of the health problem of the drainage pipe network can be flexibly decided and accurately selected according to specific application scenarios and different actual conditions, so that the health problem of the drainage pipe network can be quickly, efficiently, conveniently and accurately investigated, and the safety and reliability of the operation of the drainage pipe network are improved.

[0233] The flow diagrams and the block diagrams in the drawings are presented to 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 the flow diagrams and the block diagrams can represent a module, a segment, or a portion of code, which comprises one or more executable instructions for implementing the specified logical functions. In some alternative implementations, the functions noted in the blocks can occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently or in the reverse order, depending on the functionality involved. It will also be noted that each block of the block diagrams and / or flow diagrams, and combinations of blocks in the block diagrams and / or flow diagrams, can be implemented by dedicated hardware-based systems that carry out the specified functions or acts, or combinations of hardware and software.

[0234] The embodiments of the present disclosure have been described above, the above description is exemplary, not exhaustive, and is not limited to the disclosed embodiments. Many modifications and changes are obvious to those skilled in the art without departing from the scope and spirit of the described embodiments. The selection of the terms used herein is intended to best explain the principles, practical application or technical improvement in the market of the embodiments, or to enable other ordinary 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 method of determining whether the drainage network has health problems using the third method 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 the drainage network has inflow and infiltration problems based on the inflow and infiltration ratio.

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 mixed rainwater and sewage 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: When the drainage network is a rainwater 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 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 are determined. 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 sewage 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 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 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 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-infiltration ratio, it is determined whether there is an inflow-infiltration problem in the drainage network.

8. The method according to claim 7, characterized in that, 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.

9. The method according to claim 7, 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.

10. 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 preset water level conditions but the water quality index measurement result corresponding to the target pipeline does not meet the preset water quality conditions, using a third method. The method of determining whether the drainage network has health problems using the third method 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 at the monitoring points of the target pipeline, and a global optimization algorithm; and determining whether the drainage network has inflow and infiltration problems based on the inflow and infiltration ratio.

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