Sewage system deposition problem evaluation method and device, medium and program product

Abstract

The invention relates to the technical field of sewage treatment, and discloses a sewage system deposition problem evaluation method and device, a medium and a program product, and the method comprises the steps: constructing a target sewage system model capable of coupling a sediment movement process through integrating a sewage discharge rule, a real-time multi-source data set, a historical data set and a preset organic matter proportion parameter; the method breaks through the limitation that a traditional evaluation method only depends on single data or a simplified model, and achieves the comprehensive, dynamic and accurate evaluation of the deposition problem of the sewage system. Historical data and real-time data are combined, so that the model has historical experience support and can reflect the current system state, the introduction of preset organic matter proportion parameters considers the influence of organic matters in sewage on deposition, the model is more suitable for the actual situation, the reliability and accuracy of an evaluation result are greatly improved, and the method is suitable for popularization and application. And a scientific basis is provided for prevention and treatment of the deposition problem of a sewage system.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of sewage treatment, and particularly relates to a sewage system deposition problem evaluation method and device, a medium and a program product. BACKGROUND

[0002] In the operation and management process of a sewage system, deposition problem has been one of the key factors affecting the normal function of the system. The accumulation of sediments not only causes the decrease of pipe flow capacity and drainage efficiency, but also may cause a series of problems such as pipe blockage and water quality deterioration, bringing great challenges to the maintenance and operation of the sewage system. At present, the existing sewage system deposition problem evaluation method has many limitations. The traditional method of deposition rate calculation is relatively rough, ignoring the properties of the sediments themselves (such as particle size and organic matter proportion), resulting in inaccurate deposition rate calculation. Further, it often relies only on single historical data or experience judgment, which is difficult to comprehensively, dynamically and accurately evaluate the deposition problem of the sewage system, and cannot provide scientific and effective basis for the maintenance and management of the system, and is difficult to meet the needs of actual sewage system management. SUMMARY

[0003] Therefore, the present application provides a sewage system deposition problem evaluation method, device, medium and program product to solve the problem that the traditional method is difficult to comprehensively, dynamically and accurately evaluate the deposition problem of the sewage system, and cannot provide scientific and effective basis for the maintenance and management of the system, and is difficult to meet the needs of actual sewage system management.

[0004] In a first aspect, the present application provides a sewage system deposition problem evaluation method, which comprises: obtaining a sewage discharge rule and a historical data set of the sewage system, the historical data set representing a collection of historical basic data of all pipes in the sewage system; obtaining a real-time multi-source data set of the sewage system according to the sewage discharge rule; coupling the deposition process of the sewage system according to the real-time multi-source data set, the historical data set and a preset organic matter proportion parameter, and constructing a target sewage system model; and evaluating the deposition problem of the sewage system by using the target sewage system model to obtain an evaluation result.

[0005] The wastewater system sedimentation assessment method provided by this invention, by acquiring wastewater discharge patterns, can reflect the discharge characteristics and trends of wastewater within the system. Furthermore, based on known wastewater discharge patterns, key real-time data relevant to the current system operation can be selected, avoiding interference from irrelevant data and making the acquired data more targeted and effective, thus reflecting the current operating status of the wastewater system more promptly. Furthermore, by combining historical and real-time data and introducing preset organic matter ratio parameters to construct a target wastewater system model, the significant impact of organic matter in wastewater on sediment formation and movement can be considered, improving the accuracy of sedimentation rate calculation. Simultaneously, by coupling the sediment movement process, the model can realistically simulate the dynamic processes of sediment generation, transport, and deposition in the wastewater system, thereby ensuring that the constructed target wastewater system model possesses high accuracy and realistic characteristics. Finally, using the target wastewater system model to assess the sedimentation problem in the wastewater system can comprehensively consider the historical state of the wastewater system, real-time operation, and the impact of organic matter on sediments. It can also accurately simulate the sediment movement process, making the assessment results more comprehensive, accurate, and reliable. It can also clearly reflect the severity, distribution, and possible development trend of sedimentation problems in the wastewater system, providing a scientific and effective decision-making basis for the maintenance of the wastewater system, the formulation of dredging plans, and the design of renovation schemes. This helps to take timely measures to solve sedimentation problems and ensure the normal operation of the wastewater system.

[0006] In one optional implementation, obtaining the wastewater discharge pattern of the wastewater system includes: Obtain historical multi-source datasets of the wastewater system; process the historical multi-source datasets to obtain wastewater discharge coefficients and pipe network topology; determine the wastewater discharge patterns of the wastewater system based on the wastewater discharge coefficients and pipe network topology.

[0007] The wastewater system sedimentation problem assessment method provided by this invention obtains wastewater discharge coefficients and pipe network topology by processing historical multi-source datasets, and then determines the discharge pattern, making the determined wastewater discharge pattern more consistent with the actual wastewater flow, thus ensuring the scientific nature and accuracy of the wastewater discharge pattern.

[0008] In one optional implementation, the sediment movement process of the wastewater system is coupled and a target wastewater system model is constructed based on real-time multi-source datasets, historical datasets, and preset organic matter ratio parameters, including: An initial wastewater system model is constructed based on real-time multi-source datasets. Based on historical datasets, preset organic matter ratio parameters, and the initial wastewater system model, the sediment movement process of the wastewater system is simulated to obtain sediment thickness variations. The initial wastewater system model is adjusted using sediment thickness variations as boundary conditions to obtain the target wastewater system model.

[0009] The sewage system deposition problem evaluation method provided by the present application can reflect the current state of the system in real time by constructing an initial sewage system model based on real-time multi-source data sets. Further, the generation, migration and deposition rules of the sediment under different conditions can be accurately restored by combining the historical data set, the preset organic matter proportion parameter and the initial sewage system model and simulating the sediment movement process, so that the obtained sediment thickness change can truly reflect the dynamic evolution of the sediment over time. Further, the sediment thickness change is a direct manifestation of the sediment movement process, and by taking it as a boundary condition, the initial model can fully consider the actual impact of the sediment on the sewage flow, the pipe network flow capacity and the like when simulating. By adjusting, the initial model is modified into a target model that is more in line with the actual deposition status of the sewage system, solving the problem of theoretical deviation that may exist in the initial model, and the adjusted target model can more accurately reflect the interaction between the sewage and the sediment in the sewage system, greatly improving the reliability and pertinence of the model in evaluating the deposition problem.

[0010] In an optional embodiment, the initial sewage system model is constructed based on the real-time multi-source data set, comprising: A first sewage system model is constructed based on the real-time multi-source data set; a sewage TSS model is constructed based on the first sewage system model, to obtain a first sewage TSS concentration value of the sewage TSS model; and the first sewage system model is adjusted based on the first sewage TSS concentration value and a sewage monitoring TSS concentration value of the sewage system, to obtain the initial sewage system model.

[0011] The sewage system deposition problem evaluation method provided by the present application can preliminarily reflect the overall operation state of the current sewage system by constructing a first sewage system model based on real-time multi-source data sets. Further, the overall operation state of the sewage system can be associated with the key water quality indicators by constructing a sewage TSS model based on the first sewage system model and obtaining a first sewage TSS concentration value, focusing on the core factors affecting the deposition problem and providing specific and quantifiable reference data for the verification of the model, and further providing a more specific index for the evaluation of the model. Further, by comparing the first sewage TSS concentration value calculated by the model with the actual monitoring value, the deviation of the first sewage system model from the actual situation can be directly found and adjusted, ensuring the accuracy of the initial sewage system model in reflecting the suspended solid condition in the sewage.

[0012] In an optional embodiment, the sediment movement process of the sewage system is simulated based on the historical data set, the preset organic matter proportion parameter and the initial sewage system model, to obtain the sediment thickness change, comprising: analyzing the historical data set and determining a problem pipeline in which a deposition problem has occurred in the sewage system; obtaining pipeline data and deposit data of the problem pipeline; establishing a deposit movement control equation and a plurality of deposit transport capacity equations according to the pipeline data, the deposit data and an organic matter proportion parameter; obtaining a second sewage TSS concentration value according to an initial sewage system model; calculating a plurality of third sewage TSS concentration values according to the deposit movement control equation and the plurality of deposit transport capacity equations; and calculating a deposit thickness change according to the pipeline data, the second sewage TSS concentration value and the plurality of third sewage TSS concentration values.

[0013] The sewage system deposition problem evaluation method provided by the application can determine a problem pipeline in which a deposition problem has occurred in the sewage system by analyzing the historical data set, and then establish a deposit movement control equation and a transport capacity equation by using the actual data of the problem pipeline, so that the equations are more targeted and practical. Furthermore, the relationship between the deposit movement and the TSS concentration change can be accurately reflected by combining the second sewage TSS concentration value obtained by the initial model with the third concentration value calculated by the equation, and the calculated deposit thickness change is closer to the actual situation, which provides accurate boundary conditions for the adjustment of the target sewage system model and enhances the model's simulation ability for the deposition process.

[0014] In an optional implementation, the deposit movement control equation and the deposit transport capacity equation are established according to the pipeline data, the deposit data and the organic matter proportion parameter, and the method comprises: The deposit movement control equation is established according to the pipeline data and the deposit data; the deposits of the sewage system are divided according to different particle sizes according to the deposit data, to obtain a plurality of deposit intermediate particle sizes; and the plurality of deposit transport capacity equations are established according to the deposit data, the organic matter proportion parameter and the plurality of deposit intermediate particle sizes.

[0015] The sewage system deposition problem evaluation method provided by the application establishes a control equation according to the pipeline data and the deposit data, divides the deposits according to particle sizes and establishes a plurality of transport capacity equations in combination with the organic matter proportion parameter, considers the influence of the differences in the particle sizes of the deposits on the transport process, and then enables the plurality of transport capacity equations to more accurately describe the transport conditions of various deposits. Meanwhile, the organic matter proportion parameter is introduced, which further improves the description of the deposit movement by the equations, makes the applicability of the equations stronger, and makes the calculation results more accurate, thereby providing strong support for the accurate calculation of the deposit thickness change.

[0016] In an optional implementation, the deposit thickness change is calculated according to the pipeline data, the second sewage TSS concentration value and the plurality of third sewage TSS concentration values, and the method comprises: According to the pipe data, the pipe flow change value of the sewage system per unit time is calculated; according to the second sewage TSS concentration value and the plurality of third sewage TSS concentration values, a plurality of sewage TSS concentration difference values are calculated; according to the plurality of sewage TSS concentration difference values and the pipe flow change value per unit time, the sediment mass change is determined; and according to the sediment mass change, the sediment thickness change is calculated.

[0017] The sewage system sediment problem evaluation method provided by the present application can more accurately reflect the flow dynamics of sewage in the pipe by calculating the pipe flow change value per unit time through pipe data. Further, by calculating the sewage TSS concentration difference value, the difference between model simulation and equation calculation can be quantified. Further, by combining the sewage TSS concentration difference and the pipe flow change value, the physical law of sediment movement is followed, so that the determined sediment mass change is more in line with the actual situation. Further, by combining the sediment mass change to calculate the sediment thickness change, the abstract mass change can be converted into intuitive thickness change, which provides accurate boundary conditions for the target sewage system model, ensures that the model can accurately simulate the actual accumulation or reduction of sediment, thereby improving the accuracy of the sediment problem evaluation.

[0018] In a second aspect, the present application provides a sewage system sediment problem evaluation device, which comprises: A first acquisition module is configured to acquire sewage discharge rules and a historical data set of a sewage system, and the historical data set represents a collection of historical basic data of all pipes in the sewage system; a second acquisition module is configured to acquire a real-time multi-source data set of the sewage system according to the sewage discharge rules; a construction module is configured to couple the sediment movement process of the sewage system and construct a target sewage system model according to the real-time multi-source data set, the historical data set and a preset organic matter proportion parameter; and an evaluation module is configured to evaluate the sediment problem of the sewage system by using the target sewage system model to obtain an evaluation result.

[0019] In a third aspect, the present application provides a computer readable storage medium, which stores computer instructions for causing a computer to execute the sewage system sediment problem evaluation method of the first aspect or any of the corresponding embodiments thereof.

[0020] In a fourth aspect, the present application provides a computer program product comprising computer instructions for causing a computer to execute the sewage system sediment problem evaluation method of the first aspect or any of the corresponding embodiments thereof. BRIEF DESCRIPTION OF DRAWINGS

[0021] In order to more clearly illustrate the technical solutions in the specific embodiments of the present application or the prior art, the drawings required to be used in the specific embodiments or prior art description will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present application, and other drawings can also be obtained by those skilled in the art without creative labor on the basis of these drawings.

[0022] Figure 1 is a flowchart of a sewage system sedimentation problem evaluation method according to an embodiment of the present application; Figure 2 is a flowchart of another sewage system sedimentation problem evaluation method according to an embodiment of the present application; Figure 3 is a structural block diagram of a sewage system sedimentation problem evaluation device according to an embodiment of the present application; Figure 4 is a hardware structure schematic diagram of a computer device according to an embodiment of the present application. DETAILED DESCRIPTION

[0023] In order to make the purpose, technical solutions and advantages of the embodiments of the present application clearer, the technical solutions in the embodiments of the present application will be described clearly and completely below with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are some of the embodiments of the present application, not all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative labor are within the scope of protection of the present application.

[0024] The embodiments of the present application provide a sewage system sedimentation problem evaluation method, which integrates sewage discharge rules, real-time multi-source data sets, historical data sets and preset organic matter proportion parameters to construct a target sewage system model capable of coupling the sediment movement process, so as to achieve the effect of comprehensively, dynamically and accurately evaluating the sedimentation problem of the sewage system.

[0025] According to the embodiments of the present application, a sewage system sedimentation problem evaluation method is provided. It should be noted that the steps shown in the flowchart of the drawings can be executed in a computer system such as a group of computer executable instructions, and although the logical order is shown in the flowchart, in some cases, the steps shown or described can be executed in an order different from that shown here.

[0026] In the present embodiment, a sewage system sedimentation problem evaluation method is provided, which can be used in electronic devices such as computers, mobile phones, tablet computers, etc. Figure 1 is a flowchart of a sewage system sedimentation problem evaluation method according to an embodiment of the present application, as shown in Figure 1 The flowchart includes the following steps: Step S101, obtain the sewage discharge rule and the historical data set of the sewage system.

[0027] The sewage discharge rule represents the characteristics and patterns of periodicity, trend and correlation of the sewage discharge behavior of the sewage system during operation, which is a comprehensive dynamic rule containing time characteristics, flow allocation and correlation with related factors: (1) The change rule containing the time dimension. By analyzing the sewage discharge data of different periods such as hours, days, weeks and months, the sewage discharge curve is formed, which can reflect the sewage discharge characteristics of different time periods such as "morning, noon and evening peak", difference between weekdays and weekends, seasonal change, etc. For example, the hourly sewage flow is calculated by combining the sewage discharge coefficient with the dynamic population data, and then the discharge curve reflecting the time period characteristics is drawn.

[0028] (1) The flow allocation rule related to the spatial dimension. Combined with the pipe network topology, the sewage discharge of each node is allocated according to the connection relationship of the pipe network (such as main pipe, branch pipe, diversion node, etc.), and the flow path of sewage in the pipe network and the flow allocation of each section of pipe are determined.

[0029] (3) The coordinated change of the associated sewage quality parameters, which is accompanied by the sewage discharge and discharge time, reflects the change rule of the water quality parameters such as SS concentration in sewage, such as the significant fluctuation of organic matter concentration at a certain discharge peak period.

[0030] Further, the historical data set represents a collection of all historical basic data of each pipe in the sewage system. The historical basic data can include historical flow rate of the pipe and monitored sewage TSS historical concentration.

[0031] Further, the historical data set can also include pipe design parameters, flow data, water quality data, etc.

[0032] Step S102, obtain the real-time multi-source data set of the sewage system according to the sewage discharge rule.

[0033] Specifically, based on the determined sewage discharge rule (including daily / weekly / monthly discharge time rule, pipe network flow allocation rule, etc.), real-time operation data of the sewage system can be collected.

[0034] In some optional embodiments, first, the time nodes and frequency of real-time data collection can be determined according to the time rule of discharge amount in the sewage discharge rule, to ensure the capture of discharge characteristics at different time periods.

[0035] Secondly, in combination with the topological law of the discharge path, monitoring equipment can be deployed at important positions such as the main pipe, key shunt nodes, and pipelines where historical sediment problems frequently occur, covering the main flow path of sewage and ensuring that the data can reflect the real-time state of the core area of the pipe network.

[0036] Then, multiple types of real-time data can be collected: (1) Real-time flow and pressure data: The instantaneous flow and pressure of each key node can be collected through the flow meter and pressure sensor built into the pipeline, reflecting the real-time flow dynamics of sewage in the pipe network and matching the flow distribution characteristics in the discharge law.

[0037] (2) Real-time water quality data: Real-time SS concentration, BOD, and other water quality parameters can be collected through online monitoring equipment, focusing on indicators related to sediment formation (such as SS concentration) and combining the coordinated change characteristics of water quality over time (such as fluctuations in organic matter concentration during peak periods) in the discharge law.

[0038] (3) Real-time population and environmental data: Real-time population heat data (reflecting the flow state of the population in the region) and synchronous collection of rainfall and other environmental data (for combined sewer systems) are used to associate dynamic influencing factors related to social and economic activities and natural conditions in the sewage discharge law.

[0039] Further, the collected real-time data of various types is preliminarily verified to eliminate invalid data (such as flow and concentration values that exceed the physical reasonable range) caused by equipment failure or interference.

[0040] Finally, real-time flow, water quality, population, and other data can be classified and integrated according to the framework of the sewage discharge law (such as time segmentation and pipe network path zoning), forming a multi-dimensional real-time multi-source data set covering "time-space-index". Step S103, according to the real-time multi-source data set, the historical data set, and the preset organic matter proportion parameter, the sediment movement process of the sewage system is coupled and a target sewage system model is constructed.

[0041] Among them, the preset organic matter proportion parameter represents the proportion parameter of organic matter (such as carbohydrates, proteins, etc.) in total suspended solids (TSS) or total pollutants in sewage, which is pre-set according to the sewage source (such as the proportion of domestic sewage and industrial wastewater) in the area where the sewage system is located, historical monitoring data or industry standards, and can quantify the contribution of organic matter to sediment formation.

[0042] Further, the sediment movement process of the sewage system represents the dynamic physical processes of settling, suspending, scouring, and transporting of suspended solids (including inorganic particles and organic debris) in sewage when flowing with water in the pipeline due to changes in water flow velocity, pipeline structure (such as bends and slopes), and gravity.

[0043] Specifically, based on real-time multi-source data sets (reflecting the real-time running state of the current sewage system, such as flow, water quality, pipe parameters, etc.), historical data sets (containing data of past sediment distribution, water flow law, etc., used for calibrating the model), and preset organic matter proportion parameters (clearly defining the influence weight of organic matter in the sediment), the interaction between sewage flow and sediment movement (such as the influence of water flow velocity on sediment scouring / settling, the reaction of sediment accumulation on water flow resistance) is coupled to construct a target sewage system model that can accurately simulate the actual running state of the sewage system and the dynamic changes of the sediment.

[0044] Step S104, using the target sewage system model, evaluating the sedimentation problem of the sewage system to obtain an evaluation result.

[0045] Specifically, according to the target sewage system model that couples the processes of sewage flow and sediment movement and integrates real-time multi-source data, historical data, and organic matter proportion parameters, through simulation, analysis, and calculation, the generation, distribution, accumulation degree, and potential impact of sediment in the sewage system can be systematically evaluated.

[0046] In some optional embodiments, the target sewage system model can reproduce the actual flow state of sewage in the pipe network and the dynamic change process of sediment with water flow, such as settling, suspending, scouring, and accumulating. By running the model, the following contents can be quantitatively analyzed: (1) the specific distribution position of the sediment in the pipe (such as which pipe section is prone to accumulation); (2) the thickness, accumulation amount, and formation speed of the sediment; (3) the influence of the sediment on the pipe flow capacity (such as whether it causes flow reduction or pressure anomaly); (4) the risk level of sediment-induced blockage, corrosion, or water quality deterioration, etc.

[0047] The sewage system deposition problem evaluation method provided by the embodiment can reflect the sewage discharge characteristics and change trend in the system by obtaining the sewage discharge rule. Further, based on the known sewage discharge rule, the key real-time data related to the current system operation can be screened out, avoiding the interference of irrelevant data, so that the obtained data is more targeted and effective, and the current operation state of the sewage system can be reflected more timely. Further, the historical data and real-time data are combined, and a preset organic matter proportion parameter is introduced to construct a target sewage system model, which can consider the important influence of organic matter in sewage on the formation and movement of sediments, and improve the accuracy of the deposition rate calculation. At the same time, by coupling the sediment movement process, the model can simulate the dynamic processes such as generation, transportation and deposition of sediments in the sewage system, so that the target sewage system model constructed has high accuracy and practicality. Finally, the target sewage system model is used to evaluate the deposition problem of the sewage system, which can comprehensively consider the historical state, real-time operation and influence of organic matter on sediments of the sewage system, and accurately simulate the sediment movement process, so that the evaluation result is more comprehensive, accurate and reliable, and the severity, distribution and possible development trend of the deposition problem in the sewage system can be clearly reflected, which provides a scientific and effective decision basis for the maintenance, dredging plan and transformation scheme of the sewage system, and helps to solve the deposition problem in time and ensure the normal operation of the sewage system.

[0048] In some optional embodiments, the sewage discharge rule in step S101 can be obtained by the following steps: Step a1, obtaining a historical multi-source data set of the sewage system.

[0049] Specifically, the historical multi-source data set represents the historical data set accumulated in the past operation process of the sewage system, covering multiple sources and types, which can include: (1) Historical population heat data: obtained through a map service platform, a third-party institution or a web crawler, covering different spatial position heat values at intervals of 1 hour for at least 6 months, used to reflect the correlation between historical population dynamic distribution and sewage discharge.

[0050] (2) Historical pipe network foundation data: pipe foundation information stored in shp format, which can include pipe ID, pipe diameter, slope, buried depth, material, inspection well position and height, and is the basis for constructing the pipe network topology structure.

[0051] (3) Historical monitoring data: key node data collected by online instruments, which can include flow, BOD, SS concentration, etc., recorded at intervals of 10 minutes for at least months, reflecting the historical sewage quality and quantity characteristics.

[0052] (4) Sediment history sampling data: sediment sample analysis data (such as particle size d50, organic matter ratio) obtained from typical pipelines, and historical sediment thickness change data (daily average of 3-5 times daily measurements for 1 month).

[0053] Step a2, processing the historical multi-source data set to obtain sewage discharge coefficients and pipe network topology.

[0054] Specifically, according to the historical population heat data, the population heat value can be converted into a dynamic population quantity, as shown in the following relationship (1): (1) In the formula: represents the dynamic population quantity at spatial position , time ; represents the population heat value at spatial position , time ; represents the total heat value in the region; represents the total population quantity in the region.

[0055] Among them, the total population quantity in the region is equal to the total heat value, and the spatio-temporal distribution of the heat value corresponds to the flow of the population.

[0056] Further, the dynamic population quantity is associated with the historical monitored sewage flow data, the population data with monitored data coverage points are summed up, the total sewage quantity can correspond to the population quantity, and the sewage discharge coefficient can be obtained by inverse calculation , as shown in the following relationship (2): (2) In the formula: represents the total sewage quantity of the control area in the first hour, which is the measured value obtained by monitoring; represents the total population quantity in the area at the corresponding time.

[0057] Further, if the difference between the calculated total sewage quantity and the daily measured total discharge quantity exceeds 5%, the sewage discharge coefficient is fine-tuned according to the daily total discharge quantity until the difference is within 5%.

[0058] Further, the historical pipe network basic data (shp format) is standardized and processed, and is adjusted in batches by GIS tools to meet the requirements of the format for modeling.

[0059] Furthermore, the processed pipeline network data is imported into StormDesk software, which automatically identifies the connection relationship between pipelines and manholes, constructs a preliminary topology, and exports it as an inp file suitable for SWMM models, thus completing the digital modeling of the pipeline network topology.

[0060] Step a3: Determine the sewage discharge pattern of the sewage system based on the sewage discharge coefficient and the pipe network topology.

[0061] Specifically, based on the obtained wastewater discharge coefficient, combined with dynamic population data from different spatial locations... Calculate the hourly sewage discharge of each node (node ​​sewage flow rate = × Node dynamic population), and plot the hourly sewage volume change curve (i.e. sewage discharge curve) to reflect the characteristics of the "morning, noon and evening peak" periods during the day.

[0062] Furthermore, the calculation of weekly and monthly variation coefficients can be promoted. Specifically, hourly wastewater discharge data can be summarized by weekly and monthly cycles to analyze the total discharge and peak variation patterns in different weeks (such as weekdays and weekends) and different months (such as seasonal differences), thereby correcting the wastewater discharge curve.

[0063] Furthermore, by combining the pipeline network topology, the sewage discharge volume of each node is allocated according to the pipeline network connection relationship (such as main pipe, branch pipe, and diversion node), clarifying the flow path of sewage in the pipeline network and the flow distribution characteristics of each pipeline segment, and finally forming a complete sewage discharge pattern covering "discharge time pattern (daily / weekly / monthly changes), flow distribution pattern (path and node water volume in the pipeline network), and water quality correlation pattern (SS concentration and other changes with the discharge time period)".

[0064] By processing historical multi-source datasets, wastewater discharge coefficients and pipe network topology are obtained, thereby determining the discharge patterns. This makes the determined wastewater discharge patterns more consistent with actual wastewater flow, ensuring the scientific validity and accuracy of the wastewater discharge patterns.

[0065] In some alternative implementations, such as Figure 2 As shown, step S103 above includes: Step S1031: Construct an initial wastewater system model based on the real-time multi-source dataset.

[0066] The initial wastewater system model is the SWMM (Storm Water Management Model), which represents a comprehensive model used to simulate urban stormwater floods, drainage systems, and water quality changes.

[0067] Specifically, an initial wastewater system model is constructed using real-time multi-source datasets, enabling the constructed initial model to reflect the current state of the system in real time.

[0068] In some optional embodiments, the step S1031 comprises: Step b1, constructing a first sewage system model according to the real-time multi-source data set.

[0069] Specifically, the network model of the sewage system can be constructed in SWMM according to the sewage system basic data (generally shape file).

[0070] Among them, the sewage system model can include multiple sewage pipe network areas, multiple sub-catchment areas, multiple nodes and pipe networks, multiple outlets, multiple storage spaces and control measure gates. Ensure that these elements are set according to the layout and properties of the actual sewage system.

[0071] Further, the sewage system model can adopt dynamic wave control equation.

[0072] Further, the study area is divided into sub-catchment areas by means of GIS software. The sub-catchment areas are determined at key node positions, and the division of the sub-catchment areas should be based on factors such as terrain, land use and drainage system. The information such as the area, width, slope and impervious area ratio of the sub-catchment areas can be extracted through Raster analysis function.

[0073] Further, the parameters of the SWMM model can be set according to the collected data and literature, such as rainfall parameters, runoff parameters, infiltration parameters, etc. At the same time, appropriate simulation period, time step, simulation control equation, etc. can be set according to the actual situation.

[0074] Specifically, in order to construct the mechanism model of the selected study area, considering the integrity of the data and the use requirements of subsequent evaluation, the SWMM skeleton model of the entire case area is constructed in this embodiment. The mechanism model construction process mainly includes the establishment of topological relationship, the determination of land attribute, the determination of control strategy, the simplification of pipe network structure and other links. For the establishment of topological relationship, according to the land status and planning data and the ground elevation map, the division of sewage land and sewage catchment area is determined, and the topological connection relationship of land, pipe section and control facility of the entire sewage system is sorted out in combination with the basic data of sewage pipe network section and control facility.

[0075] Further, parameter initialization is the key to the smooth operation of the model, especially the parameters with high sensitivity directly affect the accuracy and reliability of the model calculation results. Therefore, parameter initialization should have uniformity, comprehensiveness and scientificity. In this embodiment, the parameters selected include actual measurement parameters and empirical parameters, and the basis for parameter initialization mainly includes the following three aspects: 1) directly obtained measured data; 2) indirectly obtained drawing data (CAD drawings, elevation maps, land use planning maps, etc.); 3) empirical values in the SWMM user manual and values in related literature.

[0076] In step b2, a sewage TSS model is constructed according to the first sewage system model, and a first sewage TSS concentration value of the sewage TSS model is obtained.

[0077] Total Suspended Solids (TSS) represents the total amount of suspended solid particles in water, which can be inorganic (such as sand, clay, algae, bacteria, etc.) or organic (such as animal and plant debris, feces, humus, etc.). TSS is an important indicator of water quality, and high TSS content may affect water transparency, taste, color, and even adversely affect human health and aquatic ecosystems.

[0078] Further, the first sewage TSS concentration value is a sewage TSS simulation value.

[0079] Specifically, based on the first sewage system model, the TSS model is constructed, which is the key to sediment simulation. The TSS simulation process includes surface accumulation, erosion, pipe transportation, etc. The specific construction steps are as follows: First, select TSS as the simulated pollutant: In the SWMM model settings, specify TSS as one of the simulated pollutants. This usually involves specifying TSS-related properties in the model parameters or input files.

[0080] Second, set the initial concentration and growth parameters of TSS: In the model, the initial concentration and growth parameters of TSS have important influence on the simulation results. The initial concentration can be set based on actual observation data or related literature. The accumulation parameters may include maximum accumulation, rate constant, etc., which need to be adjusted according to the characteristics and data of the specific study area.

[0081] Specifically, the accumulation equation is an exponential function, as shown in the following relationship (3): (3) In the formula: represents the accumulation amount of pollutants; represents the maximum accumulation amount of pollutants; represents the accumulation rate constant; represents the cumulative time.

[0082] More specifically, selecting localized model parameters helps improve the accuracy and reliability of the model's results. To ensure the uniformity, comprehensiveness, and scientificity of relevant parameters, the land types involved in the catchment area are mainly divided into asphalt roads and green spaces according to the land properties of the study area and the investigation. According to the average concentration of each pollutant in the initial sewage monitoring session, the SWMM user manual, the environmental conditions around the monitoring point, and the relevant literature of similar studies, the surface pollutant accumulation and flushing parameters for different land use types are set.

[0083] Thirdly, defining the runoff and flushing process: SWMM model predicts the transport and distribution of TSS by simulating the runoff and flushing process. Therefore, it is necessary to define the runoff parameters (such as runoff coefficient, runoff path, etc.) and flushing process (such as flushing coefficient, flushing amount, etc.) to reflect the flushing and migration characteristics of TSS under different land use types and soil conditions.

[0084] Specifically, the flushing equation is an exponential function, as shown in the following relationship (4): (4) In the formula: represents the pollutant flushing amount; represents the flushing coefficient; represents the flushing index; represents the runoff per unit area.

[0085] In addition, the influence of land use and soil type needs to be considered: land use type and soil type have a significant impact on the generation and transport of TSS. In the SWMM model, it is necessary to assign corresponding TSS generation and transport parameters for each sub-catchment or land use type. This includes TSS generation rates under different land use types, infiltration and flushing characteristics under different soil types, etc.

[0086] Finally, run the SWMM model and analyze the results: after inputting all the necessary data and parameters, run the SWMM model for simulation. The model will simulate the runoff process and generate TSS simulation results, i.e. the first sewage TSS concentration value, according to the input sewage data and set parameters.

[0087] Step b3, according to the first sewage TSS concentration value and the sewage monitoring TSS concentration value of the sewage system, the first sewage system model is verified and adjusted to obtain the initial sewage system model.

[0088] Wherein, the sewage monitoring TSS concentration value is the measured value of the sewage TSS.

[0089] Specifically, the output results of the model, i.e., the first sewage TSS concentration values, are compared with the monitoring data to verify the accuracy and reliability of the model. If there is a large difference between the model results and the actual data, the model parameters or structure may need to be adjusted and re-run.

[0090] For example, the Nash efficiency coefficient (Nash Sutcliffe Efficiency Coefficient, NSE) is used as a model precision evaluation method. The calculation results show that the Nash efficiency coefficient is not less than 0.683, and it is generally considered that the model results are basically consistent with the monitoring values, and the model precision meets the requirements.

[0091] The specific calculation formula of the Nash efficiency coefficient is shown in the following relationship (5): (5) In the formula: Xi represents the i-th monitoring value; Xi represents the average value of the monitoring values; Xi represents the i-th model simulation value; Xi represents the number of monitoring data. In addition, the TSS model is compared according to the monitoring data, and the simulation results meet the requirements, and the TSS concentration can be used for subsequent sediment thickness prediction and calculation.

[0092] Step S1032, simulating the sediment movement process of the sewage system according to the historical data set, the preset organic matter proportion parameter and the initial sewage system model to obtain the sediment thickness change.

[0093] Specifically, the historical data set, the preset organic matter proportion parameter and the initial sewage system model are combined and the sediment movement process is simulated, which can accurately restore the generation, migration and deposition rules of the sediment under different conditions, and further make the obtained sediment thickness change can truly reflect the dynamic evolution of the sediment with time.

[0094] In some optional embodiments, the above step S1032 comprises: Step c1, analyzing the historical data set and determining the problem pipeline in which the sedimentation problem occurs in the sewage system.

[0095] Specifically, the historical data can be analyzed according to the preset conditions to obtain the problem pipeline in which the sedimentation problem occurs in the sewage system.

[0096]

[0097] ​​In some optional embodiments, first, whether the pipe diameter, the historical flow rate of the pipe and the historical concentration of the monitored TSS of each pipe meet the preset pipe flow rate threshold (0.6 m / s), the pipe diameter threshold (400 mm) and the monitored TSS concentration threshold (500 mg / L) are judged respectively.

[0098] Specifically, the pipes can be visually inspected using a pipe endoscope, CCTV or other non-destructive testing technology. The flow rate and flow data of the drainage system are analyzed to understand the movement state of the water flow in different pipe sections. The water quality is analyzed, and in particular, the TSS concentration is monitored.

[0099] Further, when the historical flow rate of the pipe is less than the pipe flow rate threshold 0.6 m / s; the pipe diameter is less than the pipe diameter threshold 400 mm; and the historical concentration of the monitored TSS is higher than the monitored TSS concentration threshold 500 mg / L, it indicates that sedimentation problems will occur inside the pipe.

[0100] Further, the pipes that meet at least one of the preset conditions are all determined as problem pipes. The plurality of preset conditions are respectively that the pipe diameter is less than the pipe diameter threshold, the historical flow rate of the pipe is less than the pipe flow rate threshold, and the historical concentration of the monitored TSS is less than the monitored TSS concentration threshold.

[0101] Further, the pipes that meet at least one of the preset conditions are all determined as problem pipes, which are selected as the key simulation objects to simulate the change of the sediment layer.

[0102] Based on the analysis of the historical data, the areas or pipe sections that may have sedimentation problems are identified through the preset conditions, which are selected as the key simulation objects to simulate the change of the sediment layer, thereby improving the simulation efficiency of the sediments in the sewage system.

[0103] In other optional embodiments, first, the core information related to sedimentation in the historical data set is extracted, including: (1) Pipe flow anomaly records in the historical monitoring data (such as a certain pipe flow being lower than the design value for a long time, a sudden drop in flow rate), pressure fluctuation data (such as abnormal increase in local pipe pressure); (2) Thickness change records in the historical sediment sampling data (such as a certain pipe sediment thickness daily average continuously increasing, exceeding the normal range), particle accumulation characteristics (such as an abnormal proportion of large-diameter particles); (3) Pipe properties in the pipe network basic historical data (such as pipes with smaller diameter and gentler slope are more prone to sedimentation), historical maintenance records (such as information of pipes that have been dredged).

[0104] Secondly, the quantitative judgment criteria for sedimentation problems can be set according to industry standards and historical operation and maintenance experience, for example: (1) The ratio of the thickness of the sediment to the diameter of the pipe exceeds 10%; (2) The actual flow of the pipeline is continuously less than 80% of the design flow, and other factors such as pipeline damage are excluded; (3) The deviation between the SS concentration monitoring value and the model simulation value in a certain period is significant (such as the difference exceeds 10%), which indicates that there may be abnormal adsorption or release of sediments.

[0105] Finally, the pipeline indicators in the historical data can be compared with the set threshold to screen out pipelines that meet the "sediment problem characteristics": (1) For each section of pipeline, associate its historical flow, pressure data and sediment thickness change data, if both "flow drop" and "sediment thickness exceeding standard" are met, mark it as a potential problem pipeline; (2) Combined with the topological structure of the pipeline network, analyze the upstream and downstream relationship of the potential problem pipeline (such as upstream sediment may cause downstream flow anomaly), and exclude non-sediment factors (such as pipeline blockage caused by foreign matter); (3) Finally determine the list of problem pipelines that have experienced sediment problems, and record the specific location (such as pipeline ID, inspection well number), historical sediment occurrence period and severity.

[0106] Step c2, obtaining pipeline data and sediment data of the problem pipeline.

[0107] Specifically, the basic data of the problem pipeline can be obtained through PySWMM and SWMM-API.

[0108] Among them, PySWMM is a secondary development module based on (Storm Water Management Model, SWMM) software, which is a Python language.

[0109] Further, SWMM-API (Storm Water Management Model Application Programming Interface) means a set of application programming interfaces provided for SWMM model, which allows users to access and operate the functions of SWMM in a programmed way, so as to optimize, customize and develop the model, and perform automation, etc.

[0110] Step c3, establishing sediment motion control equation and multiple sediment transport capacity equations according to pipeline data, sediment data and organic matter proportion parameters.

[0111] Specifically, the actual data of the problem pipeline is used to establish the sediment motion control equation and transport capacity equation, so that the equation is more targeted and practical.

[0112] In some optional embodiments, the above step c3 comprises: Step c31, establishing a sediment motion control equation according to the pipeline data and the sediment data.

[0113] Specifically, the sediment motion control equation is shown in the following relation (6): (6) In the formula: represents the wet density of the sediment; represents the sediment area in the vertical water flow direction; represents the pipeline flow area; represents the monitoring TSS concentration inside the pipeline; represents the pipeline flow rate; represents the pipeline length.

[0114] Step c32, dividing the sediment of the sewage system according to different particle sizes according to the sediment data, to obtain a plurality of sediment median particle sizes.

[0115] Among them, the sediment median particle size (Median Sediment Particle Size) represents the particle size corresponding to the cumulative mass ratio of 50% in the sediment particle size distribution, represents the average size of the sediment particles, and determines the basic physical properties of particle settling and transport (the smaller the particle size, the easier it is to suspend; the larger the particle size, the easier it is to deposit).

[0116] Specifically, the sediment is divided into 4 groups according to different particle sizes: (1) The first group is mainly suspended load, and the sediment median particle size is 0.055 mm; (2) The second group is between suspended load and bed load, and the sediment median particle size is 0.25 mm; (3) The third group is mainly bed load, and the sediment median particle size is 0.50 mm; (4) The fourth group is mainly bed load and also contains part of the gradually deposited particles, and the sediment median particle size is 1.0 mm.

[0117] Step c33, establishing a plurality of sediment transport capacity equations according to the sediment data, the organic matter ratio parameter and the plurality of sediment median particle sizes.

[0118] Specifically, for the divided different groups of sediment, the corresponding sediment transport capacity equations are respectively shown in the following relations (7) to (10): (7) (8) (9) (10) In the formula: represents the sediment transport capacity, which is used to describe the transport and carrying capacity of suspended solids (SS) in the pipeline. The larger the value, the more sediment the pipeline can transport or carry. It is a key indicator of sediment movement state. represents the settling velocity; represents the flow velocity of the pipeline; represents the sediment layer friction coefficient, which is used to describe the frictional resistance of the deposited sediment layer to the flow in the pipeline, reflecting the influence of sediment layer surface roughness on hydraulic characteristics (the larger the value, the greater the flow resistance, and the more difficult it is to carry sediment); represents the gravitational acceleration; represents the specific gravity of the sediment; represents the dimensionless particle size; represents the hydraulic radius; represents the composite friction coefficient of the pipeline; represents the organic matter ratio; represents the wet perimeter of the sediment thickness; represents the sediment thickness; represents the pipe diameter; superscript represents an empirical coefficient, which is a constant determined by experiment, field data fitting or literature experience, used to adapt the actual situation of different pipelines and sediment types, and to calibrate the deviation of the model from the real scene.

[0119] Further, the sediment is divided into 4 groups, which can fully distinguish the movement mode and transport capacity of suspended load and bed load, and detail the relationship between the transport capacity of different particle components and the organic matter content. Specifically, the sediment transport formula corresponding to the particle type of each component is updated, and the organic matter ratio parameter ( ) is added, making the model more accurate. The influence of organic matter content on the transport capacity of sewage pipeline sediment is significant and nonlinear. With the increase of organic matter content (especially in the range of 10% to 30%), the properties of the sediment change, leading to an increase in its transport difficulty.

[0120] Further, by coupling the sediment movement equation, the problem that the existing model does not consider the erosion, transportation and deposition process of the sediment is solved, the sediment simulation function is further improved, and the efficiency of the sewage system sediment simulation is improved.

[0121] Step c4, obtaining a second sewage TSS concentration value according to the initial sewage system model.

[0122] The specific process can refer to the process of the first sewage TSS concentration value in step b2 above, which will not be repeated here.

[0123] Step c5, calculating a plurality of third sewage TSS concentration values according to the sediment movement control equation and a plurality of sediment transport capacity equations.

[0124] Specifically, by combining the sediment movement control equation and a plurality of sediment transport capacity equations, a plurality of corresponding third sewage TSS concentration values can be calculated.

[0125] Step c6, calculating the sediment thickness change according to the pipeline data, the second sewage TSS concentration value and the plurality of third sewage TSS concentration values.

[0126] In some optional embodiments, the above step c6 comprises: Step c61, calculating the pipeline flow change value of the sewage system per unit time according to the pipeline data.

[0127] Wherein, the pipeline data can include pipeline flow, pipeline flow rate and monitoring time.

[0128] Specifically, by combining the pipeline flow, the pipeline flow rate and the monitoring time, the pipeline flow change value of the sewage system per unit time can be further calculated.

[0129] Step c62, calculating a plurality of sewage TSS concentration difference values according to the second sewage TSS concentration value and the plurality of third sewage TSS concentration values.

[0130] Wherein, the sewage TSS concentration difference value is equal to the difference between the second sewage TSS concentration value and the third sewage TSS concentration value.

[0131] Specifically, comparing the second sewage TSS concentration with the third sewage TSS concentration inside the pipeline can determine the deposition and scouring situation inside the pipeline.

[0132] Further, when the second sewage TSS concentration is greater than the third sewage TSS concentration, it indicates that the sediment transport capacity inside the pipeline is insufficient to transport all the sewage TSS concentration, and a part of the sediment will settle at the bottom of the pipeline.

[0133] Further, when the second sewage TSS concentration is less than the third sewage TSS concentration, it indicates that the flow inside the pipeline has high scouring capacity and can erode the existing bottom sediment and continuously transport it to the subsequent pipeline.

[0134] Step c63, determining the sediment mass change according to the plurality of sewage TSS concentration difference values and the pipeline flow change value per unit time.

[0135] The sediment mass change represents the "increase / decrease amount" of the sediment mass in the sewer pipe per unit time (or a set time interval), and is used to reflect the accumulation or scouring trend of the sediment in the pipe.

[0136] Specifically, according to the TSS concentration difference and the pipe flow change value per unit time, the "net change" of the TSS mass per unit time can be quantified, and the sediment mass change can be derived.

[0137] Step c64, calculating the sediment thickness change according to the sediment mass change.

[0138] The sediment thickness change represents the "increase / decrease amount" of the sediment vertical thickness at the bottom of the pipe per unit time (or a set time interval), and can directly reflect the degree of occupation of the sediment layer to the pipe flow space.

[0139] Specifically, on the basis of the obtained sediment mass change, the corresponding sediment thickness change can be calculated by combining the geometric characteristics (such as pipe diameter, cross-sectional shape) of the pipe with the physical relationship of "mass-volume-thickness".

[0140] Further, a certain period can be selected as the sediment thickness update period, and then the sediment thickness change can be updated according to the selected certain period.

[0141] Step S1033, adjusting the initial sewage system model with the sediment thickness change as a boundary condition to obtain a target sewage system model.

[0142] The boundary condition represents a key constraint parameter that affects the simulation results of the sewage system model.

[0143] Specifically, taking the sediment thickness change as the boundary condition can reflect the dynamic accumulation or scouring of the sediment in the pipe in time and space (such as thickness increase reducing the flow cross-section, and thickness decrease expanding the flow cross-section), which is an important input for the sewage system model to simulate the interaction between water flow and sediment.

[0144] Further, although the initial sewage system model has integrated basic data such as pipe network topology and sewage discharge rules, it has not fully considered the influence of the sediment thickness change on the hydraulic characteristics. By taking the sediment thickness change as a boundary condition, the following adjustments can be achieved: (1) correcting the pipe flow cross-section: updating the effective water area of the pipe in real time according to the thickness change (such as a thickness increase of 10 cm corresponding to a pipe diameter reduction of 20 cm), so that the simulation of water flow velocity, pressure and other parameters in the model is more consistent with the actual situation (because the accumulation of sediment will cause the flow velocity to decrease and the local pressure to increase); (2) Optimizing sediment movement simulation: combining thickness variation to back-calculate the settling and scouring rate of sediments, and revising the empirical parameters of sediment transport formula in the model (such as the empirical coefficients in equations (7) to (10) to improve the prediction accuracy of the subsequent sediment development trend.

[0145] Further, the adjusted target sewage system model can reflect the hydraulic flow state of sewage and the dynamic change of sediments at the same time, overcoming the limitation of the initial model based on static pipe network parameters.

[0146] The sewage system sediment problem evaluation method provided by the application can preliminarily reflect the overall operation state of the current sewage system by constructing a first sewage system model through real-time multi-source data sets. Further, by constructing a sewage TSS model through the first sewage system model and obtaining a first sewage TSS concentration value, the overall operation state of the sewage system can be associated with key water quality indicators, focusing on the core factors affecting sediment problems, providing specific and quantifiable reference data for model verification, and further providing more specific indicators for model evaluation. Further, by comparing the first sewage TSS concentration value calculated by the model with the actual monitoring value, the deviation of the first sewage system model from the actual situation can be directly found and adjusted, ensuring the accuracy of the initial sewage system model in reflecting the suspended solid condition in sewage. Further, by analyzing the historical data set and determining the problem pipes in which sediment problems have occurred in the sewage system, a control equation is established according to the pipe data and sediment data, and the sediments are divided according to particle size and combined with the organic matter proportion parameter to establish multiple transport capacity equations, considering the influence of the difference in sediment particle size on the transport process, and further enabling the multiple transport capacity equations to more accurately describe the transport of various sediments. At the same time, the introduction of the organic matter proportion parameter further improves the description of sediment movement by the equation, making the equation more applicable and the calculation result more accurate. Further, the second sewage TSS concentration value obtained by the initial model and the third concentration value calculated by the equation can accurately reflect the relationship between sediment movement and TSS concentration change, and further the calculated sediment thickness change is closer to the actual situation, providing accurate boundary conditions for the adjustment of the target sewage system model, and enhancing the model's ability to simulate the deposition process.

[0147] In some optional embodiments, during the construction of the target sewage system model, data-driven algorithms can also be coupled to calibrate the key parameters of the model, which can help to predict the development of the sediment layer thickness.

[0148] ​An apparatus for assessing a sewer system deposition problem is also provided in the embodiments, which is configured to implement the above embodiments and preferred embodiments, and will not be described again. As used below, the term "module" can be a combination of software and / or hardware that implements a predetermined function. Although the apparatus described in the following embodiments is preferably implemented in software, implementation in hardware, or a combination of software and hardware, is also possible and contemplated.

[0149] The embodiments provide an apparatus for assessing a sewer system deposition problem, as shown in Figure 3 The apparatus comprises: A first obtaining module 301 is configured to obtain a sewer discharge rule and a historical data set of the sewer system, the historical data set representing a collection of historical basic data of all pipes in the sewer system.

[0150] A second obtaining module 302 is configured to obtain a real-time multi-source data set of the sewer system according to the sewer discharge rule.

[0151] A constructing module 303 is configured to couple a deposition movement process of the sewer system and construct a target sewer system model according to the real-time multi-source data set, the historical data set, and a preset organic matter proportion parameter.

[0152] An assessing module 304 is configured to assess a deposition problem of the sewer system by using the target sewer system model, and obtain an assessment result.

[0153] In some optional embodiments, the first obtaining module 301 comprises: An obtaining sub-module is configured to obtain a historical multi-source data set of the sewer system.

[0154] A processing sub-module is configured to process the historical multi-source data set to obtain a sewer discharge coefficient and a pipe network topology structure.

[0155] A determining sub-module is configured to determine the sewer discharge rule of the sewer system according to the sewer discharge coefficient and the pipe network topology structure.

[0156] In some optional embodiments, the constructing module 303 comprises: A constructing sub-module is configured to construct an initial sewer system model according to the real-time multi-source data set.

[0157] A simulating sub-module is configured to simulate the deposition movement process of the sewer system according to the historical data set, the preset organic matter proportion parameter, and the initial sewer system model, and obtain a deposition thickness change.

[0158] An adjusting sub-module is configured to adjust the initial sewer system model by taking the deposition thickness change as a boundary condition, and obtain the target sewer system model.

[0159] In some optional embodiments, the constructing submodule comprises: a first constructing unit configured to construct a first sewage system model according to the real-time multi-source data set.

[0160] a second constructing unit configured to construct a sewage TSS model according to the first sewage system model, to obtain a first sewage TSS concentration value of the sewage TSS model.

[0161] an adjusting unit configured to adjust the first sewage system model according to the first sewage TSS concentration value and a sewage monitoring TSS concentration value of the sewage system, to obtain an initial sewage system model.

[0162] In some optional embodiments, the simulation submodule comprises: an analysis and determination unit configured to analyze the historical data set and determine a problem pipe in which a deposition problem occurs in the sewage system.

[0163] a first obtaining unit configured to obtain pipe data and deposit data of the problem pipe.

[0164] a establishing unit configured to establish a deposit movement control equation and a plurality of deposit transport capacity equations according to the pipe data, the deposit data and an organic matter proportion parameter.

[0165] a second obtaining unit configured to obtain a second sewage TSS concentration value according to the initial sewage system model.

[0166] a first calculating unit configured to calculate a plurality of third sewage TSS concentration values according to the deposit movement control equation and the plurality of deposit transport capacity equations.

[0167] a second calculating unit configured to calculate a deposit thickness change according to the pipe data, the second sewage TSS concentration value and the plurality of third sewage TSS concentration values.

[0168] In some optional embodiments, the establishing unit comprises: a first establishing subunit configured to establish the deposit movement control equation according to the pipe data and the deposit data.

[0169] a dividing subunit configured to divide deposits of the sewage system according to different particle sizes according to the deposit data, to obtain a plurality of deposit median particle sizes.

[0170] a second establishing subunit configured to establish the plurality of deposit transport capacity equations according to the deposit data, the organic matter proportion parameter and the plurality of deposit median particle sizes.

[0171] In some optional embodiments, the second calculating unit comprises: The first calculation subunit is used to calculate the change in pipeline flow rate of the sewage system per unit time based on pipeline data.

[0172] The second calculation subunit is used to calculate multiple wastewater TSS concentration differences based on the second wastewater TSS concentration value and multiple third wastewater TSS concentration values.

[0173] A sub-unit is defined to determine the change in sediment mass based on the differences in TSS concentrations of multiple wastewater samples and the change in pipeline flow rate per unit time.

[0174] The third calculation subunit is used to calculate the change in sediment thickness based on the change in sediment mass.

[0175] Further functional descriptions of the above modules and units are the same as those in the corresponding embodiments described above, and will not be repeated here.

[0176] In this embodiment, the wastewater system sedimentation problem assessment device is presented in the form of a functional unit. Here, a unit refers to an ASIC (Application Specific Integrated Circuit) circuit, a processor and memory that execute one or more software or fixed programs, and / or other devices that can provide the above functions.

[0177] This invention also provides a computer device having the above-described features. Figure 3 The wastewater system sedimentation problem assessment device shown.

[0178] Please see Figure 4 , Figure 4 This is a schematic diagram of the structure of a computer device provided in an optional embodiment of the present invention, such as... Figure 4 As shown, the computer device includes one or more processors 10, memory 20, and interfaces for connecting the components, including high-speed interfaces and low-speed interfaces. The components communicate with each other via different buses and can be mounted on a common motherboard or otherwise installed as needed. The processors can process instructions executed within the computer device, including instructions stored in or on memory to display graphical information of a GUI on external input / output devices (such as display devices coupled to the interfaces). In some alternative implementations, multiple processors and / or multiple buses can be used with multiple memories, if desired. Similarly, multiple computer devices can be connected, each providing some of the necessary operations (e.g., as a server array, a group of blade servers, or a multiprocessor system). Figure 4 Take a processor 10 as an example.

[0179] The processor 10 can be a central processor, a network processor, or a combination thereof. The processor 10 can further include hardware chips. The hardware chips can be application specific integrated circuits, programmable logic devices, or a combination thereof. The programmable logic devices can be complex programmable logic devices, field programmable logic gate arrays, general array logic, or any combination thereof.

[0180] The memory 20 stores instructions executable by the at least one processor 10 to cause the at least one processor 10 to perform the methods illustrated by the above embodiments.

[0181] The memory 20 can include a program storage area and a data storage area. The program storage area can store an operating system, application programs required by at least one function, and the like. The data storage area can store data created according to the use of the computer device, and the like. In addition, the memory 20 can include a high-speed random access memory, and can further include a non-transitory memory such as at least one disk storage device, a flash memory device, or other non-transitory solid state storage device. In some alternative embodiments, the memory 20 can optionally include a memory disposed remotely from the processor 10, which can be connected to the computer device through a network. Examples of the network include, but are not limited to, the Internet, an intranet, a local area network, a mobile communication network, and a combination thereof.

[0182] The memory 20 can include a volatile memory such as a random access memory, and can also include a non-volatile memory such as a flash memory, a hard disk, or a solid state disk. The memory 20 can further include a combination of the above-mentioned types of memories.

[0183] The computer device further includes a communication interface 30 for communication of the computer device with other devices or communication networks.

[0184] The embodiments of the present application also provide a computer readable storage medium. The above-mentioned methods according to the embodiments of the present application can be implemented in hardware, firmware, or recorded in a storage medium, or stored in a remote storage medium or a non-transitory machine readable storage medium originally through network downloading and then stored in a local storage medium, so that the methods described herein can be processed by such software on a storage medium using a general purpose computer, a special purpose processor, or programmable or special purpose hardware. The storage medium can be a magnetic disk, an optical disk, a read-only memory, a random access memory, a flash memory, a hard disk, or a solid state disk, etc. Further, the storage medium can further include a combination of the above-mentioned types of memories. It can be understood that the computer, the processor, the microprocessor controller, or the programmable hardware includes a storage component that can store or receive software or computer code, which, when accessed and executed by the computer, the processor, or the hardware, implements the methods illustrated by the above embodiments.

[0185] Part of the present application can be applied as a computer program product, for example, computer program instructions, when executed by a computer, through the operation of the computer, can invoke or provide the method and / or technical solutions according to the present application. Those skilled in the art should understand that the form of computer program instructions in computer readable medium includes but is not limited to source files, executable files, installation package files, etc., and accordingly, the way of computer program instructions executed by computer includes but is not limited to: the computer directly executes the instructions, or the computer compiles the instructions and then executes the corresponding compiled program, or the computer reads and executes the instructions, or the computer reads and installs the instructions and then executes the corresponding installed program. Here, the computer readable medium can be any available computer readable storage medium or communication medium accessible to the computer.

[0186] Although the embodiments of the present application are described in conjunction with the accompanying drawings, various modifications and changes can be made by those skilled in the art without departing from the spirit and scope of the present application, and such modifications and changes fall within the scope defined by the appended claims.

Claims

1. A method of assessing a sewage system deposition problem, characterized by, The method comprises: acquiring sewage discharge rules and a historical data set of a sewage system, the historical data set representing a collection of historical basic data of all pipes in the sewage system; acquiring a real-time multi-source data set of the sewage system according to the sewage discharge rules; coupling a sediment movement process of the sewage system according to the real-time multi-source data set, the historical data set and a preset organic matter proportion parameter, and constructing a target sewage system model; evaluating a sedimentation problem of the sewage system by using the target sewage system model to obtain an evaluation result.

2. The method of claim 1, wherein, The method comprises: acquiring sewage discharge rules and a historical data set of a sewage system, the historical data set representing a collection of historical basic data of all pipes in the sewage system; acquiring a real-time multi-source data set of the sewage system according to the sewage discharge rules; acquiring a real-time multi-source data set of the sewage system according to the sewage discharge rules; 3. The method of claim 1, wherein, coupling a sediment movement process of the sewage system according to the real-time multi-source data set, the historical data set and a preset organic matter proportion parameter, and constructing a target sewage system model; acquiring a real-time multi-source data set of the sewage system according to the sewage discharge rules; coupling a sediment movement process of the sewage system according to the real-time multi-source data set, the historical data set and a preset organic matter proportion parameter, and constructing a target sewage system model, comprising: constructing an initial sewage system model according to the real-time multi-source data set; 4. The method of claim 3, wherein, simulating the sediment movement process of the sewage system according to the historical data set, the preset organic matter proportion parameter and the initial sewage system model to obtain a sediment thickness change; adjusting the initial sewage system model by taking the sediment thickness change as a boundary condition to obtain the target sewage system model. constructing an initial sewage system model according to the real-time multi-source data set, comprising: constructing a first sewage system model according to the real-time multi-source data set; 5. The method of claim 3, wherein, constructing a sewage TSS model according to the first sewage system model to obtain a first sewage TSS concentration value of the sewage TSS model; verifying and adjusting the first sewage system model according to the first sewage TSS concentration value and a sewage monitoring TSS concentration value of the sewage system to obtain the initial sewage system model. simulating the sediment movement process of the sewage system according to the historical data set, the preset organic matter proportion parameter and the initial sewage system model to obtain a sediment thickness change, comprising: analyzing the historical data set and determining a problem pipe in which a sedimentation problem has occurred in the sewage system; acquiring pipe data and sediment data of the problem pipe; establishing a sediment movement control equation and a plurality of sediment transport capacity equations according to the pipe data, the sediment data and the organic matter proportion parameter; acquiring a second sewage TSS concentration value according to the initial sewage system model; 6. The method of claim 5, wherein, calculating a plurality of third sewage TSS concentration values according to the sediment movement control equation and the plurality of sediment transport capacity equations; calculating the sediment thickness change according to the pipe data, the second sewage TSS concentration value and the plurality of third sewage TSS concentration values. establishing the sediment movement control equation and the sediment transport capacity equations according to the pipe data, the sediment data and the organic matter proportion parameter, comprising: establishing the sediment movement control equation according to the pipe data and the sediment data; According to the sediment data, the sediments of the sewage system are divided according to different particle sizes to obtain a plurality of sediment intermediate particle sizes; According to the sediment data, the organic matter proportion parameter and the plurality of sediment intermediate particle sizes, the plurality of sediment transport capacity equations are established.

7. The method of claim 5, wherein, According to the pipe data, the second sewage TSS concentration value and the plurality of third sewage TSS concentration values, the sediment thickness change is calculated, including: According to the pipe data, the pipe flow change value per unit time of the sewage system is calculated; According to the second sewage TSS concentration value and the plurality of third sewage TSS concentration values, a plurality of sewage TSS concentration difference values are calculated; According to the plurality of sewage TSS concentration difference values and the pipe flow change value per unit time, a sediment mass change is determined; According to the sediment mass change, the sediment thickness change is calculated.

8. A sewer system sedimentation problem assessment device, characterized by, The device comprises: A first obtaining module is configured to obtain sewage discharge rules and a historical data set of a sewage system, wherein the historical data set represents a collection of historical basic data of all pipes in the sewage system; A second obtaining module is configured to obtain a real-time multi-source data set of the sewage system according to the sewage discharge rules; A construction module is configured to couple a sediment movement process of the sewage system and construct a target sewage system model according to the real-time multi-source data set, the historical data set and a preset organic matter proportion parameter; An evaluation module is configured to evaluate a sediment problem of the sewage system by using the target sewage system model to obtain an evaluation result.

9. A computer-readable storage medium, characterized in that, The computer readable storage medium stores computer instructions, and the computer instructions are used to make a computer execute the sewage system sediment problem evaluation method in any one of claims 1 to 7.

10. A computer program product, characterised in that, The computer readable storage medium stores computer instructions, and the computer instructions are used to make a computer execute the sewage system sediment problem evaluation method in any one of claims 1 to 7.

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