Classified discharge management system and method for urban sewage

Abstract

The invention discloses a graded discharge management system and method for urban sewage, multiple water quality parameters are collected in real time from different monitoring nodes of a pipe network through a multi-source data fusion collection module, and time and position information are integrated to form a multi-dimensional data set, so that the actual condition of the sewage is comprehensively reflected; the complex water quality evaluation and grading module applies a multi-factor dynamic weight comprehensive pollution index calculation formula, integrates multiple parameters and dynamically adjusts the weight, so that the water quality evaluation is more scientific and accurate, the pollution degrees of different time and regions can be truly presented, the limitation of the traditional fixed weight is overcome, and the comprehensive pollution index and the multi-level grading threshold value of the sewage are calculated based on the accurate sewage comprehensive pollution index and the multi-level grading threshold value. The system realizes fine discharge grade grading, different grades correspond to different treatment requirements and standards, sewage is guided to corresponding treatment units and channels, accurate graded discharge is realized, the sewage with low pollution degree is subjected to cost reduction by adopting a simple process, and the sewage with high pollution degree is subjected to enhanced treatment to meet the standard.

Description

Technical Field

[0001] This invention relates to the field of urban sewage discharge technology, and in particular to a graded discharge management system and method for urban sewage. Background Technology

[0002] With the acceleration of urbanization and the continuous increase in urban population, the amount of urban sewage discharge is also increasing day by day. Urban sewage contains a large amount of pollutants such as organic matter, nutrients, and heavy metal ions. If it is discharged directly into natural water bodies without effective treatment, it will cause serious pollution to the water environment, destroy the ecological balance, and affect human health.

[0003] Currently, most cities have established sewage treatment systems, but traditional sewage treatment and discharge management methods have many problems. On the one hand, sewage treatment plants usually use fixed treatment processes and parameters, making it difficult to make flexible adjustments according to the dynamic changes in sewage quality and quantity. This results in some sewage not being fully treated, and the discharge water quality being unstable, making it difficult to meet increasingly stringent environmental protection requirements. On the other hand, urban sewage pipe network systems are complex, and the sewage quality varies greatly in different areas. Existing discharge management methods often lack accurate assessment and classification of sewage quality, making it impossible to achieve differentiated treatment and discharge of sewage of different grades, resulting in waste of sewage treatment resources and low treatment efficiency. Summary of the Invention

[0004] In view of this, the present invention proposes a graded discharge management system and method for urban sewage, which can effectively solve the shortcomings of the existing technology, such as the inability to flexibly adjust the treatment process and parameters according to the dynamic changes in sewage quality and quantity, and the inability to achieve differentiated treatment and discharge of sewage of different grades.

[0005] The technical solution of this invention is implemented as follows:

[0006] A graded discharge management system for urban sewage, comprising:

[0007] The multi-source data fusion acquisition module is used to collect various types of water quality parameter data from different monitoring nodes of the urban sewage pipe network in real time, and integrate the acquisition time and acquisition location information to form a multi-dimensional dataset;

[0008] The complex water quality assessment and classification module is used to receive the multi-dimensional dataset transmitted by the multi-source data fusion acquisition module, calculate the comprehensive pollution index of wastewater based on the multi-factor dynamic weight comprehensive pollution index calculation formula, and classify the wastewater discharge level according to the calculated comprehensive pollution index of wastewater and the preset multi-level classification threshold.

[0009] The intelligent discharge control and scheduling module is configured to determine and automatically control corresponding sewage treatment device operation parameters, opening or closing of a sewage discharge channel, and flow distribution between different treatment units and discharge channels according to the sewage discharge level determined by the complex water quality evaluation and grading module, in combination with a topological structure of a municipal sewage pipe network, real-time treatment capacity of a sewage treatment plant, and environmental capacity of different receiving water bodies, so as to realize precise grading discharge and optimal scheduling of different levels of sewage.

[0010] As a further optional solution of the grading discharge management system of the municipal sewage, the multi-factor dynamic weight comprehensive pollution index calculation formula is specifically as follows:

[0011] ;

[0012] wherein P is a comprehensive pollution index of sewage, is a measured concentration value of the i-th water quality parameter, is a national discharge standard limit value corresponding to the i-th water quality parameter, is a non-linear adjustment coefficient of the i-th water quality parameter, and ≥1, determined according to a sensitive degree and cumulative effect of different water quality parameters on water pollution, is a dynamic weight coefficient of the i-th water quality parameter at time t, satisfying =1, and is dynamically adjusted according to seasonal variation law of the water quality parameter, municipal sewage discharge law, and historical water quality data with time t.

[0013] As a further optional solution of the grading discharge management system of the municipal sewage, the dynamic weight coefficient is calculated in the following manner:

[0014] ;

[0015] wherein is a basic weight coefficient of the i-th water quality parameter, reflecting an important degree of the water quality parameter on water pollution under normal circumstances, is a time adjustment function of the i-th water quality parameter at time t, is calculated in the following manner:

[0016] ;

[0017] wherein , , is an adjustment coefficient, satisfying =1, is a seasonal variation period of the i-th water quality parameter, is a phase angle, used to adjust the starting time of seasonal variation, is a concentration variation range of the i-th water quality parameter in a period of time before time t, is a maximum value of the concentration variation range in the period of time.

[0018] As a further optional solution of the hierarchical discharge management system of municipal sewage, the system further comprises:

[0019] A big data storage and analysis module is configured to store the multi-dimensional data set collected by the multi-source data fusion collection module, the sewage comprehensive pollution index and discharge grade information calculated by the complex water quality evaluation and grading module, and the operation record of the intelligent discharge control and scheduling module, and to mine the correlation between water quality variation rules, discharge control effect, and system operation efficiency based on big data analysis technology.

[0020] As a further optional solution of the hierarchical discharge management system of municipal sewage, the system further comprises:

[0021] A visual monitoring and early warning module is configured to display the water quality distribution of the municipal sewage pipe network, the sewage discharge grade distribution, the sewage treatment equipment operation state, and the discharge control effect in a graphical interface, to timely issue an audible and visual alarm signal when the sewage comprehensive pollution index exceeds a preset maximum warning value or the concentration of a certain key water quality parameter exceeds an emergency threshold, and to push early warning information to relevant management personnel.

[0022] A hierarchical discharge management method of municipal sewage, specifically comprising:

[0023] A multi-source data fusion collection step is configured to collect real-time water quality parameter data of multiple types from different monitoring nodes of the municipal sewage pipe network, integrate collection time and collection location information, and form a multi-dimensional data set;

[0024] A complex water quality evaluation and grading step is configured to calculate a sewage comprehensive pollution index based on a multi-factor dynamic weight comprehensive pollution index calculation formula, and to grade sewage according to the calculated sewage comprehensive pollution index and a preset multi-level grading threshold.

[0025] An intelligent discharge control and scheduling step is configured to intelligently decide and automatically control the operation parameters of the corresponding sewage treatment equipment, the opening or closing of the sewage discharge channel, and the flow distribution between different treatment units and discharge channels of the sewage, to realize precise hierarchical discharge and optimized scheduling of different grades of sewage, in combination with the topological structure of the municipal sewage pipe network, the real-time treatment capacity of the sewage treatment plant, and the environmental capacity of different receiving water bodies.

[0026] As a further optional solution of the hierarchical discharge management method of municipal sewage, the method further comprises:

[0027] Big data storage and analysis step: store the collected multi-dimensional data set, the calculated comprehensive pollution index of sewage and discharge grade information, the operation record of discharge control and scheduling, and mine the correlation between water quality change rule, discharge control effect and system operation efficiency based on big data analysis technology.

[0028] As a further optional solution of the hierarchical discharge management method of municipal sewage, the method further comprises:

[0029] Visual monitoring and early warning step: display the water quality distribution of municipal sewage pipe network, the sewage discharge grade distribution, the sewage treatment equipment operation state and the discharge control effect in a graphical interface, and timely issue an audible and light alarm signal and push early warning information to relevant management personnel when the comprehensive pollution index of sewage exceeds the preset highest warning value or the concentration of a key water quality parameter exceeds the emergency threshold.

[0030] A computing device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the steps of the hierarchical discharge management method of municipal sewage when executing the computer program.

[0031] A computer readable storage medium, wherein the storage medium stores a computer program, and the computer program is executable on a processor to implement the steps of the hierarchical discharge management method of municipal sewage.

[0032] The beneficial effects of the present application are: the multi-source data fusion acquisition module acquires real-time water quality parameter data of multiple types from different monitoring nodes of the urban sewage pipe network, and integrates the acquisition time and acquisition location information to form a multi-dimensional data set. Compared with the traditional single data source or a small amount of parameter acquisition mode, this comprehensive and multi-dimensional data acquisition can more accurately reflect the actual water quality condition of the sewage. The complex water quality evaluation and grading module calculates the sewage comprehensive pollution index by using a multi-factor dynamic weight comprehensive pollution index calculation formula. The formula comprehensively considers multiple water quality parameters, and the weight coefficient can be dynamically adjusted according to the actual contribution degree and change rule of different water quality parameters to the water pollution, which makes the water quality evaluation result more scientific and accurate, and can truly reflect the pollution degree of the sewage at different times and in different regions, avoiding the limitations of the traditional fixed weight evaluation method. Based on the accurate sewage comprehensive pollution index and the preset multi-level grading threshold, the system can finely grade the sewage discharge, and different discharge levels correspond to different treatment requirements and discharge standards. The system can guide the sewage to the corresponding treatment unit and discharge channel according to the different discharge levels of the sewage, so as to realize the accurate grading discharge of different levels of sewage. For the sewage with low pollution degree, a relatively simple treatment process can be used to reduce the treatment cost. For the sewage with high pollution degree, the treatment intensity is strengthened to ensure that the discharge meets the standard. In this way, the sewage treatment effect can be ensured, and the utilization efficiency of sewage treatment resources can be improved. Through intelligent discharge control and scheduling, the system can dynamically adjust the operation parameters according to the real-time data, avoid the overload operation or waste of treatment capacity of the sewage treatment equipment, reasonably allocate the sewage flow, reduce the backlog and retention of the sewage in the pipe network, improve the operation efficiency of the whole sewage discharge management system, and reduce the operation cost. BRIEF DESCRIPTION OF DRAWINGS

[0033] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the prior art, the following will briefly introduce the drawings needed to be used in the embodiments or prior art description. Obviously, the drawings in the following description only some embodiments of the present application, and for those skilled in the art, other drawings can also be obtained without creative labor on the basis of these drawings.

[0034] Fig. 1 It is a composition schematic diagram of the present application, a sewage discharge grading management system of a city.

[0035] Fig. 2 It is a flowchart of the present application, a sewage discharge grading management method of a city.

[0036] Fig. 3 It is a composition schematic diagram of the present application, a computing device. DETAILED DESCRIPTION

[0037] The technical solutions in the embodiments of the present application will be clearly and completely described below. Obviously, the described embodiments are only part of the embodiments of the present application, rather than all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative work fall within the protection scope of the present application.

[0038] Reference Figs. 1 to 3 A hierarchical discharge management system for municipal sewage, comprising:

[0039] A multi-source data fusion acquisition module is configured to acquire real-time water quality parameter data of multiple types from different monitoring nodes of a municipal sewage pipe network, wherein the water quality parameter data includes chemical oxygen demand, biochemical oxygen demand, suspended solids, ammonia nitrogen, total phosphorus, total nitrogen, pH value, dissolved oxygen, and heavy metal ion concentration (including but not limited to lead Pb, mercury Hg, cadmium Cd, and chromium Cr), and the acquisition time and location information are integrated to form a multi-dimensional data set.

[0040] A complex water quality evaluation and grading module is configured to receive the multi-dimensional data set transmitted by the multi-source data fusion acquisition module, calculate a sewage comprehensive pollution index based on a multi-factor dynamic weight comprehensive pollution index calculation formula, and grade the sewage according to the calculated sewage comprehensive pollution index and a preset multi-level grading threshold.

[0041] An intelligent discharge control and scheduling module is configured to determine the sewage discharge level based on the complex water quality evaluation and grading module, combine the topological structure of the municipal sewage pipe network, the real-time processing capacity of the sewage treatment plant, and the environmental capacity of different receiving water bodies, and automatically control the operation parameters of the corresponding sewage treatment equipment, the opening or closing of the sewage discharge channel, and the flow distribution between different treatment units and discharge channels to achieve precise hierarchical discharge and optimized scheduling of different levels of sewage.

[0042] In the embodiment, the multi-source data fusion acquisition module acquires multiple types of water quality parameter data from different monitoring nodes of the urban sewage pipe network in real time, integrates the acquisition time and acquisition location information, forms a multi-dimensional data set, compared with the traditional single data source or a small amount of parameter acquisition mode, the comprehensive and multi-dimensional data acquisition can more accurately reflect the actual water quality condition of the sewage, the complex water quality evaluation and grading module calculates the comprehensive pollution index of the sewage by using a multi-factor dynamic weight comprehensive pollution index calculation formula, the formula comprehensively considers multiple water quality parameters, and the weight coefficient can be dynamically adjusted according to the actual contribution degree and variation law of different water quality parameters to the water pollution, which makes the water quality evaluation result more scientific and accurate, and can truly reflect the pollution degree of the sewage at different times and in different regions, avoids the limitation of the traditional fixed weight evaluation method, based on the accurate comprehensive pollution index of the sewage and the preset multi-level grading threshold, the system can finely grade the sewage discharge, different discharge grades correspond to different treatment requirements and discharge standards, the system can guide the sewage to the corresponding treatment unit and discharge channel according to the different discharge grades of the sewage, so as to realize the accurate grading discharge of different grades of sewage, for the sewage with low pollution degree, a relatively simple treatment process can be used to reduce the treatment cost, and for the sewage with high pollution degree, the treatment intensity is strengthened to ensure that the sewage is discharged up to the standard, which can not only ensure the sewage treatment effect, but also improve the utilization efficiency of the sewage treatment resources, through the intelligent discharge control and scheduling, the system can dynamically adjust the operation parameters according to the real-time data, avoid the overload operation or waste of the sewage treatment equipment, at the same time, reasonably allocate the sewage flow, reduce the backlog and retention of the sewage in the pipe network, improve the operation efficiency of the whole sewage discharge management system, and reduce the operation cost.

[0043] It should be noted that the water quality sensors in the multi-source data fusion acquisition module are designed redundantly, for key water quality parameters (such as COD, BOD), multiple same type sensors are arranged at each monitoring node, and the measurement data of the multiple sensors are fused by using a data fusion algorithm (such as weighted average method, Kalman filtering method), so as to improve the accuracy and reliability of data acquisition.

[0044] Preferably, the multi-factor dynamic weight comprehensive pollution index calculation formula is specifically:

[0045] ;

[0046] Wherein, P is the comprehensive pollution index of the sewage, is the measured concentration value of the i-th water quality parameter, is the national discharge standard limit value corresponding to the i-th water quality parameter, is the non-linear adjustment coefficient of the i-th water quality parameter, and ≥1, determined according to the sensitivity and cumulative effect of different water quality parameters on water pollution, is a dynamic weight coefficient of the i-th water quality parameter at time t, satisfying =1, and is dynamically adjusted according to the seasonal variation law of the water quality parameter, the urban sewage discharge law, and the historical water quality data.

[0047] In this embodiment, the formula comprehensively considers multiple water quality parameters (such as chemical oxygen demand, biochemical oxygen demand, and multiple indicators), which can more comprehensively and accurately reflect the comprehensive pollution condition of sewage than single parameter evaluation, and avoid evaluation deviation caused by single parameter abnormality; the weight coefficient is dynamically adjusted according to the seasonal variation law of the water quality parameter, the urban sewage discharge law, and the historical water quality data, which makes the evaluation adapt to the change of water quality characteristics in different periods, such as in the rainy season and the dry season, the contribution degree of different water quality parameters to pollution may be different, and the dynamic weight can more reasonably reflect this change, improve the timeliness and accuracy of the evaluation; the nonlinear adjustment coefficient is introduced, which is determined according to the sensitivity and cumulative effect of different water quality parameters on water pollution, which can more accurately reflect the complex relationship between each water quality parameter and pollution, for those parameters that have a greater impact on pollution and have cumulative effect, the evaluation result is amplified or adjusted through a suitable value, so that the evaluation result is more in line with the actual situation; since the water quality of urban sewage changes with time, season, urban activity, and other factors, the formula can capture these changes in time and adjust the evaluation result through dynamic weight and nonlinear adjustment coefficient, so that the system can adapt to the complex and changeable water quality environment, the comprehensive pollution index of sewage calculated based on the formula can provide a scientific basis for the classified discharge management of urban sewage, according to different pollution index ranges, the sewage is divided into different grades, so that targeted treatment measures are taken to improve the treatment efficiency and effect, and accurate water quality evaluation is helpful for reasonable allocation of sewage treatment resources, for sewage with lower pollution degree, a relatively simple treatment process can be used to reduce the treatment cost, and for sewage with higher pollution degree, more resources are invested for deep treatment to realize optimal allocation of resources. Through analysis of historical water quality data and adjustment of dynamic weight, the change trend of urban sewage water quality can be understood, which provides data support for long-term planning, construction, and reconstruction of urban sewage treatment facilities, and is helpful for formulating a more scientific and reasonable sewage treatment development strategy.

[0048] Preferably, the calculation method of the dynamic weight coefficient is specific as follows:

[0049] ;

[0050] wherein, is the basic weight coefficient of the i-th water quality parameter, reflecting the importance of the water quality parameter to water pollution under normal circumstances, is the time adjustment function of the i-th water quality parameter at time t, is calculated in the following manner:

[0051] ;

[0052] wherein, , , is an adjustment coefficient, satisfying =1, is the seasonal variation period of the i-th water quality parameter, is a phase angle, used to adjust the starting time of the seasonal variation, is the concentration variation amplitude of the i-th water quality parameter within a certain period of time before time t, is the maximum value of the concentration variation amplitude within the period of time.

[0053] In this embodiment, the basic weight coefficient is dynamically adjusted by the time adjustment function , so that the weight coefficient can change over time. The importance of urban sewage water quality parameters changes with factors such as season and time. For example, in summer, due to high temperature, parameters such as biochemical oxygen demand (BOD) may have a more significant impact on water pollution. This calculation method can timely capture such changes, making the weight distribution more in line with actual conditions and improving the accuracy of water quality assessment. The time adjustment function takes into account factors such as the seasonal variation period of the water quality parameter, the phase angle , and the concentration variation amplitude , which can cope with the complexity of water quality parameter changes, not only considering periodic changes, but also considering factors such as random fluctuations, more accurately reflecting the importance of water quality parameters to water pollution at different times; the calculation of the weight coefficient combines the basic weight coefficient and the time adjustment function , and is normalized ( ). This comprehensive multi-factor adjustment method avoids the one-sidedness of determining the weight by a single factor, making the weight distribution more scientific and reasonable, and more accurately reflecting the relative importance of each water quality parameter in comprehensive pollution assessment. With the passage of time and changes in water quality parameters, the weight coefficient The dynamic adjustment can realize dynamic balance between different water quality parameters. For a water quality parameter that changes significantly in a certain period and contributes more to pollution, the weight will be increased accordingly. For a relatively stable parameter with less impact, the weight will be reduced, so as to ensure that the water quality evaluation result is always based on the most reasonable weight distribution; and the dynamic weight coefficient is based on the dynamic weight coefficient The calculated comprehensive sewage pollution index P is more accurate and reliable, which provides a solid foundation for the water quality evaluation of urban sewage and can more accurately judge the degree of sewage pollution, providing a scientific basis for subsequent treatment and discharge decision. In the management of sewage grading discharge, the accurate comprehensive pollution index P helps to accurately classify sewage into different grades. Different grades of sewage can adopt different treatment processes and discharge strategies to achieve the optimization of resource allocation and the improvement of treatment efficiency. For example, for sewage with lower pollution degree, a relatively simple treatment process can be used to reduce cost. For sewage with higher pollution degree, the treatment intensity is strengthened to ensure that the discharge meets the standard.

[0054] Preferably, the system further comprises:

[0055] The big data storage and analysis module is used for storing the multi-dimensional data set collected by the multi-source data fusion acquisition module, the comprehensive sewage pollution index and discharge grade information calculated by the complex water quality evaluation and grading module, and the operation record of the intelligent discharge control and scheduling module, and mining the correlation between water quality change law, discharge control effect and system operation efficiency based on big data analysis technology.

[0056] In the present embodiment, the multi-source data fusion acquisition module collects multi-dimensional data sets, covering various types of water quality parameter data collected in real time from different monitoring nodes of the urban sewer network, as well as collection time, location and other information. The complex water quality evaluation and grading module calculates the sewage comprehensive pollution index and discharge grade information, and the intelligent discharge control and scheduling module stores the operation records. This comprehensive data integration provides a rich and complete data basis for subsequent analysis, facilitating comprehensive consideration of various aspects of urban sewage management. Based on the stored multi-dimensional water quality data sets, big data analysis techniques can be used to mine the variation rules of water quality parameters with respect to time, space and other factors. For example, the fluctuation of water quality parameters in different seasons and different regions can be analyzed to identify the periodicity and trend characteristics of water quality changes, providing a basis for predicting water quality changes in advance and developing targeted treatment strategies. By analyzing the sewage comprehensive pollution index and discharge grade information, combined with the operation records of the intelligent discharge control and scheduling module, the effectiveness of different discharge control strategies can be evaluated. For example, by comparing the sewage treatment compliance rate, pollutant removal efficiency and other indicators under different time periods and discharge levels, it can be determined whether the current discharge control measures are effective, providing data support for optimizing discharge control strategies. By mining the correlation between water quality variation rules, discharge control effectiveness and system operation efficiency, it is possible to identify key factors that affect system operation efficiency. For example, by analyzing how changes in water quality parameters affect the operation load and energy consumption of sewage treatment equipment, equipment operation parameters can be adjusted and scheduling strategies can be optimized to improve the overall operation efficiency of the sewage discharge management system and reduce operating costs. By continuously mining the correlations and rules in the data, it is possible to identify problems and potential optimization spaces in the system. For example, by adjusting the parameters of the water quality evaluation model based on water quality variation rules and optimizing the discharge scheduling algorithm based on discharge control effectiveness evaluation results, the system can be continuously optimized and upgraded, improving the overall level of urban sewage management.

[0057] It should be noted that the correlation between water quality variation rules, discharge control effectiveness and system operation efficiency based on big data analysis techniques specifically includes:

[0058] Data preprocessing step: Obtain multi-dimensional data sets from the big data storage and analysis module, which covers water quality parameter data (including but not limited to chemical oxygen demand, biochemical oxygen demand, suspended solids, ammonia nitrogen, total phosphorus, total nitrogen, pH value, dissolved oxygen, and heavy metal ion concentration) collected by the multi-source data fusion acquisition module at different times and different monitoring nodes, comprehensive pollution index and discharge grade information of sewage, operation records of intelligent discharge control and scheduling module (such as sewage treatment equipment operation parameters, sewage discharge channel opening and closing state, flow distribution), clean up the obtained data, remove outliers and missing values, and standardize the data to unify different dimensions of data into a suitable numerical range for subsequent analysis;

[0059] Water quality change rule mining step: Using time series analysis method, the trend of different water quality parameters with time is analyzed, and autoregressive integrated moving average model (ARIMA) or long short-term memory network (LSTM) and other deep learning models are used to model and predict the historical data of water quality parameters, to mine the seasonal variation rule, periodic fluctuation characteristics and long-term trend of water quality parameters; Combined with spatial analysis technology, according to the location information of different monitoring nodes, the spatial distribution heat map of water quality parameters is drawn, the spatial distribution characteristics of water quality parameters in urban sewage pipe network are analyzed, and the pollution high-risk area and pollution diffusion path are identified; Using association rule mining algorithm (such as Apriori algorithm), the association relationship between different water quality parameters is analyzed, the key water quality parameter combination that plays a leading role in water quality change is found out, and the interaction mechanism between these parameters is analyzed;

[0060] Discharge control effect evaluation step: Based on the preset discharge control target (such as sewage discharge standard rate, improvement degree of receiving water body environmental quality, etc.), an evaluation index system of discharge control effect is constructed, which includes but is not limited to sewage discharge compliance rate, pollutant removal efficiency, and water quality improvement amplitude of receiving water body; Using comparative analysis method, the actual discharge control effect is compared with the preset target, the deviation between the actual value and the target value of each evaluation index is calculated, and the discharge control effect in different time periods and different discharge grades is compared to analyze the effectiveness and stability of the discharge control measures; Using causal analysis method, the key factors affecting the discharge control effect are explored, and by constructing structural equation model (SEM) or decision tree model, the causal relationship between sewage treatment equipment operation parameters, sewage discharge channel flow distribution and discharge control effect is analyzed, and the main bottlenecks and weak links affecting the discharge control effect are found out;

[0061] System operation efficiency analysis step: define system operation efficiency evaluation indexes, including but not limited to sewage treatment cost (including energy consumption, reagent consumption, equipment maintenance cost, etc.), sewage treatment capacity utilization rate (actual treatment water quantity and design treatment water quantity ratio), equipment failure rate, system response time (time interval from water quality abnormality detection to taking corresponding control measures) and the like; collect relevant data in system operation process, use data mining algorithm (such as clustering analysis, neural network and the like) to analyze system operation efficiency indexes, classify system operation efficiency under different time periods and different operation conditions through clustering analysis, find out high-efficiency operation mode and low-efficiency operation mode; construct system operation efficiency prediction model, predict system operation efficiency in future period based on historical data and current operation state, use support vector machine (SVM) or random forest and the like algorithm to model factors influencing system operation efficiency, provide decision basis for system optimization;

[0062] Correlation relationship mining step: adopt correlation analysis method, calculate correlation coefficient between water quality change law indexes (such as water quality parameter change trend, spatial distribution characteristic parameter and the like), discharge control effect evaluation indexes and system operation efficiency evaluation indexes, preliminarily judge correlation degree between indexes; use cause-effect inference method, construct cause-effect relationship model between water quality change, discharge control effect and system operation efficiency, analyze cause-effect action path and intensity between factors based on Bayesian network or structural cause-effect model (SCM), clarify influence of water quality change on discharge control effect, action of discharge control measure on system operation efficiency and feedback mechanism between system operation efficiency and water quality change; through visualization technology, display correlation relationship mined in intuitive graphical mode, for example, draw cause-effect relationship diagram, correlation network diagram and the like, clearly present complex correlation relationship between water quality change law, discharge control effect and system operation efficiency.

[0063] Preferably, the system further comprises:

[0064] The visualization monitoring and early warning module is used to display the water quality distribution of the urban sewage pipe network, the sewage discharge grade distribution, the sewage treatment equipment operation state and the discharge control effect in a graphical interface. When the sewage comprehensive pollution index exceeds the preset highest warning value or the concentration of a key water quality parameter exceeds the emergency threshold value, an audible and visual alarm signal is timely sent, and early warning information is pushed to relevant management personnel.

[0065] In this embodiment, the water quality distribution of the urban sewage pipe network, the sewage discharge level distribution, the sewage treatment equipment operation state and the discharge control effect are displayed in a graphical interface. This intuitive display method enables the management personnel to quickly understand the operation status of the entire sewage system without deep analysis of complex data. For example, the color-coded map can clearly show the water pollution level and discharge level difference in different areas, and the chart can intuitively observe the changes of the operation parameters of the sewage treatment equipment, etc. This covers multiple key aspects of the sewage pipe network, from the spatial distribution of water quality and discharge level to the real-time operation status of the equipment and the overall discharge control effect, providing a comprehensive and systematic monitoring perspective for the management personnel, which helps them to grasp the operation of the urban sewage system as a whole and timely discover potential problems and abnormalities. When the sewage comprehensive pollution index exceeds the preset highest warning value or a key water quality parameter concentration exceeds the emergency threshold, an audible and visual alarm signal is sent out in a timely manner. This real-time early warning mechanism can quickly attract the attention of the management personnel, enabling them to take measures at the initial stage of the problem to avoid further deterioration of the problem. For example, if the sewage comprehensive pollution index in a certain area suddenly rises, it may indicate that there is sewage leakage or abnormal treatment in that area. Timely warning can prompt the management personnel to quickly investigate and handle the problem, and push the warning information to relevant management personnel to ensure that responsible personnel can obtain key information in the first time. The pushed information can include detailed contents such as specific abnormal indicators, occurrence location and possible impact, helping the management personnel to quickly locate the problem and develop response strategies, which improves the effectiveness and pertinence of the warning information and reduces the delay and error of information transmission.

[0066] A grading discharge management method for urban sewage, specifically comprising:

[0067] Multi-source data fusion collection step: real-time collection of multiple types of water quality parameter data from different monitoring nodes of the urban sewage pipe network, integration of collection time and collection location information to form a multi-dimensional data set;

[0068] Complex water quality evaluation and grading step: calculating the sewage comprehensive pollution index based on the multi-factor dynamic weight comprehensive pollution index calculation formula, and grading the sewage according to the calculated sewage comprehensive pollution index and the preset multi-level grading threshold;

[0069] Intelligent discharge control and scheduling step: combining the topological structure of the urban sewage pipe network, the real-time treatment capacity of the sewage treatment plant and the environmental capacity of different receiving water bodies, intelligently deciding and automatically controlling the operation parameters of the corresponding sewage treatment equipment, the opening or closing of the sewage discharge channel and the flow distribution between different treatment units and discharge channels, to realize the precise grading discharge and optimization scheduling of different levels of sewage.

[0070] Preferably, the method further comprises:

[0071] Big data storage and analysis step: store the collected multi-dimensional data set, the calculated comprehensive pollution index of sewage and discharge grade information, the operation record of discharge control and scheduling, and mine the correlation between water quality change rule, discharge control effect and system operation efficiency based on big data analysis technology.

[0072] Preferably, the method further comprises:

[0073] Visual monitoring and early warning step: display the water quality distribution of urban sewage pipe network, the sewage discharge grade distribution, the sewage treatment equipment operation state and the discharge control effect in a graphical interface, and timely issue an audible and light alarm signal and push early warning information to relevant management personnel when the comprehensive pollution index of sewage exceeds the preset highest warning value or the concentration of a key water quality parameter exceeds the emergency threshold.

[0074] A computing device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the steps of the urban sewage grading discharge management method when executing the computer program.

[0075] A computer readable storage medium, wherein the storage medium stores a computer program, and the computer program is executed by a processor to implement the steps of the urban sewage grading discharge management method.

[0076] The above only describes the preferred embodiments of the present application and is not intended to limit the present application. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application shall be included in the protection scope of the present application.

Claims

1. A hierarchical discharge management system for municipal wastewater, characterized by, The system comprises: A multi-source data fusion acquisition module is configured to acquire real-time data of various types of water quality parameters from different monitoring nodes of the urban sewer network, and integrate the acquisition time and location information to form a multi-dimensional data set; A complex water quality evaluation and grading module is configured to receive the multi-dimensional data set transmitted by the multi-source data fusion acquisition module, calculate a comprehensive pollution index of sewage based on a multi-factor dynamic weight comprehensive pollution index calculation formula, and grade the sewage according to the calculated comprehensive pollution index of sewage and a plurality of preset grading thresholds; An intelligent discharge control and scheduling module is configured to determine the sewage discharge grade based on the complex water quality evaluation and grading module, combine the topological structure of the urban sewer network, the real-time processing capacity of the sewage treatment plant, and the environmental capacity of different receiving water bodies, and automatically control the operation parameters of the corresponding sewage treatment equipment, the opening or closing of the sewage discharge channel, and the flow distribution between different treatment units and discharge channels to achieve precise grading and optimized scheduling of different grades of sewage.

2. A system for managing the hierarchical discharge of municipal sewage according to claim 1, wherein The multi-factor dynamic weight comprehensive pollution index calculation formula is specifically as follows: ； wherein P is the comprehensive pollution index of sewage, is the measured concentration value of the i-th water quality parameter, is the national discharge standard limit value corresponding to the i-th water quality parameter, is the non-linear adjustment coefficient of the i-th water quality parameter, and ≥1, determined according to the sensitivity and cumulative effect of different water quality parameters on water pollution, is the dynamic weight coefficient of the i-th water quality parameter at time t, satisfying =1, and is dynamically adjusted according to the seasonal variation law of the water quality parameter, the urban sewage discharge law and the historical water quality data with time t.

3. A system for the hierarchical discharge management of municipal wastewater according to claim 2, characterized in that, The dynamic weight coefficient The calculation manner of the dynamic weight coefficient is specifically: ； wherein, is the base weight coefficient of the i-th water quality parameter, reflecting the importance of the water quality parameter to water pollution in general, is the time adjustment function of the i-th water quality parameter at time t, is calculated in the following manner: ； wherein , , is an adjustment factor, satisfying = 1, is a seasonal variation period of the i-th water quality parameter, is a phase angle for adjusting the start time of the seasonal variation, is a concentration variation amplitude of the i-th water quality parameter in a period of time before time t, is a maximum value of the concentration variation amplitude in the period of time.

4. The system for the hierarchical discharge management of municipal wastewater according to claim 3, characterized in that, The system further comprises: A big data storage and analysis module is configured to store the multi-dimensional data set acquired by the multi-source data fusion acquisition module, the comprehensive pollution index of sewage and the discharge grade information calculated by the complex water quality evaluation and grading module, and the operation records of the intelligent discharge control and scheduling module, and mine the correlation between water quality change rules, discharge control effect, and system operation efficiency based on big data analysis technology.

5. A system for managing the hierarchical discharge of municipal sewage according to claim 4, wherein The system further comprises: A visual monitoring and early warning module is configured to display the water quality distribution of the urban sewer network, the discharge grade distribution of the sewage, the operation state of the sewage treatment equipment, and the discharge control effect in a graphical interface, and timely issue an audible and visual alarm signal and push early warning information to relevant management personnel when the comprehensive pollution index of sewage exceeds a preset highest warning value or the concentration of a key water quality parameter exceeds an emergency threshold.

6. A method for hierarchical discharge management of municipal wastewater, characterized by, Specifically, the method comprises: A multi-source data fusion acquisition step: acquiring real-time data of various types of water quality parameters from different monitoring nodes of the urban sewer network, and integrating the acquisition time and location information to form a multi-dimensional data set; A complex water quality evaluation and grading step: calculating a comprehensive pollution index of sewage based on a multi-factor dynamic weight comprehensive pollution index calculation formula, and grading the sewage according to the calculated comprehensive pollution index of sewage and a plurality of preset grading thresholds; An intelligent discharge control and scheduling step: combining the topological structure of the urban sewer network, the real-time processing capacity of the sewage treatment plant, and the environmental capacity of different receiving water bodies, and automatically controlling the operation parameters of the corresponding sewage treatment equipment, the opening or closing of the sewage discharge channel, and the flow distribution between different treatment units and discharge channels to achieve precise grading and optimized scheduling of different grades of sewage.

7. The method for hierarchical discharge management of municipal wastewater according to claim 6, characterized in that The method further comprises: Big data storage and analysis step: store the collected multi-dimensional data set, the calculated comprehensive pollution index of sewage and discharge grade information, the operation record of discharge control and scheduling, and mine the correlation between water quality change rule, discharge control effect and system operation efficiency based on big data analysis technology.

8. The method for hierarchical discharge management of municipal wastewater according to claim 7, wherein, The method further comprises: Visual monitoring and early warning step: the water quality distribution of urban sewage pipe network, the sewage discharge grade distribution, the sewage treatment equipment operation state and the discharge control effect are displayed in graphical interface, when the comprehensive pollution index of sewage exceeds the preset highest warning value or the concentration of a key water quality parameter exceeds the emergency threshold value, the sound and light alarm signal is sent out in time, and the early warning information is pushed to the relevant management personnel.

9. A computing device, comprising: A computer program product comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the steps of the method for grading discharge management of urban sewage according to any one of claims 6-8 when executing the computer program.

10. A computer-readable storage medium, characterized in that, The storage medium has a computer program stored thereon, and the computer program is executed by the processor to implement the steps of the method for grading discharge management of urban sewage according to any one of claims 6-8.

Images