CN112700141B - Online analysis method for municipal drainage pipe network - Google Patents
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Abstract
An online analysis method for a municipal drainage pipe network solves the problems that the existing drainage pipe network is not flexible enough in model calculation results and poor in real-time guidance, and belongs to the cross field of municipal engineering, environmental engineering, management science and computer science. The invention comprises the following steps: s1, constructing a water drainage pipe network hydrodynamic water quality calculation engine; s2, arranging a scene pipe network water quality hydrodynamic operation task into a plurality of independent task units by using a drainage pipe network hydrodynamic water quality calculation engine, dynamically distributing and scheduling the task units on a cluster distributed architecture according to an instruction of a task scheduling center and data input into a drainage pipe network, completing scene simulation of the drainage pipe network, and obtaining a drainage pipe network hydrodynamic water quality calculation result; and S3, abstracting the drainage pipe network into a two-dimensional point-line directed weighting network according to a complex network theory, and analyzing the network topology structure of the drainage pipe network and the calculation result of the hydrodynamic water quality.
Description
Technical Field
The invention relates to an on-line analysis method for a municipal drainage pipe network based on a cluster distributed architecture and a complex network theory, and belongs to the cross field of municipal engineering, environmental engineering, management and computer science.
Background
The rapid development of the Internet of things, cloud computing and big data promotes the rapid promotion of the proposal of the concept of smart city and the test point work. The drainage pipe network system is one of important infrastructures in cities and is a key link of urban intelligent management. The design standard of the early drainage pipe network system in the city is low, and the attention degree is poor, so that the drainage pipe network system has the problems of disordered management system, serious silting and aging and the like. In addition, along with the acceleration of the urbanization process, the impervious earth surfaces such as grassland, farmland, woodland and the like are gradually replaced by the impervious earth surfaces such as grassland, farmland, woodland and the like, so that the rainwater drainage pressure born by the drainage pipe network system is continuously increased, the urban waterlogging phenomenon is frequent, and the intelligent construction of the urban drainage pipe network is urgent.
According to the regulations of the handbook of design for outdoor drainage, a mathematical model method is preferably adopted when the drainage pipe network calculates the water resource space-time distribution and the hydrodynamic water quality in the pipe network converging process. Therefore, the method for establishing the drainage pipe network model to realize the network system linear simulation of the multi-scene drainage pipe becomes a mainstream technical means for evaluating the current running situation of the pipe network, analyzing the urban waterlogging risk and optimizing the pipe network construction scheme. The development technical direction of the traditional drainage pipe network offline calculation model represented by SWMM, Infoworks ICM, MIKE URBAN and the like lies in the convenience of a data sorting process and the rapidness of numerical calculation, and the extremely important result analysis in the use process of the model is ignored, so that the problem that the calculation result data volume is huge but the guiding significance is not clear occurs. Meanwhile, the offline model can only be deployed and operated in a single computer, and the model operation result calling lacks flexibility and maneuverability, and has poor real-time guidance. Therefore, on the basis of the traditional drainage pipe network model, how to realize the online calculation and intelligent result analysis of the drainage pipe network becomes a key breakthrough problem for the development of the simulation field of the drainage pipe network.
Disclosure of Invention
The invention provides an online analysis method for a municipal drainage pipe network, which operates online and gives an analysis result, aiming at the problems that the existing drainage pipe network is not flexible enough in model calculation results and poor in real-time guidance.
The invention discloses an online analysis method of a municipal drainage pipe network, which comprises the following steps:
s1, constructing a water drainage pipe network hydrodynamic water quality calculation engine;
s2, arranging a scene pipe network water quality hydrodynamic operation task into a plurality of independent task units by using a drainage pipe network hydrodynamic water quality calculation engine, dynamically distributing and scheduling the task units on a cluster distributed architecture according to an instruction of a task scheduling center and data input into a drainage pipe network, completing scene simulation of the drainage pipe network, and obtaining a drainage pipe network hydrodynamic water quality calculation result;
and S3, abstracting the drainage pipe network into a two-dimensional point-line directed weighting network according to a complex network theory, and analyzing the network topology structure of the drainage pipe network and the calculation result of the hydrodynamic water quality.
Preferably, the S3 includes:
s31, abstracting the drainage pipe network into a two-dimensional point-line directed weighting network according to a complex network theory, wherein the points are middle-point-shaped structures of the drainage pipe network and are called nodes, and the lines are middle-point-shaped structures of the drainage pipe network and are called pipe sections;
s32, calculating the pipe section connecting weight in the drainage pipe network when the overflow pollution risk and the waterlogging risk are detected:
wijrepresenting the connection risk weight of each pipe section in the drainage pipe network;
when calculating risk of waterlogging, qijQ is the ratio of the pipe section flow to the minimum flow when calculating the risk of overflow contaminationijIs 1;
sijrepresents the ratio of the tube length to the smallest tube length;
when calculating the risk of overflow contamination,/ijFor the ratio of the contamination source distance to the minimum contamination source distance, when calculating the risk of waterlogging,/ijIs 1;
bijmeans for transporting by pipeline, including pressure flow and gravity flow, if pressureFlow, pair bijAssignment of-1, if gravity flow, for bijAssignment 1, ηijRepresenting the ratio of the design capacity of the drainage pipe network to the minimum design capacity; i and j represent the labels of two different nodes in the drainage pipe network;
s33, calculating risk transfer efficiency I between nodes in drainage pipe networkij：
dijRepresenting a node viTo vjThe distance of (d);
matrix of inter-node risk transfer efficiency I:
n represents the number of nodes in the drainage pipe network;
s34, calculating a risk comprehensive analysis matrix E:
E＝0.8I+0.1SN+0.1AN
wherein, SN represents a corresponding matrix of the affected node, AN represents a response matrix of the affected node;
s35, analyzing risk influence weight of nodes in the drainage pipe network:
obtaining the influence weight value w of each node at the overflow pollution risk and the waterlogging risk by the risk comprehensive analysis matrix Ei：
eijFor the elements in the risk analysis-by-synthesis matrix E,
according to the influence weight value w of each nodeiObtaining the risk influence weight factor w of the node by combining the self comprehensive strength of the nodei′；
S36, weighting factor w of risk influence on each nodeiAnd sequencing to obtain key influence nodes influencing the overflow pollution risk and waterlogging risk of the drainage pipe network.
As a preference, the first and second liquid crystal compositions are,
wherein,
denotes viTo vjThe number of shortest paths of (a) to (b),
representing a node viThe path length of all the nodes in the drainage pipe network is dijTotal number of paths of (a);
representing all nodes in the drainage network to node vjPath length dijTotal number of paths.
Preferably, in S1, the runoff yield calculation engine is configured to equate the runoff process in the catchment area to nonlinear reservoir drainage, and obtain the net change relationship of the depth d in the unit time t by using the runoff quality conservation equation:
wherein i represents the rainfall and snowmelt rate, e represents the surface evaporation rate, f represents the infiltration rate, and q represents the runoff;
preferably, in S1, the pipeline transmission calculation engine performs finite element difference solution on the mass and momentum conservation equation of the gradual change non-constant free surface flow by using an implicit euler method:
wherein x represents a distance, a represents a flow cross-sectional area, Q represents a flow rate, Z represents a canal inner bottom elevation, Y represents a canal water depth, H is Z + Y, and Z represents a canal inner bottom elevation; y represents the depth of the canal water; sfRepresenting a friction slope; g represents the gravitational acceleration.
Preferably, in S1, the water quality calculation engine is configured to solve a one-dimensional migration mass conservation equation of the soluble component canal:
wherein c represents the concentration of the component, u represents the longitudinal velocity, D represents the longitudinal diffusion coefficient, r (c) represents the reaction rate term, and x1 represents the longitudinal distance.
Preferably, in S2, the input data of the drainage pipe network includes drainage pipe network basic data, image and image data, drainage pipe network monitoring data and application scene data;
the drainage pipe network basic data comprise basic size and operation curve scheduling information of a drainage pipe network;
the image and image data comprise remote sensing image data and digital height chart data of the drainage pipe network;
the actual data of the drainage pipe network comprise sensor monitoring data and water quality detection data of the drainage pipe network;
the application scene data is time series of rainfall intensity under different rainfall conditions of the city and pollution time series of external pollutants.
Preferably, said S2 further comprises,
the method comprises the steps of adopting a data warehouse and a mass data storage strategy, carrying out warehouse division and table division on the database, splitting the database from multiple dimensions, dividing the database into multiple data slices, and storing the calculation result of the hydrodynamic water quality of the drainage pipe network into the corresponding data slices.
Preferably, the S2 further includes accessing the database by using a Redis caching technology and a read-write separation technology, dynamically displaying the calculation result of the hydrodynamic water quality of the drainage pipe network on line by using a data slice dynamic loading strategy and based on a WebGIS and data visualization technology.
Preferably, the online dynamic display comprises node water volume dynamic visual data display, pipe section flow rate dynamic visual data display, pipe section fullness dynamic visual data display, structure operation state visual data display and discharge port discharge process visual data display.
The invention has the beneficial effects that: the invention provides an online analysis method for a municipal drainage pipe network based on a cluster distributed architecture and a complex network theory, so that online multi-scene result simulation and intelligent operation result analysis of a municipal drainage pipe network model are realized, and important technical support is provided for prevention and control of urban waterlogging and overflow pollution and operation and maintenance of the municipal drainage pipe network. The effects of the invention are mainly reflected in the following: the online simulation calculation and online result analysis of the urban drainage pipe network model are realized, and the rapid and efficient online calculation of multiple scenes of the drainage pipe network is completed based on the cluster distributed architecture server; the online visual display of the simulation result of the urban drainage pipe network and the intelligent analysis of urban inland inundation and overflow pollution risks are realized, the risk transfer efficiency among nodes is comprehensively considered based on the complex network analysis, and the accuracy of the intelligent analysis result is obviously improved; the method provided by the invention has strong application adaptability, is not influenced by factors such as regions, pipe network scale and the like, and can be used for the simulation and intelligent analysis of the hydraulic water quality of the drainage pipe network of various large, medium and small cities only by inputting the data according to the standardized model.
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FIG. 1 is a schematic flow chart of an embodiment of the present invention;
FIG. 2 is a schematic view of an abstract overview of a research scope according to an embodiment of the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
It should be noted that the embodiments and features of the embodiments may be combined with each other without conflict.
The invention is further described with reference to the following drawings and specific examples, which are not intended to be limiting.
The online analysis method for the municipal drainage pipe network in the embodiment is characterized by comprising the following steps:
step one, constructing a water drainage pipe network hydrodynamic water quality calculation engine;
step two, a water quality hydrodynamic operation task of the scene pipe network is organized into a plurality of independent task units by utilizing a water quality hydrodynamic calculation engine of the drainage pipe network, and the task units are dynamically distributed and scheduled on a cluster distributed architecture according to an instruction of a task scheduling center and data input into the drainage pipe network, so that scene simulation of the drainage pipe network is completed, and a water quality hydrodynamic calculation result of the drainage pipe network is obtained;
step one and step two construct the online model of the drainage pipe network, input the data of the drainage pipe network, obtain the operation result of the model, namely: calculating the result of the water quality of the drainage pipe network by using hydrodynamic force;
and step three, abstracting the drainage pipe network into a two-dimensional point-line directed weighting network according to a complex network theory, and analyzing the network topology structure of the drainage pipe network and the calculation result of the hydrodynamic water quality. The step of the calculation engine of the hydrodynamic water quality of the drainage pipe network in the embodiment comprises a plurality of calculation engines for calculating the hydrodynamic water quality of the drainage pipe network; the calculation engine of the embodiment solves the runoff mass conservation equation, the pipeline transmission equation and the water quality diffusion equation by using a finite element method, and realizes calculation of a solving function by programming. The computing engine adopts a cluster distributed architecture, and completes construction of drainage pipe network runoff, transmission and water quality computing engines through steps of router resource scheduling, multi-level cache management, dynamic flexible configuration, combination of a plurality of computing functions and the like, so as to realize calling of a computing process in a cloud program.
Based on the multi-core capability of the cloud server, multi-process parallel computing is called, and stable and efficient computing capability and data mining capability are improved.
The building drainage pipe network hydrodynamic water quality calculation engine comprises a production flow calculation engine, a pipeline transmission calculation engine and a water quality calculation engine;
the runoff yield calculation engine is used for enabling the runoff process of the catchment area to be equivalent to nonlinear reservoir drainage, and the net change relation of the depth d in unit time t is obtained by utilizing the runoff quality conservation equation:
wherein i represents the rainfall and snowmelt rate, e represents the surface evaporation rate, f represents the infiltration rate, and q represents the runoff;
the pipeline transmission calculation engine is used for carrying out finite element difference solution on a mass and momentum conservation equation of the gradual change non-constant free surface flow by using an implicit Euler method:
wherein x represents a distance, a represents a flow cross-sectional area, Q represents a flow rate, Z represents a canal inner bottom elevation, Y represents a canal water depth, H is Z + Y, and Z represents a canal inner bottom elevation; y represents the depth of the canal water; sfRepresenting a friction slope; g represents the gravitational acceleration.
The water quality calculation engine is used for solving a one-dimensional migration mass conservation equation of the soluble component pipe duct:
wherein c represents the concentration of the component, u represents the longitudinal velocity, D represents the longitudinal diffusion coefficient, r (c) represents the reaction rate term, and x1 represents the longitudinal distance.
When calculating the hydrodynamic water quality calculated by the drainage pipe network, the embodiment needs to determine a database for inputting data and storing data, wherein the input data comprises drainage pipe network basic data, image and image data, drainage pipe network monitoring data and application scene data;
the basic data of the drainage pipe network comprises basic size and operation curve scheduling information of the drainage pipe network such as a drainage pipe section, an inspection well, a discharge port, a pump station, a gate, a regulation pool and the like;
the image and image data mainly comprise remote sensing image data and digital height chart data of the drainage pipe network;
the actual data of the drainage pipe network comprise sensor monitoring data and water quality detection data of an inspection well, a pump station, a discharge port, a regulation and storage water tank pipeline and the like;
the application scene data is time series of rainfall intensity under different rainfall conditions of the city and pollution time series of external pollutants.
The method is characterized in that floating point type calculation can be efficiently and stably carried out tens of millions of times per second, and the method is suitable for online calculation of the drainage pipe network.
The step two pairs of water drainage pipe network hydrodynamic force water quality calculation result visualization display of this embodiment specifically includes:
analyzing the calculation result of the water quality of the drainage pipe network by water power on line: and obtaining a model calculation result file by quickly calculating the hydrodynamic water quality calculation result of the drainage pipe network on line. And analyzing and extracting data information in the model operation result file according to the model operation result analysis rule, and finally outputting a data result in the csv format.
Storing the data of the calculation result of the hydrodynamic water quality of the drainage pipe network: the model operation result is a multi-dimensional time sequence result, so that the data volume is large. Therefore, on the basis of a distributed architecture, a database and a mass data storage strategy are adopted, the database is subjected to database division and table division, the database is split from multiple dimensions and divided into multiple data slices, and a model operation result is stored in the database.
The calculation result of the hydrodynamic water quality of the drainage pipe network is visually displayed: and accessing model operation result data by adopting a Redis cache technology, a read-write separation technology and the like. And dynamically displaying the model operation result data on line by adopting a data slice dynamic loading strategy and based on a WebGIS and a data visualization technology.
Step three of the embodiment is based on a complex network analysis theory, and the operation evaluation process of the urban drainage pipe network is constructed. Through the network topology structure to drainage pipe network, the comprehensive analysis of model operation results such as flow, quality of water, ponding volume reachs drainage pipe network risk influence weight ranking list to seek the key control point of risk influence, include:
step three, abstracting a drainage pipe network into a two-dimensional point-line directed weighting network according to a complex network theory, wherein the points are point structures such as inspection wells, discharge ports, regulation and storage pools, pump stations and the like in the drainage pipe network and are called nodes, and the lines are linear structures such as rainwater pipes, sewage pipes and the like in the drainage pipe network and are called pipe sections;
the complex network theory is a new management theory method, is suitable for network optimization problems formed by a large number of nodes and edges connected among the nodes, and can be extended to realize comprehensive assessment of urban waterlogging risks and overflow risks of a discharge port and decision of a target optimization control scheme in the field of drainage pipe network management.
And step two, calculating the weight of the connection side of the pipe sections in the drainage pipe network when the overflow pollution risk and the waterlogging risk are caused, calculating the weight of the connection side according to two dimensions of water quantity and water quality, wherein the larger the weight is, the larger the risk is. The risk of municipal drainage pipe network includes waterlogging risk and the overflow pollution risk of the aspect of quality of water in the aspect of the water yield two kinds, and the risk comes from inside hydraulic condition and the external pollution input in the water resource transmission process respectively. The weights are calculated as follows:
wijrepresenting the connection risk weight of each pipe section in the drainage pipe network;
when calculating risk of waterlogging, qijQ is the ratio of the pipe section flow to the minimum flow when calculating the risk of overflow contaminationijIs 1;
sijrepresents the ratio of the tube length to the smallest tube length;
when calculating the risk of overflow contamination,/ijFor the ratio of the contamination source distance to the minimum contamination source distance, when calculating the risk of waterlogging,/ijIs 1;
bijmeans for pipeline transportation, including pressure flow and gravity flow, if pressure flow, for bijAssignment of-1, if gravity flow, for bijAssignment 1, ηijRepresenting the ratio of the design capacity of the drainage pipe network to the minimum design capacity; i and j represent the labels of two different nodes in the drainage pipe network;
step three, calculating risk transfer efficiency I between nodes in drainage pipe networkijNode viTo vjDistance d ofijThe smaller, the transfer efficiency IijHigher, viFor vjThe higher the degree of influence of (c), i.e.:
dijrepresenting a node viTo vjThe distance of (d);
matrix of inter-node risk transfer efficiency I:
n represents the number of nodes in the drainage pipe network;
step four, calculating a risk comprehensive analysis matrix E, wherein the risk comprehensive analysis matrix E is obtained by three factors, namely a node risk transfer efficiency matrix I, a corresponding matrix SN of AN influencing node and a response matrix AN of the influenced node, namely:
e ═ 0.8I +0.1SN +0.1AN equation 8
Wherein, SN represents a corresponding matrix of the affected node, AN represents a response matrix of the affected node;
wherein,
denotes viTo vjThe number of shortest paths of (a) to (b),
representing a node viThe path length of all the nodes in the drainage pipe network is dijTotal number of paths of (a);
representing all nodes in the drainage network to node vjPath length dijTotal number of paths.
Step three, analyzing risk influence weights of nodes in the drainage pipe network:
derived from the risk analysis matrix EInfluence weight value w of each node in overflow pollution risk and waterlogging riski：
eijFor the elements in the risk analysis-by-synthesis matrix E,
according to the influence weight value w of each nodeiObtaining the risk influence weight factor w of the node by combining the self comprehensive strength of the nodei′；
Step three and six, weighting factor w of risk influence on each nodeiThe method includes the steps that sorting is carried out, key influence nodes influencing overflow pollution risks and waterlogging risks of the drainage pipe network are obtained, and therefore guidance suggestions are provided for operation and maintenance of the drainage pipe network.
The specific embodiment is as follows:
the S city is a typical rainy city in south, belongs to subtropical monsoon climate, and annual precipitation reaches 2000 mm. And S, extreme rainfall events such as heavy rainstorm and the like easily occur in summer in cities under the influence of typhoon weather, and urban waterlogging frequently occurs. And the urban inland river pollution condition in the city of S is also not optimistic, the main stream and the four branches of the urban inland river in the city of S are in poor V-class water quality, and the concentration of ammonia nitrogen and total phosphorus at the river mouth of the river in rainy season exceeds the standard of the surface water in the V-class. According to the pollutant source analysis, one of the important contributors of urban inland river pollution is combined system pollution overflow of a drainage pipe network. In view of the requirements on urban waterlogging prevention and overflow pollution prevention, an S-city drainage pipe network needs to be constructed with an intelligent analysis online model. The flow chart of the embodiment is shown in fig. 1;
step one, constructing a water drainage pipe network hydrodynamic water quality calculation engine
The HIT-IAOMDN model is used for constructing a calculation engine of a drainage pipe network based on a runoff mass conservation equation, a pipeline transmission equation and a water quality diffusion equation from formula 1 to formula 4. The establishing principle of the engine is that partial differential equations of a runoff process, a pipeline transmission process and a water quality diffusion process are solved by utilizing finite element open source codes, and are packaged into a dynamic link library dll, so that the calculation module is directly called and operated.
The engine calling process is based on the multi-core capability of the system, multi-process and multi-thread parallel computing is used, stable and efficient computing capability and data mining capability are improved, and the specific working process is as follows:
(1) and (3) scheduling router resources: the computing engines are distributed using routers according to task requirements and the current operating environment.
(2) Buffering input data: and sending the task data to a cache manager, and storing the task data into a cache to become cached data.
(3) Dynamic configuration: and loading a corresponding configuration file according to the characteristics of the calculation task, and dynamically calling a configuration function in the configuration file.
(4) And (3) calling a calculation engine library: in the task computing process, calling combination is carried out according to requirements, computing functions are called in a computing engine library, and results are stored in a computing result manager.
Step two, inputting parameters and obtaining calculation results
According to the general survey database of the S municipal drainage pipe network, the total length of the S municipal drainage pipe network is 1800km, the topological structure of the drainage pipe network is complex, the inspection well nodes are 27454, and the pipe sections of a rainwater pipe, a sewage pipe, a flow-combining pipe and the like are 24559, the municipal drainage facilities comprise 4 water quality purification plants, 30 large facilities such as a rainwater and sewage pump station and a water gate, and 497 drainage ports along a river, and the system belongs to an ultra-large complex network system.
The parameter input interface comprises four types of data, namely drainage pipe network information basic data, image and image data, a drainage pipe network monitoring database and rainfall and pollution input data, wherein each type of data needs to be input according to a specified system standard format. And calling a calculation engine to perform model operation calculation after the parameters are subjected to logic inspection.
(1) The basic data of the drainage pipe network mainly comprises basic size and operation curve scheduling information of the drainage pipe network such as a drainage pipe section, an inspection well, a discharge port, a pump station, a gate, a regulation pool and the like.
The pipe section information includes: pipe section ID, pipe section attribute, pipe length, pipe diameter, shape, starting point well, end point well, starting point offset and end point offset;
the inspection well information includes: the method comprises the following steps of (1) detecting well ID, ground elevation, pipe bottom elevation, detecting well attribute, detecting well position x value and detecting well position y value;
the discharge port information includes: discharge port ID, discharge port bottom elevation, discharge port size, discharge port position x value, discharge port position y value, and whether the valve is a flap valve;
the pump station information includes: pump station ID, water inlet inspection well ID, water outlet inspection well ID, lifting capacity, initial liquid level, pump station scheduling starting liquid level, pump station scheduling closing liquid level and pump machine standby condition;
the gate information includes: the gate ID, the gate connecting pipe section ID, the gate size and the gate opening and closing liquid level;
the regulation pool information includes: the system comprises a regulation water pool ID, a regulation water pool water inlet pipe section ID, a regulation water pool water outlet pipe section ID, a regulation capacity and a regulation water pool operation opening and closing liquid level;
(2) the image and image data mainly comprise remote sensing image data and digital elevation map data
The remote sensing image data respectively stores remote sensing image images of three sources, namely LANDSAT8 multiband images, high-score six-number orthoimages and Google satellite images provided with data by Maxar;
the digital elevation map adopts a Google elevation map;
(3) the actual data of the drainage pipe network comprises the monitoring data of actual sensors such as inspection wells, pump stations, discharge ports, regulation and storage water tank pipelines and the like and the water quality detection data
The monitoring data includes: the liquid level of the inspection well, the liquid level and flow of the pump station, the flow of a discharge port, the liquid level of a regulating and storing pool, the flow of a pipeline, the flow rate of a flow rate and the like;
the detecting data includes: the method comprises the following steps of (1) carrying out sewage plant inlet water quality data, pump station forebay water quality data, regulation and storage water pool numerical data and the like;
(4) the rainfall and external pollutant input data includes a time series of rainfall intensity and a time series of pollution by the external pollutants
Rainfall sequence: rainfall time (year/month/day/hour/minute), rainfall intensity mm/h;
time series of contamination: an inspection well ID for contaminant injection, a contaminant name, time, a time sequence concentration value of the contaminant;
and (3) visually displaying a calculation result:
the visual display application comprises the processes of calculating data storage, data calling, visual dynamic effect display and the like. In the case, data display functions such as node water accumulation dynamic visualization, pipe section flow velocity dynamic visualization, pipe section fullness dynamic visualization, structure operation state visualization, discharge port discharge process visualization and the like are designed for an online model of an S city drainage pipe network. The specific implementation process is as follows:
(1) and (3) analyzing a calculation result: the original data obtained by the calculation engine is binary number, and the binary number is converted into decimal number by using a number system conversion algorithm;
(2) and (4) storing calculation result data: performing database division and table division on operation result data of the water quality hydrodynamic model of the drainage pipe network, dividing the operation result data into a plurality of data slices, and storing the operation result of the model into a database;
(3) visual display: and accessing the calculation result data by adopting a Redis cache technology, a read-write separation technology and the like. And dynamically displaying the calculation result data on line by adopting a data slice dynamic loading strategy and based on a WebGIS and a data visualization technology. Redis cache is adopted to accelerate access to a calculation result, data is reasonably and effectively transmitted to an access end by using strategies of data slicing and dynamic loading, and requirements of data transmission time and data display amount are balanced. And (4) combining with a WebGIS, and displaying a customized visual effect through multi-angle design of element types, positions, colors and the like.
Step three, intelligently analyzing waterlogging and overflow risks of urban drainage pipe network based on complex network analysis
The drainage pipe network topology structure of the S city is complex, and because the online analysis of the online waterlogging risk and the overflow risk is directly realized by adopting a program method in the embodiment, in order to explain the embodiment of the invention, a trunk pipe section and a node of a certain path of the S city are selected to perform the manual calculation process reproduction.
(1) Research scope and abstract model construction
According to the complex network theory, the drainage pipe network is abstracted into a two-dimensional point-line directional weighting network, wherein the points are point structures such as inspection wells, discharge ports, storage water tanks and pump stations, and the lines are linear structures such as rainwater pipes and sewage pipes. The research range of the embodiment comprises a complete rainwater main pipe and auxiliary branch pipes thereof, wherein the numbers v1-v25 are rainwater inspection wells, P26 is a discharge port, 1-25 are rainwater pipe sections, and the water flow direction is that the main pipe goes from west to east. As shown in fig. 2.
(2) And (3) calculating the weight of the pipeline connection edge: and calculating the side-to-side weight according to two dimensions of water quantity and water quality, wherein the larger the weight is, the larger the risk is. The risk of municipal drainage pipe network includes waterlogging risk and the overflow pollution risk of the aspect of quality of water in the aspect of the water yield two kinds, and the risk comes from inside hydraulic condition and the external pollution input in the water resource transmission process respectively.
Substituting the data of flow, pollutant concentration, pipe length, design flow and the like obtained by model prediction according to a formula 5 to obtain the weight w of each continuous edgeijThe calculation results are shown in table 1.
TABLE 1 pipe segment join weight wijCalculation table
(3) Inter-node risk transfer efficiency calculation
Efficiency of risk transfer between adjacent points Iij＝wijAnd not adjacent to the case of multiple nodes in the middle,
in the embodiment, the total number of the nodes is 25, and the size of the interaction matrix generated by two nodes is 25 x 25
The inter-node risk transfer efficiency matrix I can thus be calculated:
(4) risk analysis matrix calculation
And calculating SN and AN according to a formula 8 and a formula 9, and simultaneously combining the calculation result of the step two, obtaining a wind direction comprehensive analysis matrix E of the pipeline according to the formula 8, wherein E is a matrix of 25 x 25.
(5) Node risk impact weight analysis
And (4) obtaining the risk contribution importance of each node according to the risk comprehensive analysis matrix calculation result of the step (4) and the formula 11, the formula 12 and the formula 13. As shown in table 2.
TABLE 2 node waterlogging and overflow pollution risk contribution weight calculation Table
(6) Node weight ranking and key impact analysis
And obtaining key influence nodes influencing the waterlogging risk and the pollution risk of the drainage pipe network according to the risk weight value sequencing result, thereby providing guidance suggestions for the operation and maintenance of the drainage pipe network. The results of the sorting are shown in table 2 above. The specific conclusion is as follows:
in the rainwater pipe in the research range, the highest risk areas of waterlogging are concentrated near v5, v19, v1, v21 and v3 nodes, and the reasons for the waterlogging are that the downstream pipe diameter exceeds the capacity range, the catchment area is too large, the upstream branch pipeline has larger water inflow, so that the corresponding pipe network solutions are respectively pipeline diameter expansion, low-influence development and branch catchment pipeline reconstruction;
in a rainwater pipe in a research range, the regions with the highest contribution of overflow pollution risk sources of the discharge port P26 are concentrated near v25, v18, v17, v22 and v11 nodes, and the occurrence reasons of the overflow pollution risk sources are mainly convergence of external pollution sources, such as mixed connection of domestic sewage, mixed-system pollution input and the like, and the rain sewage flow division reconstruction or the construction of a catch well and a catch pipe is recommended to intercept the convergence of the domestic sewage.
Although the invention herein has been described with reference to particular embodiments, it is to be understood that these embodiments are merely illustrative of the principles and applications of the present invention. It is therefore to be understood that numerous modifications may be made to the illustrative embodiments and that other arrangements may be devised without departing from the spirit and scope of the present invention as defined by the appended claims. It should be understood that features described in different dependent claims and herein may be combined in ways different from those described in the original claims. It is also to be understood that features described in connection with individual embodiments may be used in other described embodiments.
Claims (9)
1. An online analysis method for a municipal drainage pipe network is characterized by comprising the following steps:
s1, constructing a water drainage pipe network hydrodynamic water quality calculation engine;
s2, arranging a scene pipe network water quality hydrodynamic operation task into a plurality of independent task units by using a drainage pipe network hydrodynamic water quality calculation engine, dynamically distributing and scheduling the task units on a cluster distributed architecture according to an instruction of a task scheduling center and data input into a drainage pipe network, completing scene simulation of the drainage pipe network, and obtaining a drainage pipe network hydrodynamic water quality calculation result;
s3, abstracting the drainage pipe network into a two-dimensional point-line directed weighting network according to a complex network theory, and analyzing the network topology structure of the drainage pipe network and the calculation result of hydrodynamic water quality;
the S3 includes:
s3l, abstracting the drainage pipe network into a two-dimensional dotted-line directed weighting network according to a complex network theory, wherein the central point is a point-shaped structure in the drainage pipe network and is called a node, and the line is a linear structure in the drainage pipe network and is called a pipe section;
s32, calculating the pipe section connecting weight in the drainage pipe network when the overflow pollution risk and the waterlogging risk are detected:
wijrepresenting the connection risk weight of each pipe section in the drainage pipe network;
when calculating risk of waterlogging, qijQ is the ratio of the pipe section flow to the minimum flow when calculating the risk of overflow contaminationijIs 1;
sijrepresents the ratio of the tube length to the smallest tube length;
when calculating the risk of overflow contamination,/ijFor the ratio of the contamination source distance to the minimum contamination source distance, when calculating the risk of waterlogging,/ijIs 1;
bijmeans for pipeline transportation, including pressure flow and gravity flow, if pressure flow, for bijAssignment of-1, if gravity flow, for bijAssignment 1, ηijRepresenting the ratio of the design capacity of the drainage pipe network to the minimum design capacity; i and j represent the labels of two different nodes in the drainage pipe network;
s33, calculating risk transfer efficiency I between nodes in drainage pipe networkij：
dijRepresenting a node viTo vjThe distance of (d);
matrix of inter-node risk transfer efficiency I:
n represents the number of nodes in the drainage pipe network;
s34, calculating a risk comprehensive analysis matrix E:
E＝0.8I+0.1SN+0.1AN
wherein SN represents AN influencing node response matrix, AN represents AN influenced node response matrix;
s35, analyzing risk influence weight of nodes in the drainage pipe network:
obtaining the influence weight value w of each node at the overflow pollution risk and the waterlogging risk by the risk comprehensive analysis matrix Ei：
eijFor the elements in the risk analysis-by-synthesis matrix E,
according to the influence weight value w of each nodeiObtaining the risk influence weight factor w of the node by combining the self comprehensive strength of the nodei′；
S36, weighting factor w of risk influence on each nodeiAnd sequencing to obtain key influence nodes influencing the overflow pollution risk and waterlogging risk of the drainage pipe network.
2. The on-line analysis method of municipal drainage pipe network according to claim 1, wherein,
wherein,
denotes viTo vjThe number of shortest paths of (a) to (b),
representing a node viThe path length of all the nodes in the drainage pipe network is dijTotal number of paths of (a);
representing all nodes in the drainage network to node vjPath length dijTotal number of paths.
3. The on-line analysis method for the urban drainage pipe network according to claim 2, wherein the drainage pipe network hydrodynamic water quality calculation engine in S1 comprises an runoff yield calculation engine, and the runoff yield calculation engine is used for equating a runoff process of a catchment area to nonlinear reservoir drainage and obtaining a net change relation of depth d in unit time t by using a runoff quality conservation equation:
in the formula, i represents the rainfall and snowmelt rate, e represents the surface evaporation rate, f represents the infiltration rate, and q represents the runoff rate.
4. The on-line analysis method for the municipal drainage pipe network according to claim 2, wherein the drainage pipe network hydrodynamic water quality calculation engine in S1 comprises a pipe transmission calculation engine, and the pipe transmission calculation engine performs finite element differential solution on the conservation of mass and momentum equation of the gradual change non-constant free surface flow by using an implicit euler method:
wherein x represents distance, a represents flow cross-sectional area, Q represents flow rate, H ═ Z + Y, and Z represents the inner bottom elevation of the canal; y represents the depth of the canal water; sfRepresenting a friction slope; g represents the gravitational acceleration.
5. The on-line analysis method for the municipal drainage pipe network according to claim 2, wherein in S1, the water quality calculation engine solves the one-dimensional migration mass conservation equation for the soluble component canal:
wherein c represents the concentration of the component, u represents the longitudinal velocity, D represents the longitudinal diffusion coefficient, r (c) represents the reaction rate term, and x1 represents the longitudinal distance.
6. The method for analyzing the municipal drainage pipe network according to claim 2, wherein in S2, the input data of the drainage pipe network comprises drainage pipe network basic data, image and image data, drainage pipe network monitoring data and application scene data;
the drainage pipe network basic data comprise basic size and operation curve scheduling information of a drainage pipe network;
the image and image data comprise remote sensing image data and digital height chart data of the drainage pipe network;
the actual data of the drainage pipe network comprise sensor monitoring data and water quality detection data of the drainage pipe network;
the application scene data is time series of rainfall intensity under different rainfall conditions of the city and pollution time series of external pollutants.
7. The municipal drainage pipe network on-line analysis method according to claim 2, wherein said S2 further comprises,
the method comprises the steps of adopting a data warehouse and a mass data storage strategy, carrying out warehouse division and table division on the database, splitting the database from multiple dimensions, dividing the database into multiple data slices, and storing the calculation result of the hydrodynamic water quality of the drainage pipe network into the corresponding data slices.
8. The method for on-line analysis of the municipal drainage pipe network according to claim 7, wherein S2 further comprises accessing the database by using Redis caching technology and read-write separation technology, dynamically loading the data slice, and dynamically displaying the result of the hydrodynamic water quality calculation of the drainage pipe network on line based on WebGIS and data visualization technology.
9. The method for on-line analysis of the municipal drainage pipe network according to claim 7, wherein the on-line dynamic display comprises node water accumulation dynamic visual data display, pipe section flow rate dynamic visual data display, pipe section fullness dynamic visual data display, structure operation state visual data display and discharge port discharge process visual data display.
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