CN111982210B - Drainage pipe network batch monitoring and distribution method for diagnosing rainfall inflow infiltration problem - Google Patents
Drainage pipe network batch monitoring and distribution method for diagnosing rainfall inflow infiltration problem Download PDFInfo
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Abstract
The application discloses a drainage pipe network batch monitoring and point distribution method for diagnosing rainfall inflow infiltration problems, wherein the method comprises the following steps: dividing a target area into drainage subareas, and arranging first batch flow online monitoring points at drainage port positions of the drainage subareas; according to the first batch of flow data analysis, selecting a drainage subarea with the largest flow multiple in rainy days and dry days as a fine diagnosis subarea to arrange second batch of flow online monitoring points, and quantitatively analyzing the problem of rainfall inflow infiltration of the drainage subarea; and (3) selecting a drainage subarea with a larger flow multiple to arrange third batch of flow online monitoring points on the basis of the fine drainage subarea monitoring analysis result, and analyzing the whole rainfall inflow infiltration condition of the target area to form a rainfall inflow infiltration subarea graph. Therefore, the blindness of one-time monitoring distribution is avoided, the number of devices required by on-line monitoring and the monitoring cost are reduced, and the use efficiency of the monitoring devices and the accuracy of analysis results are improved.
Description
Technical Field
The application relates to the technical field of on-line monitoring and diagnosis of a drainage pipe network, in particular to a drainage pipe network batch monitoring and distribution method for diagnosing rainfall inflow infiltration problems.
Background
The inflow infiltration problem caused by rainfall is one of the main problems faced by urban sewage pipe networks in China, so that rainwater enters a sewage system through inflow and infiltration modes during rainfall, an inspection well overflows, the traffic and urban environment are affected, and the operation load and the treatment cost of a sewage treatment plant are increased. Monitoring and simulation are main means for analyzing and evaluating the rainfall inflow infiltration problem, wherein an online monitoring technology can identify the inflow infiltration position by obtaining flow data of monitoring points in dry days and rainy days, so that the improvement of a sewage pipe network can be guided, and the operation efficiency of a municipal sewage system is improved.
According to related research, the analysis of rainfall inflow infiltration can utilize 20% of monitoring points to find 80% of problems, and the reasonable arrangement of the online monitoring points can not only reduce the monitoring cost, but also improve the efficiency of problem identification. The related art indicates that one online monitoring point (corresponding to 6096 meters) can be provided for every 20000 feet of pipe. However, in consideration of the actual situation of cities and towns, the sewage pipe network data are not clear, the online monitoring application time of the drainage pipe network is short, the high-density online monitoring distribution is performed at one time, although the diagnosis of the rainfall inflow infiltration problem can be supported, the monitoring cost is too high, and therefore, in the actual diagnosis project, a method of monitoring distribution in a stepwise encryption and batch manner should be preferentially adopted.
At present, research and practice work does not have a clear systematic online monitoring and point distribution method for diagnosing the rainfall inflow infiltration problem, most of the methods only emphasize the general principles of considering the average distribution of monitoring point positions and selecting downstream main pipes as much as possible, lack quantitative indexes, mainly depend on subjective experience judgment of workers when carrying out batch point distribution, and do not establish a standardized monitoring and point distribution method and flow, thereby influencing the effectiveness of monitoring point position setting, increasing the cost required by carrying out monitoring work and reducing the efficiency of problem diagnosis.
In summary, at present, the application of drainage pipe network online monitoring in China is still in the initial exploration stage, the rainfall inflow infiltration problem diagnosis is carried out by using the flow online monitoring technology, quantitative analysis and accurate positioning both depend on reasonable arrangement of monitoring points, and due to the lack of unified indexes and methods, the arrangement of the monitoring points mainly depends on artificial subjective experience judgment, so that the efficiency of drainage pipe network rainfall inflow infiltration problem diagnosis is influenced, and the overall optimization and improvement of a drainage system cannot be supported sufficiently.
Content of application
The utility model provides a rainwater inflow infiltration problem diagnostic's drainage pipe network divides batch monitoring stationing method, has avoided the blindness of disposable monitoring stationing, reduces the required equipment quantity of on-line monitoring and monitoring cost, improves monitoring devices's availability factor and the accuracy of analysis result.
The embodiment of the first aspect of the application provides a drainage pipe network batch monitoring and distribution method for diagnosing a rainfall inflow infiltration problem, which comprises the following steps:
s1, combing the topological relation of a drainage pipe network of a target area, dividing drainage partitions of the target area, arranging first batch flow online monitoring points at drainage outlets of the drainage partitions, collecting the average flow of each first batch flow online monitoring point in a dry day and the average flow of rainfall in a field in a monitoring period, and calculating to obtain the flow multiple of each first batch flow online monitoring point;
s2, taking the drainage partition with the maximum flow multiple in the flow multiple of the first batch of flow online monitoring points as a fine partition, arranging second batch of flow online monitoring points, respectively counting each second batch of flow online monitoring points in dry days and rainy days, analyzing inflow infiltration conditions caused by rainfall in a catchment range corresponding to each second batch of flow online monitoring points, and obtaining the analysis results of the second batch of flow online monitoring points;
and S3, arranging a third batch of flow online monitoring points in a drainage partition with the flow multiple larger than a preset multiple in the flow multiple of the first batch of flow online monitoring points according to the analysis result, and analyzing the inflow infiltration condition caused by rainfall in the target area to form a rainfall inflow infiltration partition map.
Optionally, the step S1 includes:
dividing drainage partitions according to the drainage pipe network, administrative divisions, river water systems and land utilization information of the target area;
arranging a preset number of first batch flow online monitoring points at the discharge port of each drainage subarea or at the position close to a sewage plant downstream of a pipe network,
collecting and counting the drought day flow data of each first batch of flow online monitoring points, and calculating the drought day average flow of each first batch of flow online monitoring points;
collecting and counting the rainy day flow data of each first batch flow online monitoring point of at least two fields, and calculating the rainy day average flow of each first batch flow online monitoring point;
and calculating to obtain the flow multiple of each first batch flow online monitoring point according to the dry-day average flow of each first batch flow online monitoring point and the rainy-day average flow of each first batch flow online monitoring point.
Optionally, the division area of the drainage partition is 3-10km2。
Optionally, the step S2 includes:
sequencing the flow multiples of the first batch of flow online monitoring points obtained through calculation, taking the drainage subarea corresponding to the monitoring point with the largest flow multiple as a fine subarea, and arranging second batch of flow online monitoring points;
in the fine partition, carrying out second batch of flow online monitoring point arrangement on the main trunk nodes of the pipe network, wherein each 1-2km is carried out2There is one monitoring point;
collecting dry day flow data of each second batch of flow online monitoring points, and averaging flow values at all moments of continuous preset days to obtain flow characteristic values at all moments of the dry day;
collecting the rainy day flow data of each second batch of flow online monitoring points for preset days, and calculating the inflow infiltration amount of each second batch of flow online monitoring points caused by rainfall;
under each rainfall, counting the total rainfall and the inflow infiltration amount of each second batch of flow online monitoring points, and calculating the inflow infiltration amount of a unit area according to the catchment area corresponding to each second batch of flow online monitoring points;
and analyzing the correlation between the inflow infiltration amount of each rainfall unit area of each second batch of flow online monitoring points and the accumulated rainfall amount of each rainfall, obtaining a fitting curve through linear fitting, and taking the slope of the curve as the basis for evaluating the inflow infiltration of the rainfall of the second batch of flow online monitoring points.
Optionally, the flow multiple of each first batch of online flow monitoring point is calculated by the following formula:
βi＝Qi2/Qi1；
wherein, betaiIs the flow multiple, Q of the ith first batch flow online monitoring pointi1Average flow, Q, of the ith first batch flow on-line monitoring points on dry daysi2For the ith first batch flowAnd (4) the average flow of the line monitoring point field in the raining process, wherein i is a positive integer.
Optionally, the flow characteristic value of each time of the drought day is calculated by the following formula:
wherein Q isi1kThe average flow Q at the moment k of the ith second batch flow online monitoring point on the drought dayi1knAnd the instantaneous flow of the ith second batch of flow online monitoring point at the k moment of the nth drought day is obtained.
Optionally, the inflow infiltration amount of each second batch of flow online monitoring points caused by rainfall is calculated by the following formula:
Rimk＝Pimk-Qi1k；
wherein R isimkThe method comprises the steps that the inflow infiltration amount caused by rainfall at the k moment in a corresponding water receiving range under the mth rainfall of the ith second batch of flow online monitoring point is measured; qi11kThe average flow at the moment k of the ith second batch of flow online monitoring point is obtained; pimkAnd the flow is monitored at the kth moment of the ith second batch of flow online monitoring point under the mth rainfall.
Alternatively, the inflow infiltration per unit area is calculated by the following formula:
wherein r isimThe method comprises the steps that the inflow infiltration amount caused by rainfall in unit area in the corresponding water collection range under the mth rainfall of the ith second batch of flow online monitoring point is set; siThe catchment area corresponding to the ith second batch flow online monitoring point is obtained; t is the time interval for online data collection.
According to the method, the purpose of diagnosing the rainfall inflow infiltration problem is taken, the flow online monitoring points are distributed in batches in the target area, the whole distribution is subjected to fine diagnosis, and then the overall analysis is carried out, so that the blindness of one-time monitoring distribution is avoided, the number of devices and the monitoring cost required by online monitoring are reduced, and the use efficiency of the monitoring devices and the accuracy of analysis results are improved.
Additional aspects and advantages of the present application will be set forth in part in the description which follows and, in part, will be obvious from the description, or may be learned by practice of the present application.
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The foregoing and/or additional aspects and advantages of the present application will become apparent and readily appreciated from the following description of the embodiments, taken in conjunction with the accompanying drawings of which:
fig. 1 is a flowchart of a method for monitoring and distributing points of a drainage pipe network in batches for diagnosing a rainfall inflow infiltration problem according to an embodiment of the present application;
FIG. 2 is a schematic diagram illustrating a target area pipe network topology relationship combing according to an embodiment of the present application;
FIG. 3 is a schematic diagram of drainage zoning and first batch flow monitoring point placement according to one embodiment of the present application;
FIG. 4 is a schematic view of a fine drainage sector monitoring point arrangement according to one embodiment of the present application;
FIG. 5 is a schematic view of a flow rate variation curve under rainfall conditions according to an embodiment of the present application;
FIG. 6 is a schematic diagram of a third batch of traffic online monitoring points in a target area according to an embodiment of the present application;
FIG. 7 is a schematic illustration of a target area unit rainfall inflow infiltration distribution according to one embodiment of the present application;
fig. 8 is a flowchart of a method for monitoring distribution of drainage pipe network in batches for diagnosing the problem of rainfall inflow infiltration according to an embodiment of the present application.
Detailed Description
Reference will now be made in detail to embodiments of the present application, examples of which are illustrated in the accompanying drawings, wherein like or similar reference numerals refer to the same or similar elements or elements having the same or similar function throughout. The embodiments described below with reference to the drawings are exemplary and intended to be used for explaining the present application and should not be construed as limiting the present application.
The following describes a drainage pipe network batch monitoring and distribution method for diagnosing the rainfall inflow infiltration problem according to the embodiment of the present application with reference to the accompanying drawings.
Specifically, fig. 1 is a schematic flow chart of a drainage pipe network batch-wise monitoring and point-distributing method for diagnosing a rainfall inflow infiltration problem according to an embodiment of the present disclosure.
As shown in fig. 1, the method for monitoring and distributing the point of the drainage pipe network in batches for diagnosing the rainfall inflow infiltration problem comprises the following steps:
in step S1, the topological relation of the drainage pipe network in the target area is combed, the target area is divided into drainage partitions, first-batch flow online monitoring points are arranged at the drainage outlet of each drainage partition, the average flow of each first-batch flow online monitoring point in the dry day and the average flow of rainfall in the field in the monitoring period are collected, and the flow multiple of each first-batch flow online monitoring point is calculated.
Optionally, in some embodiments, step S1 includes: dividing drainage subareas according to drainage pipe networks, administrative divisions, river systems and land utilization information of a target area, wherein each drainage subarea has independence; the division area of the drainage subareas is 3-10km2The independence is shown in that the node can be obviously divided into boundaries with other drainage partitions, and drainage partition discharge openings can be positioned.
For example, the total sewage receiving area of the sewage treatment plant is about 71km2Mainly adopts split-flow drainage, is provided with 2 pump stations in total, combs the topological relation of the drainage pipe network, as shown in figure 2,
and (3) dividing the drainage subareas in the target area by taking the topological relation of the pipe network as a main basis, and dividing 11 drainage subareas in total.
And arranging a preset number of first batch flow online monitoring points at the position close to a sewage plant at the discharge port of each drainage subarea or at the downstream of the pipe network.
Specifically, 1-2 flow online monitoring points are arranged at the positions close to a sewage plant at the discharge port of each drainage subarea or at the downstream of a pipe network, and serve as first batch flow online monitoring points;
according to the drainage subarea division, online flow monitoring points are arranged at subarea nodes and a drainage port, if some drainage subareas basically have no drainage pipe network, the points are not distributed, 9 flow monitoring points are arranged in the first batch, and the positions are shown in fig. 3.
And collecting and counting the flow data of each first batch of flow online monitoring point on the dry day, and calculating the average flow of each first batch of flow online monitoring point on the dry day.
Specifically, collecting and counting the dry day flow data of each monitoring point, including working days and weekends, and calculating the dry day average flow Q of each monitoring point1；
Taking the monitoring point No. 8 as an example, the real-time flow change of 7 continuous days in dry seasons is obtained, on the whole trend, the flow peak value is near 12:00 and 21:00 of each day, the flow concave point is near 05:00 and 16:30, the flow on the weekend is slightly higher than that on the whole working day, and the drainage flow change accords with the domestic water usage rule of residents. The daily average flow at the 8 th point is 13139m3And d, calculating the average flow of each point in the dry season according to the continuous flow of each monitoring point in the dry season for 7 days.
Collecting and counting the rainy day flow data of each first batch of flow online monitoring point of at least two fields, and calculating the rainy day average flow of each first batch of flow online monitoring point.
Specifically, collecting flow data of first batch flow on-line monitoring points under 2 effective rainfall conditions, and calculating average flow Q of each first batch flow on-line monitoring point under rainfall2(ii) a Effective rainfall requires no rainfall for at least 48 hours before rainfall, and the cumulative rainfall of 24 hours is more than 10 mm.
And in the monitoring period of the first batch of distribution points, screening for 2 months, 15 days and 19 days, wherein the daily accumulated rainfall is 24.6mm and 20.50mm respectively, and respectively counting the average flow of 9 first batch of flow online monitoring points under two rains.
And calculating to obtain the flow multiple of each first batch flow online monitoring point according to the dry-day average flow of each first batch flow online monitoring point and the rainy-day average flow of each first batch flow online monitoring point.
Optionally, in some embodiments, the flow multiple of each first batch of online flow monitoring points is calculated by the following formula:
βi＝Qi2/Qi1；
wherein, betaiIs the flow multiple, Q of the ith first batch flow online monitoring pointi1Average flow, Q, of the ith first batch flow on-line monitoring points on dry daysi2The average flow of the ith first batch of flow in the field of on-line monitoring points in raining is measured, wherein i is a positive integer.
Specifically, calculating the flow multiple beta of each first batch of flow online monitoring point in rainy days and dry days:
βi＝Qi2/Qi1；
wherein beta isiFor the ith monitored flow multiple, Qi1Average flow, Q, for the dry day of the ith monitoring pointi2The average rainfall flow is the ith monitoring point field;
the average flow rate of the 9 monitoring points in dry weather and the average flow meter flow rate multiple under each rainfall field are shown in table 1.
TABLE 1
In step S2, the drainage partition with the largest flow multiple among the calculated flow multiples of the first batch of online flow monitoring points is used as a fine partition, and second batch of online flow monitoring points are arranged, each second batch of online flow monitoring point is counted in dry days and rainy days, and inflow infiltration caused by rainfall in a catchment range corresponding to each second batch of online flow monitoring point is analyzed to obtain an analysis result of the second batch of online flow monitoring points.
Optionally, in some embodiments, step S2 includes:
sequencing the flow multiples of the first batch of flow online monitoring points obtained through calculation, taking the drainage subarea corresponding to the monitoring point with the largest flow multiple as a fine subarea, and arranging second batch of flow online monitoring points;
specifically, the method can sequence the flow multiples beta of all the first-batch flow online monitoring points, and select the beta with the largest flow multipleimaxThe corresponding drainage subareas are used as fine drainage subareas to arrange second batch of flow online monitoring points;
according to the statistical result in table 1, the flow multiple of the monitoring point No. 6 is the largest, so the drainage subarea corresponding to the monitoring point No. 6 is taken as the fine drainage subarea.
In the fine partition, carrying out second batch of flow online monitoring point arrangement on the main trunk nodes of the pipe network, wherein each 1-2km is carried out2There is one monitoring point;
specifically, in the fine drainage subarea, the second batch of flow online monitoring points are arranged on the main trunk nodes of the pipe network, and the flow online monitoring points are ensured to be arranged every 1-2km2A monitoring point should be provided;
the second batch of flow online monitoring points in the fine drainage subarea are arranged as shown in FIG. 4, and 7 monitoring points are arranged in total.
Collecting dry day flow data of each second batch of flow online monitoring points, and averaging flow values at all moments of continuous preset days to obtain flow characteristic values at all moments of the dry day;
optionally, in some embodiments, the flow characteristic value at each time of the dry day is calculated by the following formula:
wherein Q isi1kThe average flow Q at the moment k of the ith second batch flow online monitoring point on the drought dayi1knAnd the instantaneous flow of the ith second batch of flow online monitoring point at the k moment of the nth drought day is obtained.
Specifically, the flow data of all second batch of flow online monitoring points in the fine drainage subarea in the effective dry day can be collected, and the flow values at all moments in 7 consecutive days are averaged to obtain flow characteristic values of the second batch of flow online monitoring points at all moments in the dry day;
continuously collecting real-time flow data of each point in a monitoring period from 3 months, 27 days to 4 months, 2 days as a dry day, and averaging flow values at each moment to obtain a characteristic flow value at each moment in the dry day;
wherein Qi1kIs the average flow at the ith monitoring point dry day k time, m3/s；Qi1knIs the instantaneous flow of the ith monitoring point at the k moment of the nth drought day, m3/s。
Collecting the rainy day flow data of each second batch of flow online monitoring points for preset days, and calculating the inflow infiltration amount of each second batch of flow online monitoring points caused by rainfall;
optionally, in some embodiments, the inflow infiltration amount of each second batch of traffic online monitoring points caused by rainfall is calculated by the following formula:
Rimk＝Pimk-Qi1k；
wherein R isimkThe method comprises the steps that the inflow infiltration amount caused by rainfall at the k moment in a corresponding water receiving range under the mth rainfall of the ith second batch of flow online monitoring point is measured; qi1kThe average flow at the moment k of the ith second batch of flow online monitoring point is obtained; pimkAnd the flow is monitored at the kth moment of the ith second batch of flow online monitoring point under the mth rainfall.
Specifically, the method and the device can collect flow data of 5 effective rains in the fine drainage subarea and calculate inflow infiltration R caused by rainfalli：
Under each rainfall, calculating the inflow infiltration amount caused by rainfall by time of each monitoring point within 24 hours
Rimk＝Pimk-Qi1k；
Wherein R isimkThe inflow infiltration amount caused by rainfall at the moment k in the corresponding water receiving range under the mth rainfall at the ith monitoring point, m3；Qi1kAverage for ith monitoring point dry day time kFlow rate, m3；PimkThe monitoring flow of the ith monitoring point at the kth moment under the mth rainfall, m3。
Under the conditions of 5 rainfall fields of 3 months, 2 days, 5 days, 9 days, 15 days and 22 days, field rainfall flow collection statistics is carried out on No. 10-15 monitoring points, and the rainfall of No. 14 points in 3 months and 2 days is taken as an example, and the flow change process is shown in FIG. 5.
Under each rainfall, counting the total rainfall and the inflow infiltration amount of each second batch of flow online monitoring points, and calculating the inflow infiltration amount of a unit area according to the catchment area corresponding to each second batch of flow online monitoring points;
alternatively, in some embodiments, the influent infiltration volume per unit area is calculated by the following formula:
wherein r isimThe method comprises the steps that the inflow infiltration amount caused by rainfall in unit area in the corresponding water collection range under the mth rainfall of the ith second batch of flow online monitoring point is set; siThe catchment area corresponding to the ith second batch flow online monitoring point is obtained; t is the time interval for online data collection.
It can be understood that under each rainfall, the total rainfall and the total inflow infiltration amount of each monitoring point are counted, and the inflow infiltration amount r of the unit area is calculated according to the catchment area corresponding to the monitoring pointsim
Wherein r isimThe unit area of the inflow infiltration amount caused by rainfall in the corresponding water receiving range of the ith monitoring point under the mth rainfall field, m3/km2；SiFor the catchment area, km, corresponding to the ith monitoring point2(ii) a t is the time interval for online data collection, min.
Taking the monitoring point No. 14 as an example, the corresponding water receiving area is 8.17km2In the screened 5-rain condition, the inflow infiltration amount per rain and the inflow infiltration amount per unit area are shown in table 2.
TABLE 2
| Rainy day | Rainfall (mm) | Infiltration of rainfall inflow (m)3) | Inflow per unit area (m)3/km2) |
| 3 month and 2 days | 31.7 | 13168.18 | 1611.58 |
| 3 month and 5 days | 17 | 8896.49 | 1088.79 |
| 3 month and 9 days | 33.5 | 13351.40 | 1634.00 |
| 3 month and 15 days | 14.6 | 4075.25 | 498.75 |
| 3 month22 days | 17.8 | 3776.60 | 462.20 |
And analyzing the correlation between the inflow infiltration amount of each rainfall unit area of each second batch of flow online monitoring points and the accumulated rainfall amount of each rainfall, obtaining a fitting curve through linear fitting, and taking the slope of the curve as the basis for evaluating the inflow infiltration amount of the rainfall of the second batch of flow online monitoring points.
Therefore, the method and the device can perform correlation analysis on the inflow infiltration amount of each rainfall unit area of each monitoring point and the accumulated rainfall amount of each rainfall, obtain a fitting curve by utilizing linear fitting, and take the slope of the curve as the basis for evaluating the inflow infiltration amount of the rainfall of the monitoring point
y＝ax+b；
Y in the curve formula is the inflow infiltration amount of the unit area of the monitoring point; x is rainfall; the slope a of the curve indicates that every 1km of rainfall will be produced for every 1mm increase2Inflow infiltration volume in the pipe network of the water receiving range. It should be noted that, correlation analysis is performed on the inflow infiltration amount per unit area of rainfall at each monitoring point and the accumulated rainfall amount per rainfall, a fitting curve is obtained by linear fitting, a pearson correlation coefficient is needed to be used to check the correlation degree between the inflow infiltration amount and the accumulated rainfall amount, and the correlation degree should be greater than 0.7.
Specifically, as the rainfall is larger, the rainfall inflow infiltration value per unit area is larger, linear fitting is carried out on the unit area inflow infiltration value and the rainfall, a fitting curve formula corresponding to the monitoring point No. 14 is obtained, the fitting curve formula is that y is 52.826 x-266.3, the Pearson correlation coefficient is as high as 0.9, the correlation is high, namely, when the rainfall is 4.6mm, the flow rate can be responded, and on the basis, the rainfall can be increased by 1mm to cause the situation that the rainfall per 1km is increased by 1mm2Inflow infiltration amount of 52.826m in pipe network of water receiving area3。
In step S3, a third batch of online flow monitoring points are arranged in drainage partitions where the flow multiple is greater than the preset multiple among the flow multiple of the online flow monitoring points of the first batch according to the analysis result, and inflow infiltration caused by rainfall in the target area is analyzed to form a rainfall inflow infiltration partition map.
It can be understood that the drainage subarea with the flow multiple beta being more than or equal to 1.5 can be selected for carrying out encryption arrangement on the online flow monitoring points, and the encryption arrangement can be ensured to be carried out every 2-3km2A monitoring point is needed, and if the target area flow multiple beta is less than 1.5, the rainfall inflow infiltration problem of the area is not serious as a whole;
in the case area, except the monitoring point No. 6, monitoring points with the flow multiple beta of more than or equal to 1.5 in rainy days and dry days in the monitoring points of the first batch are monitoring points No. 4, 8 and 9, and the third batch of encrypted points distribution is carried out in the corresponding drainage subareas, as shown in FIG. 6.
Further, collecting the flow data of the screened drainage subarea monitoring points and the flow data of the drainage subarea discharge openings in the step S1, and performing inflow infiltration quantitative analysis during rainfall of each monitoring point;
the inflow infiltration value per unit area of rainfall can be obtained by analyzing the data of all 21 flow monitoring points, as shown in table 3.
TABLE 3
| Numbering | 1 | 2 | 3 | 4 | 5 | 6 | 7 |
| Inflow infiltration | 20.27 | 26.83 | 43.73 | 66.23 | 30.45 | 974.76 | 828.33 |
| Numbering | 8 | 9 | 10 | 11 | 12 | 13 | 14 |
| Inflow infiltration | 489.72 | 112.34 | 472.32 | 113.22 | 1023.43 | 156.89 | 52.70 |
| Numbering | 15 | 16 | 17 | 18 | 19 | 20 | 21 |
| Inflow infiltration | 1784.10 | 39.76 | 67.54 | 369.89 | 699.82 | 99.54 | 120.56 |
Furthermore, the rainfall inflow infiltration distribution map of the target area can be drawn according to the result of quantitative analysis of the data of the three batches of monitoring points.
Based on the monitoring analysis results, classification is performed according to [0,50 ], [50,100 ], [100,500 ], [500,1000) and [1000, ∞), and characterization is performed by using different patterns and color blocks, so that a distribution map of rainfall inflow infiltration of the whole target region can be obtained, as shown in fig. 7.
In order to enable those skilled in the art to further understand the drainage pipe network batch monitoring and point distribution method for diagnosing the rainfall inflow infiltration problem in the embodiment of the present application, as shown in fig. 8, the present application performs drainage partition division on a target area, and performs first batch flow online monitoring point distribution at a drainage partition discharge port position; according to the first batch of flow data analysis, selecting a drainage subarea with the largest multiple of flow in rainy days and dry days as a fine diagnosis subarea to carry out second batch of flow online monitoring point arrangement, and quantitatively analyzing the problem of rainfall inflow infiltration of the drainage subarea; and on the basis of the monitoring and analysis results of the fine drainage subareas, selecting the drainage subareas with larger flow multiples to arrange flow online monitoring points of a third batch, and analyzing the whole rainfall inflow infiltration condition of the target area to form a rainfall inflow infiltration subarea graph.
According to the drainage pipe network batch monitoring and distribution method for diagnosing the rainfall inflow infiltration problem, which is provided by the embodiment of the application, the aim of diagnosing the rainfall inflow infiltration problem is fulfilled, the batch flow online monitoring points are distributed in a target area, the whole area is subjected to fine diagnosis and then is subjected to global analysis, the blindness of one-time monitoring and distribution is avoided, the number of devices and the monitoring cost required by online monitoring are reduced, and the use efficiency of monitoring devices and the accuracy of analysis results are improved.
In the description herein, reference to the description of the term "one embodiment," "some embodiments," "an example," "a specific example," or "some examples," etc., means that a particular feature, structure, material, or characteristic described in connection with the embodiment or example is included in at least one embodiment or example of the application. In this specification, the schematic representations of the terms used above are not necessarily intended to refer to the same embodiment or example. Furthermore, the particular features, structures, materials, or characteristics described may be combined in any suitable manner in any one or N embodiments or examples. Furthermore, various embodiments or examples and features of different embodiments or examples described in this specification can be combined and combined by one skilled in the art without contradiction.
Furthermore, the terms "first", "second" and "first" are used for descriptive purposes only and are not to be construed as indicating or implying relative importance or implicitly indicating the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include at least one such feature. In the description of the present application, "N" means at least two, e.g., two, three, etc., unless specifically limited otherwise.
Any process or method descriptions in flow charts or otherwise described herein may be understood as representing modules, segments, or portions of code which include one or more N executable instructions for implementing steps of a custom logic function or process, and alternate implementations are included within the scope of the preferred embodiment of the present application in which functions may be executed out of order from that shown or discussed, including substantially concurrently or in reverse order, depending on the functionality involved, as would be understood by those reasonably skilled in the art of implementing the embodiments of the present application.
The logic and/or steps represented in the flowcharts or otherwise described herein, e.g., an ordered listing of executable instructions that can be considered to implement logical functions, can be embodied in any computer-readable medium for use by or in connection with an instruction execution system, apparatus, or device, such as a computer-based system, processor-containing system, or other system that can fetch the instructions from the instruction execution system, apparatus, or device and execute the instructions. For the purposes of this description, a "computer-readable medium" can be any means that can contain, store, communicate, propagate, or transport the program for use by or in connection with the instruction execution system, apparatus, or device. More specific examples (a non-exhaustive list) of the computer-readable medium would include the following: an electrical connection (electronic device) having one or N wires, a portable computer diskette (magnetic device), a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber device, and a portable compact disc read-only memory (CDROM). Additionally, the computer-readable medium could even be paper or another suitable medium upon which the program is printed, as the program can be electronically captured, via for instance optical scanning of the paper or other medium, then compiled, interpreted or otherwise processed in a suitable manner if necessary, and then stored in a computer memory.
It should be understood that portions of the present application may be implemented in hardware, software, firmware, or a combination thereof. In the above embodiments, the N steps or methods may be implemented in software or firmware stored in a memory and executed by a suitable instruction execution system. If implemented in hardware, as in another embodiment, any one or combination of the following techniques, which are known in the art, may be used: a discrete logic circuit having a logic gate circuit for implementing a logic function on a data signal, an application specific integrated circuit having an appropriate combinational logic gate circuit, a Programmable Gate Array (PGA), a Field Programmable Gate Array (FPGA), or the like.
It will be understood by those skilled in the art that all or part of the steps carried by the method for implementing the above embodiments may be implemented by hardware related to instructions of a program, which may be stored in a computer readable storage medium, and when the program is executed, the program includes one or a combination of the steps of the method embodiments.
In addition, functional units in the embodiments of the present application may be integrated into one processing module, or each unit may exist alone physically, or two or more units are integrated into one module. The integrated module can be realized in a hardware mode, and can also be realized in a software functional module mode. The integrated module, if implemented in the form of a software functional module and sold or used as a stand-alone product, may also be stored in a computer readable storage medium.
The storage medium mentioned above may be a read-only memory, a magnetic or optical disk, etc. Although embodiments of the present application have been shown and described above, it is understood that the above embodiments are exemplary and should not be construed as limiting the present application, and that variations, modifications, substitutions and alterations may be made to the above embodiments by those of ordinary skill in the art within the scope of the present application.
Claims (6)
1. A drainage pipe network batch monitoring and point distribution method for diagnosing rainfall inflow infiltration problems is characterized by comprising the following steps:
s1, combing the topological relation of a drainage pipe network of a target area, dividing the drainage area into drainage partitions, arranging first-batch flow online monitoring points at the drainage outlet of each drainage partition, collecting the average flow of each first-batch flow online monitoring point in a dry day and the average flow of rainfall in a monitoring period, and calculating to obtain the flow multiple of each first-batch flow online monitoring point, wherein the flow multiple of each first-batch flow online monitoring point is as follows:
βi＝Qi2/Qi1；
wherein, betaiIs the flow multiple, Q of the ith first batch flow online monitoring pointi1Average flow, Q, of the ith first batch flow on-line monitoring points on dry daysi2The average flow of the ith first batch of flow in the field is monitored on line, wherein i is a positive integer;
s2, taking the drainage partition with the maximum flow multiple among the flow multiples of the first batch of flow online monitoring points obtained through calculation as a fine partition, arranging second batch of flow online monitoring points, respectively counting each second batch of flow online monitoring points in dry days and rainy days, analyzing inflow infiltration conditions caused by rainfall in a catchment range corresponding to each second batch of flow online monitoring points, and obtaining analysis results of the second batch of flow online monitoring points, wherein the step S2 further comprises the following steps: sequencing the flow multiples of the first batch of flow online monitoring points obtained through calculation, taking the drainage subarea corresponding to the monitoring point with the largest flow multiple as a fine subarea, and arranging second batch of flow online monitoring points; in the fine partition, carrying out second batch of flow online monitoring point arrangement on the main trunk nodes of the pipe network, wherein each 1-2km is carried out2There is one monitoring point; collecting dry day flow data of each second batch of flow online monitoring points, and averaging flow values at all moments of continuous preset days to obtain flow characteristic values at all moments of the dry day; collecting the rainy day flow data of each second batch of flow online monitoring points for preset days, and calculating the inflow infiltration amount of each second batch of flow online monitoring points caused by rainfall; under each rainfall, counting the total rainfall and the inflow infiltration amount of each second batch of flow online monitoring points, and calculating the inflow infiltration amount of a unit area according to the catchment area corresponding to each second batch of flow online monitoring points; analyzing the correlation between the inflow infiltration amount of each rainfall unit area of each second batch of flow online monitoring points and the accumulated rainfall amount of each rainfall, obtaining a fitting curve through linear fitting, and taking the slope of the curve as the rainfall inflow of the second batch of flow online monitoring pointsBasis for evaluation of influx infiltration;
and S3, arranging a third batch of flow online monitoring points in a drainage partition with the flow multiple larger than a preset multiple in the flow multiple of the first batch of flow online monitoring points according to the analysis result, and analyzing the inflow infiltration condition caused by rainfall in the target area to form a rainfall inflow infiltration partition map.
2. The method according to claim 1, wherein the step S1 includes:
dividing drainage partitions according to the drainage pipe network, administrative divisions, river water systems and land utilization information of the target area;
arranging a preset number of first batch flow online monitoring points at the position close to a sewage plant at the discharge port of each drainage subarea or at the downstream of a pipe network;
collecting and counting the drought day flow data of each first batch of flow online monitoring points, and calculating the drought day average flow of each first batch of flow online monitoring points;
collecting and counting the rainy day flow data of each first batch flow online monitoring point of at least two fields, and calculating the rainy day average flow of each first batch flow online monitoring point;
and calculating to obtain the flow multiple of each first batch flow online monitoring point according to the dry-day average flow of each first batch flow online monitoring point and the rainy-day average flow of each first batch flow online monitoring point.
3. The method as claimed in claim 2, wherein the drainage partition is divided into areas of 3-10km2。
4. The method of claim 1, wherein the flow characteristic value at each moment of the drought is calculated by the following formula:
wherein Q isi1kThe average flow Q at the moment k of the ith second batch flow online monitoring point on the drought dayi1knAnd the instantaneous flow of the ith second batch of flow online monitoring point at the k moment of the nth drought day is obtained.
5. The method of claim 1, wherein the inflow infiltration amount of each second batch of flow online monitoring points caused by rainfall is calculated by the following formula:
Rimk＝Pimk-Qi1k；
wherein R isimkThe method comprises the steps that the inflow infiltration amount caused by rainfall at the k moment in a corresponding water receiving range under the mth rainfall of the ith second batch of flow online monitoring point is measured; qi1kThe average flow at the moment k of the ith second batch of flow online monitoring point is obtained; pimkAnd the flow is monitored at the kth moment of the ith second batch of flow online monitoring point under the mth rainfall.
6. The method of claim 1, wherein the influent infiltration volume per unit area is calculated by the following formula:
wherein r isimThe method comprises the steps that the inflow infiltration amount caused by rainfall in unit area in the corresponding water collection range under the mth rainfall of the ith second batch of flow online monitoring point is set; siThe catchment area corresponding to the ith second batch flow online monitoring point is obtained; t is the time interval of online data collection; rimkAnd the flow infiltration amount caused by rainfall at the moment k in the corresponding water collection range under the mth rainfall is the ith second batch of flow online monitoring point.
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| CN116126963A (en) * | 2022-12-30 | 2023-05-16 | 哈尔滨航天恒星数据系统科技有限公司 | Inflow infiltration diagnosis method for nonlinear multi-source heterogeneous drainage model |
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