A method for judging a key inflow area based on sewer network on-line monitoring

Abstract

The application relates to the field of sewer network detection, and discloses a method for judging a key inflow area based on on-line monitoring of a sewer network, which comprises the following steps: determining a segmented sewer network, and obtaining monitoring data of the sewer network; loading a segmented mass balance model; the segmented mass balance model is used for expressing the relationship among inflow sewage characteristics, background sewage characteristics, directly received external water characteristics and mixed out sewage characteristics of each segment, and the inflow severity; calculating an inflow severity coefficient; according to the inflow severity coefficient, calculating the segmented external water flow of each segment of the sewer network based on the segmented mass balance model; and according to the segmented external water flow, sorting each segment of the sewer network, and judging the key inflow area. According to the above technical scheme, the key inflow area can be judged, a basis can be provided for determining a network checking strategy, the overall checking cost can be reduced, and the checking efficiency can be improved.

Description

Technical Field

[0001] This invention relates to the field of drainage pipe network inspection, and more specifically, to a method for identifying key inflow areas based on monitoring along the drainage pipe network. Background Technology

[0002] In the in-depth inspection and repair of drainage pipe networks, the inflow of external water is a key factor affecting sewage transport efficiency, sewage treatment capacity, and pollution risk. Analyzing the inflow of external water based on water quantity and quality monitoring data is crucial for identifying problematic pipe sections, optimizing inspection resources, and developing precise repair strategies.

[0003] However, existing external water inflow analysis techniques have significant limitations in practical applications. On the one hand, some research teams use characteristic compounds (such as acesulfame potassium and other artificial sweeteners) as tracers for measurement and modeling, inferring the source and inflow of external water by detecting changes in their concentration in the pipe network. However, such methods are costly to measure, and model construction relies on a large number of prior parameters and complex calibration processes, making them difficult to promote and apply in routine operation and maintenance scenarios. At the same time, the environmental background concentration of characteristic compounds is difficult to obtain accurately due to factors such as regional dietary habits and hydrogeological conditions, resulting in large fluctuations in the accuracy of modeling results and insufficient reliability. On the other hand, traditional hydraulic analysis methods (such as the triangulation method and the minimum nighttime flow method) are based on specific hydraulic assumptions and calculate the area-scale external water inflow through flow balance or concentration gradient. These methods make many assumptions, have stringent requirements for the spatiotemporal continuity of monitoring data, and can only achieve quantitative estimation of external water at the area level. They cannot further locate the key inflow areas of specific pipe sections or nodes, making it difficult to meet the spatial targeting requirements of remediation projects. Furthermore, in actual engineering projects, the design of water quality and quantity monitoring point layout schemes and data analysis often rely on the experience and judgment of engineers, lacking systematic methodological guidance. This leads to unreasonable allocation of monitoring resources, highly subjective analysis results, and poor repeatability, making it difficult to support the transformation of pipeline network operation and maintenance from experience-driven to data-driven.

[0004] Therefore, a technical solution is needed that, based on conventional water quality and quantity monitoring data, systematically identifies each inflow area of ​​the drainage network, calculates the inflow degree of each area, and then classifies each area and determines the investigation strategy, thereby reducing the overall investigation cost and improving detection efficiency. Summary of the Invention

[0005] To achieve the above objectives, this application provides a method for identifying key inflow areas based on pipeline monitoring along drainage networks, comprising the following steps: Determine the segments of the drainage network and obtain monitoring data for the network; the monitoring data includes the output flow of each segment. Segmented output of wastewater concentration Segmented input flow Segmented inflow sewage concentration ; Load the segmented mass balance model; the segmented mass balance model is used to express the relationship and inflow severity of the characteristics of inflow wastewater, background wastewater, directly received external water, and mixed outflow wastewater in each segment; the inflow severity is expressed by the inflow severity coefficient. This is reflected in the segmented quality balance model, where an inflow severity coefficient is defined. This indicates the ratio of the segmented external water flow to the segmented background flow; The severity coefficient of the inflow is calculated based on the segmented output flow rate, segmented output wastewater concentration, segmented input flow rate, and the ratio between the segmented inflow wastewater concentration and the background wastewater concentration. ; Based on the severity coefficient of inflow Based on monitoring data and a segmented mass balance model, the external water flow rate of each segment of the drainage network is calculated. The segmented external water flow rate Used to reflect the actual inflow rate of each segment; Based on segmented external water flow The drainage pipe network is sorted into different sections to identify key inflow areas.

[0006] The segmented mass balance model is expressed as follows: , , in, For segmented input flow, To segment the concentration of incoming sewage, For segmented output flow, To output wastewater concentration in stages, For segmented baseline flow, To segment the background wastewater concentration, For the severity coefficient of inflow, The pollution coefficient is determined by the impact of external water.

[0007] Before loading the segmented mass balance model, construct the segmented mass balance model; The construction process of the segmented mass balance model includes: Establish the mass balance equation for each segment, expressed as: , , in, For segmented output flow, To output wastewater concentration in stages, For segmented baseline flow, To segment the background wastewater concentration, For segmented input flow, To segment the concentration of incoming sewage, For segmented external water flow, The concentration of external wastewater; Pollution coefficient influenced by external water Determine the concentration of external wastewater , is represented as: ; The inflow severity coefficient α is defined as the multiple of the external water flow rate in a segment relative to the background flow rate in that segment, expressed as: ; The mass balance equation is simplified to form a piecewise mass balance model.

[0008] Furthermore, the severity coefficient of the inflow The calculation method is as follows: ,in, The coefficient represents the difference between the segmented input and output.

[0009] The method for calculating the coefficient K of the piecewise input-output difference is as follows: ,in, For segmented output flow, To output wastewater concentration in stages, To segment the background wastewater concentration, For segmented input flow, The concentration of wastewater flowing in at different stages.

[0010] Furthermore, the external water flow rate of each section of the drainage pipe network. The calculation method is as follows: .

[0011] Among them, segmented output flow Segmented output of wastewater concentration Segmented input flow Segmented inflow sewage concentration These are the measurement values ​​obtained from monitoring along the route; External water impact pollution coefficient The preset value range is 0 to 0.05.

[0012] Furthermore, the severity coefficient of the inflow The calculation method also includes: obtaining the total number of sewage outlets, randomly sampling N sewage outlets, measuring the output flow of each of the N sewage outlets, obtaining the average estimated flow of each sewage outlet, multiplying the average estimated flow by the total number of sewage outlets to obtain the estimated value of the total background flow; measuring the total input flow and total output flow at the beginning and end of the pipe section respectively, and then using the equation... Calculate the external water volume; divide the external water volume by the total background flow rate to obtain the α value.

[0013] According to the present invention, the effectiveness of quantitative calculation data can be improved, the stability of the calculation model can be improved, and the measurement cost and implementation difficulty can be effectively reduced. At the same time, the identification of key inflow areas through the present invention can provide a basis for determining pipeline network investigation strategies, reduce the overall investigation cost, and improve investigation efficiency. Attached Figure Description

[0014] Figure 1 This is a step diagram of a method for determining key inflow areas based on monitoring along the drainage pipe network according to an embodiment of the present invention; Figure 2 This is a schematic diagram of the pipe section input and output indicators provided in an embodiment of the present invention. Detailed Implementation

[0015] This invention provides a method for determining key inflow areas in a drainage network. By monitoring the main pipe of the study area along its length, water quality and quantity balance equations are established in segments. Based on the information required by the equations, characteristic indicators are determined, and the total outflow and total inflow of each area are solved to determine the severity of inflow in each segment.

[0016] The specific implementation of the present invention will now be described in detail with reference to the accompanying drawings.

[0017] The steps of the method for determining key inflow areas provided by this invention are as follows: Figure 1 As shown, it includes: Step S100: Determine the drainage network segments and obtain monitoring data of the network; First, the intercepting sewers along the drainage network are divided into several sections, and flow and water quality monitoring equipment is installed at the junction of each section to obtain input and output monitoring data for each section.

[0018] To ensure data reliability, the monitoring data includes the total flow rate and average wastewater concentration collected by each segment of the pipeline network during a specified time period; the average wastewater concentration is the wastewater concentration value after mixing water samples at the same time interval.

[0019] The monitoring data obtained in this step specifically includes: the segmented output flow of each segment. Segmented output of wastewater concentration Segmented input flow Segmented inflow sewage concentration .

[0020] Step S110: Load the segmented mass balance model. The segmented mass balance model can be used to express the relationship and inflow severity of the characteristics of inflow wastewater, background wastewater, directly received external water, and mixed outflow wastewater in each segment. Each characteristic is represented by flow rate and wastewater concentration values; the inflow severity is expressed by the inflow severity coefficient. reflect.

[0021] Before loading the piecewise mass balance model, construct the piecewise mass balance model, including the following steps: 1) Establish the mass balance equation for each segment; In the pipeline network, the inflow to each segment includes sewage transferred from the previous segment, background sewage directly received in that segment, and external water directly received in that segment; simultaneously, all water flows out of that segment after mixing. However, the directly received background sewage and the directly received external water are mixed and cannot be directly distinguished. Therefore, in this step, based on the law of conservation of mass, a mass balance equation can be established as follows: , , in, For segmented output flow, To output wastewater concentration in stages, For segmented baseline flow, To segment the background wastewater concentration, For segmented input flow, To segment the concentration of incoming sewage, For segmented external water flow, This refers to the concentration of external wastewater.

[0022] 2) Simplify the mass balance equation; Typically, external water consists of clean water bodies such as groundwater and river water, and its wastewater concentration is much lower than the background wastewater concentration. Therefore, a small coefficient can be preset to reflect the degree of pollution caused by external water. This coefficient is defined as the external water pollution impact coefficient. The value range is usually 0 to 0.05 (or calculated based on the actual measured value).

[0023] Based on this, the mass balance equation can be simplified: Pollution coefficient influenced by external water Determine the concentration of external wastewater , is represented as: ; Define an inflow severity coefficient α to represent the ratio of the external water flow rate in a segment to the background flow rate in that segment, i.e.: The larger α is, the higher the inflow rate and the greater the severity of the inflow in the region.

[0024] The severity coefficient of inflow α and the pollution coefficient of external water impact are used to determine the severity coefficient of inflow and the pollution coefficient of external water impact. Substituting into the mass balance equation, we construct a piecewise mass balance model, which is expressed as: , , in, For segmented input flow, To segment the concentration of incoming sewage, For segmented output flow, To output wastewater concentration in stages, For segmented baseline flow, To segment the background wastewater concentration, For the severity coefficient of inflow, The pollution coefficient is determined by the impact of external water.

[0025] The meanings of each indicator for each pipe section are as follows: Figure 2 As shown.

[0026] Step S120: Calculate the inflow severity coefficient by using the segmented output flow rate, segmented output wastewater concentration, segmented input flow rate, and the ratio between the segmented inflow wastewater concentration and the background wastewater concentration. This is used to determine the severity of external water inflow. In the process of monitoring along the route, the available measurements include , , and External water pollution coefficient The background wastewater concentration can be determined in advance. Water quality data were obtained by sampling and testing at community exits, higher elevations, or other locations where there is no risk of external water intrusion.

[0027] Based on the segmented mass balance model, the segmented input-output difference coefficient K, which can be obtained through measurement, can be expressed as: ; Furthermore, the severity coefficient of the inflow It can be represented as: .

[0028] In general, the severity coefficient of inflow can also be calculated from the background sewage flow rate. And achieve the same effect. The specific steps are as follows: Obtain the total number of sewage outlets in the segmented sewage receiving area by searching the data (i.e., the number of all sewage-generating units connected to the municipal pipe segment in the segmented sewage receiving area); randomly sample N sewage outlets and measure the output flow of each of the N sewage outlets to obtain the average estimated flow of each sewage outlet; multiply the average estimated flow by the total number of sewage outlets to obtain the total background flow; measure the total input flow and total output flow at the beginning and end of the pipe segment respectively, and use the equation The external water volume is calculated; the external water volume is divided by the total background flow rate to obtain the α value. However, measuring the total flow rate is much more difficult than measuring the concentration: on the one hand, the total flow rate is a summation concept, requiring the measurement and accumulation of all flows; while the concentration is a weighted average concept, which can be estimated by averaging multiple representative points. On the other hand, the concentration range of domestic sewage does not vary much. Two similar communities but different sizes may have similar concentrations (both are residential water use), but the water volume can differ greatly. For example, if the population of one community is twice that of another, then the water consumption will also be nearly twice that of the other community. Therefore, in this invention, the background sewage concentration is calculated in segments. It can effectively improve detection efficiency.

[0029] Step S130: Based on the inflow severity coefficient Based on monitoring data and a segmented mass balance model, the external water flow rate of each segment of the drainage network is calculated. The segmented external water flow rate Used to reflect the actual inflow rate of each segment.

[0030] First, based on We can obtain: That is, through monitoring data and the severity coefficient of inflow. Calculate the segmented background flow; Secondly, combining The segmented external water flow rate can be determined. The calculation method is as follows: .

[0031] Therefore, in this step, the segmented external water flow rate can be obtained based on the segmented output flow rate and segmented input flow rate collected by the equipment. .

[0032] Step S140: Based on the segmented external water flow rate The drainage pipe network is sorted into different sections to identify key inflow areas.

[0033] In this step, the external water flow rate of each pipe section is used as a reference. Comparisons are made to identify key inflow areas in the drainage network.

[0034] In this invention, the drainage network is segmented, and based on directly measurable data (such as segmented output flow and segmented input flow, segmented output wastewater concentration and segmented input wastewater concentration), the baseline wastewater concentration can be calculated. Establish a segmented mass balance model, combining pre-set data (external water pollution coefficient). This invention calculates the actual inflow rate at the lowest cost as the basis for judging the inflow level of each segment. This not only improves the effectiveness of the quantitative calculation data and the stability of the calculation model, but also effectively reduces measurement costs and implementation difficulty. Furthermore, by realizing the judgment of key inflow areas through this invention, a basis can be provided for determining pipeline network investigation strategies, reducing the overall investigation cost and improving investigation efficiency.

[0035] The above-disclosed embodiments are merely a few specific examples of the present invention. However, the present invention is not limited thereto, and any variations that can be conceived by those skilled in the art should fall within the protection scope of the present invention.

Claims

1. A method for identifying key inflow areas based on monitoring along the drainage pipe network, characterized in that, Includes the following steps: Determine the segments of the drainage pipe network and acquire monitoring data of the network; the monitoring data includes the segmented output flow rate. Segmented output of wastewater concentration Segmented input flow Segmented inflow sewage concentration ; A segmented mass balance model is loaded; in the segmented mass balance model, an inflow severity coefficient α is defined to represent the ratio of the external water flow rate to the background flow rate of the segment; the segmented mass balance model is used to express the relationship and inflow severity between the inflow sewage characteristics, background sewage characteristics, directly received external water characteristics, and mixed outflow sewage characteristics of each segment; the inflow severity is expressed by the inflow severity coefficient. The segmented mass balance model is represented as follows: ， ,in, For segmented input flow, To segment the concentration of incoming sewage, For segmented output flow, To output wastewater concentration in stages, For segmented baseline flow, To segment the background wastewater concentration, For the severity coefficient of inflow, The pollution coefficient is determined by the impact of external water. The inflow severity coefficient is calculated by considering the segmented output flow rate, segmented output wastewater concentration, segmented input flow rate, and the ratio between the segmented inflow wastewater concentration and the segmented background wastewater concentration. The severity coefficient of the inflow The calculation method is as follows: ,in, The segmented input-output difference coefficient K is used for calculation. ; Based on the inflow severity coefficient Based on the monitoring data and the segmented mass balance model, the segmented external water flow of each segment of the drainage network is calculated. The segmented external water flow rate The calculation method is as follows: This is used to represent the actual inflow rate of each segment. ; Based on segmented external water flow The drainage pipe network is sorted into different sections to identify key inflow areas.

2. The method for determining key inflow areas based on drainage pipe network monitoring according to claim 1, characterized in that, Before loading the segmented mass balance model, a segmented mass balance model is constructed. The construction process of the segmented mass balance model includes: Establish the mass balance equation for each segment; The mass balance equation is simplified to form a piecewise mass balance model.

3. The method for determining key inflow areas based on drainage pipe network monitoring according to claim 2, characterized in that, The mass balance equation is expressed as: ， ， in, For segmented output flow, To output wastewater concentration in stages, For segmented baseline flow, To segment the background wastewater concentration, For segmented input flow, To segment the concentration of incoming sewage, For segmented external water flow, The concentration of external wastewater; Pollution coefficient influenced by external water Determine the concentration of external wastewater , is represented as: ; The inflow severity coefficient α is defined as the ratio of the external water flow rate in a segment to the background flow rate in that segment, expressed as: 。 4. The method for determining key inflow areas based on drainage pipe network monitoring according to claim 1, characterized in that, External water impact pollution coefficient The preset value range is 0 to 0.

05.

5. The method for determining key inflow areas based on drainage network monitoring according to claim 3, characterized in that, The severity coefficient of inflow The calculation method also includes: obtaining the total number of sewage outlets, randomly sampling N sewage outlets, measuring the output flow of each of the N sewage outlets, and obtaining the average estimated flow of each sewage outlet; multiplying the average estimated flow by the total number of sewage outlets to obtain the total background flow; measuring the total input flow and total output flow at the beginning and end of the pipe section respectively, and then using the equation... Calculate the external water volume; divide the external water volume by the total background flow rate to obtain the α value.

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