A method for locating pollutant concentration areas in sewage pipe networks

Abstract

The present invention discloses a method for locating pollutant concentration zones in a sewage pipe network, which comprises the following steps: screening sewage treatment pipes, straight drainage pipes and tributaries; collecting sewage concentrations C on each tributary pipe, straight drainage pipe and sewage treatment pipe; and calculating the sewage concentration sequence C. 0 ={C 0 (k)}=(c1,c2,...c n ) and sewage concentration series C 1 ={C 1 (k)}; Build a prediction model for sewage concentration after it flows through the tributary pipes and output the final prediction model. Use the final prediction model to predict the sewage concentration entering the tributary pipes and develop drainage plans to prevent high-concentration sewage from entering lakes or rivers. This plan combines historically collected sewage concentration data from tributaries, direct drainage pipes, and sewage treatment pipes to develop a prediction model. This allows for tracing the source of high-concentration sewage to the tributary pipes, helping managers prepare emergency plans in advance, significantly reducing monitoring costs and achieving greater economic benefits.

Description

Technical Field

[0001] The present invention relates to the technical field of sewage treatment prediction, and in particular to a method for locating pollutant concentration zones in a sewage pipe network. Background Art

[0002] The main sources of sewage in sewage treatment plants are domestic sewage, commercial sewage and industrial wastewater. The pollutant concentrations of the three water bodies directly affect the operating efficiency of the sewage treatment plant. If the pollutant concentration is too high, it will exceed the treatment load of the sewage treatment plant. If the pollutant concentration is too low, it will cause the sewage treatment plant to operate inefficiently. Therefore, in order to ensure the normal operation of the sewage treatment plant, the pollutant concentration of the sewage treatment plant's influent should be guaranteed.

[0003] Low pollutant concentrations in sewage are a common problem in sewage pipe networks. To address this issue, the main approach is to trace the source and then separate rainwater and sewage to increase the pollutant concentration in sewage. Existing methods for tracing the source of drainage pipe networks mainly include: a pollutant source tracing method that detects pollutant concentrations in target areas, an artificial intelligence-based drainage pipe network pollutant source tracing system and method, a water quality monitoring method based on water environment profiling and pollutant source tracing, and a GIS-based drainage pipe network problem diagnosis device and method.

[0004] First, these methods are based on the analysis of measured data, which requires the deployment of a large number of monitoring instruments, is expensive, and has low efficiency. Second, the measured water quality data changes in real time, and there are time intervals between instrument measurements. Shorter time intervals result in excessive data volume, making it difficult to locate areas with low pollutant concentrations in a targeted manner. Summary of the Invention

[0005] In view of the above-mentioned deficiencies in the prior art, the present invention provides a method for locating pollutant concentration zones in a sewage pipe network, which can realize intelligent management of the pipe network.

[0006] In order to achieve the above-mentioned object of the invention, the technical solution adopted by the present invention is:

[0007] A method for locating pollutant concentration zones in a sewage network is provided, comprising the following steps:

[0008] S1: Based on the topological structure of the sewage pipe network, filter out sewage treatment pipes that discharge into sewage treatment plants, direct drainage pipes that discharge directly into rivers or lakes, and branch pipes distributed upstream of sewage treatment pipes or direct drainage pipes;

[0009] S2: Establish sewage detection points and water pressure detection points on the tributary pipe and the straight drainage pipe, and on the tributary pipe and the sewage treatment pipe, and collect the sewage concentration c on each tributary pipe, straight drainage pipe and sewage treatment pipe;

[0010] S3: Collect the sewage concentration of each confluence branch and obtain the sewage concentration sequence C 0 ={C 0 (k)}=(c1,c2,...c n ), where n is the total number of tributaries and k is the number of the tributaries;

[0011] S4: Collect the sewage concentration of the branch pipe every set time, and in the sewage concentration sequence {C 0 (k)} is accumulated to obtain the sewage concentration sequence C 1 ={C 1 (k)}, where m is the number of times the confluence branch collects sewage concentration, i is the number of times the sewage concentration is collected;

[0012] S5: Establish the sewage treatment concentration sequence C according to the sewage concentration of the sewage treatment pipeline and the direct drainage pipeline collected each time w and the concentration sequence C of direct drainage z , During the sewage treatment process, when the sewage concentration reaches the concentration threshold c that requires it to enter the sewage treatment plant for treatment, yuzhi When it is discharged into the sewage treatment pipeline, otherwise it will directly enter the direct drainage pipeline; q is the number of times the sewage concentration is collected in the sewage treatment pipeline, and v is the number of times the sewage concentration is collected in the direct drainage pipeline;

[0013] S6: Establish a prediction model for sewage concentration after sewage flows from the confluence branch, and use the sewage concentration sequence C 1 and sewage concentration series C 0 Train the prediction model and output the final prediction model;

[0014] S7: Collect the sewage concentration of two adjacent confluence branches, input it into the final prediction model, and output the predicted sewage concentration value after confluence and As long as the concentration and Any one of them exceeds the concentration threshold c yuzhi , then open the sewage treatment pipe and lead the sewage into the sewage treatment plant for purification treatment, and execute step S8; otherwise, close the sewage treatment pipe. At this time, the concentration of sewage pollutants is low, and the direct drainage pipe can be directly opened to discharge the sewage into rivers or lakes;

[0015] S8: Find the location of the branch pipe according to the collected branch pipe number k, and set the upstream area of ​​the branch pipe k as a high pollutant emission area.

[0016] Furthermore, step S6 includes:

[0017] S61: Establish a prediction model for sewage concentration after sewage flows from the confluence branch pipe:

[0018]

[0019] Among them, a z , b z , a w , b w are the prediction coefficients respectively;

[0020] S62: Take sewage concentration sequence C 0 , sewage concentration sequence C 1 The two adjacent sewage concentrations are used as input data, and the sewage treatment concentration sequence C w , concentration sequence C of direct discharge z The corresponding concentration value is used as the output data, substituted into the prediction model, and the prediction coefficient a is output. z 、b z 、a w 、b w ;

[0021] S63: Get the prediction coefficient matrix:

[0022] S64: Calculate the average value of each prediction coefficient, and calculate the fluctuation parameter of each prediction coefficient based on the average value, screen out the prediction coefficient that meets the fluctuation requirements, and output the optimal prediction coefficient:

[0023]

[0024] in, is the maximum value of the allowed fluctuation range of the prediction coefficient, is the average value of the prediction coefficient, e is any prediction coefficient in the prediction coefficient matrix, is the optimal prediction coefficient of the output, is the forecast coefficient that meets the volatility requirements;

[0025] S65: Repeat step S64 to calculate the optimal prediction coefficient corresponding to each prediction coefficient Get the final prediction model:

[0026]

[0027] in, and are the sewage concentrations of the confluence branch pipe collected twice adjacently, and is the predicted sewage concentration value after confluence, and The collection time interval is shorter than the time required for the sewage from the branch pipe here to flow into the sewage treatment pipeline.

[0028] The beneficial effects of the present invention are as follows: this solution combines the historically collected sewage concentrations on the confluence branch, direct drainage pipe and sewage treatment pipe, establishes a sewage concentration prediction model after the confluence downstream of the confluence branch is completed through numerical simulation, and calculates the parameters related to the prediction model; in the later stage of sewage concentration monitoring, the monitored sewage concentration is directly input into the prediction model to obtain the downstream sewage concentration. According to the predicted downstream sewage concentration, drainage operations are carried out in a timely manner. If the sewage concentration is too high, it will be directly discharged into the sewage treatment plant to avoid direct discharge pollution to the environment, while effectively improving the efficiency of the sewage treatment plant; if the sewage concentration is low, it can be directly discharged into rivers or lakes to avoid occupying the resources of the sewage treatment plant. At the same time, the confluence branch that causes high-concentration sewage is traced back to the source, thereby helping managers to prepare emergency plans in advance, greatly reducing monitoring costs and being more economical. BRIEF DESCRIPTION OF THE DRAWINGS

[0029] Figure 1 Flowchart of the method for locating pollutant concentration zones in sewage networks. DETAILED DESCRIPTION

[0030] The specific embodiments of the present invention are described below to facilitate understanding of the present invention by those skilled in the art. However, it should be clear that the present invention is not limited to the scope of the specific embodiments. For those skilled in the art, as long as various changes are within the spirit and scope of the present invention as defined and determined by the appended claims, these changes are obvious, and all inventions and creations utilizing the concepts of the present invention are protected.

[0031] like Figure 1 As shown, the method for locating pollutant concentration zones in the sewage pipe network of this scheme includes the following steps:

[0032] S1: Based on the topological structure of the sewage pipe network, filter out sewage treatment pipes that discharge into sewage treatment plants, direct drainage pipes that discharge directly into rivers or lakes, and branch pipes distributed upstream of sewage treatment pipes or direct drainage pipes;

[0033] S2: Establish sewage detection points and water pressure detection points on the tributary pipe and the straight drainage pipe, and on the tributary pipe and the sewage treatment pipe, and collect the sewage concentration c on each tributary pipe, straight drainage pipe and sewage treatment pipe;

[0034] S3: Collect the sewage concentration of each confluence branch and obtain the sewage concentration sequence C 0 ={C 0 (k)}=(c1,c2,...c n), where n is the total number of tributaries and k is the number of the tributaries;

[0035] S4: Collect the sewage concentration of the branch pipe every set time, and in the sewage concentration sequence {C 0 (k)} is accumulated to obtain the sewage concentration sequence C 1 ={C 1 (k)}, where m is the number of times the confluence branch collects sewage concentration, i is the number of times the sewage concentration is collected;

[0036] S5: Establish the sewage treatment concentration sequence C according to the sewage concentration of the sewage treatment pipeline and the direct drainage pipeline collected each time w and the concentration sequence C of direct drainage z , During the sewage treatment process, when the sewage concentration reaches the concentration threshold c that requires it to enter the sewage treatment plant for treatment, yuzhi When it is discharged into the sewage treatment pipeline, otherwise it will directly enter the direct drainage pipeline; q is the number of times the sewage concentration is collected in the sewage treatment pipeline, and v is the number of times the sewage concentration is collected in the direct drainage pipeline;

[0037] S6: Establish a prediction model for sewage concentration after sewage flows from the confluence branch, and use the sewage concentration sequence C 1 and sewage concentration series C 0 Train the prediction model and output the final prediction model;

[0038] S7: Collect the sewage concentration of two adjacent confluence branches, input it into the final prediction model, and output the predicted sewage concentration value after confluence and As long as the concentration and Any one of them exceeds the concentration threshold c yuzhi , then open the sewage treatment pipe and lead the sewage into the sewage treatment plant for purification treatment, and execute step S8; otherwise, close the sewage treatment pipe. At this time, the concentration of sewage pollutants is low, and the direct drainage pipe can be directly opened to discharge the sewage into rivers or lakes;

[0039] S8: Find the location of the branch pipe according to the collected branch pipe number k, and set the upstream area of ​​the branch pipe k as a high pollutant emission area.

[0040] Step S6 includes:

[0041] S61: Establish a prediction model for sewage concentration after sewage flows from the confluence branch pipe:

[0042]

[0043] Among them, a z , b z , a w , b w are the prediction coefficients respectively;

[0044] S62: Take sewage concentration sequence C 0 , sewage concentration sequence C 1 The two adjacent sewage concentrations are used as input data, and the sewage treatment concentration sequence C w , concentration sequence C of direct discharge z The corresponding concentration value is used as the output data, substituted into the prediction model, and the prediction coefficient a is output. z 、b z 、a w 、b w ;

[0045] S63: Get the prediction coefficient matrix:

[0046] S64: Calculate the average value of each prediction coefficient, and calculate the fluctuation parameter of each prediction coefficient based on the average value, screen out the prediction coefficient that meets the fluctuation requirements, and output the optimal prediction coefficient:

[0047]

[0048] in, is the maximum value of the allowed fluctuation range of the prediction coefficient, is the average value of the prediction coefficient, e is any prediction coefficient in the prediction coefficient matrix, is the optimal prediction coefficient of the output, is the forecast coefficient that meets the volatility requirements;

[0049] S65: Repeat step S64 to calculate the optimal prediction coefficient corresponding to each prediction coefficient Get the final prediction model:

[0050]

[0051] in, and are the sewage concentrations of the confluence branch pipe collected twice adjacently, and is the predicted sewage concentration value after confluence, and The collection time interval is shorter than the time required for the sewage from the branch pipe here to flow into the sewage treatment pipeline.

[0052] This solution combines historically collected sewage concentration data from tributaries, direct drainage pipes, and sewage treatment pipes. Through numerical simulation, it establishes a sewage concentration prediction model for the downstream confluence of the tributaries and calculates the relevant parameters of the prediction model. Later, during sewage concentration monitoring, the monitored sewage concentration is directly input into the prediction model to determine the downstream sewage concentration. Based on the predicted downstream sewage concentration, timely drainage operations can be implemented. If the sewage concentration is too high, it can be directly discharged into the sewage treatment plant, avoiding direct discharge pollution and effectively improving the efficiency of the sewage treatment plant. If the sewage concentration is low, it can be directly discharged into rivers or lakes, avoiding tying up sewage treatment plant resources. This helps managers prepare emergency plans in advance, significantly reducing monitoring costs and being more economical.

Claims

1. A method for locating pollutant concentration zones in a sewage network, characterized in that: The following steps are involved: S1: Based on the topological structure of the sewage pipe network, the sewage treatment pipes that discharge into the sewage treatment plant, the direct drainage pipes that discharge directly into rivers or lakes, and the confluence branches distributed upstream of the sewage treatment pipes or direct drainage pipes are screened out; S2: Establish sewage detection points and water pressure detection points on the branch pipes and straight drainage pipes, and on the branch pipes and sewage treatment pipes, and collect sewage concentration data on each branch pipe, straight drainage pipe and sewage treatment pipe. c ; S3: Collect the sewage concentration of each confluence branch and obtain the sewage concentration sequence C 0 ={ C 0 ( k )}=( c 1, c 2,... c n ),in, n is the total volume of the branch pipes, k The number of the branch pipe; S4: Collect the sewage concentration of the branch pipe every set time, and in the sewage concentration sequence { C 0 ( k )} is accumulated to obtain the sewage concentration sequence C 1 ={ C 1 ( k )},in, , m The number of times the sewage concentration is collected for the branch pipe, i Number of times the sewage concentration was collected; S5: Establish a sewage treatment concentration sequence based on the sewage concentration of the sewage treatment pipe and the direct drainage pipe collected each time C w and concentration series of direct drainage C z , , In the sewage treatment process, when the sewage concentration reaches the threshold value that requires it to enter the sewage treatment plant for treatment c yuzhi When it is discharged into the sewage treatment pipeline, otherwise it will directly enter the direct drainage pipeline; , v + q = m , q The number of times the sewage concentration is collected in the sewage treatment pipeline, v The number of times the sewage concentration is collected in the direct drainage pipe; S6: Establish a prediction model for sewage concentration after sewage flows from the confluence branch, and use the sewage concentration series C 1 and sewage concentration series C 0 Train the prediction model and output the final prediction model; S7: Collect the sewage concentration of two adjacent confluence branches, input it into the final prediction model, and output the predicted sewage concentration value after confluence and , as long as the concentration value and Any of the above concentration thresholds c yuzhi , then open the sewage treatment pipe and lead the sewage into the sewage treatment plant for purification treatment, and execute step S8; otherwise, close the sewage treatment pipe. At this time, the concentration of sewage pollutants is low, and the direct drainage pipe can be directly opened to discharge the sewage into rivers or lakes; S8: According to the number of the collected branch pipes k Find the location of the manifold and move the manifold to the k The upstream area is designated as a high pollutant emission area.

2. The method for locating pollutant concentration areas in a sewage pipe network according to claim 1, characterized in that: The step S6 comprises: S61: Establish a prediction model for sewage concentration after sewage flows from the confluence branch pipe: in, a z , b z , a w , b w are the prediction coefficients respectively; S62: Get sewage concentration sequence C 0 , sewage concentration series C 1 The concentration of two adjacent sewage is used as input data, and the concentration sequence of sewage treatment is C w , concentration series of direct discharge C z The corresponding concentration value is used as the output data, substituted into the prediction model, and the prediction coefficient is output. a z 、 b z 、 a w 、 b w ; S63: Get the prediction coefficient matrix: , ; S64: Calculate the average value of each prediction coefficient, and calculate the fluctuation parameter of each prediction coefficient based on the average value, screen out the prediction coefficient that meets the fluctuation requirements, and output the optimal prediction coefficient: in, is the maximum value of the allowed fluctuation range of the prediction coefficient, is the average value of the prediction coefficients, is any prediction coefficient in the prediction coefficient matrix, is the optimal prediction coefficient of the output, is the forecast coefficient that meets the volatility requirements; S65: Repeat step S64 to calculate the optimal prediction coefficient corresponding to each prediction coefficient 、 、 、 , and get the final prediction model: ； in, and are the sewage concentrations of the confluence branch pipe collected twice adjacently, and is the predicted sewage concentration value after confluence, and The collection time interval is shorter than the time required for the sewage from the branch pipe here to flow into the sewage treatment pipeline.

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