Sewage toxicity monitoring multi-source risk aggregation tracing method and system

Abstract

The invention belongs to a sewage monitoring technology, and particularly provides a multi-source risk aggregation tracing method and system for sewage poison monitoring, and the tracing method comprises the steps: A1, collecting the current monitoring data of sewage at each point (i, j), the data comprising a poison content detection value D (i, j), time and a place; a2, obtaining a traceability matrix M (i, j) according to the detection value matrix Dk (i, j) of each point location in N rounds; a3, a point location with a value greater than 0 in the matrix M (i, j) is a traceable point location; and A4, visually displaying the point location of the traceability and the mark of the M value corresponding to the point location. The method has the advantages of accurate traceability and the like.

Description

TECHNICAL FIELD

[0001] The present application relates to sewage monitoring technology, in particular to a sewage drug situation monitoring multi-source risk aggregation and tracing method and system. BACKGROUND

[0002] Sewage drug situation monitoring is an important means for drug control, drug situation discovery and drug-related clues excavation in the jurisdiction, and each region has a clear scheme, requirement and specification for sewage drug situation monitoring work, and has been implemented.

[0003] At present, the commonly used method is to compare the detection result with the early warning threshold to determine whether the drug content of the sampling point exceeds the standard, so as to infer whether there are drug users or drug-related emissions in the enterprises of easily-made toxic chemicals. In the sewage discharge process, the concentration will decrease as the distance from the source increases. After each sampling analysis, a new sampling point detection result distribution map will be generated. From the map, multiple sampling points will be warned once the discharge occurs. Due to the normal discharge of sewage at the location, the detected drug content may be high or low, and the content of the upstream may be higher than that of the normal discharge. The staff often reviews the sampling point detection result distribution map to comprehensively determine which area has a relatively high drug content, and locates the source. However, in the face of so many point positions and detection result distribution maps, the normal discharge effect also needs to be considered, and it is time-consuming and laborious to rely on the naked eye to analyze and statistics, and it is not accurate enough. SUMMARY

[0004] In order to solve the above problems in the prior art, the present application provides a sewage drug situation monitoring multi-source risk aggregation and tracing method.

[0005] The purpose of the present application is achieved by the following technical solutions: The sewage drug situation monitoring multi-source risk aggregation and tracing method comprises the following steps: A1. Collecting current monitoring data of sewage at each point (i, j), the data including drug content detection value D(i, j), time and location; A2. Obtaining a tracing matrix M(i, j) according to the detection value matrix D of each point in N rounds k (i, j), k = 1, 2,..., N; M(i, j) = A(i, j) · C(i, j), A(i, j) = Σ N k=1 (W k ·D k (i, j)) / N; C(i, j) = Σ N k=1 (W k ·B k (i, j)); A is the average risk intensity matrix, C is the risk consistency matrix, according to the original matrix D k (i,j) to generate a mask matrix B k (i,j), if D(i,j) is greater than a threshold, B k (i,j)=1, otherwise B k (i,j)=0, W k is the weight of each round of detection results; A3. The point position with a value greater than 0 in the matrix M(i,j) is the traced point position; A4. Visualize the traced point position and the mark corresponding to the M value of the point position.

[0006] The purpose of the present application is also to provide a sewage toxic situation monitoring multi-source risk aggregation tracing system for implementing the above-mentioned analysis method, and the purpose is achieved through the following technical solutions: The sewage toxic situation monitoring multi-source risk aggregation tracing system comprises: A collection module, which is used to collect current monitoring data of sewage at each point position (i,j), and the data comprises a drug content detection value D(i,j), time and location; A storage module, which is used to store the current monitoring data, historical monitoring data and early warning threshold; A calculation module, which is used to call N rounds of monitoring data of the storage module, obtain a tracing matrix M(i,j), and determine that the point position with a value greater than 0 in the matrix M(i,j) is a traced point position, k=1,2,..., N; M(i,j)= A(i,j)·C(i,j), A(i,j)=Σ N k=1 (W k ·D k (i,j)) / N; C(i,j)=Σ N k=1 (W k ·B k (i,j)); A is the average risk intensity matrix, C is the risk consistency matrix, according to the original matrix D k (i,j) to generate a mask matrix B k (i,j), if D(i,j) is greater than a threshold, B k (i,j)=1, otherwise B k (i,j)=0, W k is the weight of each round of detection results; A visualization module, which is used to visualize the traced point position and the mark corresponding to the M value of the point position.

[0007] Compared with the prior art, the present invention has the following beneficial effects.

[0008] 1. The results are scientifically accurate; We've added smoothing and noise reduction processing to make the results more scientific and accurate. The calculation and interference of non-early warning points were removed, and two algorithms were superimposed to highlight the points with greater risks, resulting in a smaller traceability range and a more intuitive highlighting of the early warning location; 2. Improve traceability efficiency; The system can automatically calculate and display the results in real time after each round of sampling, detection and analysis, achieving a 100% efficiency improvement; 3. Supports repeated analysis and assessment; Staff can adjust the time range and the weight of key time periods according to actual needs to conduct rapid and repeated analysis. Attached Figure Description

[0009] The disclosure of this invention will become more readily understood with reference to the accompanying drawings. It will be readily understood by those skilled in the art that these drawings are merely illustrative of the technical solutions of this invention and are not intended to limit the scope of protection of this invention. In the drawings: Figure 1 This is a flowchart of a multi-source risk aggregation and tracing method for wastewater toxicity monitoring; Figure 2 It is a visual display effect diagram. Detailed Implementation

[0010] Figures 1-2 The following description illustrates optional embodiments of the invention to teach those skilled in the art how to implement and reproduce the invention. Some conventional aspects have been simplified or omitted to teach the technical solutions of the invention. Those skilled in the art should understand that variations or substitutions derived from these embodiments will be within the scope of the invention. Those skilled in the art should understand that the following features can be combined in various ways to form multiple variations of the invention. Therefore, the invention is not limited to the optional embodiments described below, but is defined only by the claims and their equivalents.

[0011] Example 1

[0012] The wastewater toxicity monitoring multi-source risk aggregation and tracing method in this embodiment, such as... Figure 1 As shown, the steps include: A1. Regularly collect current monitoring data of wastewater at each point (i,j), including the drug content detection value D(i,j), time, and location (including name and latitude and longitude coordinates).

[0013] A2. Based on the detection value matrix D of each point in N rounds. k (i,j) yields the source matrix M(i,j), k=1,2···N; M(i,j) = A(i,j) · C(i,j), A(i,j) =∑ N k=1 (W k ·D k (i,j)) / N; C(i,j) =∑ N k=1 (W k ·B k (i,j)).

[0014] A is the average risk intensity matrix, C is the risk consistency matrix, and the mask matrix B k (i,j) is generated according to the original matrix D k (i,j), if D(i,j) is greater than a threshold, B k (i,j) = 1, otherwise B k (i,j) = 0, W k is the weight of the detection result of each round.

[0015] A3. The point position with a value greater than 0 in the matrix M(i,j) is the traced point position.

[0016] A4. Visual display of the traced point position and the label corresponding to the M value of the point position. For example, color is used as a label, and the larger the M value, the darker the color. For example Figure 2 as shown.

[0017] A5. The supervisor conducts on-site disposal according to the traced point position.

[0018] The sewage drug situation monitoring multi-source risk aggregation and tracing system of the embodiment, i.e. the system for implementing the tracing method of the embodiment, comprises: A collection module for collecting current monitoring data of sewage at each point position (i,j), the data including drug content detection value D(i,j), time and location.

[0019] A storage module for storing the current monitoring data, historical monitoring data and early warning threshold.

[0020] A calculation module for calling N rounds of monitoring data of the storage module, obtaining a tracing matrix M(i,j), and determining that the point position with a value greater than 0 in the matrix M(i,j) is a traced point position, k = 1, 2, ···, N.

[0021] M(i,j) = A(i,j) · C(i,j), A(i,j) =∑ N k=1 (W k ·D k (i,j)) / N; C(i,j) =∑ Nk=1 (W k ·B k (i,j))。

[0022] A is the average risk intensity matrix, C is the risk consistency matrix, and the mask matrix B k (i,j) is generated according to the original matrix D k (i,j), if D(i,j) is greater than a threshold, B k (i,j)=1, otherwise B k (i,j)=0, W k is the weight of the detection result of each round.

[0023] a visualization module for visualizing the traced point and the label of the M value corresponding to the point.

[0024] Embodiment 2

[0025] The sewage toxicity monitoring multi-source risk aggregation and tracing method and system according to Embodiment 1 of the present application are implemented in a certain place in Southeast China for toxicity monitoring.

[0026] In this embodiment, there are 10 sampling points in a certain place, namely a town, a street, a dental hospital, a garden, a back street, a community, a courtyard, a mansion, a street, and a luxury garden, for sewage toxicity tracing.

[0027] Periodically obtain sewage samples from the 10 sampling points and send them to the instrument for drug content detection.

[0028] The detection result of the current round is: {"detection value": "cocaine 0.7 ng / L", "detection time": "202x-07-20 10:00:00", "sampling point name": "a town", "sampling point coordinates": "X1, Y1"}.

[0029] {"detection value": "cocaine 0.8 ng / L", "detection time": "202x-07-20 10:00:00", "sampling point name": "a street", "sampling point coordinates": "X2, Y2"}.

[0030] {"detection value": "cocaine 0.3 ng / L", "detection time": "202x-07-20 10:00:00", "sampling point name": "a dental hospital", "sampling point coordinates": "X3, Y3"}.

[0031] {"detection value": "cocaine 0.2 ng / L", "detection time": "202x-07-20 10:00:00", "sampling point name": "a garden", "sampling point coordinates": "X4, Y4"}.

[0032] {"detection value": "cocaine 0.3 ng / L", "detection time": "202x-07-20 10:00:00", "sampling point name": "a back street", "sampling point coordinates": "X5, Y5"}.

[0033] {"detection value": "cocaine 0.2 ng / L", "detection time": "202x-07-20 10:00:00", "sampling point name": "a community", "sampling point coordinates": "X6, Y6"}.

[0034] {"detection value": "cocaine 0.3 ng / L", "detection time": "202x-07-20 10:00:00", "sampling point name": "a garden", "sampling point coordinates": "X7, Y7"}.

[0035] {"detection value": "cocaine 0.2 ng / L", "detection time": "202x-07-20 10:00:00", "sampling point name": "a mansion", "sampling point coordinates": "X8, Y8"}.

[0036] {"detection value": "cocaine 0.3 ng / L", "detection time": "202x-07-20 10:00:00", "sampling point name": "a street", "sampling point coordinates": "X9, Y9"}.

[0037] {"detection value": "cocaine 0.2 ng / L", "detection time": "202x-07-20 10:00:00", "sampling point name": "a luxury garden", "sampling point coordinates": "X 10 ,Y 10 "}.

[0038] Call the detection results of the previous 2 rounds.

[0039] {"detection value": "cocaine 0.9 ng / L", "detection time": "202x-06-20 10:00:00", "sampling point name": "a town", "sampling point coordinates": "X1, Y1"}.

[0040] {"detection value": "Cocaine 0.8 ng / L", "detection time": "202x-06-20 10:00:00", "sampling point name": "A street", "sampling point coordinates": "X2, Y2"}.

[0041] {"detection value": "Cocaine 0.2 ng / L", "detection time": "202x-06-20 10:00:00", "sampling point name": "A dental hospital", "sampling point coordinates": "X3, Y3"}.

[0042] {"detection value": "Cocaine 0.3 ng / L", "detection time": "202x-06-20 10:00:00", "sampling point name": "A garden", "sampling point coordinates": "X4, Y4"}.

[0043] {"detection value": "Cocaine 0.2 ng / L", "detection time": "202x-06-20 10:00:00", "sampling point name": "A back street", "sampling point coordinates": "X5, Y5"}.

[0044] {"detection value": "Cocaine 0.3 ng / L", "detection time": "202x-06-20 10:00:00", "sampling point name": "A community", "sampling point coordinates": "X6, Y6"}.

[0045] {"detection value": "Cocaine 0.2 ng / L", "detection time": "202x-06-20 10:00:00", "sampling point name": "A garden", "sampling point coordinates": "X7, Y7"}.

[0046] {"detection value": "Cocaine 0.3 ng / L", "detection time": "202x-06-20 10:00:00", "sampling point name": "A mansion", "sampling point coordinates": "X8, Y8"}.

[0047] {"detection value": "Cocaine 0.2 ng / L", "detection time": "202x-06-20 10:00:00", "sampling point name": "A street", "sampling point coordinates": "X9, Y9"}.

[0048] {"detection value": "Cocaine 0.3 ng / L", "detection time": "202x-06-20 10:00:00", "sampling point name": "A garden", "sampling point coordinates": "X 10 ,Y 10 "}.

[0049] {"detection value": "Cocaine 0.8 ng / L", "detection time": "202x-05-20 10:00:00", "sampling point name": "a town", "sampling point coordinates": "X1, Y1"}.

[0050] {"detection value": "Cocaine 0.9 ng / L", "detection time": "202x-05-20 10:00:00", "sampling point name": "a street", "sampling point coordinates": "X2, Y2"}.

[0051] {"detection value": "Cocaine 0.2 ng / L", "detection time": "202x-05-20 10:00:00", "sampling point name": "a dental hospital", "sampling point coordinates": "X3, Y3"}.

[0052] {"detection value": "Cocaine 0.3 ng / L", "detection time": "202x-05-20 10:00:00", "sampling point name": "a garden", "sampling point coordinates": "X4, Y4"}.

[0053] {"detection value": "Cocaine 0.2 ng / L", "detection time": "202x-05-20 10:00:00", "sampling point name": "a back street", "sampling point coordinates": "X5, Y5"}.

[0054] {"detection value": "Cocaine 0.3 ng / L", "detection time": "202x-05-20 10:00:00", "sampling point name": "a community", "sampling point coordinates": "X6, Y6"}.

[0055] {"detection value": "Cocaine 0.2 ng / L", "detection time": "202x-05-20 10:00:00", "sampling point name": "a garden", "sampling point coordinates": "X7, Y7"}.

[0056] {"detection value": "Cocaine 0.3 ng / L", "detection time": "202x-05-20 10:00:00", "sampling point name": "a mansion", "sampling point coordinates": "X8, Y8"}.

[0057] {"detection value": "Cocaine 0.2 ng / L", "detection time": "202x-05-20 10:00:00", "sampling point name": "a street", "sampling point coordinates": "X9, Y9"}.

[0058] {"Detection value": "Cocaine 0.3 ng / L", "Detection time": "202x-05-20 10:00:00", "Sampling point name": "A certain mansion", "Sampling point coordinates": "X 10 ,Y 10 "}.

[0059] "D1"="[ 0.7,0.8,0.3;0.2,0.3,0.2;0.3,0.2,0.3;0.2]".

[0060] "D2"="[ 0.9,0.8,0.2;0.3,0.2,0.3;0.2,0.3,0.2;0.3]".

[0061] "D3"="[ 0.8,0.9,0.2;0.3,0.2,0.3;0.2,0.3,0.2;0.3]".

[0062] The weight value 1 / 3 (N=3) of each round of detection results is substituted into the traceability formula M(i,j)=A(i,j)·C(i,j) to obtain the traceability matrix M(i,j).

[0063] According to the original matrix D k (i,j), a mask matrix B k (i,j) is generated. If D k (i,j) is greater than the threshold value 0.5, B k (i,j)=1, otherwise B k (i,j)=0.

[0064] B1=[1,1,0;0,0,0;0,0,0;0], B2=[1,1,0;0,0,0;0,0,0;0], and B3=[1,1,0;0,0,0;0,0,0;0] can be obtained.

[0065] According to C(i,j)=Σ 3 k=1 (W k · B k (i,j)), C=[1,1,0;0,0,0;0,0,0;0] can be obtained.

[0066] According to A(i,j)=Σ 3 k=1 (W k ·D k (i,j)) / 3, A=[0.27,0.28,0.08;0.09,0.08,0.09;0.08,0.09,0.08;0.09] can be obtained.

[0067] According to M(i,j)= A(i,j)·C(i,j), we can get M=[0.27,0.28,0;0,0,0;0,0,0;0].

[0068] According to M=[0.27,0.28,0;0,0,0;0,0,0;0], we know that the source was traced to two points, namely M(X1,Y1)=0.27 and M(X2,Y2)=0.28.

[0069] Monitoring data from two locations can be obtained: {"M": "0.27","Detection Time": "202×-07-20 10:00:00","Sampling Point Name": "A Certain Town","Sampling Point Coordinates": "X1,Y1"}.

[0070] {"M": "0.28","Detection Time": "202×-07-20 10:00:00","Sampling Point Name": "A Certain Street","Sampling Point Coordinates": "X2,Y2"}.

[0071] When plotting a risk heat map on a GIS map, because the M value > 0, the sampling point is identified as the source of sewage discharge and marked in red; the larger the M value, the redder the color. For example... Figure 2 As shown.

[0072] Staff members took on-site action based on the location information of the two points used for tracing the source.

Claims

1. A multi-source risk aggregation and tracing method for wastewater toxicity monitoring, characterized in that, The source tracing method includes the following steps: A1. Collect current monitoring data of wastewater at each point (i,j), including the drug content detection value D(i,j), time, and location; A2. Based on the detection value matrix D of each point in N rounds. k (i,j) yields the source matrix M(i,j), k=1,2···N; M(i,j)= A(i,j)·C(i,j),A(i,j)=Σ N k=1 (W k ·D k (i,j)) / N;C(i,j)=Σ N k=1 (W k ·B k (i,j)); A is the average risk intensity matrix, C is the risk consistency matrix, and based on the original matrix D... k (i,j) Generate mask matrix B k (i,j), if D(i,j) is greater than the threshold, B k (i,j)=1, otherwise B k (i,j)=0, W k It is the weight of the test results in each round; A3. Points in matrix M(i,j) with values ​​greater than 0 are the points used for tracing back to the source. A4. Visualize the location of the source and the marker of the corresponding M value.

2. The tracing method according to claim 1, characterized in that, The marking method is as follows: Using color as a marker, the larger the M value, the darker the color.

3. The tracing method according to claim 1, characterized in that, Weight W k =1 / N.

4. The tracing method according to claim 1, characterized in that, The source tracing method also includes the following steps: A5. Regulatory personnel will conduct on-site handling based on the traceability points.

5. A multi-source risk aggregation and tracing system for wastewater toxicity monitoring, characterized in that, The traceability system includes: The data acquisition module is used to collect current monitoring data of wastewater at each point (i,j), including the drug content detection value D(i,j), time, and location. The storage module is used to store the current monitoring data, historical monitoring data, and early warning thresholds; The calculation module is used to call the N rounds of monitoring data from the storage module to obtain the source tracing matrix M(i,j), and the points in matrix M(i,j) with values ​​greater than 0 are the source tracing points, k=1,2···N; M(i,j)= A(i,j)·C(i,j),A(i,j)=Σ N k=1 (W k ·D k (i,j)) / N;C(i,j)=Σ N k=1 (W k ·B k (i,j)); A is the average risk intensity matrix, C is the risk consistency matrix, and based on the original matrix D... k (i,j) Generate mask matrix B k (i,j), if D(i,j) is greater than the threshold, B k (i,j)=1, otherwise B k (i,j)=0, W k It is the weight of the test results in each round; A visualization module is used to visualize and display the source location and the marker of the corresponding M value.

6. The traceability system according to claim 1, characterized in that, The marking method is as follows: Using color as a marker, the larger the M value, the darker the color.

7. The traceability system according to claim 1, characterized in that, Weight W k =1 / N.

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