An intelligent interception method for reducing overflow pollution load of a drainage system

Abstract

The application discloses an intelligent interception method for reducing overflow pollution load of a drainage system, and particularly relates to the technical field of intelligent interception of the drainage system, which comprises a drainage system pipeline group, an intelligent control device and an interception pump, the drainage system pipeline group is provided with a first water quality sensor, a second water quality sensor and a flow sensor, the intelligent control device is connected with a data acquisition module, a data analysis and processing module and a control execution module, the data acquisition module acquires real-time drainage basic information in real time, the data analysis and processing module acquires an initial interception multiple, an interception multiple adjustment characteristic and an interception flow adjustment amount according to the real-time drainage basic information, an actual interception flow of the last time and adjustment weight information, and the control execution module controls the interception pump to perform interception adjustment, and the application comprehensively considers various factors such as water quantity, water quality, biological treatment feedback and interception flow deviation, so that effective reduction and intelligent control of the overflow pollution load of the drainage system are realized.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of intelligent interception of drainage systems, and specifically relates to an intelligent interception method for reducing overflow pollution load of drainage systems. BACKGROUND

[0002] With the acceleration of urbanization, urban drainage systems are facing great challenges. In the case of rainfall, the runoff may exceed the transport and treatment capacity of the drainage system, causing the mixed water of untreated sewage and rainwater to overflow the drainage system directly into the receiving water body, causing serious overflow pollution.

[0003] The existing drainage system design and interception method often cannot adapt to complex and variable rainfall conditions and sewage discharge characteristics, and cannot effectively reduce the overflow pollution load. Specifically, in the case of heavy rainfall, the existing drainage system will cause part of the mixed water of sewage and rainwater to overflow directly into the receiving water body due to unreasonable interception multiple setting. At the same time, it fails to pay attention to the difference in pollutant concentration between rainfall runoff and dry flow sewage, and cannot dynamically adjust the interception strategy according to water quality changes. Moreover, the biological treatment process is not effectively coupled with the interception process, which specifically manifests as a lack of real-time monitoring and feedback adjustment mechanism for the actual water quality at the biological treatment inlet of the sewage treatment plant.

[0004] Therefore, the present application provides an intelligent interception method for reducing the overflow pollution load of drainage systems to solve the problems raised in the background. SUMMARY

[0005] The technical problem solved by the present application is to provide an intelligent interception method for reducing the overflow pollution load of drainage systems to achieve the effect of determining the initial interception multiple by comprehensively considering water quantity and water quality factors, introducing a biological treatment feedback mechanism to adjust the interception multiple, and dynamically adjusting the final interception flow based on the interception flow deviation.

[0006] To solve the above problems, the present application provides the following technical solutions:

[0007] An intelligent interception method for reducing the overflow pollution load of drainage systems, comprising a drainage system pipeline group, an intelligent control device and an interception pump, wherein the drainage system pipeline group is provided with a first water quality sensor, a second water quality sensor and a flow sensor;

[0008] The intelligent control device is connected with a data acquisition module, a data analysis and processing module and a control execution module;

[0009] The specific implementation method steps are as follows:

[0010] Step 1: collecting real-time drainage basic information including rainfall runoff forecast flow, dry flow sewage amount, first chemical oxygen demand, second chemical oxygen demand and third chemical oxygen demand in real time by using the data acquisition module;

[0011] Step 2: the data analysis and processing module receives the real-time drainage basic information, and extracts the last actual interception flow and adjustment weight information stored in the internal memory;

[0012] Step 2.1: obtaining an initial interception multiple according to the rainfall runoff forecast flow, the dry flow sewage amount, the first chemical oxygen demand, the second chemical oxygen demand and the adjustment weight information;

[0013] Step 2.2: obtaining an interception multiple adjustment feature according to the initial interception multiple, the adjustment weight information, the third chemical oxygen demand and the first chemical oxygen demand;

[0014] Step 2.3: obtaining an interception flow adjustment amount according to the interception multiple adjustment feature, the adjustment weight information, the last actual interception flow, the rainfall runoff forecast flow and the dry flow sewage amount;

[0015] Step 3: the control execution module receives and obtains a comparison trigger result according to the comparison between the interception flow adjustment amount and the last actual interception flow;

[0016] Step 3.1: delivering the comparison trigger result to the intelligent control device and the interception pump, and controlling the interception pump to perform interception adjustment.

[0017] Further, the data acquisition module includes a weather acquisition module, a water quality acquisition module and a flow acquisition module;

[0018] The weather acquisition module is connected with a data processing output end of a weather station, and obtains the rainfall runoff forecast flow and the first chemical oxygen demand;

[0019] The water quality acquisition module is connected with the collection output ends of the first water quality sensor and the second water quality sensor, and is used to obtain the third chemical oxygen demand and the second chemical oxygen demand;

[0020] The flow acquisition module is connected with the collection output end of the flow sensor, and is used to obtain the dry flow sewage amount and the last actual interception flow;

[0021] The first chemical oxygen demand is the chemical oxygen demand in the rainfall runoff forecast flow;

[0022] The second chemical oxygen demand is the chemical oxygen demand in the outlet water pipe;

[0023] The third chemical oxygen demand is the chemical oxygen demand in the import water pipe.

[0024] Further, the adjustment weight information comprises a first adjustment feature, a second adjustment feature, a third adjustment feature and a fourth adjustment feature.

[0025] The first adjustment feature, the second adjustment feature, the third adjustment feature and the fourth adjustment feature are all in the range of {0-1}.

[0026] Further, the step 2.1 of obtaining the initial interception multiple comprises the following steps:

[0027] Step 2.1.1: According to the rainfall runoff prediction flow, the dry flow sewage quantity and the first adjustment feature, a water quantity influence degree feature reflecting the degree of rainfall impact on the water quantity of the drainage system is obtained, and is used to measure the influence of the water quantity factor on the initial interception multiple.

[0028] Step 2.1.2: According to the first chemical oxygen demand, the second chemical oxygen demand and the second adjustment feature, a water quality influence feature reflecting the degree of high and low of the pollutant concentration in the rainfall runoff relative to the pollutant concentration in the dry flow sewage is obtained, and is used to measure the influence of the water quality factor on the initial interception multiple.

[0029] Step 2.1.3: The water quantity influence degree feature and the water quality influence feature are added to obtain the initial interception multiple.

[0030] Further, the step 2.3 of obtaining the interception multiple adjustment feature comprises the following steps:

[0031] Step 2.2.1: The third chemical oxygen demand is subtracted by the product of the initial interception multiple and the first chemical oxygen demand to obtain a chemical oxygen demand deviation reflecting the deviation of the actual sewage chemical oxygen demand entering the sewage treatment pipe from the predicted value.

[0032] Step 2.2.2: According to the chemical oxygen demand deviation feature, the third adjustment feature and the first chemical oxygen demand, an interception multiple adjustment degree feature reflecting the adjustment degree of the biological treatment feedback on the interception multiple is obtained.

[0033] Step 2.2.3: The product of the interception multiple adjustment degree feature and the initial interception multiple is obtained to obtain the interception multiple adjustment feature.

[0034] Further, the step 2.3 of obtaining the interception flow adjustment quantity comprises the following steps:

[0035] Step 2.3.1: subtracting the product of the last actual interception flow and the interception multiple adjustment feature from the dry flow sewage quantity to obtain a dry flow sewage difference quantity reflecting the deviation between the last actual interception and the current theoretical interception;

[0036] wherein the dry flow sewage difference quantity is a positive value indicating that the actual interception flow is greater than the theoretical value;

[0037] the dry flow sewage difference quantity is a negative value indicating that the actual interception flow is less than the theoretical value;

[0038] Step 2.3.2: obtaining an adjustment degree influence feature reflecting the adjustment degree of the flow deviation on the final interception flow adjustment degree according to the dry flow sewage difference quantity, the rainfall runoff prediction flow and the fourth adjustment feature, which takes into account the bearing capacity and response requirements of the drainage system to flow changes;

[0039] Step 2.3.3: obtaining the interception flow adjustment quantity according to the adjustment degree influence feature, the dry flow sewage quantity and the interception multiple adjustment feature.

[0040] Further: the comparison trigger result includes that the interception flow adjustment quantity is greater than the last actual interception flow, the interception flow adjustment quantity is less than the last actual interception flow, and the interception flow adjustment quantity is equal to the last actual interception flow;

[0041] If the interception flow adjustment quantity is greater than the last actual interception flow, the intelligent control device controls the interception pump to increase the speed;

[0042] If the interception flow adjustment quantity is less than the last actual interception flow, the intelligent control device controls the interception pump to decrease the speed;

[0043] If the interception flow adjustment quantity is equal to the last actual interception flow, the intelligent control device controls to keep the current speed of the interception pump.

[0044] Further: the first water quality sensor is installed at the sewage inlet of the drainage system pipe group;

[0045] The second water quality sensor and the flow sensor are installed at the drainage outlet of the drainage system pipe group.

[0046] The effects of the above scheme are as follows:

[0047] 1、The present application collects data through the data acquisition module, and comprehensively considers the rainfall runoff prediction flow, the dry flow sewage quantity, the first chemical oxygen demand, the second chemical oxygen demand and the adjustment weight information by using the data analysis and processing module, so that the obtained initial interception multiple can be determined more accurately according to the real-time water quantity and water quality information.

[0048] In the actual situation of large rainfall runoff and high pollutant concentration, by considering the real-time water quantity and water quality information, more sewage and rainwater mixed water can be intercepted and treated, and the overflow pollution load can be effectively reduced.

[0049] 2、The third chemical oxygen demand at the sewage treatment inlet of the drainage system pipeline group is monitored in real time, the deviation of the calculated and predicted values, i.e., the chemical oxygen demand deviation, is calculated, the initial interception multiple is adjusted by combining the third adjustment feature of the biological treatment feedback, so that the interception multiple can be dynamically optimized according to the actual operation of the biological treatment, the interception multiple is adjusted in time, the biological treatment efficiency is improved, and the purpose of ensuring that the water quality of the final discharge meets the standard and is stable is achieved.

[0050] 3、The deviation of the theoretical interception flow obtained by multiplying the last actual interception flow, the interception multiple adjustment feature and the dry flow sewage volume, i.e., the dry flow sewage difference, is considered, and the interception flow adjustment amount is obtained after adjusting the rainfall runoff prediction flow and the fourth adjustment feature.

[0051] The obtained interception flow adjustment amount can adjust the interception flow in real time according to the actual operation state of the drainage system and the last interception, avoiding the problems of too large or too small interception flow, and when the hydraulic conditions of the drainage system change, the interception flow can effectively reduce the overflow pollution load and maintain the stable operation of the drainage system, improving the adaptability and reliability of the intelligent interception method. BRIEF DESCRIPTION OF DRAWINGS

[0052] Figure 1 It is a structure front view of the overall drainage system of the present application.

[0053] Figure 2 It is a method flow diagram of the overall application.

[0054] Figure 3 It is a schematic diagram of the functions of each module of the intelligent control device in the present application.

[0055] In the figure: 1-drainage system pipeline group, 2-intelligent control device, 3-interception pump, 4-first water quality sensor, 6-second water quality sensor, 7-flow sensor. DETAILED DESCRIPTION

[0056] The technical solutions in the embodiments of the present application will be clearly and completely introduced below with reference to the drawings in the embodiments of the present application.

[0057] Example one, please refer to Figures 1 to 3The utility model provides an intelligent interception method for reducing sewage system overflow pollution load, including drainage system pipeline group 1, intelligent control equipment 2 and interception pump 3, first water quality sensor 4, second water quality sensor 6 and flow sensor 7 are installed on drainage system pipeline group 1, and first water quality sensor 4 is installed at the sewage import of drainage system pipeline group 1;

[0058] Second water quality sensor 6 and flow sensor 7 are installed at the drainage export of drainage system pipeline group 1;

[0059] Intelligent control equipment 2 is connected with data acquisition module, data analysis and processing module and control execution module in;

[0060] The method steps are as follows:

[0061] Step 1: using data acquisition module, real-time drainage basic information including rainfall path forecast flow, dry flow sewage quantity, first chemical oxygen demand, second chemical oxygen demand and third chemical oxygen demand is collected in real time;

[0062] Step 2: data analysis and processing module receives real-time drainage basic information, and the last actual interception flow and adjustment weight information stored in are extracted, and adjustment weight information includes first adjustment feature, second adjustment feature, third adjustment feature and fourth adjustment feature;

[0063] The value of first adjustment feature, second adjustment feature, third adjustment feature and fourth adjustment feature is {0-1};

[0064] Step 2.1: according to rainfall path forecast flow, dry flow sewage quantity, first chemical oxygen demand, second chemical oxygen demand and adjustment weight information, obtain initial interception multiple;

[0065] Step 2.2: according to initial interception multiple, adjustment weight information, third chemical oxygen demand and first chemical oxygen demand, obtain interception multiple adjustment feature;

[0066] Step 2.3: according to interception multiple adjustment feature, adjustment weight information, the last actual interception flow, rainfall path forecast flow and dry flow sewage quantity, obtain interception flow adjustment amount;

[0067] Step 3: control execution module receives and according to the comparison of interception flow adjustment amount and the last actual interception flow, obtains comparison trigger result;

[0068] Step 3.1: comparison trigger result is delivered to intelligent control equipment 2 and interception pump 3, and interception pump 3 is controlled to carry out interception adjustment;

[0069] Data acquisition module includes weather acquisition module, water quality acquisition module and flow acquisition module;

[0070] The weather collection module is connected with a data processing output end of a weather station, and obtains the rainfall runoff prediction flow and the first chemical oxygen demand;

[0071] The water quality collection module is connected with collection output ends of the first water quality sensor 4 and the second water quality sensor 6, and is used to obtain the third chemical oxygen demand and the second chemical oxygen demand;

[0072] The flow collection module is connected with a collection output end of the flow sensor 7, and is used to obtain the dry flow sewage amount and the last actual interception flow;

[0073] The first chemical oxygen demand is the chemical oxygen demand in the rainfall runoff prediction flow;

[0074] The second chemical oxygen demand is the chemical oxygen demand in the outlet water pipe;

[0075] The third chemical oxygen demand is the chemical oxygen demand in the inlet water pipe.

[0076] In the embodiment, first, the real-time drainage basis information of the rainfall runoff prediction flow, the dry flow sewage amount, the first chemical oxygen demand, the second chemical oxygen demand and the third chemical oxygen demand is transmitted to the intelligent control device data analysis and processing module through the weather collection module, the water quality collection module and the flow collection module connected with the weather station, the first water quality sensor 4, the second water quality sensor 6 and the flow sensor 7;

[0077] Secondly, the data analysis and processing module obtains the initial interception multiple influenced by the water quantity and water quality, the interception multiple adjustment feature adjusted after biological treatment, and the final interception flow adjustment amount determined in combination with the last interception flow according to the real-time drainage basis information, the last actual interception flow and the adjustment weight information;

[0078] Finally, the intelligent control device 2 adjusts the interception pump according to the interception flow adjustment amount, realizes intelligent interception, and the interception flow adjustment amount of this time will affect the dry flow sewage amount of next time, forming a cycle optimization.

[0079] In summary, the intelligent interception method can comprehensively consider multiple factors to dynamically adjust the interception strategy, effectively reduce the overflow pollution load of the drainage system, and improve the operation efficiency and stability of the drainage system.

[0080] As shown in Figure 2 , the last actual interception flow is also detected by the flow sensor and stored in the data analysis and processing module.

[0081] Please refer to Figure 2 and Figure 3 , the specific steps of step 2.1 for obtaining the initial interception multiple are as follows:

[0082] Step 2.1.1: According to the predicted runoff of rainfall, the dry flow sewage volume, and the first adjustment characteristic, a water quantity influence degree characteristic reflecting the degree of water quantity impact of rainfall on the drainage system is obtained, and is used to measure the influence of the water quantity factor on the initial interception multiple;

[0083] Step 2.1.2: According to the first chemical oxygen demand, the second chemical oxygen demand, and the second adjustment characteristic, a water quality influence characteristic reflecting the degree of high and low of the pollutant concentration in the rainfall runoff relative to the pollutant concentration in the dry flow sewage is obtained, and is used to measure the influence of the water quality factor on the initial interception multiple;

[0084] Step 2.1.3: The water quantity influence degree characteristic and the water quality influence characteristic are added to obtain the initial interception multiple;

[0085] In this embodiment, the calculation formula of the initial interception multiple is as follows:

[0086] ;

[0087] Wherein:

[0088] J1 is the initial interception multiple;

[0089] YL is the predicted runoff of rainfall, and HW is the dry flow sewage volume;

[0090] a is the first adjustment characteristic, which mainly relates to the influence of the predicted runoff of rainfall YL and the dry flow sewage volume HW on the initial interception multiple J1, and the value thereof depends on the importance of the water quantity factor relative to the overall interception decision when the drainage system faces rainfall;

[0091] For the drainage system with relatively small pipe diameter, limited drainage capacity, and large influence of runoff on overflow risk in rainfall events, the first adjustment characteristic a will take a value close to 1 to highlight the importance of the water quantity factor;

[0092] The calculation result of YL-a is the water quantity influence degree characteristic, wherein, The calculation result of YL-a represents the relative size relationship between the predicted runoff of rainfall YL and the dry flow sewage volume HW. The larger the rainfall runoff, the higher the interception multiple relative to the dry flow sewage volume to cope with the possible overflow risk;

[0093] YH is the first chemical oxygen demand, and WH is the second chemical oxygen demand;

[0094] b is the second adjustment characteristic, which relates to the influence of the first chemical oxygen demand YH in the predicted rainfall runoff and the second chemical oxygen demand in the dry flow sewage on the initial interception multiple J1, and the value thereof reflects the weight of the water quality factor in the interception decision;

[0095] If the pollutants in the sewage of the area are complex and have a great impact on the water quality of the receiving water body, the second adjustment characteristic b is close to 0.7 to emphasize the control of water quality;

[0096] If the water quality of the sewage in the area is relatively good, or the self-purification ability of the receiving water body is strong, the second adjustment characteristic b is close to 0.3;

[0097] The calculation result is the water quality influence characteristic, wherein, reflects the comparison between the first chemical oxygen demand YH in the predicted rainfall runoff and the second chemical oxygen demand WH in the dry flow sewage. If the first chemical oxygen demand YH in the rainfall runoff is high, the interception multiple should be appropriately increased to ensure that more pollutants can enter the sewage treatment plant for treatment.

[0098] In addition, the drainage system characteristics and rainfall conditions are different in different regions. By adjusting the values of the first adjustment characteristic a and the second adjustment characteristic b, the influence weight of the water quantity and water quality factors on the interception multiple can be flexibly distributed according to the actual situation of the local area.

[0099] Please refer to Figure 2 and Figure 3 , and the specific steps of step 2.3 for obtaining the interception multiple adjustment characteristic are as follows:

[0100] Step 2.2.1: Subtract the product of the third chemical oxygen demand and the first chemical oxygen demand from the initial interception multiple to obtain the chemical oxygen demand deviation reflecting the actual chemical oxygen demand of the sewage entering the sewage treatment pipeline and the predicted value;

[0101] Step 2.2.2: According to the chemical oxygen demand deviation characteristic, the third adjustment characteristic and the first chemical oxygen demand, obtain the interception multiple adjustment degree characteristic reflecting the adjustment degree of the biological treatment feedback to the interception multiple;

[0102] Step 2.2.3: According to the product of the interception multiple adjustment degree characteristic and the initial interception multiple, obtain the interception multiple adjustment characteristic;

[0103] In this embodiment, the calculation formula of the interception multiple adjustment characteristic is as follows:

[0104] ;

[0105] △H=RH-J1×YH;

[0106] Wherein:

[0107] J2 is the interception multiple adjustment characteristic;

[0108] c is the third adjustment characteristic of biological treatment feedback, and the value thereof is determined according to the sensitivity of sewage treatment to the change of the water quality and the adaptability of the treatment capacity;

[0109] △H is the chemical oxygen demand deviation, RH is the third chemical oxygen demand;

[0110] the result is the interception multiple adjustment degree characteristic;

[0111] It is worth noting that if the biological treatment process is advanced and stable, the third adjustment characteristic c is close to 0.2;

[0112] On the contrary, if the biological treatment process is traditional and sensitive to water quality fluctuations, the third adjustment characteristic c is close to 0.6.

[0113] Please refer to Figure 2 and Figure 3 , the specific steps of step 2.3 to obtain the interception flow adjustment amount are as follows:

[0114] Step 2.3.1: Subtract the product of the interception multiple adjustment characteristic and the dry flow sewage amount from the last actual interception flow to obtain the dry flow sewage difference amount reflecting the deviation between the last actual interception and the current theoretical interception;

[0115] Wherein, the dry flow sewage difference amount is positive, indicating that the actual interception flow is greater than the theoretical value;

[0116] The dry flow sewage difference amount is negative, indicating that the actual interception flow is less than the theoretical value;

[0117] Step 2.3.2: According to the dry flow sewage difference amount, the rainfall runoff prediction flow and the fourth adjustment characteristic, obtain the adjustment degree influence characteristic reflecting the adjustment degree of the flow deviation to the final interception flow adjustment degree, which considers the bearing capacity and response requirement of the drainage system to the flow change;

[0118] Step 2.3.3: According to the adjustment degree influence characteristic, the dry flow sewage amount and the interception multiple adjustment characteristic, obtain the interception flow adjustment amount;

[0119] In this embodiment, the calculation formula of the interception flow adjustment amount is as follows:

[0120] ;

[0121] △JL=JL old -J2×HW;

[0122] Wherein:

[0123] JL is the interception flow adjustment amount;

[0124] d is the fourth adjustment characteristic reflecting the flow adjustment, whose value depends on the hydraulic characteristics of the drainage system and the requirement for interception flow stability;

[0125] In the drainage system with complex hydraulic conditions and sensitive to the change of the interception flow, to avoid the interception flow fluctuation caused by the deviation of the previous interception flow, the fourth adjustment characteristic d is close to 0.2;

[0126] In the system with relatively simple hydraulic conditions, capable of bearing certain flow fluctuation and requiring rapid response to the previous deviation for adjustment, the fourth adjustment characteristic d is close to 0.5;

[0127] △JL is the adjustment degree influence characteristic, JL old is the actual interception flow of the previous time;

[0128] The result is the adjustment degree influence characteristic;

[0129] In addition, when the hydraulic conditions of the drainage system change, the interception flow adjustment amount JL can be adjusted in time, so that the interception operation can better adapt to different rainfall conditions and drainage system states, which helps to maintain the stable operation of the drainage system, reduces the drainage difficulty or overflow phenomenon caused by improper interception, and improves the adaptability and reliability of the entire drainage system.

[0130] In the second embodiment, please refer to Figure 2 and Figure 3 Figure 2 Figure 3 The comparison trigger result includes that the interception flow adjustment amount is greater than the actual interception flow of the previous time, the interception flow adjustment amount is less than the actual interception flow of the previous time, and the interception flow adjustment amount is equal to the actual interception flow of the previous time;

[0131] If the interception flow adjustment amount is greater than the actual interception flow of the previous time, the intelligent control device 2 controls the interception pump 3 to increase the rotating speed;

[0132] If the interception flow adjustment amount is less than the actual interception flow of the previous time, the intelligent control device 2 controls the interception pump 3 to decrease the rotating speed;

[0133] If the interception flow adjustment amount is equal to the actual interception flow of the previous time, the intelligent control device 2 controls to keep the current rotating speed of the interception pump 3;

[0134] In this embodiment, it is worth noting that if the interception flow adjustment amount JL is greater than the actual interception flow JL old of the previous time, it indicates that the current interception flow needs to be increased, at this time the intelligent control device 2 sends a signal to the interception pump 3, for the interception pump 3 using frequency conversion control, the rotating speed of the interception pump 3 can be increased by increasing the output frequency of the frequency converter, thereby increasing the flow, the specific signal content and adjustment method depend on the control system and communication protocol adopted by the interception pump 3, which is not described in detail.

[0135] If the interception flow adjustment amount JL is less than the actual interception flow JL oldIf so, the intercept flow needs to be reduced, and the rotating speed of intercept pump 3 is reduced accordingly;

[0136] In addition, intercept flow adjustment amount JL will affect the amount of dry flow sewage HW in the next rainfall event. When intercept flow adjustment amount JL is greater than the actual intercept flow JL in the last rainfall event old , the amount of dry flow sewage accumulated in the drainage system subsequently is relatively reduced, so that the value of dry flow sewage amount HW is correspondingly smaller in the next rainfall event, which will affect the calculation result of , and further change the initial intercept multiple J1;

[0137] This cyclic effect forms a dynamic optimization of intelligent intercept system, so that the intercept strategy can be constantly adjusted and optimized according to the actual operation of the drainage system.

[0138] Although the present application is disclosed as above, the present application is not limited to this. Any person skilled in the art can make various changes and modifications without departing from the spirit and scope of the present application, so the protection scope of the present application should be limited by the scope defined in the claims.

Claims

1. An intelligent interception method for reducing the pollution load of sewer overflows, characterized in that: The drainage system pipeline group (1) is provided with a first water quality sensor (4), a second water quality sensor (6) and a flow sensor (7); The intelligent control device (2) is connected with a data acquisition module, a data analysis and processing module and a control execution module; The specific implementation method steps are as follows: Step 1: using the data acquisition module, real-time collection of real-time drainage basic information including rainfall runoff forecast flow, dry flow sewage volume, first chemical oxygen demand, second chemical oxygen demand and third chemical oxygen demand; Step 2: the data analysis and processing module receives the real-time drainage basic information, and extracts the last actual interception flow and adjustment weight information stored in the inner; Step 2.1: according to the rainfall runoff forecast flow, the dry flow sewage volume, the first chemical oxygen demand, the second chemical oxygen demand and the adjustment weight information, the initial interception multiple is obtained; Step 2.2: according to the initial interception multiple, the adjustment weight information, the third chemical oxygen demand and the first chemical oxygen demand, the interception multiple adjustment feature is obtained; Step 2.3: according to the interception multiple adjustment feature, the adjustment weight information, the last actual interception flow, the rainfall runoff forecast flow and the dry flow sewage volume, the interception flow adjustment amount is obtained; Step 3: the control execution module receives and compares the interception flow adjustment amount and the last actual interception flow, and obtains a comparison trigger result; Step 3.1: the comparison trigger result is delivered to the intelligent control device (2) and the interception pump (3), and the interception pump (3) is controlled to adjust the interception; The data acquisition module includes a weather acquisition module, a water quality acquisition module and a flow acquisition module; The weather acquisition module is connected with the data processing output end of the weather station, and obtains the rainfall runoff forecast flow and the first chemical oxygen demand; The water quality acquisition module is connected with the collection output end of the first water quality sensor (4) and the second water quality sensor (6), and is used for obtaining the third chemical oxygen demand and the second chemical oxygen demand; The flow acquisition module is connected with the collection output end of the flow sensor (7), and is used for obtaining the dry flow sewage volume and the last actual interception flow; The first chemical oxygen demand is the chemical oxygen demand in the rainfall runoff forecast flow; The second chemical oxygen demand is the chemical oxygen demand in the outlet water pipe; The third chemical oxygen demand is the chemical oxygen demand in the inlet water pipe; The adjustment weight information includes a first adjustment feature, a second adjustment feature, a third adjustment feature and a fourth adjustment feature; The values of the first adjustment feature, the second adjustment feature, the third adjustment feature and the fourth adjustment feature are all {0-1}; The specific steps of step 2.1 to obtain the initial interception multiple are as follows: Step 2.1.1: according to the rainfall runoff forecast flow, the dry flow sewage volume and the first adjustment feature, a water volume influence degree feature is obtained; Step 2.1.2: obtaining a water quality influence characteristic according to the first chemical oxygen demand, the second chemical oxygen demand and the second adjustment characteristic; Step 2.1.3: adding the water quantity influence degree characteristic and the water quality influence characteristic to obtain the initial interception multiple; The specific steps of the step 2.3 for obtaining the interception multiple adjustment characteristic are as follows: Step 2.2.1: subtracting the product of the third chemical oxygen demand and the initial interception multiple from the first chemical oxygen demand to obtain a chemical oxygen demand deviation; Step 2.2.2: obtaining an interception multiple adjustment degree characteristic according to the chemical oxygen demand deviation characteristic, the third adjustment characteristic and the first chemical oxygen demand; Step 2.2.3: obtaining the interception multiple adjustment characteristic according to the product of the interception multiple adjustment degree characteristic and the initial interception multiple; The specific steps of the step 2.3 for obtaining the interception flow adjustment amount are as follows: Step 2.3.1: subtracting the product of the interception multiple adjustment characteristic and the dry flow sewage quantity from the last actual interception flow to obtain a dry flow sewage difference quantity; Step 2.3.2: obtaining an adjustment degree influence characteristic according to the dry flow sewage difference quantity, the rainfall runoff prediction flow and the fourth adjustment characteristic; Step 2.3.3: obtaining the interception flow adjustment amount according to the adjustment degree influence characteristic, the dry flow sewage quantity and the interception multiple adjustment characteristic.

2. A smart interception method for reducing the pollution load of an overflow of a drainage system according to claim 1, characterized in that: The comparison trigger result includes that the interception flow adjustment amount is greater than the last actual interception flow, the interception flow adjustment amount is less than the last actual interception flow, and the interception flow adjustment amount is equal to the last actual interception flow; If the interception flow adjustment amount is greater than the last actual interception flow, the intelligent control device (2) controls the interception pump (3) to increase the rotating speed; If the interception flow adjustment amount is less than the last actual interception flow, the intelligent control device (2) controls the interception pump (3) to decrease the rotating speed; If the interception flow adjustment amount is equal to the last actual interception flow, the intelligent control device (2) controls to keep the current rotating speed of the interception pump (3).

3. The intelligent interception method for reducing the pollution load of overflow of drainage system according to claim 1, characterized in that: The first water quality sensor (4) is installed at the sewage inlet of the drainage system pipeline group (1); The second water quality sensor (6) and the flow sensor (7) are installed at the drainage outlet of the drainage system pipeline group (1).

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