A control system and method for a smart pumping station

Abstract

The present invention discloses a control system and method for a smart pump station, comprising: a data acquisition module, a data processing module, and a pump station control module; it relates to the field of pump station control technology and solves the technical problem that the existing technology is difficult to accurately control the water delivery volume of the pump station, as well as the subsequent maintenance cost of the pump station; the present invention obtains the equipment operation information and working environment information of each water pump in the pump station; calculates the actual water consumption of the corresponding irrigation area in a set time period based on the irrigation water consumption and rainfall information of each irrigation area; and adjusts the operating status of the pump station based on the actual water consumption and the water pump scheduling priority sequence. The present invention comprehensively collects the target farmland planting information, rainfall information, and the equipment operation and working environment information of each water pump in the pump station, uses the crop water use database to match and obtain the optimal irrigation water consumption, and optimizes the pump station operation based on this information in combination with the water pump scheduling priority sequence, thereby reducing the subsequent maintenance cost of the pump station.

Description

Technical Field

[0001] The present invention belongs to the technical field of pump station control, and specifically relates to a control system and method for a smart pump station. Background Art

[0002] With the continuous development of agriculture, the demand for crop irrigation continues to increase. However, due to the uneven distribution of water resources in my country, uneven seasonal rainfall, and insufficient regulation capacity, the contradiction between supply and demand of agricultural irrigation has become increasingly prominent. To alleviate this contradiction, most current methods use irrigation reservoirs to ensure agricultural water supply.

[0003] The existing technology obtains historical water usage information of the farmland to be irrigated, analyzes the historical water usage information, obtains the estimated water consumption, and determines the number of water pumps that need to be turned on at the pump station based on the estimated water consumption. However, the amount of water used for irrigation of farmland is related to factors such as the type of crop, growth cycle, and weather. The existing technology makes it difficult to control the water delivery volume of the pump station based on these factors, resulting in inaccurate water supply at the pump station. In addition, during the actual operation of the pump station, the workload and working environment of different water pumps in the pump station are not the same. For example, the wear rate of the water pump will be higher when it is running under high load and in water bodies with high sediment content. The existing technology only evaluates the degree of wear of the water pump based on the operating time, which makes the evaluated degree of wear of the water pump less accurate, resulting in poor wear uniformity of several water pumps in the pump station, and increases the subsequent maintenance cost of the pump station.

[0004] The present invention proposes a control system and method for a smart pump station to solve the above technical problems. Summary of the Invention

[0005] The present invention aims to solve at least one of the technical problems existing in the prior art; to this end, the present invention proposes a control system and method for a smart pumping station, which is used to solve the problem that the prior art is difficult to accurately control the water delivery volume of the pumping station according to the type of crop, growth cycle and weather; in addition, the prior art only evaluates the degree of wear of the water pump based on the operating time, resulting in poor wear uniformity of several water pumps in the pumping station, thereby increasing the subsequent maintenance cost of the pumping station.

[0006] To achieve the above-mentioned object, a first aspect of the present invention provides a control system for a smart pumping station, comprising: a data processing module, and a data acquisition module and a pumping station control module connected thereto;

[0007] The data acquisition module is used to collect planting information and rainfall information of the target farmland; obtain equipment operation information and working environment information of each water pump in the pump station; wherein the planting information includes the type and growth cycle of the currently planted crops; the operation information includes the accumulated operation time and average workload; the working environment information includes the sediment content;

[0008] The data processing module is used to divide the target farmland based on the types of crops currently planted to obtain a number of irrigation areas; input the planting information of each irrigation area into the crop water use database for matching to obtain the corresponding irrigation water volume; calculate the actual water volume of the corresponding irrigation area in a set time period based on the irrigation water volume and rainfall information of each irrigation area; and

[0009] Construct a water pump dispatch priority sequence based on the equipment operation information and working environment information of each water pump;

[0010] The pump station control module is used to adjust the operating status of the pump station based on the actual water consumption and the water pump scheduling priority sequence.

[0011] Preferably, the control system of the smart pumping station further includes a crop water use database, which contains the water consumption per unit area of ​​several crop types in different growth cycles.

[0012] Preferably, the dividing of target farmland based on the types of crops currently planted includes:

[0013] The target farmland is divided into several sub-areas of equal area, and the types of crops currently planted in each sub-area are extracted; it is determined whether the types of crops currently planted in adjacent sub-areas are the same; if yes, the adjacent sub-areas are merged into one irrigation area; if not, the corresponding sub-areas are treated as separate irrigation areas.

[0014] Preferably, the step of inputting the planting information of each irrigation area into the crop water use database for matching includes:

[0015] A1: Extract the planting information of each irrigation area and obtain the planting area of ​​each irrigation area;

[0016] A2: Input the type and growth cycle of the currently planted crops in the planting information into the crop water usage database to obtain the water consumption per unit area;

[0017] A3: Multiply the water consumption per unit area of ​​the current crops planted in each irrigation area by the corresponding planting area to obtain the irrigation water consumption of each irrigation area.

[0018] Preferably, the calculation of the actual water consumption of the corresponding irrigation area in a set time period based on the irrigation water consumption and rainfall information of each irrigation area includes:

[0019] B1: Extract the irrigation water consumption and rainfall information of each irrigation area in several consecutive periods;

[0020] B2: Input the irrigation water consumption of several consecutive periods into the irrigation water consumption prediction model to obtain the irrigation water consumption forecast value of the park; the irrigation water consumption prediction model is constructed based on the artificial intelligence model;

[0021] B3: Using time as the independent variable and irrigation water consumption and rainfall information as dependent variables, generate the irrigation water consumption curve fi(t) and rainfall curve gi(t) through curve fitting. Where i = 1, 2, …, n, where n is the total number of irrigation areas.

[0022] B4: By formula Calculate the actual water consumption SYLi of irrigation area i within the set time period; where t is time, t1 is the start time of the set time period, t2 is the end time of the set time period, and t1≤t≤t2.

[0023] It should be noted that the length of the set time period is determined according to the growth cycle of the crops planted in the irrigation area.

[0024] Preferably, the irrigation water consumption prediction model is constructed based on an artificial intelligence model, including:

[0025] The irrigation water consumption of each irrigation area in several consecutive cycles is extracted and integrated into several groups of training data and test data; the artificial intelligence model is trained using the training data, and the trained artificial intelligence model is tested using the test data, and the artificial intelligence model is adjusted according to the test results; finally, an irrigation water consumption prediction model is obtained, whose input is the irrigation water consumption of several recent consecutive cycles and whose output is the predicted value of the irrigation water consumption in the prediction cycle; wherein the artificial intelligence model includes a BP neural network model or an RBF neural network model.

[0026] Preferably, the step of constructing a water pump scheduling priority sequence based on the equipment operation information and working environment information of each water pump includes:

[0027] Extract the equipment operation information and working environment information of each water pump; calculate the wear assessment coefficient of each water pump based on the equipment operation information and working environment information; sort the wear assessment coefficients in ascending order to obtain the water pump scheduling priority sequence.

[0028] Preferably, the calculation of the wear assessment coefficient of each water pump based on the equipment operation information and the working environment information includes:

[0029] Extract the equipment operation information and working environment information of each water pump; through the formula Calculate the wear assessment coefficient MPXj of water pump j; where LJSj is the cumulative operating time of water pump j, GFZj is the average workload of water pump j, and NSHj is the sediment content in the working environment of water pump j; a, b, and c are all proportional coefficients greater than 0, and the specific values ​​of a, b, and c are set according to the experience of technicians in this field; j = 1, 2, …, m, where m is the total number of water pumps in the pumping station; e is a natural constant, and ln() is a logarithmic function with the natural constant as the base.

[0030] Preferably, the adjusting the operating status of the pump station based on the actual water consumption and the water pump scheduling priority sequence includes:

[0031] C1: Extract the water pump scheduling priority sequence and the actual water consumption of each irrigation area, calculate the sum of the actual water consumption of each irrigation area and mark it as the expected total water consumption;

[0032] C2: Select several pumps from the priority list of water pump scheduling in ascending order of wear assessment coefficients and mark them as pumps to be activated. Calculate the sum of the flow rates of the pumps to be activated and mark it as the expected water supply flow rate. Flow rate refers to the volume of water delivered by the pump per unit time.

[0033] C3: Calculate the product of the expected water supply flow and the set time period to obtain the expected water supply volume;

[0034] C4: Determine whether the expected water supply is less than the expected total water consumption; if so, continue to select several pumps from the pump scheduling priority sequence and mark them as pumps to be activated; if not, set the operating state of the pump to be activated with the largest wear assessment coefficient to be off;

[0035] C5: Set the operating status of the water pump to be activated to on; the operating status includes on and off.

[0036] A second aspect of the present invention provides a control method for a smart pumping station, comprising:

[0037] S1: Collect planting information and rainfall information of the target farmland; obtain equipment operation information and working environment information of each water pump in the pump station;

[0038] S2: Divide the target farmland based on the types of crops currently planted to obtain several irrigation areas;

[0039] S3: Input the planting information of each irrigation area into the crop water use database for matching and obtain the corresponding irrigation water amount;

[0040] S4: Calculating the actual water consumption of the corresponding irrigation area in the set time period based on the irrigation water consumption and rainfall information of each irrigation area;

[0041] S5: Constructing a water pump scheduling priority sequence based on the equipment operation information and working environment information of each water pump;

[0042] S6: Adjust the operating status of the pumping station based on actual water consumption and pump scheduling priority sequence.

[0043] Compared with the prior art, the present invention has the following beneficial effects:

[0044] 1. This invention achieves precise division of farmland and calculates the actual water consumption of each irrigation area by comprehensively collecting target farmland planting information, rainfall information, and equipment operation and working environment information of each pump in the pump station. The optimal irrigation water consumption is matched with the crop water database, and based on this, pump station operation is optimized in combination with the pump scheduling priority sequence, thereby improving water resource utilization, reducing waste, and ensuring that different crops receive the appropriate water supply at different growth stages. At the same time, it extends the service life of water pumps, reduces energy consumption, improves irrigation efficiency and the economic benefits of agricultural production, and meets the needs of modern agricultural precision and intelligent management.

[0045] 2. The present invention accurately calculates the actual water consumption of each irrigation area and summarizes it into an estimated total water consumption. Combined with the water pump scheduling priority sequence and wear assessment coefficient, it intelligently selects the water pumps to be activated and calculates the estimated water supply flow, and then determines the estimated water supply according to the set time period. By comparing the estimated water supply with the estimated total water consumption, the number of water pumps to be activated is dynamically adjusted to ensure sufficient and efficient water supply. After the water supply meets the demand, the water pump with the largest wear assessment coefficient is shut down first to extend the life of the equipment and save energy. Finally, the determined water pumps to be activated are set to the on state to achieve precise irrigation. This solution effectively improves the flexibility of the irrigation system and the efficiency of water resource utilization, reduces operating costs, and ensures the accuracy and sustainability of farmland irrigation.

[0046] 3. The present invention obtains the wear assessment coefficient of each water pump by extracting the equipment operation information and working environment information of each water pump in the pump station and substituting them into the formula for calculation; the present invention comprehensively considers factors such as the cumulative operating time of the water pump, the average workload and the sediment content in the working environment, and the impact of the wear caused by the water pump during actual operation; compared with the traditional scheme of only evaluating the degree of wear based on the operating time of the water pump, the wear assessment coefficient calculated by the present invention can more accurately reflect the actual degree of wear of the water pump; it provides a basis for the subsequent scheduling optimization of several water pumps in the pump station, ensures the uniformity of the wear degree between different water pumps in the pump station, and thus helps to reduce the operation and maintenance level of the pump station. BRIEF DESCRIPTION OF THE DRAWINGS

[0047] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0048] Figure 1 This is an overall flow chart of the control method of the smart pump station of the present invention;

[0049] Figure 2 This is a schematic diagram of the control system of the smart pump station of the present invention;

[0050] Figure 3 This is a flow chart of adjusting the operating status of the pump station in the present invention. DETAILED DESCRIPTION

[0051] The technical solutions of the present invention will be clearly and completely described below in conjunction with the embodiments. Obviously, the embodiments described are only some embodiments of the present invention, not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.

[0052] See also Figure 1-Figure 3 , a first aspect of the present invention provides a control system for a smart pumping station, comprising: a data processing module, and a data acquisition module and a pumping station control module connected thereto;

[0053] Data collection module: used to collect planting information and rainfall information of the target farmland; obtain equipment operation information and working environment information of each water pump in the pump station; planting information includes the type and growth cycle of the current crop; operation information includes the cumulative operation time and average workload; working environment information includes sediment content;

[0054] Data processing module: used to divide the target farmland based on the types of crops currently planted to obtain several irrigation areas; input the planting information of each irrigation area into the crop water use database for matching to obtain the corresponding irrigation water volume; calculate the actual water consumption of the corresponding irrigation area in a set time period based on the irrigation water volume and rainfall information of each irrigation area; and

[0055] Construct a water pump dispatch priority sequence based on the equipment operation information and working environment information of each water pump;

[0056] Pump station control module: used to adjust the operating status of the pump station based on actual water consumption and pump scheduling priority sequence.

[0057] In this embodiment, a control system of a smart pumping station further includes a crop water use database, which includes the water consumption per unit area of ​​several crop types in different growth cycles.

[0058] For example, when the crop type is rice, the specific data of the crop water use database is represented by the following table:

[0059]

[0060] In this embodiment, the target farmland is divided based on the types of crops currently planted, including:

[0061] The target farmland is divided into several sub-areas of equal area, and the types of crops currently planted in each sub-area are extracted; it is determined whether the types of crops currently planted in adjacent sub-areas are the same; if yes, the adjacent sub-areas are merged into one irrigation area; if not, the corresponding sub-areas are treated as separate irrigation areas.

[0062] For example, the target farmland is divided into four adjacent sub-areas of equal area, the crops planted in sub-area 1 and sub-area 3 are rice, the crop planted in sub-area 2 is cotton, and the crop planted in sub-area 4 is corn; since the types of crops currently planted in sub-area 1 and sub-area 3 are the same, sub-area 1 and sub-area 3 are merged into one irrigation area.

[0063] In this embodiment, the planting information of each irrigation area is input into the crop water use database for matching, including:

[0064] A1: Extract the planting information of each irrigation area and obtain the planting area of ​​each irrigation area;

[0065] A2: Input the type and growth cycle of the currently planted crops in the planting information into the crop water usage database to obtain the water consumption per unit area;

[0066] A3: Multiply the water consumption per unit area of ​​the current crops planted in each irrigation area by the corresponding planting area to obtain the irrigation water consumption of each irrigation area.

[0067] For example, if the type of crop currently planted in irrigation area 1 is rice and the growth cycle is the seedling stage, then by inputting the crop water use database, the corresponding water consumption per unit area is 1,000 cubic meters / mu; if the planting area of ​​irrigation area 1 is set to 3 mu, then combined with the water consumption per unit area of ​​irrigation area 1, the irrigation water consumption of irrigation area 1 is 3,000 cubic meters.

[0068] In this embodiment, the actual water consumption of the corresponding irrigation area in a set time period is calculated based on the irrigation water consumption and rainfall information of each irrigation area, including:

[0069] B1: Extract the irrigation water consumption and rainfall information of each irrigation area in several consecutive periods;

[0070] B2: Input the irrigation water consumption of several consecutive periods into the irrigation water consumption prediction model to obtain the irrigation water consumption forecast value of the park; the irrigation water consumption prediction model is constructed based on the artificial intelligence model;

[0071] B3: Using time as the independent variable and irrigation water consumption and rainfall information as dependent variables, generate the irrigation water consumption curve fi(t) and rainfall curve gi(t) through curve fitting. Where i = 1, 2, …, n, where n is the total number of irrigation areas.

[0072] B4: By formula Calculate the actual water consumption SYLi of irrigation area i within the set time period; where t is time, t1 is the start time of the set time period, t2 is the end time of the set time period, and t1≤t≤t2.

[0073] In this embodiment, the irrigation water consumption prediction model is constructed based on an artificial intelligence model, including:

[0074] The irrigation water consumption of each irrigation area in several consecutive cycles is extracted and integrated into several groups of original data, 80% of the original data is used as training data and 20% as test data; the artificial intelligence model is trained using the training data, and the trained artificial intelligence model is tested using the test data, and the artificial intelligence model is adjusted according to the test results; finally, an irrigation water consumption prediction model is obtained, whose input is the irrigation water consumption of several recent consecutive cycles and whose output is the predicted value of the irrigation water consumption in the prediction cycle; wherein the artificial intelligence model includes a BP neural network model or an RBF neural network model.

[0075] In this embodiment, a water pump scheduling priority sequence is constructed based on the equipment operation information and working environment information of each water pump, including:

[0076] Extract the equipment operation information and working environment information of each water pump; calculate the wear assessment coefficient of each water pump based on the equipment operation information and working environment information; sort the wear assessment coefficients in ascending order to obtain the water pump scheduling priority sequence.

[0077] For example, the wear assessment coefficients of water pump 1, water pump 2, water pump 3, water pump 4, and water pump 5 are set to MPX1=78.48, MPX2=45.58, MPX3=52.37, MPX4=48.63, and MPX5=85.61, respectively; and the water pump scheduling priority sequence is obtained by sorting them in ascending order according to the wear assessment coefficients as {water pump 2, water pump 4, water pump 3, water pump 1, water pump 5}.

[0078] In this embodiment, the wear assessment coefficient of each water pump is calculated based on the equipment operation information and the working environment information, including:

[0079] Extract the equipment operation information and working environment information of each water pump; through the formula Calculate the wear assessment coefficient MPXj of water pump j; where LJSj is the cumulative operating time of water pump j, GFZj is the average workload of water pump j, and NSHj is the sediment content in the working environment of water pump j; a, b, and c are all proportional coefficients greater than 0, and the specific values ​​of a, b, and c are set according to the experience of technicians in this field; j = 1, 2, …, m, where m is the total number of water pumps in the pumping station; e is a natural constant, and ln() is a logarithmic function with the natural constant as the base.

[0080] For example, the proportional coefficients a=1.2, b=0.1, and c=3 are set; the cumulative operating time of water pump 1 LJS1=150h, the average workload of water pump 1 GFZ1=80%, and the sediment content NSH1 in the working environment of water pump 1=120g / m3; the wear assessment coefficient of water pump 1 MPX1≈78.48 is calculated by the formula.

[0081] The present invention obtains the wear assessment coefficient of each water pump by extracting the equipment operation information and working environment information of each water pump in the pump station and substituting them into the formula for calculation; the present invention comprehensively considers factors such as the cumulative operating time of the water pump, the average workload and the sediment content in the working environment, and the impact of the wear caused by the water pump during the actual operation process; compared with the traditional scheme of evaluating the degree of wear only according to the operating time of the water pump, the wear assessment coefficient calculated by the present invention can more accurately reflect the actual degree of wear of the water pump; it provides a basis for the subsequent scheduling optimization of several water pumps in the pump station, ensures the uniformity of the wear degree between different water pumps in the pump station, and is conducive to reducing the operation and maintenance level of the pump station.

[0082] In this embodiment, the operating status of the pump station is adjusted based on the actual water consumption and the priority sequence of the water pump scheduling, including:

[0083] C1: Extract the water pump scheduling priority sequence and the actual water consumption of each irrigation area, calculate the sum of the actual water consumption of each irrigation area and mark it as the expected total water consumption;

[0084] C2: Select several pumps from the priority list of water pump scheduling in ascending order of wear assessment coefficients and mark them as pumps to be activated. Calculate the sum of the flow rates of the pumps to be activated and mark it as the expected water supply flow rate. Flow rate refers to the volume of water delivered by the pump per unit time.

[0085] C3: Calculate the product of the expected water supply flow and the set time period to obtain the expected water supply volume;

[0086] C4: Determine whether the expected water supply is less than the expected total water consumption; if so, continue to select several pumps from the pump scheduling priority sequence and mark them as pumps to be activated; if not, set the operating state of the pump to be activated with the largest wear assessment coefficient to be off;

[0087] C5: Set the operating status of the water pump to be activated to on; the operating status includes on and off.

[0088] The present invention accurately calculates the actual water consumption of each irrigation area and summarizes it into an estimated total water consumption. In combination with the water pump scheduling priority sequence and the wear assessment coefficient, it intelligently selects the water pumps to be activated and calculates the estimated water supply flow, and then determines the estimated water supply according to the set time period. By comparing the estimated water supply with the estimated total water consumption, the number of water pumps to be activated is dynamically adjusted to ensure sufficient and efficient water supply. After the water supply meets the demand, the water pump with the largest wear assessment coefficient is shut down first to extend the life of the equipment and save energy. Finally, the determined water pumps to be activated are set to the on state to achieve precise irrigation. This solution effectively improves the flexibility of the irrigation system and the efficiency of water resource utilization, reduces operating costs, and ensures the accuracy and sustainability of farmland irrigation.

[0089] A second embodiment of the present invention provides a method for controlling a smart pump station, comprising:

[0090] S1: Collect planting information and rainfall information of the target farmland; obtain equipment operation information and working environment information of each water pump in the pump station;

[0091] S2: Divide the target farmland based on the types of crops currently planted to obtain several irrigation areas;

[0092] S3: Input the planting information of each irrigation area into the crop water use database for matching and obtain the corresponding irrigation water amount;

[0093] S4: Calculating the actual water consumption of the corresponding irrigation area in the set time period based on the irrigation water consumption and rainfall information of each irrigation area;

[0094] S5: Constructing a water pump scheduling priority sequence based on the equipment operation information and working environment information of each water pump;

[0095] S6: Adjust the operating status of the pumping station based on actual water consumption and pump scheduling priority sequence.

[0096] Some of the data in the above formula are calculated by removing the dimensions and taking their numerical values. The formula is a formula that is closest to the actual situation obtained by software simulation of a large amount of collected data; the preset parameters and preset thresholds in the formula are set by technical personnel in this field according to actual conditions or obtained through simulation of a large amount of data.

[0097] Working principle of the present invention:

[0098] The present invention collects planting information and rainfall information of target farmland; obtains equipment operation information and working environment information of each water pump in the pump station; divides the target farmland according to the types of currently planted crops to obtain several irrigation areas; inputs the planting information of each irrigation area into a crop water use database for matching to obtain the corresponding irrigation water volume; calculates the actual water consumption of the corresponding irrigation area in a set time period based on the irrigation water volume and rainfall information of each irrigation area; constructs a water pump scheduling priority sequence based on the equipment operation information and working environment information of each water pump; and adjusts the operating status of the pump station based on the actual water volume and the water pump scheduling priority sequence.

[0099] The above embodiments are only used to illustrate the technical method of the present invention and are not intended to limit the present invention. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical method of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical method of the present invention.

Claims

1. A control system for a smart pumping station, comprising: The data processing module, and the data acquisition module and pump station control module connected thereto are characterized in that: The data acquisition module is used to collect planting information and rainfall information of the target farmland; obtain equipment operation information and working environment information of each water pump in the pump station; wherein the planting information includes the type and growth cycle of the currently planted crops; The data processing module is used to divide the target farmland based on the types of crops currently planted to obtain a number of irrigation areas; input the planting information of each irrigation area into the crop water use database for matching to obtain the corresponding irrigation water volume; calculate the actual water volume of the corresponding irrigation area in a set time period based on the irrigation water volume and rainfall information of each irrigation area; and Construct a water pump dispatch priority sequence based on the equipment operation information and working environment information of each water pump; The pump station control module is used to adjust the operating status of the pump station based on the actual water consumption and the water pump scheduling priority sequence; The method of constructing a water pump scheduling priority sequence based on the equipment operation information and working environment information of each water pump includes: Extracting the equipment operation information and working environment information of each water pump; calculating the wear assessment coefficient of each water pump based on the equipment operation information and working environment information; sorting the wear assessment coefficients from small to large to obtain the water pump scheduling priority sequence; The calculation of the wear assessment coefficient of each water pump based on the equipment operation information and the working environment information includes: The equipment operation information and working environment information of each water pump are extracted; the wear assessment coefficient is calculated through a linear mapping relationship between the sediment content, average workload and accumulated working time in the working environment of the corresponding water pump.

2. The control system of a smart pumping station according to claim 1, characterized in that: The crop water use database includes water consumption per unit area of ​​several crop types in different growth cycles.

3. The control system of a smart pumping station according to claim 1, characterized in that: The target farmland is divided based on the types of crops currently planted, including: The target farmland is divided into several sub-areas of equal area, and the types of crops currently planted in each sub-area are extracted; it is determined whether the types of crops currently planted in adjacent sub-areas are the same; if yes, the adjacent sub-areas are merged into one irrigation area; if not, the corresponding sub-areas are treated as separate irrigation areas.

4. The control system of a smart pumping station according to claim 1, characterized in that: The step of inputting the planting information of each irrigation area into the crop water use database for matching includes: A1: Extract the planting information of each irrigation area and obtain the planting area of ​​each irrigation area; A2: Input the type and growth cycle of the currently planted crops in the planting information into the crop water usage database to obtain the water consumption per unit area; A3: Multiply the water consumption per unit area of ​​the current crops planted in each irrigation area by the corresponding planting area to obtain the irrigation water consumption of each irrigation area.

5. The control system of a smart pumping station according to claim 1, characterized in that: The calculation of the actual water consumption of the corresponding irrigation area in a set time period based on the irrigation water consumption and rainfall information of each irrigation area includes: B1: Extract the irrigation water consumption and rainfall information of each irrigation area in several consecutive periods; B2: Input the irrigation water consumption of several consecutive periods into the irrigation water consumption prediction model to obtain the irrigation water consumption forecast value of the park; the irrigation water consumption prediction model is constructed based on the artificial intelligence model; B3: Using time as the independent variable and irrigation water consumption and rainfall information as dependent variables, generate the irrigation water consumption curve fi(t) and rainfall curve gi(t) through curve fitting. Where i = 1, 2, …, n, where n is the total number of irrigation areas. B4: By formula Calculate the actual water consumption SYLi of irrigation area i within the set time period; where t is time, t1 is the start time of the set time period, t2 is the end time of the set time period, and t1≤t≤t2.

6. The control system of a smart pumping station according to claim 5, characterized in that: The irrigation water consumption prediction model is constructed based on an artificial intelligence model and includes: The irrigation water consumption of each irrigation area in several consecutive cycles is extracted and integrated into several groups of training data and test data; the artificial intelligence model is trained using the training data, and the trained artificial intelligence model is tested using the test data, and the artificial intelligence model is adjusted according to the test results; finally, an irrigation water consumption prediction model is obtained, whose input is the irrigation water consumption of several recent consecutive cycles and whose output is the predicted value of the irrigation water consumption in the prediction cycle; wherein the artificial intelligence model includes a BP neural network model or an RBF neural network model.

7. The control system of a smart pumping station according to claim 1, characterized in that: The adjustment of the operating status of the pump station based on the actual water consumption and the water pump scheduling priority sequence includes: C1: Extract the water pump scheduling priority sequence and the actual water consumption of each irrigation area, calculate the sum of the actual water consumption of each irrigation area and mark it as the expected total water consumption; C2: Select several pumps from the priority list of water pump scheduling in ascending order of wear assessment coefficients and mark them as pumps to be activated. Calculate the sum of the flow rates of the pumps to be activated and mark it as the expected water supply flow rate. Flow rate refers to the volume of water delivered by the pump per unit time. C3: Calculate the product of the expected water supply flow and the set time period to obtain the expected water supply volume; C4: Determine whether the expected water supply is less than the expected total water consumption; if so, continue to select several pumps from the pump scheduling priority sequence and mark them as pumps to be activated; if not, set the operating state of the pump to be activated with the largest wear assessment coefficient to be off; C5: Set the operating status of the water pump to be activated to on; the operating status includes on and off.

8. A control method for a smart pumping station, based on the control system of a smart pumping station according to any one of claims 1 to 7, characterized in that: include: S1: Collect planting information and rainfall information of the target farmland; obtain equipment operation information and working environment information of each water pump in the pump station; S2: Divide the target farmland based on the types of crops currently planted to obtain several irrigation areas; S3: Input the planting information of each irrigation area into the crop water use database for matching and obtain the corresponding irrigation water amount; S4: Calculating the actual water consumption of the corresponding irrigation area in the set time period based on the irrigation water consumption and rainfall information of each irrigation area; S5: Constructing a water pump scheduling priority sequence based on the equipment operation information and working environment information of each water pump; S6: Adjust the operating status of the pumping station based on actual water consumption and pump scheduling priority sequence.

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