Method, equipment and storage medium for locating monitoring sites of agricultural irrigation wells using electricity to convert water into electricity

Abstract

The present invention relates to the technical field of agricultural irrigation using electricity to convert water, and in particular to a method, device, and storage medium for locating monitoring stations for agricultural irrigation wells using electricity to convert water. An embodiment of the present invention analyzes the basic characteristics of agricultural irrigation wells using electricity to convert water based on a historical irrigation data set and clusters the agricultural irrigation wells based on the basic characteristics, so that the agricultural irrigation wells clustered into one category have similar characteristics of using electricity to convert water. An embodiment of the present invention divides irrigation areas based on agricultural irrigation wells with similar characteristics of using electricity to convert water, and selects typical agricultural irrigation wells as monitoring stations based on the regional divisions. The selected stations are typical, and the station settings should conform to the characteristics of local water and electricity consumption, thereby ensuring the accuracy of calculating monitoring of using electricity to convert water while reducing the construction of unnecessary stations.

Description

Technical Field

[0001] The present invention relates to the technical field of converting electricity into water for agricultural irrigation, and in particular to a method, equipment and storage medium for locating a monitoring station for converting electricity into water for agricultural irrigation wells. Background Art

[0002] The "electricity-to-water" method analyzes the relationship between electricity consumption and water withdrawal to determine the water withdrawal amount. This method then uses the power consumption and water withdrawal coefficient to derive water withdrawal amounts. Currently, most electricity-to-water conversion methods use historical statistical data to determine the conversion coefficient, which is then used to calculate irrigation water volume based on electricity consumption. This method has the advantage of a simple algorithm, but it also presents a problem of significant data bias.

[0003] As an improvement to the electricity-to-water conversion method, some technologies have proposed building large models based on historical data, attempting to calculate irrigation water volume by inputting relevant parameters of agricultural irrigation wells and electricity usage data. This approach aims to include comprehensive data on factors affecting electricity-to-water conversion, but it faces difficulties due to the massive amount of data required, complex modeling processes, and extensive data processing, making its promotion and implementation difficult.

[0004] Other technologies propose using monitoring stations to collect statistics on electricity and water usage. Agricultural irrigation wells surrounding the monitoring stations use the monitoring stations as a reference to determine water usage. Alternatively, small models can be constructed based on the monitoring station's conditions to determine irrigation water volumes for surrounding agricultural irrigation wells. Station setup should be tailored to local water and electricity usage characteristics. Blindly placing stations will result in areas not accurately reflecting the relationship between water and electricity. High density of monitoring stations can lead to high duplication of equipment construction, and excessive resource investment can lead to waste.

[0005] Based on this, it is necessary to develop and design a method for locating agricultural irrigation well monitoring stations using electricity to convert water into electricity. Summary of the Invention

[0006] The embodiments of the present invention provide a method, device and storage medium for locating monitoring stations for agricultural irrigation wells using electricity to convert water into electricity, which is used to solve the problem in the prior art of lack of reasonable configuration of monitoring stations to achieve more accurate irrigation water statistics with less resource investment.

[0007] In a first aspect, an embodiment of the present invention provides a method for locating monitoring stations for agricultural irrigation wells using electricity-converted water, comprising:

[0008] Acquire multiple irrigation history data sets, wherein the irrigation history data sets represent data on agricultural irrigation well parameters, electricity consumption, and irrigation characteristics;

[0009] Constructing a plurality of electricity-to-water conversion feature vectors based on the plurality of irrigation history data sets, clustering the plurality of electricity-to-water conversion feature vectors to obtain a plurality of clustering results, wherein each electricity-to-water conversion feature vector corresponds to an agricultural irrigation well, and the electricity-to-water conversion feature vector characterizes the characteristics of the agricultural irrigation well in terms of electricity-to-water conversion;

[0010] The irrigation zone is determined based on the location of the agricultural irrigation wells corresponding to the electricity-to-water feature vectors that exceed the threshold in each clustering result;

[0011] Based on the electricity-to-water conversion characteristics of the agricultural irrigation wells in the zoned area, the electricity-to-water conversion monitoring sites for the agricultural irrigation wells are determined.

[0012] In one possible implementation, the irrigation history dataset includes: irrigation equipment parameters, irrigation electricity consumption data, irrigation area, and irrigation duration. Multiple electricity-to-water feature vectors are constructed based on the multiple irrigation history datasets, and the multiple electricity-to-water feature vectors are clustered to obtain multiple clustering results, including:

[0013] According to the correspondence with the agricultural irrigation wells, the plurality of irrigation history data sets are grouped into a plurality of well data groups, wherein each agricultural irrigation well corresponds to one well data group;

[0014] For each irrigation history dataset, the quotient of the irrigation area and the irrigation duration is calculated, and the obtained result is used as the irrigation flow index of the irrigation history dataset;

[0015] Constructing the first equation that represents the relationship between irrigation equipment parameters and irrigation electricity data and irrigation flow index;

[0016] Constructing a plurality of equation groups based on the plurality of pumped well data groups and the first equation, and constructing a plurality of electricity-to-water characteristic equations based on the plurality of equation groups, wherein each electricity-to-water characteristic equation corresponds to an agricultural irrigation pumped well;

[0017] Constructing multiple coefficients of each electricity-to-water characteristic equation into electricity-to-water characteristic vectors, thereby obtaining multiple electricity-to-water characteristic vectors;

[0018] The multiple electricity-to-water feature vectors are clustered to obtain multiple clustering results.

[0019] In one possible implementation, constructing multiple equation groups based on the multiple pumped well data groups and the first equation, and constructing multiple electricity-to-water characteristic equations based on the multiple equation groups includes:

[0020] For each well data group, perform the following steps:

[0021] Substituting the irrigation equipment parameters, irrigation electricity data, and irrigation flow index of each irrigation history data set into the first equation, thereby obtaining a plurality of intermediate equations, wherein each intermediate equation corresponds to one irrigation history data set;

[0022] Combining the multiple intermediate equations to obtain an equation system;

[0023] Obtaining a plurality of coefficient solutions of the first equation according to the set of equations;

[0024] Substituting the multiple coefficient solutions into the first equation, a characteristic equation of electricity-to-water conversion is obtained.

[0025] In one possible implementation, the first equation is:

[0026]

[0027] Where, is the irrigation flow index, For the The first coefficient, The historical data set parameters, is the total number of parameter data in the historical data set, is the total number of exponentials, is the first constant.

[0028] In one possible implementation, each clustering result corresponds to an agricultural irrigation well class, and each agricultural irrigation well class includes multiple electricity-to-water feature vectors, which characterize the characteristics of the agricultural irrigation wells in terms of electricity-to-water. The method of determining the irrigation zone based on the location of the agricultural irrigation wells corresponding to the electricity-to-water feature vectors whose proportion in each clustering result exceeds a proportion threshold includes:

[0029] For each agricultural irrigation well type, perform the following steps:

[0030] Determine multiple locations of agricultural irrigation wells according to multiple agricultural irrigation wells corresponding to the characteristic vectors of electricity converted to water, wherein each agricultural irrigation well location corresponds to a characteristic vector of electricity converted to water;

[0031] For each agricultural irrigation well location, find the location closest to the multiple agricultural irrigation well locations as a first target location, and use the distance to the first target location as a reference distance, thereby obtaining multiple reference distances;

[0032] Randomly selecting a location from the plurality of agricultural irrigation well locations as a second target location and adding the location to the location set;

[0033] Searching for a location from the plurality of agricultural irrigation well locations, the distance from the second target location being less than a search distance, wherein the search distance is determined in proportion to an average of the plurality of reference distances;

[0034] If there is a position whose distance from the second target position is less than the search distance, the position whose distance from the second target position is less than the search distance is taken as the second target position and added to the position set, and the process jumps to the step of searching for a position whose distance from the second target position is less than the search distance from the multiple agricultural irrigation well positions;

[0035] Otherwise, the ratio of the number of agricultural irrigation well locations not included in the location set to the total number of the plurality of agricultural irrigation well locations is used as the first ratio;

[0036] If the first ratio is less than the proportion threshold, the irrigation area is delineated according to the locations of the concentrated agricultural irrigation wells.

[0037] In one possible implementation, each agricultural irrigation well in the zoning area corresponds to a characteristic vector of electricity-to-water conversion, and the characteristic vector of electricity-to-water conversion characterizes the characteristics of the agricultural irrigation well in terms of electricity-to-water conversion. Determining the monitoring station for the agricultural irrigation well in terms of electricity-to-water conversion based on the characteristics of the agricultural irrigation well in the zoning area includes:

[0038] Extracting the electricity-to-water characteristic vectors of the plurality of agricultural irrigation wells in the segmented area as a plurality of first vectors;

[0039] extracting a mean vector of the plurality of first vectors;

[0040] Calculating the Euclidean distance of each first vector from the mean vector and the cosine similarity to the mean vector respectively, to obtain a plurality of Euclidean distances and a plurality of cosine similarities;

[0041] Determining a plurality of comprehensive distance indices based on the plurality of Euclidean distances and the plurality of cosine similarities, wherein the comprehensive distance indices characterize the typicality of converting electricity into water in agricultural irrigation wells;

[0042] An agricultural irrigation well is selected from a plurality of agricultural irrigation wells according to the plurality of comprehensive distance indices as an electricity-to-water monitoring site.

[0043] In one possible implementation, determining multiple comprehensive distance indices based on the multiple Euclidean distances and the multiple cosine similarities includes:

[0044] A plurality of comprehensive distance indices are determined based on the third formula, the plurality of Euclidean distances, and the plurality of cosine similarities, wherein each comprehensive distance index corresponds to an agricultural irrigation well. The third formula is:

[0045]

[0046] Where, For the The comprehensive distance index of agricultural irrigation wells, For the The Euclidean distance between the irrigation wells, is the maximum Euclidean distance, For the The cosine similarity of the agricultural irrigation wells, is the second coefficient, is the third coefficient.

[0047] In a second aspect, an embodiment of the present invention provides a device for locating a monitoring station for water conversion by electricity in an agricultural irrigation well, which is used to implement the method for locating a monitoring station for water conversion by electricity in an agricultural irrigation well as described in the first aspect or any possible implementation of the first aspect. The device for locating a monitoring station for water conversion by electricity in an agricultural irrigation well includes:

[0048] A historical data acquisition module is used to acquire multiple irrigation history data sets, wherein the irrigation history data sets represent data on agricultural irrigation well parameters, electricity consumption, and irrigation characteristics;

[0049] a feature extraction and clustering module, configured to construct a plurality of electricity-to-water feature vectors based on the plurality of irrigation history data sets, cluster the plurality of electricity-to-water feature vectors, and obtain a plurality of clustering results, wherein each electricity-to-water feature vector corresponds to an agricultural irrigation well, and the electricity-to-water feature vector characterizes the characteristics of the agricultural irrigation well in terms of electricity-to-water;

[0050] The irrigation area division module is used to determine the irrigation area according to the location of the agricultural irrigation wells corresponding to the electricity-to-water feature vectors in each clustering result that exceed the threshold;

[0051] as well as,

[0052] The monitoring site positioning module is used to determine the electricity-to-water conversion monitoring sites of the agricultural irrigation wells according to the electricity-to-water conversion characteristics of the agricultural irrigation wells in the divided area.

[0053] In a third aspect, an embodiment of the present invention provides an electronic device comprising a memory and a processor, wherein the memory stores a computer program that can be run on the processor, and when the processor executes the computer program, it implements the steps of the method described in the first aspect or any possible implementation of the first aspect.

[0054] In a fourth aspect, an embodiment of the present invention provides a computer-readable storage medium, which stores a computer program. When the computer program is executed by a processor, it implements the steps of the method described in the first aspect or any possible implementation of the first aspect.

[0055] Compared with the prior art, the embodiments of the present invention have the following beneficial effects:

[0056] The embodiment of the present invention discloses a method for locating monitoring stations for electricity-to-water conversion for agricultural irrigation wells. The method first obtains multiple irrigation history data sets, wherein the irrigation history data sets represent data on agricultural irrigation well parameters, electricity consumption, and irrigation characteristics; then, based on the multiple irrigation history data sets, multiple electricity-to-water conversion feature vectors are constructed, and the multiple electricity-to-water conversion feature vectors are clustered to obtain multiple clustering results, wherein each electricity-to-water conversion feature vector corresponds to an agricultural irrigation well, and the electricity-to-water conversion feature vector represents the characteristics of the agricultural irrigation wells in terms of electricity-to-water conversion; then, based on the locations of the agricultural irrigation wells corresponding to the electricity-to-water conversion feature vectors whose proportion in each clustering result exceeds a proportion threshold, an irrigation zone is determined; finally, based on the electricity-to-water conversion characteristics of the agricultural irrigation wells in the zoned area, an electricity-to-water conversion monitoring station for the agricultural irrigation wells is determined. The embodiment of the present invention analyzes the basic characteristics of the agricultural irrigation wells in terms of electricity-to-water conversion based on the irrigation history data sets and clusters the agricultural irrigation wells based on the basic characteristics, so that the agricultural irrigation wells clustered into one category have similar electricity-to-water conversion characteristics. The implementation mode of the present invention divides the irrigation area into sections based on agricultural irrigation wells with similar electricity-to-water characteristics, and selects typical agricultural irrigation wells as monitoring sites based on the regional division. The selected sites are typical, and the site settings should be in line with the characteristics of local water and electricity consumption, ensuring the accuracy of electricity-to-water monitoring calculations while reducing the construction of unnecessary sites. BRIEF DESCRIPTION OF THE DRAWINGS

[0057] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the embodiments or descriptions 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 labor.

[0058] Figure 1 This is a flow chart of a method for locating monitoring stations for agricultural irrigation wells using electricity to convert water into electricity, provided by an embodiment of the present invention;

[0059] Figure 2 This is a schematic diagram of the irrigation zone demarcation process provided by an embodiment of the present invention;

[0060] Figure 3 This is a functional block diagram of a device for monitoring and locating agricultural irrigation wells using electricity to convert water into electricity, provided by an embodiment of the present invention;

[0061] Figure 4 This is a functional block diagram of an electronic device provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0062] In the following description, specific details such as particular system structures and techniques are provided for purposes of illustration, not limitation, to facilitate a thorough understanding of the embodiments of the present invention. However, it will be apparent to those skilled in the art that the present invention may be practiced in alternative embodiments without these specific details. In other instances, detailed descriptions of well-known systems, devices, and methods are omitted so as not to obscure the description of the present invention with unnecessary detail.

[0063] In order to make the objectives, technical solutions and advantages of the present invention more clear, the following will be described through specific implementation methods in conjunction with the accompanying drawings.

[0064] The following is a detailed description of an embodiment of the present invention. This example is implemented based on the technical solution of the present invention, and provides a detailed implementation method and specific operation process, but the protection scope of the present invention is not limited to the following embodiment.

[0065] Figure 1 This is a flow chart of a method for locating monitoring stations for agricultural irrigation wells using electricity to convert water into electricity, provided in an embodiment of the present invention.

[0066] like Figure 1 As shown, it shows a flowchart of the implementation method of the agricultural irrigation well water monitoring station positioning method provided by the embodiment of the present invention, which is detailed as follows:

[0067] In step 101, a plurality of irrigation history data sets are obtained, wherein the irrigation history data sets represent data on agricultural irrigation well parameters, electricity consumption, and irrigation characteristics.

[0068] In step 102, a plurality of electricity-to-water feature vectors are constructed based on the plurality of irrigation history data sets, and the plurality of electricity-to-water feature vectors are clustered to obtain a plurality of clustering results, wherein each electricity-to-water feature vector corresponds to an agricultural irrigation well, and the electricity-to-water feature vector characterizes the characteristics of the electricity-to-water feature vector of the agricultural irrigation well.

[0069] In some embodiments, the irrigation history dataset includes: irrigation equipment parameters, irrigation electricity usage data, irrigation area, and irrigation duration. The method constructs multiple electricity-to-water feature vectors based on the multiple irrigation history datasets, clusters the multiple electricity-to-water feature vectors, and obtains multiple clustering results, including:

[0070] According to the correspondence with the agricultural irrigation wells, the plurality of irrigation history data sets are grouped into a plurality of well data groups, wherein each agricultural irrigation well corresponds to one well data group;

[0071] For each irrigation history dataset, the quotient of the irrigation area and the irrigation duration is calculated, and the obtained result is used as the irrigation flow index of the irrigation history dataset;

[0072] Constructing the first equation that represents the relationship between irrigation equipment parameters and irrigation electricity data and irrigation flow index;

[0073] Constructing a plurality of equation groups based on the plurality of pumped well data groups and the first equation, and constructing a plurality of electricity-to-water characteristic equations based on the plurality of equation groups, wherein each electricity-to-water characteristic equation corresponds to an agricultural irrigation pumped well;

[0074] Constructing multiple coefficients of each electricity-to-water characteristic equation into electricity-to-water characteristic vectors, thereby obtaining multiple electricity-to-water characteristic vectors;

[0075] The multiple electricity-to-water feature vectors are clustered to obtain multiple clustering results.

[0076] In some embodiments, constructing multiple equation groups based on the multiple pumped well data groups and the first equation, and constructing multiple electricity-to-water characteristic equations based on the multiple equation groups includes:

[0077] For each well data group, perform the following steps:

[0078] Substituting the irrigation equipment parameters, irrigation electricity data, and irrigation flow index of each irrigation history data set into the first equation, thereby obtaining a plurality of intermediate equations, wherein each intermediate equation corresponds to one irrigation history data set;

[0079] Combining the multiple intermediate equations to obtain an equation system;

[0080] Obtaining a plurality of coefficient solutions of the first equation according to the set of equations;

[0081] Substituting the multiple coefficient solutions into the first equation, a characteristic equation of electricity-to-water conversion is obtained.

[0082] In some embodiments, the first equation is:

[0083]

[0084] Where, is the irrigation flow index, For the The first coefficient, The historical data set parameters, is the total number of parameter data in the historical data set, is the total number of exponentials, is the first constant.

[0085] Exemplarily, an embodiment of the present invention constructs a characteristic vector of electricity-to-water conversion based on a historical data set, clusters agricultural irrigation wells based on the characteristic vector of electricity-to-water conversion, delineates irrigation zones according to the clustering results, and determines a typical monitoring site and irrigation land from the irrigation zones. It should be noted that the characteristic vector of electricity-to-water conversion is a vector that reflects the relationship between irrigation equipment parameters, electricity consumption data and irrigation water flow, and characterizes the characteristics of electricity-to-water conversion. The meaning of the clustering result is to group agricultural irrigation wells with similar characteristics of electricity-to-water conversion together, and finally divide the irrigation area and determine the monitoring sites based on the characteristic vector of electricity-to-water conversion combined with the position of the agricultural irrigation wells. Among them, the historical data set includes irrigation equipment parameters, irrigation electricity consumption data, irrigation area and irrigation time, that is, the historical data set is a statistical set of irrigation data of a certain agricultural irrigation well in a certain period of time. Irrigation equipment parameters may include: water pump rated power, head, flow, rated voltage, rated current and structural form; electricity consumption data may include: voltage, total active power and total reactive power; and because the irrigation water flow cannot be directly obtained before the establishment of a monitoring station, the embodiment of the present invention uses the ratio of the irrigation area to the irrigation duration as the irrigation flow index to characterize the irrigation water flow.

[0086] To achieve the above objectives, the embodiment of the present invention first constructs a first equation that characterizes the relationship between irrigation equipment parameters and irrigation electricity data and irrigation flow index:

[0087]

[0088] Where, is the irrigation flow index, For the The first coefficient, The historical data set parameters, is the total number of parameter data in the historical data set, is the total number of exponentials, is the first constant.

[0089] Then, for each irrigation well, the corresponding dataset is extracted from the historical dataset. These datasets are substituted into the first equation and solved simultaneously to obtain the solutions to the multiple coefficients of the first equation. We can see that the solutions to the multiple coefficients of the first equation are key to reflecting the relationship between irrigation equipment parameters, irrigation electricity data, and irrigation water flow. Therefore, the embodiments of the present invention arrange the multiple solutions in the first equation in a predetermined order to construct a power-to-water characteristic vector. That is, each irrigation well corresponds to a power-to-water vector, and the power-to-water vector represents the power-to-water characteristic.

[0090] By clustering multiple electricity-to-water vectors, the electricity-to-water vectors in each cluster obtained have high consistency, and the corresponding agricultural irrigation wells also have similar electricity-to-water characteristics.

[0091] The clustering method can be DBSCAN or kmeans clustering algorithm.

[0092] In step 103, the irrigation zone is determined according to the location of the agricultural irrigation well corresponding to the electricity-to-water feature vector whose proportion exceeds the proportion threshold in each clustering result.

[0093] In some embodiments, each clustering result corresponds to an agricultural irrigation well class, each agricultural irrigation well class includes a plurality of electricity-to-water feature vectors, and the electricity-to-water feature vectors characterize the characteristics of the agricultural irrigation wells in terms of electricity-to-water. Determining the irrigation zone based on the locations of the agricultural irrigation wells corresponding to the electricity-to-water feature vectors whose proportion in each clustering result exceeds a proportion threshold includes:

[0094] For each agricultural irrigation well type, perform the following steps:

[0095] Determine multiple locations of agricultural irrigation wells according to multiple agricultural irrigation wells corresponding to the characteristic vectors of electricity converted to water, wherein each agricultural irrigation well location corresponds to a characteristic vector of electricity converted to water;

[0096] For each agricultural irrigation well location, find the location closest to the multiple agricultural irrigation well locations as a first target location, and use the distance to the first target location as a reference distance, thereby obtaining multiple reference distances;

[0097] Randomly selecting a location from the plurality of agricultural irrigation well locations as a second target location and adding the location to the location set;

[0098] Searching for a location from the plurality of agricultural irrigation well locations, the distance from the second target location being less than a search distance, wherein the search distance is determined in proportion to an average of the plurality of reference distances;

[0099] If there is a position whose distance from the second target position is less than the search distance, the position whose distance from the second target position is less than the search distance is taken as the second target position and added to the position set, and the process jumps to the step of searching for a position whose distance from the second target position is less than the search distance from the multiple agricultural irrigation well positions;

[0100] Otherwise, the ratio of the number of agricultural irrigation well locations not included in the location set to the total number of the plurality of agricultural irrigation well locations is used as the first ratio;

[0101] If the first ratio is less than the proportion threshold, the irrigation area is delineated according to the location of the agricultural irrigation wells in the concentration.

[0102] For example, the wells corresponding to the electricity-to-water vectors in the clusters obtained through the preceding steps are geographically densely distributed—in other words, they are relatively concentrated in a continuous area. In reality, however, because the first equation model simply expresses the electricity-to-water relationship, the resulting well locations may not be compact, with some wells even being far from others. Therefore, we should verify the clustering results using geographic location and use this verification to define irrigation zones.

[0103] Based on the above analysis, the embodiment of the present invention determines a distance parameter based on the distance from each pumped well to the nearest pumped well. For example, it is 1.5 to 2 times the average value of the distance to the nearest pumped well. Then, as Figure 2 As shown, a well location 201 is randomly selected from these well locations 201 as the collection location target (the black filled circle in the figure), and a well location 201 whose distance from the collection location target is less than the distance parameter is searched. When found, the found well location 201 is added to the well location set, and the found well location is used as the trajectory location target again. The above operation is repeated. After repetition, we find that some well locations 201 may not be added to the well location set. If the proportion of this part is small, at this time, the irrigation demarcation area is delineated based on the location in the well location set. Otherwise, the clustering method of the above steps needs to be readjusted.

[0104] In this way, the embodiment of the present invention completes the demarcation of irrigation areas based on the electricity-to-water characteristics and geographical location, making it convenient to use the monitoring site as a reference to determine the water intake situation, or to build a small model based on the situation of the monitoring site to determine the irrigation water volume of the surrounding agricultural irrigation wells.

[0105] In step 104, based on the electricity-to-water conversion characteristics of the agricultural irrigation wells in the stratified area, monitoring sites for electricity-to-water conversion of the agricultural irrigation wells are determined.

[0106] In some embodiments, each agricultural irrigation well in the slicing area corresponds to a characteristic vector of electricity-to-water conversion, and the characteristic vector of electricity-to-water conversion characterizes the characteristics of the agricultural irrigation well in terms of electricity-to-water conversion. Determining the monitoring station for the agricultural irrigation well in terms of electricity-to-water conversion based on the characteristics of the agricultural irrigation well in the slicing area includes:

[0107] Extracting the electricity-to-water characteristic vectors of the plurality of agricultural irrigation wells in the segmented area as a plurality of first vectors;

[0108] extracting a mean vector of the plurality of first vectors;

[0109] Calculating the Euclidean distance of each first vector from the mean vector and the cosine similarity to the mean vector respectively, to obtain a plurality of Euclidean distances and a plurality of cosine similarities;

[0110] Determining a plurality of comprehensive distance indices based on the plurality of Euclidean distances and the plurality of cosine similarities, wherein the comprehensive distance indices characterize the typicality of converting electricity into water in agricultural irrigation wells;

[0111] An agricultural irrigation well is selected from a plurality of agricultural irrigation wells according to the plurality of comprehensive distance indices as an electricity-to-water monitoring site.

[0112] In some embodiments, determining a plurality of comprehensive distance indices based on the plurality of Euclidean distances and the plurality of cosine similarities includes:

[0113] A plurality of comprehensive distance indices are determined based on the third formula, the plurality of Euclidean distances, and the plurality of cosine similarities, wherein each comprehensive distance index corresponds to an agricultural irrigation well. The third formula is:

[0114]

[0115] Where, For the The comprehensive distance index of agricultural irrigation wells, For the The Euclidean distance between the irrigation wells, is the maximum Euclidean distance, For the The cosine similarity of the agricultural irrigation wells, is the second coefficient, is the third coefficient.

[0116] Exemplarily, in determining the electricity-to-water conversion monitoring stations of the agricultural irrigation wells based on the electricity-to-water conversion characteristics of the agricultural irrigation wells in the zoned area, an embodiment of the present invention extracts the electricity-to-water conversion vectors of the agricultural irrigation wells in the zoned area, and performs averaging calculation based on these vectors to obtain a mean vector.

[0117] Then calculate the Euclidean distance and cosine similarity between the mean vector and each electricity-to-water vector. The Euclidean distance represents the distance between vectors in space, while the cosine similarity represents the similarity of vectors in the spatial direction. In fact, both play an important role in determining typical sites. The embodiment of the present invention uses the third formula to assign a comprehensive distance index to each agricultural irrigation well:

[0118]

[0119] Where, For the The comprehensive distance index of agricultural irrigation wells, For the The Euclidean distance between the irrigation wells, is the maximum Euclidean distance, For the The cosine similarity of the agricultural irrigation wells, is the second coefficient, is the third coefficient.

[0120] It should be noted that the smaller this index is, the more suitable it is as a typical site. That is to say, the comprehensive distance index obtained by the third formula is applied, and the agricultural irrigation well corresponding to the smallest comprehensive distance index is selected as the agricultural irrigation well electricity-to-water monitoring site.

[0121] The present invention provides an implementation method for locating monitoring stations for electricity-to-water conversion for agricultural irrigation wells. The method first obtains multiple historical irrigation data sets, wherein the historical irrigation data sets represent data on agricultural irrigation well parameters, electricity consumption, and irrigation characteristics; then, based on the multiple historical irrigation data sets, multiple electricity-to-water conversion feature vectors are constructed, and the multiple electricity-to-water conversion feature vectors are clustered to obtain multiple clustering results, wherein each electricity-to-water conversion feature vector corresponds to an agricultural irrigation well, and the electricity-to-water conversion feature vector represents the characteristics of the agricultural irrigation wells in terms of electricity-to-water conversion; then, based on the locations of the agricultural irrigation wells corresponding to the electricity-to-water conversion feature vectors whose proportion in each clustering result exceeds a proportion threshold, an irrigation zone is determined; finally, based on the electricity-to-water conversion characteristics of the agricultural irrigation wells in the zoned area, an electricity-to-water conversion monitoring station for the agricultural irrigation wells is determined. The implementation method of the present invention analyzes the basic characteristics of the agricultural irrigation wells in terms of electricity-to-water conversion based on the historical irrigation data sets and clusters the agricultural irrigation wells based on the basic characteristics, so that the agricultural irrigation wells clustered into one category have similar electricity-to-water conversion characteristics. The implementation mode of the present invention divides the irrigation area into sections based on agricultural irrigation wells with similar electricity-to-water characteristics, and selects typical agricultural irrigation wells as monitoring sites based on the regional division. The selected sites are typical, and the site settings should be in line with the characteristics of local water and electricity consumption, ensuring the accuracy of electricity-to-water monitoring calculations while reducing the construction of unnecessary sites.

[0122] It should be understood that the size of the serial numbers of each step in the above embodiment does not mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiment of the present invention.

[0123] The following is an embodiment of the device of the present invention. For details not described in detail, please refer to the corresponding method embodiment described above.

[0124] Figure 3 This is a functional block diagram of the device for monitoring the location of agricultural irrigation wells using electricity to convert water into electricity, provided by the embodiment of the present invention. Figure 3 The device for monitoring station positioning of agricultural irrigation wells using electricity to convert water into electricity includes: a historical data acquisition module, a feature extraction and clustering module, an irrigation area division module, and a monitoring station positioning module, wherein:

[0125] The historical data acquisition module 301 is used to acquire a plurality of irrigation history data sets, wherein the irrigation history data sets represent data on agricultural irrigation well parameters, electricity consumption, and irrigation characteristics;

[0126] A feature extraction and clustering module 302 is configured to construct a plurality of electricity-to-water feature vectors based on the plurality of irrigation history data sets, cluster the plurality of electricity-to-water feature vectors, and obtain a plurality of clustering results, wherein each electricity-to-water feature vector corresponds to an agricultural irrigation well, and the electricity-to-water feature vector represents the characteristics of the agricultural irrigation well in terms of electricity-to-water.

[0127] The irrigation area division module 303 is configured to determine the irrigation area division according to the location of the agricultural irrigation well corresponding to the electricity-to-water feature vector in each clustering result that exceeds the threshold;

[0128] The monitoring site positioning module 304 is used to determine the monitoring sites of the agricultural irrigation wells based on the electricity-to-water conversion characteristics of the agricultural irrigation wells in the divided area.

[0129] Figure 4 : is a functional block diagram of an electronic device provided by an embodiment of the present invention. Figure 4 As shown, the electronic device 4 of this embodiment includes: a processor 400 and a memory 401, wherein the memory 401 stores a computer program 402 that can be run on the processor 400. When the processor 400 executes the computer program 402, the steps in the above-mentioned method and embodiment for locating each agricultural irrigation well by using electricity to convert water into monitoring stations are implemented, such as Figure 1 Steps 101 to 104 are shown.

[0130] Illustratively, the computer program 402 may be divided into one or more modules / units, and the one or more modules / units are stored in the memory 401 and executed by the processor 400 to implement the present invention.

[0131] The electronic device 4 may be a computing device such as a desktop computer, a notebook, a PDA, or a cloud server. The electronic device 4 may include, but is not limited to, a processor 400 and a memory 401. Those skilled in the art will understand that Figure 4 It is only an example of the electronic device 4 and does not constitute a limitation of the electronic device 4. It may include more or fewer components than shown in the figure, or a combination of certain components, or different components. For example, the electronic device 4 may also include input and output devices, network access devices, buses, etc.

[0132] The processor 400 may be a central processing unit (CPU), or other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. A general-purpose processor may be a microprocessor or any conventional processor.

[0133] The memory 401 may be an internal storage unit of the electronic device 4, such as a hard drive or memory of the electronic device 4. The memory 401 may also be an external storage device of the electronic device 4, such as a plug-in hard drive, a Smart Media Card (SMC), a Secure Digital (SD) card, a flash memory card, etc. equipped on the electronic device 4. Furthermore, the memory 401 may include both an internal storage unit of the electronic device 4 and an external storage device. The memory 401 is used to store the computer program 402 and other programs and data required by the electronic device 4. The memory 401 may also be used to temporarily store data that has been output or is about to be output.

[0134] Those skilled in the art can clearly understand that, for the convenience and brevity of description, only the division of the above-mentioned functional units and modules is used as an example for illustration. In actual applications, the above-mentioned functions can be distributed and completed by different functional units and modules as needed, that is, the internal structure of the device can be divided into different functional units or modules to complete all or part of the functions described above. The functional units and modules in the implementation method can be integrated into one processing unit, or each unit can exist physically alone, or two or more units can be integrated into one unit. The above-mentioned integrated unit can be implemented in the form of hardware or in the form of software functional units. In addition, the specific names of the functional units and modules are only for the convenience of distinguishing each other, and are not used to limit the scope of protection of this application. The specific working process of the units and modules in the above-mentioned system can refer to the corresponding process in the aforementioned method implementation method, and will not be repeated here.

[0135] In the above embodiments, the description of each embodiment has its own focus. For parts that are not described or recorded in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0136] Those skilled in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professionals and technicians may use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of the present invention.

[0137] In the embodiments provided by the present invention, it should be understood that the disclosed devices / electronic devices and methods can be implemented in other ways. For example, the device / electronic device embodiments described above are merely illustrative. For example, the division of the modules or units is merely a logical function division. In actual implementation, there may be other division methods, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or units, which can be electrical, mechanical or other forms.

[0138] The units described as separate components may or may not be physically separate, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed across multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of this embodiment.

[0139] In addition, the functional units in various embodiments of the present invention may be integrated into a single processing unit, each unit may exist physically separately, or two or more units may be integrated into a single unit. The aforementioned integrated units may be implemented in the form of hardware or software functional units.

[0140] If the integrated module / unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the present invention can also implement all or part of the processes in the above-mentioned method embodiments by instructing the relevant hardware through a computer program. The computer program can be stored in a computer-readable storage medium. When executed by a processor, the computer program can implement the steps of the above-mentioned method and device embodiments. The computer program includes computer program code, which can be in source code form, object code form, executable file, or some intermediate form. The computer-readable medium can include: any entity or device capable of carrying the computer program code, recording medium, USB flash drive, mobile hard drive, magnetic disk, optical disk, computer memory, read-only memory (ROM), random access memory (RAM), electrical carrier signal, telecommunication signal, and software distribution medium.

[0141] The above-described embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit the same. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. These modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the various embodiments of the present invention, and should all be included in the scope of protection of the present invention.

Claims

1. A method for locating monitoring stations for agricultural irrigation wells using electricity to convert water into electricity, characterized in that: include: Acquire multiple irrigation history data sets, wherein the irrigation history data sets represent data on agricultural irrigation well parameters, electricity consumption, and irrigation characteristics; Constructing a plurality of electricity-to-water conversion feature vectors based on the plurality of irrigation history data sets, clustering the plurality of electricity-to-water conversion feature vectors to obtain a plurality of clustering results, wherein each electricity-to-water conversion feature vector corresponds to an agricultural irrigation well, and the electricity-to-water conversion feature vector characterizes the characteristics of the agricultural irrigation well in terms of electricity-to-water conversion; The irrigation zone is determined based on the location of the agricultural irrigation wells corresponding to the electricity-to-water feature vectors that exceed the threshold in each clustering result; Based on the electricity-to-water conversion characteristics of the agricultural irrigation wells in the zoned area, the electricity-to-water conversion monitoring sites for the agricultural irrigation wells are determined.

2. The method for locating monitoring stations for agricultural irrigation wells using electricity to convert water into electricity according to claim 1, characterized in that: The irrigation history data set includes: irrigation equipment parameters, irrigation electricity data, irrigation area, and irrigation duration. The multiple electricity-to-water feature vectors are constructed based on the multiple irrigation history data sets, and the multiple electricity-to-water feature vectors are clustered to obtain multiple clustering results, including: According to the correspondence with the agricultural irrigation wells, the plurality of irrigation history data sets are grouped into a plurality of well data groups, wherein each agricultural irrigation well corresponds to one well data group; For each irrigation history dataset, the quotient of the irrigation area and the irrigation duration is calculated, and the obtained result is used as the irrigation flow index of the irrigation history dataset; A first equation is constructed to characterize the relationship between irrigation equipment parameters, irrigation electricity data, and irrigation flow index, wherein the first equation is: Where, is the irrigation flow index, For the The first coefficient, The historical data set parameters, is the total number of parameter data in the historical data set, is the total number of exponentials, is the first constant; Constructing a plurality of equation groups based on the plurality of pumped well data groups and the first equation, and constructing a plurality of electricity-to-water characteristic equations based on the plurality of equation groups, wherein each electricity-to-water characteristic equation corresponds to an agricultural irrigation pumped well; Constructing multiple coefficients of each electricity-to-water characteristic equation into electricity-to-water characteristic vectors, thereby obtaining multiple electricity-to-water characteristic vectors; The multiple electricity-to-water feature vectors are clustered to obtain multiple clustering results.

3. The method for locating monitoring stations for agricultural irrigation wells using electricity to convert water into electricity according to claim 2, characterized in that: The step of constructing a plurality of equation groups based on the plurality of pumped well data groups and the first equation, and constructing a plurality of electricity-to-water characteristic equations based on the plurality of equation groups, includes: For each well data group, perform the following steps: Substituting the irrigation equipment parameters, irrigation electricity data, and irrigation flow index of each irrigation history data set into the first equation, thereby obtaining a plurality of intermediate equations, wherein each intermediate equation corresponds to one irrigation history data set; Combining the multiple intermediate equations to obtain an equation system; Obtaining a plurality of coefficient solutions of the first equation according to the set of equations; Substituting the multiple coefficient solutions into the first equation, a characteristic equation of electricity-to-water conversion is obtained.

4. The method for locating monitoring stations for agricultural irrigation wells using electricity to convert water into electricity according to claim 1, characterized in that: Each clustering result corresponds to an agricultural irrigation well class, and each agricultural irrigation well class includes multiple electricity-to-water feature vectors, which characterize the characteristics of the agricultural irrigation wells in terms of electricity-to-water. The method of determining the irrigation zone based on the location of the agricultural irrigation wells corresponding to the electricity-to-water feature vectors whose proportion exceeds a threshold in each clustering result includes: For each agricultural irrigation well type, perform the following steps: Determine multiple locations of agricultural irrigation wells according to multiple agricultural irrigation wells corresponding to the characteristic vectors of electricity converted to water, wherein each agricultural irrigation well location corresponds to a characteristic vector of electricity converted to water; For each agricultural irrigation well location, find the location closest to the multiple agricultural irrigation well locations as a first target location, and use the distance to the first target location as a reference distance, thereby obtaining multiple reference distances; Randomly selecting a location from the plurality of agricultural irrigation well locations as a second target location and adding the location to the location set; Searching for a location from the plurality of agricultural irrigation well locations, the distance from the second target location being less than a search distance, wherein the search distance is determined in proportion to an average of the plurality of reference distances; If there is a position whose distance from the second target position is less than the search distance, the position whose distance from the second target position is less than the search distance is taken as the second target position and added to the position set, and the process jumps to the step of searching for a position whose distance from the second target position is less than the search distance from the multiple agricultural irrigation well positions; Otherwise, the ratio of the number of agricultural irrigation well locations not included in the location set to the total number of the plurality of agricultural irrigation well locations is used as the first ratio; If the first ratio is less than the proportion threshold, the irrigation area is delineated according to the location of the agricultural irrigation wells in the concentration.

5. The method for locating monitoring stations for agricultural irrigation wells using electricity to convert water into electricity according to any one of claims 1 to 4, characterized in that: Each agricultural irrigation well in the zoning area corresponds to a characteristic vector of electricity-to-water conversion, and the characteristic vector of electricity-to-water conversion represents the characteristics of the agricultural irrigation well in terms of electricity-to-water conversion. Determining the monitoring site of the agricultural irrigation well in terms of electricity-to-water conversion based on the characteristics of the agricultural irrigation well in the zoning area includes: Extracting the electricity-to-water characteristic vectors of the plurality of agricultural irrigation wells in the segmented area as a plurality of first vectors; extracting a mean vector of the plurality of first vectors; Calculating the Euclidean distance of each first vector from the mean vector and the cosine similarity to the mean vector respectively, to obtain a plurality of Euclidean distances and a plurality of cosine similarities; Determining a plurality of comprehensive distance indices based on the plurality of Euclidean distances and the plurality of cosine similarities, wherein the comprehensive distance indices characterize the typicality of the agricultural irrigation well in terms of electricity conversion to water; An agricultural irrigation well is selected from a plurality of agricultural irrigation wells according to the plurality of comprehensive distance indices as an electricity-to-water monitoring site.

6. The method for locating monitoring stations for agricultural irrigation wells using electricity to convert water into electricity according to claim 5, characterized in that: Determining a plurality of comprehensive distance indices according to the plurality of Euclidean distances and the plurality of cosine similarities comprises: A plurality of comprehensive distance indices are determined based on the third formula, the plurality of Euclidean distances, and the plurality of cosine similarities, wherein each comprehensive distance index corresponds to an agricultural irrigation well. The third formula is: Where, For the The comprehensive distance index of agricultural irrigation wells, For the The Euclidean distance between the irrigation wells, is the maximum Euclidean distance, For the The cosine similarity of the agricultural irrigation wells, is the second coefficient, is the third coefficient.

7. A device for locating monitoring stations for agricultural irrigation wells using electricity to convert water into electricity, characterized in that: For implementing the method for locating a monitoring station for agricultural irrigation wells using electricity to convert water as described in any one of claims 1 to 6, the device for locating a monitoring station for agricultural irrigation wells using electricity to convert water comprises: A historical data acquisition module is used to acquire multiple irrigation history data sets, wherein the irrigation history data sets represent data on agricultural irrigation well parameters, electricity consumption, and irrigation characteristics; a feature extraction and clustering module, configured to construct a plurality of electricity-to-water feature vectors based on the plurality of irrigation history data sets, cluster the plurality of electricity-to-water feature vectors, and obtain a plurality of clustering results, wherein each electricity-to-water feature vector corresponds to an agricultural irrigation well, and the electricity-to-water feature vector characterizes the characteristics of the agricultural irrigation well in terms of electricity-to-water; The irrigation area division module is used to determine the irrigation area according to the location of the agricultural irrigation wells corresponding to the electricity-to-water feature vectors in each clustering result that exceed the threshold; as well as, The monitoring site positioning module is used to determine the electricity-to-water conversion monitoring sites of the agricultural irrigation wells according to the electricity-to-water conversion characteristics of the agricultural irrigation wells in the divided area.

8. An electronic device comprising a memory and a processor, wherein the memory stores a computer program that can be run on the processor, characterized in that: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 6 are implemented.

9. A computer-readable storage medium storing a computer program, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 6 are implemented.

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