Farmland water level monitoring system and method

Abstract

The invention belongs to the technical field of agricultural management, and particularly discloses a farmland water level monitoring system and method. Comprising a first data acquisition module, the first data acquisition module comprises two positioning frames, the front surfaces of the two positioning frames are connected with a monitoring station through telescopic cylinders, the tops of the two positioning frames are connected with the monitoring station through a length measuring mechanism, and the bottoms of the two positioning frames are provided with depth measuring mechanisms; two supporting frames are arranged on the outer sides of the two positioning frames and located at the positions corresponding to the depth measuring mechanism, and a monitoring assembly used for measuring the water level height and the water temperature is arranged in the monitoring table. The second data module is used for acquiring rainfall information; the third data module is used for acquiring crop water demand and crop growth stage information; and a control module. Collected monitoring data are accurate and reliable, the farmland water level can be predicted according to data information, and actual paddy field management is guided according to a prediction result.

Description

Technical Field

[0001] The present invention belongs to the technical field of agricultural management, and more specifically, relates to a farmland water level monitoring system and method. Background Art

[0002] Farmland is also called arable land. In geography, all land that can be used to grow crops is called farmland. According to the different landforms of farmland, farmland can be divided into terraced fields, dam fields, paddy fields, etc. Farmland that needs artificial irrigation or water replenishment usually needs irrigation. Farmland water conservancy refers to water conservancy engineering measures aimed at increasing agricultural production, that is, through the construction and use of various water conservancy engineering measures, to regulate and improve the moisture conditions of farmland and regional water conditions, improve the ability to resist natural disasters, promote the virtuous cycle of the ecological environment, and make it conducive to the production of crops. Among the many farmland water conservancy measures, monitoring of water levels to prevent excessive irrigation water from affecting the normal growth of crops and ensuring the health and high yield of crops through scientific monitoring methods is an extremely important link.

[0003] In the existing technology, the monitoring and management of paddy field water levels still have the following deficiencies: (1) Traditional water level monitoring equipment may lack an effective fixing mechanism and cannot be firmly positioned in the farmland. It is easy to move due to soil erosion or water erosion, thereby reducing the reliability of the monitoring results. (2) Existing technology may only provide a single water level monitoring function without integrating other related measurement functions such as length and depth measurement, which limits the comprehensive application ability of the equipment in farmland hydrological monitoring and management. (3) The in-depth analysis and application of data are neglected, resulting in the inability to effectively convert monitoring data into useful information to support decision-making. Summary of the invention

[0004] In view of the above defects or improvement needs of the prior art, the present invention provides a farmland water level monitoring system and method, wherein a farmland water level monitoring system and method are designed accordingly in combination with the characteristics of farmland water level management and data management features. Through innovative designs, such as the use of a positioning frame combined with a depth measurement mechanism and a reinforcing column, the stability of the equipment is significantly improved. This enhanced stability effectively avoids the tilt caused by external forces and ensures the accuracy of the monitoring data. In addition, the use of a second positioning pin at the bottom of the monitoring station further stabilizes the monitoring component and ensures accurate monitoring of water level changes in a dynamic water environment. At the same time, the data collected by monitoring is deeply analyzed, and the principal components of the key monitoring indicators extracted by principal component analysis, combined with a multi-objective optimization linear Lasso regression model, can more accurately predict crop yields and irrigation efficiency. This comprehensive analysis method provides agricultural managers with more accurate data support, helping them make more reasonable irrigation and crop planting decisions, thereby improving crop yields and water resource utilization efficiency.

[0005] To achieve the above object, according to one aspect of the present invention, a farmland water level monitoring system is proposed, comprising:

[0006] The first data acquisition module includes two sets of positioning frames, the front faces of the two sets of positioning frames are connected to the monitoring platform through telescopic cylinders, the tops of the two sets of positioning frames are connected to the monitoring platform through length measuring mechanisms, the bottoms of the two sets of positioning frames are provided with depth measuring mechanisms, two sets of support frames are provided on the outsides of the two sets of positioning frames and at positions corresponding to the depth measuring mechanisms, and the interior of the monitoring platform is provided with a monitoring component for measuring water level height and water temperature;

[0007] A second data module, the second data module is used to obtain rainfall information;

[0008] The third data module is used to obtain crop water requirement and crop growth stage information;

[0009] The control module is in communication with the first data acquisition module, the second data module and the third data module, and is used to collect data information, predict the farmland water level according to the data information, and guide the actual paddy field management according to the prediction results.

[0010] As a further preferred embodiment, the outer side of the positioning frame and the front and rear sides of the depth measuring mechanism are connected with reinforcement columns through hinge seats, the bottom of each group of reinforcement columns is fixedly connected with reinforcement nails, and the top of each group of hinge seats is fixedly connected with a limiting block.

[0011] As a further preferred embodiment, the depth measuring mechanism includes four groups of lifting cylinders, a lifting plate, a height measuring plate, a height scale, a height pointer and a first positioning pin. The four groups of lifting cylinders are respectively fixedly connected to the front and rear sides of the bottom of the two groups of positioning frames. A lifting plate is fixedly connected below the positioning frame and between the two groups of lifting cylinders. The lifting plate is connected to the height measuring plate through a connecting frame. The outer side of the height measuring plate is engraved with a height scale. A height pointer is fixedly connected to the outer side of the positioning frame and located on the outer side of the height measuring plate. The first positioning pins are fixedly connected to the bottom of the lifting plate and at positions corresponding to the two groups of lifting cylinders.

[0012] As a further preferred embodiment, the monitoring platform is connected to the monitoring assembly via a number of connecting rods, the bottom of the monitoring platform and on the left and right sides of the monitoring assembly are threadedly connected with positioning columns, the bottoms of the two groups of positioning columns are fixedly connected with second positioning nails, the outer sides of each group of positioning columns are threadedly connected with connecting sleeves, the outer sides of the connecting sleeves are fixedly connected with three groups of fixing frames, and the bottom of the outer side of the monitoring platform is provided with a number of water-permeable holes, which penetrate the monitoring platform and extend to the interior of the monitoring platform.

[0013] As a further preferred embodiment, the monitoring assembly includes a monitoring frame, a connecting column, a monitoring float, a circular frame, a stabilizing column and a water inlet hole. The monitoring frame is fixedly connected to the interior of the monitoring platform through a connecting rod. The interior of the monitoring frame is slidably connected with a connecting column. The bottom of the connecting column and the interior of the monitoring frame is fixedly connected with a monitoring float. The external structure size of the monitoring float is set corresponding to the internal structure size of the monitoring frame. The monitoring float and the monitoring frame are connected in a sliding manner. The top of the connecting column is fixedly connected with a circular frame. The bottom of the circular frame is fixedly connected with stabilizing columns all around. The outside of the connecting column is marked with a water level scale. Four groups of stabilizing columns are cross-shaped with several connecting rods. The several connecting rods are respectively circular and evenly spaced on the outside of the monitoring frame. Several water inlet holes are opened on the outside of the bottom of the monitoring frame. The horizontal height of the monitoring float is higher than the horizontal height of the top of the water inlet hole. A water temperature measurement sensor for measuring the water temperature is installed on the outside of the monitoring frame.

[0014] As further preferred, the second data module includes an optical rainfall sensor;

[0015] The control module predicts the farmland water level according to the data information, and guides the actual paddy field management according to the prediction results, including: standardizing the data so that each indicator has a mean of 0 and a standard deviation of 1; performing principal component analysis on the standardized data to reduce the dimension of the data and extract the principal components, using the extracted principal components as independent variables, crop yield and irrigation efficiency as dependent variables, and constructing a multi-objective optimized Lasso regression model; training the Lasso regression model, estimating the regularization parameter λ in the Lasso regression, and verifying the performance of the Lasso regression model; predicting the farmland water level based on the Lasso regression model, and guiding the actual paddy field management according to the prediction results.

[0016] According to another aspect of the present invention, there is also provided a method for monitoring farmland water level, comprising the following steps:

[0017] Step 1: data collection, collecting paddy field water level monitoring indicator data;

[0018] Step 2: standardize the data so that each indicator has a mean of 0 and a standard deviation of 1;

[0019] Step 3: Perform principal component analysis on the standardized data to reduce the dimension of the data and extract the principal components. The extracted principal components are used as independent variables, and crop yield and irrigation efficiency are used as dependent variables to construct a multi-objective optimization Lasso regression model.

[0020] Step 4, training the Lasso regression model, estimating the regularization parameter λ in the Lasso regression, and verifying the performance of the Lasso regression model;

[0021] Step five, predicting the farmland water level based on the Lasso regression model, and guiding the actual paddy field management according to the prediction results.

[0022] As further preferred, in step one, the paddy field water level monitoring indicators include: water level height, soil moisture, rainfall, irrigation amount, water temperature, crop water requirement and crop growth stage.

[0023] As further preferred, in step 2, the principal component analysis includes the following steps:

[0024] (21) Calculate the covariance matrix of the standardized data to determine the correlation between variables:

[0025]

[0026] Where Σ is the covariance matrix, X is the standardized data matrix, and n is the number of samples;

[0027] (22) Solve the eigenvalue λ and the corresponding eigenvector v of the covariance matrix:

[0028] ∑v=λv

[0029] (23) According to the size of the eigenvalue, the eigenvector corresponding to the eigenvalue with the largest cumulative contribution rate is selected as the principal component;

[0030] (24) Using the selected eigenvectors as weights, the original data is transformed into the principal component space:

[0031] PC=X·V

[0032] Where PC is the principal component matrix, V is the selected eigenvector matrix;

[0033] (25) Explain that each principal component represents a linear combination of the original variables.

[0034] As a further preferred embodiment, in step 4, the Lasso regression model includes:

[0035]

[0036] Among them, Y1 and Y2 are the observed values ​​of crop yield and irrigation efficiency, respectively, X is the design matrix composed of principal components, β1 and β2 are regression coefficient vectors, and λ1 and λ2 are regularization parameters;

[0037] Preferably, a multi-objective optimization algorithm is used to search for the Pareto optimal solution.

[0038] In general, the above technical solution conceived by the present invention has the following technical advantages compared with the prior art:

[0039] 1. The farmland water level monitoring device of the present invention significantly improves the stability of the device through innovative designs, such as the use of a positioning frame combined with a depth measurement mechanism and a reinforcement column. This enhanced stability effectively avoids tilting caused by external forces and ensures the accuracy of monitoring data. In addition, the use of a second positioning pin at the bottom of the monitoring station further stabilizes the monitoring assembly and ensures accurate monitoring of water level changes in a dynamic water environment.

[0040] 2. The present invention integrates the length measurement mechanism and the depth measurement mechanism, which can not only monitor the farmland water level in real time, but also accurately measure the length and depth of the farmland. This integrated design simplifies the monitoring process, reduces the need for multiple independent devices, improves monitoring efficiency, and the data obtained through the integrated device is more consistent and reliable, which helps to conduct more accurate farmland hydrological analysis and water resources management.

[0041] 3. The present invention can help farm managers obtain key hydrological information in real time, such as water level changes and farmland volume, which is essential for rationally allocating irrigation water and optimizing irrigation plans. The design of the equipment not only improves the scientific nature of monitoring, but also strengthens agricultural water resource management through its practicality, which helps to improve irrigation efficiency, save water resources, and promote sustainable agricultural development.

[0042] 4. The present invention can more accurately predict crop yield and irrigation efficiency by extracting the principal components of key monitoring indicators through principal component analysis and combining them with a multi-objective optimization linear Lasso regression model. This comprehensive analysis method provides agricultural managers with more accurate data support, helping them make more reasonable irrigation and crop planting decisions, thereby improving crop yield and water resource utilization efficiency.

[0043] 5. The present invention utilizes the PCA dimension reduction and the regularization characteristics of Lasso regression. The model can identify the key factors that have the greatest impact on crop yield and irrigation efficiency, reduce unnecessary resource input, and optimize the allocation of agricultural resources. This method not only improves irrigation efficiency, but also helps to reduce agricultural production costs, achieving a dual improvement in economic and environmental benefits. BRIEF DESCRIPTION OF THE DRAWINGS

[0044] Figure 1 It is a structural schematic diagram of a farmland water level monitoring system of the present invention;

[0045] Figure 2 This is a structural diagram of the first data acquisition module of the present invention.

[0046] Figure 3 It is a partial three-dimensional structural schematic diagram of the first data acquisition module of the present invention;

[0047] Figure 4It is a schematic diagram of the three-dimensional structure of the monitoring platform involved in the first data acquisition module of the present invention;

[0048] Figure 5 It is a schematic diagram of the three-dimensional structure of the positioning frame involved in the first data acquisition module of the present invention;

[0049] Figure 6 It is a schematic diagram of the three-dimensional structure of the monitoring component involved in the first data acquisition module of the present invention;

[0050] Figure 7 It is a schematic diagram of the three-dimensional structure of the monitoring frame involved in the first data acquisition module of the present invention.

[0051] In all the drawings, the same reference numerals represent the same technical features, specifically: 1. positioning frame; 101. hinge seat; 102. reinforcement column; 103. reinforcement nail; 2. telescopic cylinder; 3. monitoring platform; 301. positioning column; 302. second positioning nail; 303. connecting sleeve; 304. fixing frame; 305. water permeable hole; 4. length measuring mechanism; 401. protective sleeve; 402. winding roller; 403. tape measure; 404. limit frame ; 405, rotating roller; 406, protective cover; 407, length scale; 5, depth measuring mechanism; 501, lifting cylinder; 502, lifting plate; 503, height measuring plate; 504, height scale; 505, height pointer; 506, first positioning pin; 6, support frame; 7, monitoring component; 701, monitoring frame; 702, connecting column; 703, monitoring float; 704, circular frame; 705, stabilizing column; 706, water inlet hole. DETAILED DESCRIPTION

[0052] In order to make the purpose, technical solutions and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the present invention. In addition, the technical features involved in the various embodiments of the present invention described below can be combined with each other as long as they do not conflict with each other.

[0053] like Figures 1 to 7As shown, a farmland water level monitoring system provided by an embodiment of the present invention includes: a first data acquisition module, the first data acquisition module includes two groups of positioning frames 1, the front of the two groups of positioning frames 1 is connected to a monitoring platform 3 through a telescopic cylinder 2, the top of the two groups of positioning frames 1 is connected to the monitoring platform 3 through a length measuring mechanism 4, the bottom of the two groups of positioning frames 1 is provided with a depth measuring mechanism 5, and two groups of support frames 6 are provided on the outside of the two groups of positioning frames 1 and at positions corresponding to the depth measuring mechanism 5, and the interior of the monitoring platform 3 is provided with a monitoring component 7 for measuring water level height and water temperature; a second data module, the second data module is used to obtain rainfall information; a third data module is used to obtain crop water demand and crop growth stage information; a control module, which is communicatively connected with the first data acquisition module, the second data module and the third data module, and is used to collect data information, predict the farmland water level according to the data information, and guide actual paddy field management according to the prediction results.

[0054] In a specific embodiment of the present invention, first, two groups of positioning frames 1 are fixed on one side of the farmland through the depth measuring mechanism 5. The depth measuring mechanism 5 firmly fixes the positioning frame 1 in the farmland, and the depth of the farmland can also be measured. The reinforcing column 102 is screwed out of the hinge seat 101, and the reinforcing column 102 is inserted into the farmland through the reinforcing nail 103. The stability of the positioning frame 1 is improved by the reinforcing column 102 and the reinforcing nail 103 to avoid the positioning frame 1 from tipping over during use. The monitoring platform 3 and the monitoring component 7 are inserted into the interior of the farmland. At this time, the monitoring platform 3 and the monitoring component 7 are connected by a connecting rod. The water in the farmland flows into the monitoring component 7 through the monitoring platform 3. The water level is monitored in real time by the monitoring component 7. The monitoring platform 3 can also be pulled to the other side of the farmland, and the length of the farmland can be measured by the length measuring mechanism 4. The monitoring platform 3 further improves the stability of the monitoring equipment.

[0055] Also, see Figure 2 , Figure 3 as well as Figure 5The tops of the two sets of positioning frames 1 are connected to the monitoring platform 3 through a length measuring mechanism 4; the length measuring mechanism 4 is used to accurately measure the length of the farmland, and the specific structure of the length measuring mechanism 4 is as follows: the length measuring mechanism 4 includes a protective sleeve 401, a winding roller 402, a tape measure 403, a limit frame 404, a rotating roller 405, a protective sleeve 406 and a length scale 407, the protective sleeve 401 is fixedly connected to the top of the positioning frame 1 and is located on a side away from the monitoring platform 3, the interior of the protective sleeve 401 is rotatably connected to the winding roller 402, and the winding roller 402 is connected to the tape measure 403. It is connected to the monitoring platform 3, and a limiting frame 404 is fixedly connected to the top of the positioning frame 1 and on the side away from the protective sleeve 401. A rotating roller 405 is rotatably connected to the inner side of the limiting frame 404, and the measuring tape 403 passes through between the limiting frame 404 and the rotating roller 405. A storage opening is provided on the side of the protective sleeve 401 close to the monitoring platform 3, and a protective sleeve 406 is fixedly connected to the side of the protective sleeve 401 close to the monitoring platform 3 and on the outside of the storage opening. The rotating roller 405 is rotatably connected to the limiting frame 404 through a rotating shaft, and a length scale 407 is engraved on the outer side of the measuring tape 403.

[0056] Specifically, the length of the farmland is measured by the length measuring mechanism 4, the length measuring mechanism 4 at the bottom of the positioning frame 1 is inserted into one side of the farmland, and the reinforcing column 102 and the reinforcing nail 103 are inserted into the adjacent farmland, so as to effectively improve the stability of the positioning frame 1 during use. The positioning frame 1 is connected to the monitoring platform 3 and the limit frame 404 through the telescopic cylinder 2, and the telescopic cylinder 2 is started to drive the monitoring platform 3 and the limit frame 404 to move, and the monitoring platform 3 and the limit frame 404 drive the measuring tape 403 to slide out of the storage port. At this time, the protective sleeve 406 protects the measuring tape 403, and the outer side of the protective sleeve 406 is polished into an arc shape. The bottom end of the protective sleeve 406 is on the same horizontal plane as the top end of the rotating roller 405, and the winding roller 402 is driven by the measuring tape 403 to move in the protective sleeve 40 1, at this time, the measuring tape 403 moves on the rotating roller 405, and the monitoring platform 3 and the limiting frame 404 are inserted into the other side of the farmland. At this time, the length scale 407 exposed by the measuring tape 403 is the length of the farmland. After measuring the length of the farmland, a driving motor is arranged on the back of the protective sleeve 401, and the driving shaft of the driving motor passes through the protective sleeve 401 and is connected to the winding roller 402. The connection mode of the winding roller 402 and the positioning frame 1 is a rotational connection, and the connection mode of the winding roller 402 and the protective sleeve 401 is a rotational connection. The driving motor is started, and the driving motor drives the winding roller 402 to rotate in the protective sleeve 401, and rewinds the measuring tape 403 through the winding roller 402, so that the measuring tape 403 is rewound to the outside of the winding roller 402.

[0057] Then, see Figure 2 , Figure 3 as well as Figure 5A depth measuring mechanism 5 is provided at the bottom of the two groups of positioning frames 1; the depth measuring mechanism 5 is used to accurately measure the height of the farmland, and the specific structure of the depth measuring mechanism 5 is as follows: the depth measuring mechanism 5 includes four groups of lifting cylinders 501, a lifting plate 502, a height measuring plate 503, a height scale 504, a height pointer 505 and a first positioning nail 506. The four groups of lifting cylinders 501 are respectively fixedly connected to the front and rear sides of the bottom of the two groups of positioning frames 1, and a lifting plate 502 is fixedly connected below the positioning frame 1 and between the two groups of lifting cylinders 501. The lifting plate 502 is connected to the height measuring plate 503 through a connecting frame, and the outer side of the height measuring plate 503 is engraved with a height scale 504. The outer side of the positioning frame 1 and the outer side of the height measuring plate 503 are fixedly connected with a height pointer 505. The bottom of the lifting plate 502 and the corresponding positions of the two groups of lifting cylinders 501 are fixedly connected with the first positioning nail 506.

[0058] Specifically, the depth of the farmland is measured by the depth measuring mechanism 5, and two sets of positioning frames 1 are placed at the edge of the farmland. The lifting plate 502 and the first positioning pin 506 are driven to move by the lifting cylinder 501. The lifting plate 502 drives the height scale 504 to move when moving, and the first positioning pin 506 is inserted into the farmland. The positioning frame 1 is positioned by the first positioning pin 506. At this time, the lifting plate 502 is flush with the farmland, and the depth of the farmland can be accurately calculated by the position indicated by the height pointer 505. At the same time, the first positioning pin 506 is inserted into the farmland to improve the stability of the positioning frame 1 and avoid tipping over during use. In addition, a plurality of soil moisture meters for measuring soil moisture are also arranged on the first positioning pin 506.

[0059] In a preferred embodiment of the present invention, the monitoring component 7 is used to monitor the water level of the farmland in real time. The specific structure of the monitoring component 7 is as follows: the monitoring platform 3 is connected to the monitoring component 7 through a plurality of connecting rods. The bottom of the monitoring platform 3 and the left and right sides of the monitoring component 7 are threadedly connected with positioning columns 301. The bottoms of the two groups of positioning columns 301 are fixedly connected with second positioning nails 302. The outer side of each group of positioning columns 301 is threadedly connected with a connecting sleeve 303. The outer side of the connecting sleeve 303 is fixedly connected with three groups of fixing frames 304. A plurality of water holes 305 are opened at the bottom of the outer side of the monitoring platform 3. The water holes 305 penetrate the monitoring platform 3 and extend to the interior of the monitoring platform 3.

[0060] The monitoring assembly 7 includes a monitoring frame 701, a connecting column 702, a monitoring floating plate 703, a circular frame 704, a stabilizing column 705 and a water inlet 706. The monitoring frame 701 is fixedly connected to the inside of the monitoring platform 3 through a connecting rod. The inside of the monitoring frame 701 is slidably connected with the connecting column 702. The bottom of the connecting column 702 and the inside of the monitoring frame 701 are fixedly connected with the monitoring floating plate 703. The external structure size of the monitoring floating plate 703 is set corresponding to the internal structure size of the monitoring frame 701. The connection method of the monitoring floating plate 703 and the monitoring frame 701 is a sliding connection. The connecting column 702 is fixedly connected to the monitoring frame 701. A circular frame 704 is fixedly connected to the top of 02, and stabilizing columns 705 are fixedly connected to the four sides of the bottom of the circular frame 704. A water level scale is engraved on the outer side of the connecting column 702. Four groups of stabilizing columns 705 are cross-shaped with a number of connecting rods, and the several connecting rods are respectively circular and evenly spaced on the outer side of the monitoring frame 701. A number of water inlet holes 706 are opened on the outer side of the bottom of the monitoring frame 701. The horizontal height of the monitoring float 703 is higher than the horizontal height of the top of the water inlet hole 706. An alarm and a water temperature measurement sensor for measuring the water temperature are installed on the outer side of the monitoring frame 701.

[0061] Specifically, the length of the positioning column 301 is adjusted through a threaded connection, and the positioning column 301 is inserted into the farmland through the second positioning nail 302. The positioning column 301 and the second positioning nail 302 are used to position the monitoring platform 3. Subsequently, the height of the three sets of fixing frames 304 are adjusted through the connecting sleeve 303 to unfold the three sets of fixing frames 304. The positioning column 301 is propped up by the three sets of fixing frames 304 to improve the supporting effect of the monitoring platform 3. The monitoring component 7 is installed inside the monitoring platform 3 through the connecting rod. The water level of the farmland is monitored through the monitoring component 7, and the water in the farmland enters the inside of the monitoring platform 3 through the water permeable hole 305 on the outside of the monitoring platform 3. , after entering the monitoring frame 701 through the water inlet hole 706, the monitoring float 703 is driven by the buoyancy of the water to move inside the monitoring frame 701, and then the connecting column 702 is driven to rise through the monitoring frame 701, and the circular frame 704 is driven to rise through the connecting column 702. When the circular frame 704 rises, it drives the stabilizing column 705 to rise. The stabilizing column 705 improves the stability of the monitoring float 703 when it moves, thereby improving the monitoring accuracy. The outer side of the connecting column 702 is engraved with a water level scale. The water level height can be calculated by the water level scale exposed when the connecting column 702 rises. The entire operation process is easy and fast, and is convenient for users to use.

[0062] In this embodiment, the implementation scenario is specifically as follows: in actual use, first, two groups of positioning frames 1 are fixed on one side of the farmland through the depth measuring mechanism 5. The depth measuring mechanism 5 firmly fixes the positioning frame 1 in the farmland, and at the same time, the depth of the farmland can be measured. The reinforcing column 102 is unscrewed from the hinge seat 101, and the reinforcing column 102 is inserted into the farmland through the reinforcing nail 103. The stability of the positioning frame 1 is improved by the reinforcing column 102 and the reinforcing nail 103 to avoid the positioning frame 1 from tipping over during use. The monitoring platform 3 and the monitoring component 7 are inserted into the interior of the farmland. At this time, the monitoring platform 3 and the monitoring component 7 are connected by a connecting rod. The water in the farmland flows into the monitoring component 7 through the monitoring platform 3. The water level is monitored in real time through the monitoring component 7. The monitoring platform 3 can also be pulled to the other side of the farmland, and the length of the farmland can be measured by the length measuring mechanism 4. The monitoring platform 3 further improves the stability of the monitoring equipment.

[0063] In a preferred embodiment of the present invention, the second data module includes an optical rainfall sensor. Of course, in order to ensure the accuracy of the data, in the present invention, the second data module is also used to obtain rainfall information from the automatic weather station, and then the optical rainfall sensor and the rainfall information from the automatic weather station are fused and calibrated.

[0064] The control module predicts the farmland water level according to the data information, and guides the actual paddy field management according to the prediction results, including: standardizing the data so that each indicator has a mean of 0 and a standard deviation of 1; performing principal component analysis on the standardized data to reduce the dimension of the data and extract the principal components, using the extracted principal components as independent variables, crop yield and irrigation efficiency as dependent variables, and constructing a multi-objective optimized Lasso regression model; training the Lasso regression model, estimating the regularization parameter λ in the Lasso regression, and verifying the performance of the Lasso regression model; predicting the farmland water level based on the Lasso regression model, and guiding the actual paddy field management according to the prediction results.

[0065] According to another aspect of the present invention, a method for monitoring farmland water level is provided, characterized in that it comprises the following steps:

[0066] Step 1: Data collection: collecting paddy field water level monitoring index data, wherein the paddy field water level monitoring index includes: water level, soil moisture, rainfall, irrigation volume, water temperature, crop water requirement and crop growth stage.

[0067] Step 2: Standardize the data so that each indicator has a mean of 0 and a standard deviation of 1.

[0068] In this step, since PCA is sensitive to the scale of the original data, all features need to be scaled to the same scale. Common methods include z-score standardization or range normalization.

[0069] (21) Standardization

[0070] The z-score standardization method is used to standardize the mean, standard deviation, mean square error, maximum value, minimum value, peak value, skewness, kurtosis, crest factor, waveform factor, impulse factor, margin factor, center of gravity frequency, mean square frequency, root mean square frequency, frequency variance, and frequency standard.

[0071] For all observations in the input parameters, calculate their arithmetic mean μ and standard deviation σ, then the z-score standardized value x of each observation i It can be calculated by the following formula:

[0072]

[0073] Perform the above steps for each feature in the dataset separately to convert the entire dataset into a standard form.

[0074] The dataset is then divided into training set, test set, and validation set.

[0075] (2) Calculate the correlation matrix

[0076] Calculate the covariance. The specific formula is as follows:

[0077]

[0078] Where Xj is any input parameter j, Xk is another different input parameter k, μj is the average value of input parameter j, μk is the average value of another input parameter k; Xij-μj is the deviation of parameter j, and Xik-μk is the deviation of parameter k.

[0079] Calculate the correlation coefficient R jk , the specific formula is as follows:

[0080]

[0081] Where σj and σk are the standard deviations of input parameters j and k respectively.

[0082] Step 3: Perform principal component analysis on the standardized data to reduce the dimension of the data and extract the principal components. The extracted principal components are used as independent variables, and crop yield and irrigation efficiency are used as dependent variables to construct a multi-objective optimization Lasso regression model.

[0083] In step three, the principal component analysis includes the following steps:

[0084] (31) Calculate the covariance matrix of the standardized data to determine the correlation between variables:

[0085]

[0086] Where Σ is the covariance matrix, X is the standardized data matrix, and n is the number of samples;

[0087] (32) Solve for the eigenvalue λ and the corresponding eigenvector v of the covariance matrix:

[0088] ∑v=λv

[0089] (33) According to the size of the eigenvalue, the eigenvector corresponding to the eigenvalue with the largest cumulative contribution rate is selected as the principal component; generally, the first few principal components with a contribution rate of more than 80% are selected according to the cumulative contribution rate of the eigenvalue, and the original data is transformed using the selected eigenvector to obtain a low-dimensional principal component representation.

[0090] (34) Using the selected eigenvectors as weights, the original data is transformed into the principal component space:

[0091] PC=X·V

[0092] Where PC is the principal component matrix, V is the selected eigenvector matrix;

[0093] (35) Explain that each principal component represents a linear combination of the original variables.

[0094] The Lasso regression model includes:

[0095]

[0096] Among them, Y1 and Y2 are the observed values ​​of crop yield and irrigation efficiency, respectively, X is the design matrix composed of principal components, β1 and β2 are regression coefficient vectors, and λ1 and λ2 are regularization parameters.

[0097] In the above steps, objective function (f1) is the predicted value of crop yield, and objective function (f2) is the predicted value of irrigation efficiency.

[0098] Preferably, a multi-objective optimization algorithm is used to search for the Pareto optimal solution.

[0099] Step 4: Train the Lasso regression model, estimate the regularization parameter λ in the Lasso regression, and verify the performance of the Lasso regression model.

[0100] In this step, the regression model is trained on the training set and the model prediction ability is evaluated on the test set to analyze its R 2(coefficient of determination), mean square error (MSE), and root mean square error (RMSE) to select appropriate parameters.

[0101] Step five, predicting the farmland water level based on the Lasso regression model, and guiding the actual paddy field management according to the prediction results.

[0102] The above calculation steps are as follows:

[0103] (1) Perform PCA to obtain the principal components PC1, PC2, ..., PCk.

[0104] (2) Construct a design matrix X, whose columns consist of principal components.

[0105] (3) For each target variable Y1 and Y2, perform the following steps respectively:

[0106] a. Use cross-validation to determine the regularization parameter λ.

[0107] b. Apply Lasso regression:

[0108] (4) The coordinate descent method or other optimization algorithms are usually used to solve the Lasso regression problem.

[0109] It will be easily understood by those skilled in the art that the above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions and improvements made within the spirit and principles of the present invention should be included in the protection scope of the present invention.

Claims

1. A farmland water level monitoring system, characterized in that: include: A first data acquisition module, the first data acquisition module comprising two groups of positioning frames (1), the front faces of the two groups of positioning frames (1) being connected to a monitoring platform (3) via a telescopic cylinder (2), the tops of the two groups of positioning frames (1) being connected to the monitoring platform (3) via a length measuring mechanism (4), the bottoms of the two groups of positioning frames (1) being provided with a depth measuring mechanism (5), two groups of supporting frames (6) being provided on the outsides of the two groups of positioning frames (1) and at positions corresponding to the depth measuring mechanism (5), and a monitoring component (7) for measuring water level height and water temperature being provided inside the monitoring platform (3); A second data acquisition module, the second data module is used to obtain rainfall information; The third data collection module is used to obtain crop water demand and crop growth stage information; The control module is in communication with the first data acquisition module, the second data module and the third data module, and is used to collect data information, predict the farmland water level according to the data information, and guide the actual paddy field management according to the prediction results.

2. A farmland water level monitoring system according to claim 1, characterized in that: The outer side of the positioning frame (1) and the front and rear sides of the depth measuring mechanism (5) are connected to reinforcement columns (102) through hinge seats (101), the bottom of each group of reinforcement columns (102) is fixedly connected to a reinforcement nail (103), and the top of each group of hinge seats (101) is fixedly connected to a limiting block.

3. A farmland water level monitoring system according to claim 1, characterized in that: The depth measuring mechanism (5) comprises four groups of lifting cylinders (501), a lifting plate (502), a height measuring plate (503), a height scale (504), a height pointer (505) and a first positioning pin (506). The four groups of lifting cylinders (501) are respectively fixedly connected to the front and rear sides of the bottom of the two groups of positioning frames (1). The lifting plate (502) is fixedly connected below the positioning frame (1) and between the two groups of lifting cylinders (501). The lifting plate (502) is connected to the height measuring plate (503) via a connecting frame. The outer side of the height measuring plate (503) is marked with a height scale (504). The height pointer (505) is fixedly connected to the outer side of the positioning frame (1) and located on the outer side of the height measuring plate (503). The first positioning pin (506) is fixedly connected to the bottom of the lifting plate (502) and located at positions corresponding to the two groups of lifting cylinders (501).

4. A farmland water level monitoring system according to claim 1, characterized in that: The monitoring platform (3) is connected to the monitoring assembly (7) via a plurality of connecting rods; the bottom of the monitoring platform (3) and the left and right sides of the monitoring assembly (7) are both threadedly connected with positioning columns (301); the bottoms of the two groups of positioning columns (301) are both fixedly connected with second positioning nails (302); the outer sides of each group of positioning columns (301) are both threadedly connected with connecting sleeves (303); the outer sides of the connecting sleeves (303) are fixedly connected with three groups of fixing frames (304); the bottom of the outer side of the monitoring platform (3) is provided with a plurality of water-permeable holes (305); the water-permeable holes (305) penetrate the monitoring platform (3) and extend into the interior of the monitoring platform (3).

5. A farmland water level monitoring system according to claim 1, characterized in that: The monitoring assembly (7) comprises a monitoring frame (701), a connecting column (702), a monitoring floating plate (703), a circular frame (704), a stabilizing column (705) and a water inlet hole (706); the monitoring frame (701) is fixedly connected to the inside of the monitoring platform (1) via a connecting rod; the inside of the monitoring frame (701) is slidably connected to the connecting column (702); the bottom of the connecting column (702) and the inside of the monitoring frame (701) are fixedly connected to the monitoring floating plate (703); the external structure size of the monitoring floating plate (703) is arranged to correspond to the internal structure size of the monitoring frame (701); the monitoring floating plate (703) and the monitoring frame (701) are connected in the following manner: The connecting column (702) is connected to a circular frame (704) on the top, and the bottom of the circular frame (704) is fixedly connected to stabilizing columns (705) on all sides. The outer side of the connecting column (702) is marked with a water level scale. Four groups of stabilizing columns (705) and a plurality of connecting rods are in a cross shape. The plurality of connecting rods are in a circular shape and are evenly spaced on the outer side of the monitoring frame (701). A plurality of water inlet holes (706) are opened on the outer side of the bottom of the monitoring frame (701). The horizontal height of the monitoring floating plate (703) is higher than the horizontal height of the top of the water inlet hole (706). A water temperature measuring sensor for measuring the water temperature is installed on the outer side of the monitoring frame (701).

6. A farmland water level monitoring system according to claim 1, characterized in that: The second data module includes an optical rainfall sensor; The control module predicts the farmland water level according to the data information, and guides the actual paddy field management according to the prediction results, including: standardizing the data so that each indicator has a mean of 0 and a standard deviation of 1; performing principal component analysis on the standardized data to reduce the dimension of the data and extract the principal components, using the extracted principal components as independent variables, crop yield and irrigation efficiency as dependent variables, and constructing a multi-objective optimized Lasso regression model; training the Lasso regression model, estimating the regularization parameter λ in the Lasso regression, and verifying the performance of the Lasso regression model; predicting the farmland water level based on the Lasso regression model, and guiding the actual paddy field management according to the prediction results.

7. A method for monitoring farmland water level, characterized in that: The following steps are involved: Step 1: data collection, collecting paddy field water level monitoring indicator data; Step 2: standardize the data so that each indicator has a mean of 0 and a standard deviation of 1; Step 3: Perform principal component analysis on the standardized data to reduce the dimension of the data and extract the principal components. The extracted principal components are used as independent variables, and crop yield and irrigation efficiency are used as dependent variables to construct a multi-objective optimization Lasso regression model. Step 4, training the Lasso regression model, estimating the regularization parameter λ in the Lasso regression, and verifying the performance of the Lasso regression model; Step five, predicting the farmland water level based on the Lasso regression model, and guiding the actual paddy field management according to the prediction results.

8. A method for monitoring farmland water level according to claim 7, characterized in that: In step one, the paddy field water level monitoring indicators include: water level height, soil moisture, rainfall, irrigation amount, water temperature, crop water requirement and crop growth stage.

9. A method for monitoring farmland water level according to claim 7, characterized in that: In step 2, the principal component analysis includes the following steps: (21) Calculate the covariance matrix of the standardized data to determine the correlation between variables: Where Σ is the covariance matrix, X is the standardized data matrix, and n is the number of samples; (22) Solve the eigenvalue λ and the corresponding eigenvector v of the covariance matrix: ∑v=λv (23) According to the size of the eigenvalue, the eigenvector corresponding to the eigenvalue with the largest cumulative contribution rate is selected as the principal component; (24) Using the selected eigenvectors as weights, the original data is transformed into the principal component space: PC=X·V Where PC is the principal component matrix, V is the selected eigenvector matrix; (25) Explain that each principal component represents a linear combination of the original variables.

10. A method for monitoring farmland water level according to claim 7, characterized in that: In step 4, the Lasso regression model includes: Among them, Y1 and Y2 are the observed values ​​of crop yield and irrigation efficiency, respectively, X is the design matrix composed of principal components, β1 and β2 are regression coefficient vectors, and λ1 and λ2 are regularization parameters; Preferably, a multi-objective optimization algorithm is used to search for the Pareto optimal solution.

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