Method and device for monitoring the working state of agricultural machinery

Abstract

The application discloses a working state monitoring method and device for agricultural machine operation, and the method comprises the following steps: acquiring operation coordinate points of the agricultural machine in the operation process in real time to determine a first set comprising the acquired operation coordinate points; extracting a boundary of the first set and determining concave points in the boundary to divide each concave polygon comprising the concave points into convex polygons; classifying each operation coordinate point in the first set based on corresponding vertices of each convex polygon to obtain a plurality of second sets comprising corresponding classified operation coordinate points; constructing a corresponding triangular net based on each second set and determining an operation area of the agricultural machine based on areas of the triangular nets; and monitoring the working state of the agricultural machine operation based on the operation area.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of agricultural machinery, and particularly relates to a working state monitoring method and device for agricultural machine operation. BACKGROUND

[0002] Agricultural machinery, i.e. agricultural machine, refers to various machines used in crop planting and livestock production processes, and initial processing and treatment processes of agricultural and livestock products. Agricultural machinery is widely used in farmland construction, soil tillage, planting and fertilization, farmland irrigation and drainage, and crop harvesting.

[0003] With the development of science and technology, various automatic or unmanned intelligent agricultural machines are also widely used. By combining the size of the farmland for agricultural machine operation and the parameters of the agricultural machine, the path of the agricultural machine operation can be planned in advance and the agricultural machine can be controlled to automatically execute. However, in the process of agricultural machine operation, the pre-planning may be insufficient, which cannot well match the actual operation situation.

[0004] How to understand the working state of the agricultural machine operation in the process of the agricultural machine operation, so as to provide conditions for the optimization of the operation is a technical problem to be solved at present. SUMMARY

[0005] The purpose of the embodiments of the present application is to provide a working state monitoring method and device for agricultural machine operation, so as to solve the problems in the planning of the agricultural machine operation.

[0006] In order to solve the above technical problems, the present specification is implemented as follows:

[0007] In a first aspect, a working state monitoring method for agricultural machine operation is provided, comprising:

[0008] obtaining in real time operation coordinate points of the agricultural machine in the operation process to determine a first set comprising the obtained operation coordinate points;

[0009] extracting a boundary of the first set and determining concave points in the boundary to divide each concave polygon comprising the concave points into convex polygons;

[0010] classifying each operation coordinate point in the first set based on the corresponding vertex of each convex polygon to obtain a plurality of second sets comprising the corresponding classified operation coordinate points;

[0011] constructing a corresponding triangular mesh based on each second set, and determining an operation area of the agricultural machine based on the area of each triangular mesh;

[0012] monitoring the working state of the agricultural machine operation based on the operation area.

[0013] Optionally, the working coordinate points of the agricultural machine in the working process are acquired in real time to determine a first set including the acquired working coordinate points, including:

[0014] The navigation positioning coordinate points of the agricultural machine are acquired in real time by a GPS data acquisition device arranged on the agricultural machine, and the navigation positioning coordinate points include the longitude and latitude coordinate points and the direction angle of the agricultural machine at the target working point;

[0015] The longitude and latitude coordinate points of each working point are converted into two-dimensional coordinate points in a plane rectangular coordinate system;

[0016] The first set is determined based on the two-dimensional coordinate points corresponding to each working point.

[0017] Optionally, after the conversion of the longitude and latitude coordinate points of each working point into the two-dimensional coordinate points in the plane rectangular coordinate system, the method further includes:

[0018] Based on the two-dimensional coordinate points corresponding to each working point, the direction angle and the working width of the agricultural machine, a plurality of expanded two-dimensional coordinate points located in the working width region of the agricultural machine are expanded, wherein the two-dimensional coordinate points of the working point reflect the position of the agricultural machine, and the plurality of expanded two-dimensional coordinate points reflect the horizontal width occupied by the agricultural machine;

[0019] The first set is determined based on the two-dimensional coordinate points corresponding to each working point, including:

[0020] The first set is determined based on the two-dimensional coordinate points and the expanded two-dimensional coordinate points corresponding to each working point.

[0021] Optionally, the boundary of the first set is extracted, including:

[0022] Within a first working duration before the agricultural machine starts working to the first time when the agricultural machine experiences a turn, the boundary of the first set is extracted based on an Alpha Shapes boundary extraction function, the two-dimensional coordinate points of the working points corresponding to the first set and a first shrinkage factor;

[0023] After the agricultural machine experiences the turn for the first time, the boundary of the first set is extracted based on the Alpha Shapes boundary extraction function, the two-dimensional coordinate points of the working points corresponding to the first set and a second shrinkage factor, and the second shrinkage factor is greater than the first shrinkage factor;

[0024] The Alpha Shapes boundary extraction function is boundary(x, y, s), the parameters x and y correspond to the two-dimensional coordinate points of the working points, and the parameter s represents the shrinkage factor.

[0025] Optionally, the second shrinkage factor is determined according to the following steps:

[0026] determining a first number of working coordinate points included in the first set in a current working process after the agricultural machine first experiences a turn;

[0027] determining a second number of working coordinate points included in the first set in the first working time length;

[0028] determining the second contraction factor based on the first number and the second number.

[0029] Optionally, determining a concave point in the boundary comprises:

[0030] traversing each vertex of the boundary;

[0031] translating an i-th vertex currently traversed to an origin of a plane rectangular coordinate system;

[0032] rotating the boundary so that an i+1-th vertex is on a positive half axis of an x-axis of the plane rectangular coordinate system;

[0033] determining that the i+1-th vertex is a concave point in the boundary in a case where the i+1-th vertex satisfies a following formula:

[0034] y i+k <0 k=2,3,4,...,[0.01m]+1,

[0035]

[0036] wherein m represents a number of each vertex of the boundary, and θ represents a smooth angle between the i+1-th vertex and an i+k-th vertex.

[0037] Optionally, dividing each concave polygon including a concave point into a convex polygon comprises:

[0038] setting the i+1-th vertex determined as the concave point as a first division point;

[0039] determining a first vertex on a positive half axis of a y-axis of the plane rectangular coordinate system by traversing backward from the i+1-th vertex and setting the vertex as a second division point;

[0040] connecting the first division point and the second division point to form a division line;

[0041] dividing a concave polygon including the i+1-th vertex by the division line.

[0042] Optionally, classifying each working coordinate point in the first set based on each vertex corresponding to a convex polygon to obtain a plurality of second sets including corresponding classified working coordinate points comprises:

[0043] The vertices corresponding to each convex polygon and the coordinate points of each task in the first set are sequentially input into the inpolygon function to determine the coordinate points of the task located in each closed convex polygon. The vertices corresponding to a convex polygon constitute a closed convex polygon.

[0044] By summing the coordinates of all operation points located within the same closed convex polygon, a corresponding second set is obtained.

[0045] Optionally, the step of constructing corresponding triangular meshes based on each of the second sets, and determining the operating area of ​​the agricultural machinery based on the area of ​​each triangular mesh, includes:

[0046] Based on the Bowyer-Wastson function and the work coordinates in each second set, a triangulation network corresponding to each second set is constructed sequentially.

[0047] Calculate the area of ​​each triangle included in each triangulation;

[0048] The operating area of ​​the agricultural machinery is obtained by summing the areas of the triangles included in each triangulation.

[0049] In a second aspect, a working status monitoring device for agricultural machinery is provided, including a memory and a processor electrically connected to the memory, the memory storing a computer program executable by the processor, the computer program performing the steps of the method described in the first aspect when executed by the processor.

[0050] In this embodiment, the operation coordinates of agricultural machinery during operation are acquired in real time to determine a first set including the acquired operation coordinates; the boundary of the first set is extracted, and concave points in the boundary are determined to divide each concave polygon including the concave points into convex polygons; based on the vertices corresponding to each convex polygon, each operation coordinate point in the first set is classified to obtain multiple second sets including the corresponding classified operation coordinates; a corresponding triangular mesh is constructed based on each second set, and the operation area of ​​the agricultural machinery is determined based on the area of ​​each triangular mesh; the working status of the agricultural machinery is monitored based on the operation area. Thus, the operation area of ​​the agricultural machinery can be calculated based on the triangular mesh constructed from the operation trajectory coordinates of the agricultural machinery at the current moment, and based on the triangulation of the triangular mesh. Each point of the constructed triangular mesh is a convex point, which will not form an illegal triangle. The calculation of the operation area is based on each set of operation coordinates, excluding boundary data, and is not affected by boundary extraction errors, which can improve the accuracy of the constructed triangular mesh, thereby improving the accuracy of the calculated agricultural machinery operation area, realizing accurate monitoring of the working status of agricultural machinery operation, and providing reliable conditions and basis for optimizing agricultural machinery operation. Attached Figure Description

[0051] The accompanying drawings, which are included to provide a further understanding of the application and are incorporated in and constitute a part of this application, illustrate embodiments of the application and together with the description serve to explain the application. In the drawings:

[0052] Figure 1 is a flowchart of a working state monitoring method for agricultural machine operation according to an embodiment of the application.

[0053] Figure 2 is a schematic diagram of concave polygon boundary segmentation according to an embodiment of the application.

[0054] Figure 3 is a structural block diagram of a working state monitoring device for agricultural machine operation according to an embodiment of the application. DETAILED DESCRIPTION

[0055] The technical solutions in the embodiments of the application will be clearly and completely described below with reference to the drawings in the embodiments of the application. Obviously, the described embodiments are only some of the embodiments of the application, but not all of the embodiments of the application. Based on the embodiments in the application, all other embodiments obtained by those of ordinary skill in the art without creative work fall within the protection scope of the application. The figure numbers in the application are only used to distinguish each step in the solution, and are not used to limit the execution order of each step, and the specific execution order is subject to the description in the specification.

[0056] To solve the problems in the prior art, the embodiments of the application provide a working state monitoring method for agricultural machine operation, Figure 1 is a flowchart of a working state monitoring method for agricultural machine operation according to an embodiment of the application.

[0057] As shown in Figure 1 , the method comprises the following steps:

[0058] In step 102, real-time acquisition of operation coordinate points of the agricultural machine in the operation process is performed to determine a first set comprising the acquired operation coordinate points.

[0059] In this step, the operation coordinate point refers to a coordinate point constituting an operation path or an operation track of the agricultural machine in the operation process. The current corresponding operation coordinate point of the agricultural machine, that is, the current position point of the agricultural machine, can be continuously collected at a predetermined time interval. The acquisition is started from the beginning of the operation of the agricultural machine and is ended until the current operation process is completed. Each acquired operation coordinate point is added to the first set, comprising the operation coordinate points acquired from the beginning of the operation of the agricultural machine to the current time point, and the next acquired operation coordinate point is added to the first set to update the first set.

[0060] Optionally, the real-time acquisition of the work coordinate points of the agricultural machine in the work process to determine the first set including the acquired work coordinate points comprises: acquiring the navigation positioning coordinate points of the agricultural machine in real time through the GPS data acquisition device arranged on the agricultural machine, the navigation positioning coordinate points including the longitude and latitude coordinates and the direction angle of the agricultural machine at the target work point; converting the longitude and latitude coordinates of each work point into two-dimensional coordinates of a plane rectangular coordinate system; and determining the first set based on the two-dimensional coordinates corresponding to each work point.

[0061] For example, the GPS data acquisition device is arranged at the top central position of the agricultural machine, and the navigation positioning data of the work point of the agricultural machine is acquired in real time at a frequency of 10 Hz (i.e. 10 times of sampling per second), including the longitude and latitude coordinates and the direction angle relative to the ground coordinate system. Through Gauss projection coordinate direct calculation, the longitude and latitude coordinate data acquired each time can be converted into two-dimensional coordinates of a plane rectangular coordinate system and added to the first set, and then the work coordinate points corresponding to the work path of the agricultural machine in the work process are obtained to serve as the basis for subsequent calculation of the work area of the agricultural machine.

[0062] In the above embodiment, the work coordinate points of the agricultural machine are combined to correspond to a line of the work path of the agricultural machine, and the difference in the density of the work coordinate points is too large. If the work coordinate points are directly used as the basis for subsequent calculation of the work area of the agricultural machine, the area calculation will inevitably have errors.

[0063] Optionally, in an embodiment, after the conversion of the longitude and latitude coordinates of each work point into two-dimensional coordinates of a plane rectangular coordinate system, the method further comprises: based on the two-dimensional coordinates corresponding to each work point, the direction angle and the work width of the agricultural machine, expanding a plurality of expanded two-dimensional coordinates located in the work width area of the agricultural machine, wherein the two-dimensional coordinates of the work point reflect the position of the agricultural machine, and the plurality of expanded two-dimensional coordinates reflect the horizontal width occupied by the agricultural machine; and the determination of the first set based on the two-dimensional coordinates corresponding to each work point comprises: the determination of the first set based on the two-dimensional coordinates and the expanded two-dimensional coordinates corresponding to each work point.

[0064] In this embodiment, after obtaining the work points with two-dimensional coordinates, each work point is expanded in combination with the direction angle of the agricultural machine corresponding to each work point in the navigation positioning data and the work width of the agricultural machine, i.e. each coordinate point is converted into a row of coordinate points reflecting the position of the agricultural machine and the horizontal width occupied by the agricultural machine through certain conversion. The number of the plurality of expanded two-dimensional coordinates is related to the work width of the agricultural machine, and the greater the work width, the more the expanded coordinate points, and vice versa.

[0065] Specifically, for any acquired navigation positioning coordinate point, it is assumed that the two-dimensional coordinates of the converted i-th work coordinate point (x i3 , y i3 ) are (x i , y i), which is located at the middle of the working width of the agricultural machine, and the direction angle of the agricultural machine at this point is δ, and the working width of the agricultural machine is 1.

[0066] On the basis of the coordinate point, four two-dimensional coordinates (x i1 , y i1 ), (x i2 , y i2 ), (x i4 , y i4 ) and (x i5 , y i5 ) are additionally expanded along the working width area of the agricultural machine, and are respectively located at both sides of the i-th working coordinate point along the working width direction.

[0067] Then, each expanded working coordinate point is represented as follows:

[0068]

[0069]

[0070]

[0071]

[0072] x i3 = x i

[0073] y i3 = y i

[0074] Thus, on the basis of the i-th working coordinate point, the point coordinates of the converted row-reaction agricultural machine position (x i , y i ) and the horizontal width (x i1 , y i1 ), (x i2 , y i2 ), (x i4 , y i4 ) and (x i5 , y i5 ) occupied by the agricultural machine are expanded, and are used as the working coordinate points in the first set.

[0075] By traversing all the collected navigation positioning coordinate points and repeating the above two-dimensional coordinate conversion and expansion steps, a new coordinate set of the agricultural machine working points can be obtained.

[0076] The expanded work coordinate points are uniformly distributed, and the density difference between the work coordinate points is small. Combining the expanded work coordinate points as input can better reflect the work condition of the agricultural machine, and is more suitable as a basis for subsequent calculation of the work area of the agricultural machine, thereby reducing calculation errors and improving the accuracy of the work area.

[0077] In step 104, the boundaries of the first set are extracted, and concave points in the boundaries are determined to divide each concave polygon including the concave points into convex polygons.

[0078] Optionally, within a first work duration from the start of work to the first time of experiencing a turn, the boundaries of the first set are extracted based on an Alpha Shapes boundary extraction function and two-dimensional coordinates of the work points corresponding to the first set, and a first shrinkage factor; after the first time of experiencing a turn, the boundaries of the first set are extracted based on the Alpha Shapes boundary extraction function and the two-dimensional coordinates of the work points corresponding to the first set, and a second shrinkage factor, the second shrinkage factor being greater than the first shrinkage factor; wherein the Alpha Shapes boundary extraction function is boundary(x, y, s), the parameters x and y correspond to the two-dimensional coordinates of the work points, and s represents the shrinkage factor.

[0079] In the embodiments of the present application, the Alpha Shapes boundary extraction function boundary(x, y, s) built-in in Matlab can be used, the parameters x and y correspond to the two-dimensional coordinates of the work points, and the shrinkage factor s represents the shrinkage factor, which is an Alpha-related parameter in the interval of 0-1. The smaller the shrinkage factor s, the larger the Alpha value, and the more expanded the extracted boundaries; on the contrary, the larger the shrinkage factor s, the smaller the Alpha value, and the more contracted the extracted boundaries.

[0080] Here, the shrinkage factor s in the Alpha Shapes boundary extraction function is adaptively adjusted. The adaptive adjustment is based on two considerations:

[0081] 1. When the agricultural machine just starts to move, it is obviously a straight-line motion and there is no need to consider concave points. At this time, the number of work coordinate points in the first set is small. If the boundary extraction algorithm is too contracted under this condition, the extracted boundaries may contain unnecessary false concave points (i.e., not truly concave points), and unnecessary division operations will occur in the subsequent concave polygon division step, increasing unnecessary calculation amount. Therefore, it is expected that within a small period of time when the agricultural machine just starts to move, i.e., within the first work duration from the start of work to the first time of experiencing a turn, a smaller s value (first shrinkage factor) is selected before the first turn, so that the boundaries do not have unnecessary concave points to directly skip the concave polygon division step;

[0082] 2. After the agricultural machinery has been running for a period of time, it will begin to exhibit turning trajectories. Taking a farmland that is 33.3m long and 20m wide, with each work row being 20m long, as an example, and assuming the machinery's operating speed is 2m / s, the time from the start of operation to the first turn is approximately 10 seconds. Assuming the frequency of obtaining work coordinate points is 10 samples per second, and the work coordinate points are expanded to a five-fold number, the number of work coordinate points obtained in the first set during the first turn is approximately 500.

[0083] Therefore, the value of the contraction factor s can be adjusted by combining the number of work coordinate points in the first set when the agricultural machinery makes its first turn and the number of work coordinate points in the first set at subsequent times.

[0084] Optionally, the second shrinkage factor is determined according to the following steps: determining a first number of work coordinate points included in the first set during the current operation after the agricultural machinery first experiences a turn; determining a second number of work coordinate points included in the first set within the first operation duration; and determining the second shrinkage factor based on the first number and the second number.

[0085] For example, using -n / 500 as the coefficient of the exponent, where 500 is the number of work coordinate points in the first set when the agricultural machinery makes its first turn, and n is the number of work coordinate points in the first set at the current time after the first turn, an adaptive expression for the contraction factor s is given:

[0086]

[0087] Of course, this coefficient -n / 500 can be adjusted according to the different farmland specifications.

[0088] Boundary extraction experiments were conducted on various concave point operation coordinate points with a shrinkage factor s between [0.4-0.8] at intervals of 0.02 seconds. It can be seen that the initial value of s, i.e. the first shrinkage factor, is taken around 0.5 to satisfy the first point of consideration, and the constant value of s, i.e. the second shrinkage factor, is taken around 0.6 to satisfy the second point of consideration.

[0089] It should be noted that the purpose of the shrinkage factor s parameter adaptation here is to reduce the amount of calculation, and the subsequent operation area calculation result is almost not affected. That is, the real trajectory may start to appear false concave points, so it is expected that after running for a period of time, the shrinkage factor s remains around a larger value, so that the boundary can be shrunk as much as possible to ensure that all the concave points of the real boundary are obtained. In other words, in order to make the recall rate of the concave points reach 100%. However, considering that setting the value of the shrinkage factor s too large will excessively shrink to generate a closed boundary, and removing the redundant boundary requires unnecessary additional steps, therefore the value of the second shrinkage factor s cannot be too large.

[0090] In an actual scene, by obtaining a corresponding number n of operation coordinate points from the first set and inputting the boundary() function, the corresponding boundary extracted from the first set can be obtained, thereby obtaining a series of boundary vertex coordinate sets connected in sequence.

[0091] In the embodiment in which the first set includes the augmented operation coordinate points, because the density of each operation coordinate point is relatively uniform, a more accurate extraction result can be obtained when extracting the boundary.

[0092] After the boundary is extracted, the concave points in the boundary are determined, thereby determining the corresponding concave polygons and segmenting them into convex polygons.

[0093] Optionally, determining the concave points in the boundary includes: traversing each vertex of the boundary;

[0094] translating the i-th vertex currently traversed to the origin of the plane rectangular coordinate system; rotating the boundary so that the i+1-th vertex is on the positive half-axis of the x-axis of the plane rectangular coordinate system; and determining the i+1-th vertex as a concave point in the boundary in a case where the i+1-th vertex satisfies the following formula:

[0095] y i+k <0 k=2,3,4,...,[0.01m]+1,

[0096]

[0097] wherein m represents the number of vertices of the boundary, and θ represents a smooth angle between the i+1-th vertex and the i+k-th vertex.

[0098] The boundary obtained by extracting the boundary from the discrete operation coordinate point set will be irregular, and the edges of the boundary will have burrs similar to the burrs but cannot reflect the actual boundary of the point set. Therefore, in the embodiment of the present application, the situation is judged, and the judgment condition for concave polygon segmentation is modified before the concave polygon segmentation.

[0099] Specifically, in the first step, each vertex of the boundary extracted by the Alpha Shapes extraction function is traversed first, and the ith point (x i , y i ) is translated to the origin, i.e., x i = 0, y i = 0. Then, the boundary is rotated so that the (i+1)th point (x i+1 , y i+1 ) is on the positive half of the x-axis, i.e., x i+1 > 0, y i+1 = 0.

[0100] In the second step, if the total number of vertices on the boundary is m, the (i+1)th point is determined to be a concave point if the following conditions are met, and the point is set as the first split point. If the conditions are not met, the point is determined to be a convex point, and no operation is performed, and the next point is continued to be traversed. The determination conditions are as follows:

[0101] y i+k < 0 k = 2, 3, 4,..., [0.01m] + 1

[0102]

[0103] where θ represents the smooth angle between the (i+1)th vertex and the (i+k)th vertex, and is, for example, [25 degrees, 35 degrees].

[0104] After the next concave point is traversed in the above manner, the split operation can be performed.

[0105] Optionally, each concave polygon including the concave point is split into a convex polygon, including: setting the (i+1)th vertex determined to be a concave point as a first split point; determining a first vertex on the positive half of the y-axis of the Cartesian coordinate system and setting the vertex as a second split point by traversing backward from the (i+1)th vertex; connecting the first split point and the second split point to form a split line; and splitting the concave polygon including the (i+1)th vertex by the split line.

[0106] Specifically, in the third step, after the (i+1)th point is determined to be a concave point, the traversal is continued backward from the (i+1)th point until a first point with a vertical coordinate greater than 0 is found, and the point is set as a second split point. Connecting the first split point and the second split point forms a split line, and the splitting of the concave polygon is completed. Then, the loop of the first step is jumped back to until the traversal of all points on the boundary is completed.

[0107] As Figure 2As shown, the left figure is the extracted original boundary, and the first segmentation point a and the second segmentation point b are determined as concave points through the above steps, and then the right figure is obtained through segmentation. That is, the concave polygon including the concave point in the left figure is segmented into two convex polygons in the right figure.

[0108] Thus, through the smoothing correction of the concave point, some false concave points can be better skipped, and correct judgment can also be made on the true concave point.

[0109] In step 106, based on the vertices corresponding to each convex polygon, each work coordinate point in the first set is classified to obtain a plurality of second sets including the corresponding classified work coordinate points.

[0110] For the several boundaries obtained through segmentation, it is obvious that they can all constitute a closed region. The inpolygon algorithm is used to divide the work coordinate points in the first set.

[0111] Optionally, based on the vertices corresponding to each convex polygon, each work coordinate point in the first set is classified to obtain a plurality of second sets including the corresponding classified work coordinate points, including: sequentially inputting the vertices corresponding to each convex polygon and each work coordinate point in the first set into the inpolygon function to determine the work coordinate points located in each closed convex polygon, and the vertices corresponding to each convex polygon constitute a closed convex polygon; by collecting each work coordinate point located in the same closed convex polygon, a corresponding second set is obtained.

[0112] Specifically, the vertex set corresponding to each convex polygon constitutes a closed region of the boundary, and the boundary connected by the plurality of vertices included in the target convex polygon corresponds to the closed region of the convex polygon.

[0113] The vertex set of all convex polygons obtained through the segmentation of the concave polygon in step 104 and the first set of a plurality of work coordinate points obtained in step 102 are sequentially input into the inpolygon function, so as to determine in which closed region each work coordinate point falls, thereby classifying each work coordinate point into the corresponding closed region. For example, if the number of segmented convex polygons is 3, then through this step, each work coordinate point in the first set can be classified into 3 categories, that is, 3 sets. The closed region of each convex polygon corresponds to a certain number of work coordinate points, and the classified work coordinate points are located in the closed region. Thus, the work coordinate points in each closed region are collected to obtain the coordinate point set corresponding to the closed region.

[0114] In step 108, a corresponding triangular mesh is constructed based on each second set, and the work area of the agricultural machine is determined based on the area of each triangular mesh.

[0115] Optionally, the constructing the corresponding triangular mesh based on each second set respectively, and determining the working area of the agricultural machine based on the area of each triangular mesh comprises: constructing the triangular mesh corresponding to each second set in sequence based on the Bowyer-Wastson function and the working coordinate points in each second set; calculating the area of the triangle included in each triangular mesh respectively; and obtaining the working area of the agricultural machine by summing the area of the triangle included in each triangular mesh.

[0116] In step 108, the triangular mesh is constructed in sequence for each second set obtained in step 106, and one second set constructs one triangular mesh. In the embodiment of the present application, the Bowyer-Wastson algorithm is used to complete the triangular mesh construction of the working coordinate points in each second set. Each triangular mesh includes multiple triangles, and the area of each triangular mesh can be obtained by calculating the area of the triangle. The final working area of the agricultural machine can be obtained by accumulating the area of the multiple constructed triangular meshes.

[0117] The area of the triangular mesh can be solved by using the determinant form. It is assumed that the three points of the triangle are A(a, b), B(c, d), and C(e, f), and the formula is as follows:

[0118]

[0119] Therefore, based on the working coordinate points of the agricultural machine obtained at the current moment, the working area of the current agricultural machine can be determined.

[0120] In this embodiment, each point used for constructing the triangular mesh is a convex point, so that no illegal triangle is formed, the accuracy of the constructed triangular mesh is improved, and the extracted boundary can accurately express the area occupied by the working points. In addition, by using the Bowyer-Wastson algorithm, the above-mentioned situation can be further avoided, and the network construction speed can be faster.

[0121] In step 110, the working state of the agricultural working is monitored based on the working area.

[0122] Through the above steps, the working area of the agricultural machine can be obtained in real time, so that the current working state of the agricultural machine can be understood, thereby providing data support and optimization for fine tillage.

[0123] For example, the working area can be used to determine whether the path planning of the agricultural working is reasonable. In the case of reasonable planning, the planned path is adjusted or optimized, or the working area can also be cross-compared with the oil consumption of the agricultural machine, which is used to formulate a working scheme with a larger effective working area per unit of oil consumption, so as to save the oil consumption loss of the agricultural machine.

[0124] In the embodiment of the present application, the working coordinate points of the agricultural machine in the working process are acquired in real time to determine a first set including the acquired working coordinate points; the boundary of the first set is extracted, and the concave points in the boundary are determined to divide each concave polygon including the concave points into a convex polygon; each working coordinate point in the first set is classified based on the corresponding vertex of each convex polygon to obtain a plurality of second sets including the corresponding classified working coordinate points; a corresponding triangular mesh is constructed based on each second set, and the working area of the agricultural machine is determined based on the area of each triangular mesh; and the working state of the agricultural machine is monitored based on the working area. Thus, the triangular mesh can be constructed based on the working trajectory coordinate points of the agricultural machine at the current time, and the working area of the agricultural machine can be calculated based on the triangulation of the triangular mesh. Each point of the constructed triangular mesh is a convex point and cannot form an illegal triangle. The calculation of the working area is based on each set of working coordinate points and does not include the data of the boundary, so it is not affected by the extraction error of the boundary. The accuracy of the constructed triangular mesh can be improved, and thus the accuracy of the calculated working area of the agricultural machine can be improved, so that the working state of the agricultural machine can be accurately monitored, and reliable conditions and basis can be provided for the optimization of the agricultural machine working.

[0125] Optionally, the embodiment of the present application also provides a working state monitoring device for agricultural machine working, Figure 3 which is a structural block diagram of the working state monitoring device for agricultural machine working of the embodiment of the present application.

[0126] As shown in Figure 3 , the working state monitoring device for agricultural machine working 2000 includes a memory 2200 and a processor 2400 electrically connected with the memory 2200. The memory 2200 stores a computer program which can be run on the processor 2400. The computer program is executed by the processor to implement each process of any one of the above-mentioned working state monitoring method embodiments for agricultural machine working and achieve the same technical effects. To avoid repetition, details are not described herein.

[0127] The embodiment of the present application also provides a computer readable storage medium, which stores a computer program. The computer program is executed by a processor to implement each process of any one of the above-mentioned working state monitoring method embodiments for agricultural machine working and achieve the same technical effects. To avoid repetition, details are not described herein. The computer readable storage medium includes a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk, etc.

[0128] It should be noted that, in the present document, the terms "comprises / comprising" or any other variations thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but can also include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element preceded by "comprises... a" does not, without more constraints, foreclose the existence of additional identical elements in the process, method, article, or apparatus that comprises the recited element.

[0129] Through the above description of the embodiments, those skilled in the art can clearly understand that the above-mentioned embodiment methods can be realized by means of software and necessary general hardware platforms, of course, they can also be realized by hardware, but in many cases, the former is a better embodiment. Based on such understanding, the technical solutions of the present application can be embodied in the form of a software product in essence or in the form of a part of the prior art that makes a contribution. The computer software product is stored in a storage medium (such as a ROM / RAM, a magnetic disk, or an optical disk) and includes a plurality of instructions for causing a terminal (which can be a mobile phone, a computer, a server, an air conditioner, or a network device, etc.) to execute the methods described in the various embodiments of the present application.

[0130] The embodiments of the present application are described above in combination with the accompanying drawings, but the present application is not limited to the above-mentioned specific embodiments, and the above-mentioned specific embodiments are only illustrative and not restrictive. Those skilled in the art can make many forms under the inspiration of the present application without departing from the scope of the present application and the scope of protection of the claims.

Claims

1. A method for monitoring the working status of agricultural machinery, characterized in that, include: The coordinates of the agricultural machinery during operation are acquired in real time to determine a first set including the acquired coordinates. Extract the boundary of the first set and determine the concave points in the boundary to divide each concave polygon including the concave points into convex polygons; Based on the vertices corresponding to each convex polygon, the task coordinate points in the first set are classified to obtain multiple second sets including the corresponding classified task coordinate points; Construct corresponding triangulations based on each second set, and determine the operating area of ​​the agricultural machinery based on the area of ​​each triangulation. The working status of the agricultural machinery is monitored based on the operating area.

2. The method as described in claim 1, characterized in that, The coordinates of the agricultural machinery during operation are acquired in real time to determine a first set including the acquired coordinates, which includes: The navigation and positioning coordinates of the agricultural machinery are collected in real time by a GPS data acquisition device installed on the agricultural machinery. The navigation and positioning coordinates include the latitude and longitude coordinates and direction angle of the agricultural machinery at the target work point. Convert the latitude and longitude coordinates of each work point into two-dimensional coordinates in a Cartesian coordinate system; The first set is determined based on the two-dimensional coordinates corresponding to each work point.

3. The method as described in claim 2, characterized in that, After converting the latitude and longitude coordinates of each work point into two-dimensional coordinates in a Cartesian coordinate system, the method further includes: Based on the two-dimensional coordinates and orientation angles corresponding to each work point and the working width of the agricultural machinery, multiple extended two-dimensional coordinates are expanded within the working width area of ​​the agricultural machinery. The two-dimensional coordinates of the work point reflect the position of the agricultural machinery, and the multiple extended two-dimensional coordinates reflect the horizontal width occupied by the agricultural machinery. The determination of the first set based on the two-dimensional coordinates corresponding to each work point includes: The first set is determined based on the two-dimensional coordinates and extended two-dimensional coordinates corresponding to each work point.

4. The method as described in claim 2 or 3, characterized in that, Extracting the boundary of the first set includes: During the first operating time from the start of operation to the first turn of the agricultural machinery, the boundary of the first set is extracted based on the Alpha Shapes boundary extraction function, the two-dimensional coordinates of the corresponding operating points of the first set, and the first shrinkage factor. After the agricultural machinery first turns, the boundary of the first set is extracted based on the Alpha Shapes boundary extraction function, the two-dimensional coordinates of the corresponding work point of the first set, and the second shrinkage factor, wherein the second shrinkage factor is greater than the first shrinkage factor; The Alpha Shapes boundary extraction function is boundary(x,y,s), where parameters x and y correspond to the two-dimensional coordinates of the work point, and parameter s represents the shrinkage factor.

5. The method as described in claim 4, characterized in that, The second contractility factor is determined according to the following steps: Determine the first number of work coordinate points included in the first set during the current operation after the agricultural machinery first experiences a turn; Determine the second number of work coordinate points included in the first set within the first work duration; The second contraction factor is determined based on the first quantity and the second quantity.

6. The method as described in claim 1, characterized in that, Determining the concave points in the boundary includes: Traverse each vertex of the boundary; Translate the i-th vertex currently being traversed to the origin of the Cartesian coordinate system; Rotate the boundary so that the (i+1)th vertex is located on the positive x-axis of the Cartesian coordinate system; The (i+1)th vertex is determined to be a concave point in the boundary if the following formula is satisfied: the i+k <0 k=2,3,4,...,[0.01m]+1, Where m represents the number of vertices of the boundary, and θ represents the smooth angle between the (i+1)th vertex and the (i+k)th vertex.

7. The method as described in claim 6, characterized in that, Divide each concave polygon, including the concave point, into convex polygons, including: The (i+1)th vertex that is determined to be a concave point is set as the first dividing point; By traversing backwards from the (i+1)th vertex, the first vertex located on the positive half-axis of the y-axis of the Cartesian coordinate system is determined and set as the second dividing point; Connect the first dividing point and the second dividing point to form a dividing line; The concave polygon, including the (i+1)th vertex, is divided by the dividing line.

8. The method as described in claim 1, characterized in that, Based on the vertices corresponding to each convex polygon, the task coordinate points in the first set are classified to obtain multiple second sets including the corresponding classified task coordinate points, including: The vertices corresponding to each convex polygon and the coordinate points of each task in the first set are sequentially input into the inpolygon function to determine the coordinate points of the task located in each closed convex polygon. The vertices corresponding to a convex polygon constitute a closed convex polygon. By summing the coordinates of all operation points located within the same closed convex polygon, a corresponding second set is obtained.

9. The method as described in claim 8, characterized in that, The step of constructing corresponding triangulations based on each of the second sets, and determining the operating area of ​​the agricultural machinery based on the area of ​​each triangulation, includes: Based on the Bowyer-Wastson function and the work coordinates in each second set, a triangulation network corresponding to each second set is constructed sequentially. Calculate the area of ​​each triangle included in each triangulation; The operating area of ​​the agricultural machinery is obtained by summing the areas of the triangles included in each triangulation.

10. A device for monitoring the working status of agricultural machinery, characterized in that, include: A memory and a processor electrically connected to the memory, the memory storing a computer program executable by the processor, the computer program, when executed by the processor, implementing the steps of the method as described in any one of claims 1 to 9.

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