Subsoiler capable of monitoring dynamic change of soil in real time

Abstract

The application provides a subsoiler for monitoring dynamic changes of soil in real time, and relates to the technical field of intelligent subsoiling, which comprises a rack, a speed sensor, a subsoiling device, a traction device and a soil morphology monitoring device; the speed sensor is installed on the rack and used for detecting the moving speed of the subsoiler in real time; the traction device is fixedly connected with the rack; the subsoiling device comprises a subsoiling shovel and is used for subsoiling soil; the soil morphology monitoring device is installed behind the subsoiling device and comprises a line laser emitter, a binocular camera and an upper computer; the line laser emitter emits line laser behind the subsoiling shovel; the binocular camera is installed directly above the light; the binocular camera sends the line laser picture to the upper computer in real time, and the upper computer processes the picture to generate soil point cloud data at each moment. The subsoiler can monitor the soil morphology changes in the whole subsoiling process, realize the visualization of the whole subsoiling process and reduce the amount of manpower used during work.

Description

Technical Field

[0001] This application relates to the field of intelligent subtilization, specifically a subtilization machine that monitors dynamic changes in soil in real time. Background Technology

[0002] Deep tillage is a tillage technique that can reduce soil bulk density and increase infiltration rate, and it is effective in solving soil compaction problems caused by heavy agricultural machinery. However, the level of intelligence in deep tillage technology is still not high, especially in terms of deep tillage monitoring technology, which lacks integration with advanced technologies.

[0003] Stereo vision technology has been widely researched and applied in various scientific, engineering, and industrial fields due to its advantages of simple and lightweight tools. Digital point clouds acquired by combining line structured light with binocular vision can provide rich, high-quality, high-detail, and high-precision 3D information, enabling the digitization of complex freeform surfaces and the rapid creation or reproduction of accurate object models. This allows for effective monitoring of soil dynamics during deep tillage. Summary of the Invention

[0004] The purpose of this application is to address the current challenges in deep tillage monitoring by designing a deep tillage machine capable of real-time monitoring of the soil during the deep tillage process and generating a high-fidelity soil model. Simultaneously, it ensures flexibility and facilitates the installation of various auxiliary mechanisms. The technical solution adopted in this application is as follows:

[0005] A subsoiler for real-time monitoring of dynamic changes in soil, characterized in that it includes a frame, a speed sensor, a subsoiler device, a traction device, and a soil morphology monitoring device;

[0006] The speed sensor is mounted on the frame and is used to detect the moving speed of the subsoiler in real time;

[0007] The traction device is fixedly connected to the frame and is used to connect with the tractor to pull the subsoiler forward.

[0008] The deep tillage device includes a deep tillage shovel for deep tillage of the soil;

[0009] The soil morphology monitoring device is installed behind the subtilizing device and includes a line laser emitter, a binocular camera, and a host computer. The line laser emitter emits a line laser behind the subtilizing shovel, with the light on the soil that has just been subtilized. The binocular camera is installed directly above the light, with the light at the center of the camera's field of view. The binocular camera captures line laser images and sends them to the host computer in real time. The host computer processes the images to generate soil point cloud data for each moment.

[0010] Preferably, the frame includes a front beam, a middle beam, a rear beam, depth-limiting wheels, and a soil morphology monitoring device support plate. The front beam, middle beam, and rear beam are welded together to form a frame. Multiple depth-limiting wheels are installed at the lower end of the frame, and the soil morphology monitoring device support plate is fixedly connected to the middle of the frame.

[0011] Preferably, the deep loosening shovel includes a shovel head capable of deep loosening the soil, and the number of deep loosening shovels is one or more, all of which are fixed to the front beam of the frame by U-shaped connectors and bolts and nuts.

[0012] Preferably, the traction device includes a fixed link, two upper suspension links, and two lower suspension links. The fixed link is welded to the front beam of the frame. The two upper suspension links are symmetrical from left to right, and their lower ends are bolted to the middle beam of the frame. The two lower suspension links are symmetrical from left to right, and their lower ends are bolted to the fixed link. The upper ends of the upper and lower suspension links are fixed together with bolts, and the upper ends of the bolts are reserved with through holes for connection with the tractor.

[0013] Preferably, the real-time soil monitoring method is as follows:

[0014] First, line laser images are acquired using a binocular camera. The host computer then obtains the line laser images from the left and right cameras at the same time. The center line of the line laser image is extracted using the gray-scale centroid method. Based on the calibration data of the binocular camera and the parallax method, all point cloud data on the laser image are calculated to obtain the soil morphology at each time.

[0015] Preferably, the specific steps for extracting the center line of a line laser image using the grayscale centroid method are as follows:

[0016] S1 processes each row of light stripes according to the gray distribution characteristics within the cross-section of each row. By calculating and extracting the gray centroid of the light stripe region in the direction of the row coordinates, the point is used to represent the position of the center point of the light stripe in the cross-section. Finally, all the center points are fitted to form the center line of the light stripe.

[0017] Let the width of the captured image be W and the height be H. The formula for calculating the center point of the light stripes using the gray-scale centroid method is as follows:

[0018]

[0019] Where: c x Let I(x,y) be the center line position, and let x and y be the grayscale image, where x and y represent the horizontal and vertical coordinates of the image, respectively.

[0020] After obtaining the center line of the line laser, S2 uses the images of the left and right cameras after extracting the center line as input, and combines the disparity mapping matrix and step size to calculate the three-dimensional coordinates of each pixel based on the disparity:

[0021] First, calculate the depth value from the parallax:

[0022]

[0023] Then, the coordinates of the pixel in the camera coordinate system are calculated using the camera intrinsic parameters and disparity values:

[0024]

[0025] In the formula, Z represents the depth of the object from the camera, X and Y represent the horizontal and vertical coordinates of the object in the camera coordinate system, respectively, that is, (X,Y,Z) is the three-dimensional coordinates of the object in the camera coordinate system; (u,v) is the coordinate of the pixel on the image, (c x ,c y ) is the coordinate of the principal point; f is the focal length of the camera; B is the baseline distance between the left and right cameras; d is the parallax value of the corresponding pixels of the left and right cameras.

[0026] S3 can generate point cloud data for the location of the laser based on a series of coordinate points, thereby generating a soil curve model.

[0027] In summary, the technical solutions provided in the embodiments of this application have the following technical effects or advantages:

[0028] 1. The subsoiler of the present invention can monitor the changes in soil morphology throughout the entire subsoil process, realize the visualization of the entire subsoil process, and reduce the amount of manpower required during operation;

[0029] 2. The subsoiler of the present invention can be equipped with different subsoil shovels and various auxiliary tools, such as vibrators and air compressors, to adapt to different working requirements. Attached Figure Description

[0030] Figure 1 This is a structural diagram of the deep tillage machine for real-time monitoring of dynamic changes in soil according to the present invention.

[0031] Figure 2 This is a schematic diagram of the soil morphology monitoring device in this invention.

[0032] Among them: 1: front beam of frame, 2: middle beam of frame, 3: rear beam of frame, 4: deep loosening shovel, 5: depth limiting wheel, 6: laser emitter, 7: binocular camera, 8: upper suspension link, 9: lower suspension link, 10: fixed link, 11: soil morphology monitoring device support plate, 12: U-shaped connector; 13: soil. Detailed Implementation

[0033] To enable those skilled in the art to better understand the technical solutions in this specification, the technical solutions in the embodiments of this specification will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments.

[0034] A subsoil machine that monitors soil dynamics in real time, see [link / reference] Figure 1 As shown, it includes a frame, a deep tillage device, a traction device, and a soil morphology monitoring device.

[0035] The frame includes a front beam 1, a middle beam 2, a rear beam 3, a soil morphology monitoring device support plate 11, and a traction device. The front beam, middle beam, and rear beam are welded together to form a horizontal rectangular frame structure. The soil morphology monitoring device support plate is bolted to the middle of the rectangular frame structure. The traction device is fixedly connected to the frame above the soil morphology monitoring device support plate. Depth-limiting wheels are installed on both sides of the lower end of the rectangular frame structure. The depth-limiting wheels are used to drive the frame to move as a whole. The soil morphology monitoring device support plate is used to connect the soil morphology monitoring device. A speed sensor (not shown in the figure) is also installed on the frame to detect the moving speed of the frame and feed the speed data back to the host computer.

[0036] The subsoiling device mainly includes subsoiling shovels 4. The number and shape of the shovels can be adjusted according to actual production requirements. Each subsoiling shovel 4 is fixed to the front beam of the frame by a set of U-shaped connectors 12 and bolts and nuts. The subsoiling device, including the subsoiling shovels, can be modified into a vibratory subsoiling machine by installing a vibration device; it can also be modified into a pneumatic subsoiling machine by installing an air compressor, motor, belt, and air tank, making it suitable for different working requirements.

[0037] The traction device includes a fixed link 10, two upper suspension links 8 and two lower suspension links 9. The fixed link is welded to the front beam of the frame. The two upper suspension links are symmetrical from left to right, and their lower ends are bolted to the middle beam of the frame. The two lower suspension links are symmetrical from left to right, and their lower ends are bolted to the fixed link. The upper ends of the upper and lower suspension links are fixed together by bolts, and the upper ends of the bolts are reserved with through holes for connection with the tractor.

[0038] The soil morphology monitoring device includes a binocular camera 7, a laser emitter 6, and a host computer. Various parameters of the binocular camera can be adjusted via the host computer, and the angle of the line laser emitter is adjustable, allowing control of the line laser position behind the shovel handle. The binocular camera in the soil morphology monitoring device can have various parameters adjusted via the host computer, and the angle of the line laser emitter is adjustable, used to control the line laser position behind the shovel handle.

[0039] See appendix Figure 2As shown, a soil morphology monitoring method using the aforementioned subsoiler is as follows: The subsoiler is mounted on a tractor via a traction device. As the subsoiler moves forward, the soil morphology changes. The laser intersects with the changing soil, and the laser emitter continuously emits laser light. A binocular camera takes pictures above the laser light to obtain images from the left and right cameras at each moment.

[0040] The laser centerline was extracted using the gray-scale centroid method.

[0041] The grayscale distribution characteristics within the cross-section of each row of light stripes are processed row by row. The grayscale centroid of the light stripe region is calculated and extracted row by row along the direction of the row coordinates. This point is used to represent the position of the center point of the light stripe in that cross-section. Finally, all the center points are fitted to form the center line of the light stripe.

[0042] Let the width of the captured image be W and the height be H. The formula for calculating the center point of the light stripes using the gray-scale centroid method is as follows:

[0043]

[0044] Where: c x Let I(x,y) be the center line position, and let x and y be the grayscale image, where x and y represent the horizontal and vertical coordinates of the image, respectively.

[0045] After obtaining the center line of the linear laser, using the images of the left and right cameras after extracting the center line as input, and combining the disparity mapping matrix and the step size, the three-dimensional coordinates of each pixel are calculated based on the disparity:

[0046] First, calculate the depth value from the parallax:

[0047]

[0048] Then, the coordinates of the pixel in the camera coordinate system are calculated using the camera intrinsic parameters and disparity values:

[0049]

[0050]

[0051] In the formula, Z represents the depth of the object from the camera, X and Y represent the horizontal and vertical coordinates of the object in the camera coordinate system, respectively, that is, (X,Y,Z) is the three-dimensional coordinates of the object in the camera coordinate system; (u,v) is the coordinate of the pixel on the image, (c x ,c y ) is the coordinate of the principal point; f is the focal length of the camera; B is the baseline distance between the left and right cameras; and d is the parallax value of the corresponding pixels of the left and right cameras.

[0052] Point cloud data for the location of the laser can be generated from a series of coordinate points, thus creating a soil curve model.

[0053] The foregoing description is merely an exemplary embodiment of this disclosure and should not be construed as limiting the scope of this disclosure. Any equivalent changes and modifications made in accordance with the teachings of this disclosure shall still fall within the scope of this disclosure. Those skilled in the art will readily conceive of other embodiments of this disclosure upon considering the specification and the disclosure of practical truth. This application is intended to cover any variations, uses, or adaptations of this disclosure that follow the general principles of this disclosure and include common knowledge or customary techniques in the art not described in this disclosure. The specification and embodiments are considered exemplary only, and the scope and spirit of this disclosure are defined by the claims.

Claims

1. A monitoring method for a subsoiler that monitors soil dynamics in real time, characterized in that, The subsoiler includes a frame, speed sensor, subsoil device, traction device, and soil morphology monitoring device; The speed sensor is mounted on the frame and is used to detect the moving speed of the subsoiler in real time; The traction device is fixedly connected to the frame and is used to connect with the tractor to pull the subsoiler forward. The deep tillage device includes a deep tillage shovel for deep tillage of the soil; The soil morphology monitoring device is installed behind the subtilizing device and includes a line laser emitter, a binocular camera, and a host computer. The line laser emitter emits a line laser behind the subtilizing shovel, with the light on the soil that has just been subtilized. The binocular camera is installed directly above the light, with the light in the center of the camera's field of view. The binocular camera captures line laser images and sends them to the host computer in real time. The host computer processes the images to generate soil point cloud data for each moment. First, line laser images are acquired using a binocular camera. The host computer obtains the line laser images from the left and right cameras at the same time. The center line of the line laser image is extracted using the gray-scale centroid method. Based on the calibration data of the binocular camera and the parallax method, all point cloud data on the laser image are calculated to obtain the soil morphology at each time. The specific steps for extracting the center line of a line laser image using the gray-scale centroid method are as follows: S1 processes each row of light stripes according to the gray distribution characteristics within the cross-section of each row. By calculating and extracting the gray centroid of the light stripe region in the direction of the row coordinates, the point is used to represent the position of the center point of the light stripe in the cross-section. Finally, all the center points are fitted to form the center line of the light stripe. Let the width of the captured image be W and the height be H. The formula for calculating the center point of the light stripes using the gray-scale centroid method is as follows: in: The centerline position, It is a grayscale image. and These represent the horizontal and vertical coordinates of the image, respectively. After obtaining the center line of the line laser, S2 uses the images of the left and right cameras after extracting the center line as input, and combines the disparity mapping matrix and step size to calculate the three-dimensional coordinates of each pixel based on the disparity: First, calculate the depth value from the parallax: Then, the coordinates of the pixel in the camera coordinate system are calculated using the camera intrinsic parameters and disparity values: In the formula, Indicates the depth of the object from the camera. and These represent the horizontal and vertical coordinates of the object in the camera coordinate system, respectively. These are the three-dimensional coordinates of the object in the camera coordinate system. These are the coordinates of a pixel on the image. These are the coordinates of the principal point; It's the camera's focal length. It is the baseline distance between the left and right cameras. It is the parallax value of corresponding pixels of the left and right cameras; S3 can generate point cloud data for the location of the laser based on a series of coordinate points, thereby generating a soil curve model.

2. The monitoring method for a subsoiler for real-time monitoring of soil dynamic changes according to claim 1, characterized in that, The frame includes a front beam, a middle beam, a rear beam, depth-limiting wheels, and a support plate for the soil morphology monitoring device. The front beam, middle beam, and rear beam are connected by welding to form a frame. Multiple depth-limiting wheels are installed at the lower end of the frame, and the support plate for the soil morphology monitoring device is fixedly connected to the middle of the frame.

3. The monitoring method for a subsoiler for real-time monitoring of soil dynamic changes according to claim 1, characterized in that, The deep loosening shovel includes a shovel head capable of deep loosening the soil. There are one or more deep loosening shovels, and all one or more deep loosening shovels are fixed to the front beam of the frame by U-shaped connectors and bolts and nuts.

4. The monitoring method for a subsoiler for real-time monitoring of soil dynamic changes according to claim 1, characterized in that, The traction device includes a fixed link, two upper suspension links, and two lower suspension links. The fixed link is welded to the front beam of the frame. The two upper suspension links are symmetrical from left to right, and their lower ends are bolted to the middle beam of the frame. The two lower suspension links are symmetrical from left to right, and their lower ends are bolted to the fixed link. The upper ends of the upper and lower suspension links are fixed together with bolts, and the upper ends of the bolts are reserved with through holes for connection with the tractor.

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