Rice cultivation seedbed field surface terrain and cultivation depth integrated measurement method and rice cultivation seedbed preparation equipment

Abstract

According to the rice cultivation seedbed field surface terrain and cultivation depth integrated measurement method and the rice cultivation seedbed preparation equipment, a rotary cultivator serves as a measurement platform, and a double-antenna GNSS and an IMU are installed on a rack and a dragging plate respectively so as to measure the course angle, the pitch angle and the roll angle of the cultivator and the rotation angle of the dragging plate relative to the rack; establishing a vehicle body coordinate system; establishing a spatial position vector of the deepest soil cutting point of the rotating blade and a carriage profiling point under a vehicle body coordinate system; during rotary tillage operation, a homogeneous coordinate transformation method is adopted to synchronously measure three-dimensional coordinates of the deepest soil cutting point and the profiling point under coordinates of the east, north and sky, and a deepest soil cutting point set and a profiling point set are constructed; combining the two point sets, extracting plane coordinates of the farmland boundary, and arranging plane grid points; estimating the field terrain height of each plane grid point by using the profiling point set; and estimating the tilling bottom layer terrain height of each plane grid point by using the deepest soil point set, and calculating the tilling depth of each grid point. The invention has high efficiency and accuracy, and belongs to the mechanical agricultural equipment manufacturing technology.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of mechanized agricultural implement manufacturing, in particular to an intelligent agricultural machine used in rice cultivation, and further relates to a method for integrated measurement of field surface topography and plowing depth using the intelligent agricultural machine. BACKGROUND

[0002] Rice seedbed preparation is a key link in rice production, directly affecting subsequent planting and growth. Plowing depth significantly affects the growth and development of rice, and also provides guidance information for precise field leveling. Field surface topography is the basis for setting the leveling reference height, distributing the earthwork volume, and planning the path. At present, the main methods of rice field leveling are "dry leveling" and "horizontal leveling", among which dry leveling is in high demand due to its high efficiency.

[0003] Plowing depth measurement methods are divided into contact and non-contact types. The contact method is based on the terrain following driving of machine wheels or ground wheels, combined with the geometric relationship of the lifting arm or rocker arm rotation angle to calculate the plowing depth. The non-contact method uses non-contact sensors, such as ultrasonic sensors and optical sensors, to monitor the height of the machine frame relative to the ground to calculate the plowing depth. However, factors such as soil moisture content, operating temperature, and surface residue in farmland can affect the accuracy of non-contact measurement. More importantly, in existing research, the contact method of profiling wheel bottom point and the non-contact method of field surface monitoring point are not vertically distributed with the deepest plowing point, resulting in a principle error in plowing depth measurement accuracy. In addition, the distribution of farmland plowing depth lacks planar coordinate information, making it difficult to effectively connect with subsequent operation links.

[0004] Field surface topography measurement methods are mainly divided into remote sensing and vehicle-mounted types. The remote sensing method refers to using a drone as a platform to carry non-contact sensors to measure farmland topography. However, remote sensing measurement requires a lot of post-processing time, and frequent data transmission increases the time cost. The vehicle-mounted method refers to using an all-terrain vehicle, tractor, and rice transplanter as a platform to carry measurement equipment to obtain farmland three-dimensional topography. Although both vehicle-mounted and remote sensing measurement methods are suitable for all stages of leveling operations, when measuring the topography before leveling operations, soil transportation cannot be performed, increasing labor and energy costs. Therefore, there is an urgent need to develop an efficient and cost-effective topography measurement method before leveling operations.

[0005] Plowing depth and field surface topography are important references for fine field leveling operations, especially in rice production. However, independent measurement of plowing depth and field surface topography information increases cost investment, prolongs operation time, and increases the risk of field compaction. Currently, there is no reported research on integrated measurement of plowing depth and field surface topography. SUMMARY

[0006] In view of the technical problems existing in the prior art, the present application aims to provide a rice cultivation seedbed field surface terrain and tillage depth integrated measurement method, which can more efficiently and accurately achieve measurement.

[0007] Another object of the present application is to provide a rice cultivation seedbed preparation device.

[0008] In order to achieve the above-mentioned objects, the present application adopts the following technical solutions: A rice cultivation seedbed field surface terrain and tillage depth integrated measurement method, a rotary tillage tool is used as a measurement platform, the rotary tillage tool includes a frame, a rotary blade shaft, rotary blades, a cover shell, and a drag board; during operation, the rotary blade shaft drives the rotary blades to cut soil and throw it to the rear, the soil impacts the cover shell and the drag board and is finely broken and falls to the ground surface, the end of the drag board is in contact with the field surface and moves along with the terrain profile; the method includes the following steps, S1. A double-antenna GNSS and an IMU are respectively installed on the frame and the drag board to measure the heading angle, the pitch angle, and the roll angle of the tool, and the rotation angle of the drag board relative to the frame; S2. A vehicle body coordinate system is established , the GNSS main antenna positioning point is taken as the origin O, the forward direction of the tool is taken as the X-axis, the left side of the forward direction is taken as the Y-axis, and the Z-axis is determined according to the right-hand orthogonal rule; S3. The spatial position vectors of the deepest soil cutting point of the rotary blade and the profile point of the drag board in the vehicle body coordinate system are established; S4. In the rotary tillage operation, the homogeneous coordinate transformation method is used to synchronously measure the three-dimensional coordinates of the deepest soil cutting point and the profile point in the northeast celestial coordinate system, and the deepest soil cutting point set and the profile point set are constructed; S5. The deepest soil cutting point set and the profile point set are combined, the planar coordinates of the farmland boundary are extracted, and planar grid points are arranged; S6. The field surface terrain height of each planar grid point is estimated by taking the profile point set as a data sample, and the tillage bottom layer terrain height of each planar grid point is estimated by taking the deepest soil cutting point set as a data sample, and the tillage depth of each grid point is calculated.

[0009] As a preferred, in step S1, the baseline direction of the double-antenna GNSS is the direction of the main antenna pointing to the slave antenna, the baseline direction is perpendicular to the width direction of the frame, and is used to measure the heading angle and the pitch angle of the tool; the X-axis or the Y-axis of the internal coordinate system of the IMU is parallel to the width direction of the frame, and is used to measure the roll angle of the tool and the rotation angle of the drag board relative to the frame.

[0010] As a preferred, in step S3, the spatial position vector of the deepest soil cutting point changes with the pitch angle The position vector of the center of the rotating blade is set as , and the rotating radius of the blade is . The spatial position vector of the deepest soil cutting point is established as , and the expression is as follows: .

[0011] As a preferred embodiment, in step S3, the drag plate rotates in real time during operation, and the spatial position vector of the profiling point changes accordingly, and is jointly affected by the pitch angle of the rotary tiller and the rotation angle of the drag plate relative to the frame . The rotation center position vector of the drag plate is set as , the distance between the profiling point and the rotation center is , and the spatial position vector of the profiling point is established as , and the expression is as follows: .

[0012] As a preferred embodiment, in step S4, the coordinates of the origin of the vehicle coordinate system in the northeast celestial coordinate system are set as , and the rotation matrix is . The northeast celestial coordinates of the deepest soil cutting point and the profiling point are calculated using the homogeneous coordinate transformation method as and . .

[0013] As a preferred embodiment, in step S5, the long side and short side directions of the farmland are determined according to the set of deepest soil cutting points or the set of profiling points, so that the grid points are distributed along the long side and short side directions of the farmland. The distribution of the grid points meets the subsequent requirements of the operation heading, and the spacing between adjacent grid points in the short side direction of the farmland is determined by the operation width.

[0014] As a preferred embodiment, in step S5, the principal component analysis method is used to analyze the correlation between the X and Y variables, and the maximum correlation direction is determined. The maximum correlation direction is the direction of the largest eigenvalue of the covariance matrix, which represents the long side direction of the farmland. The singular value decomposition algorithm is used to calculate the eigenvalues and eigenvectors of the covariance matrix.

[0015] As a preferred embodiment, in step S6, for the same grid point, the field surface terrain height and the tillage bottom terrain height are estimated to ensure the accuracy of the calculation of the tillage depth and to avoid errors caused by the non-vertical distribution of the field surface terrain height points and the tillage bottom terrain height points in traditional tillage depth measurement.

[0016] As a preferred embodiment, in step S6, according to the characteristics of rotary tillage operation, the sample approximation Gaussian process regression algorithm is used to estimate the field surface terrain height and the tillage bottom terrain height of any grid point.

[0017] A rice cultivation bed preparation device adopts a rotary tillage tool and implements a rice cultivation bed surface topography and tillage depth integrated measurement method.

[0018] The present application has the following advantages: 1. The present application adopts an intelligent agricultural machine, which accurately measures the tillage depth according to the information of the field surface topography height and the tillage bottom layer topography height of the same grid point, effectively reducing the error of the traditional non-vertical tillage depth measurement method.

[0019] 2. The field surface topography and tillage depth integrated measurement method reduces the production cost of independent measurement of field surface topography and independent measurement of tillage depth, reduces the number of times of agricultural machinery entering the field, and effectively reduces the compaction risk of agricultural machinery to farmland.

[0020] 3. In the preparation of farmland, the rotary tillage operation stage can directly obtain the field surface topography and tillage depth information, and through information processing, accurate guidance is provided for farmland leveling operation, significantly reducing the time cost and energy consumption cost generated by traditional topography measurement before leveling operation. BRIEF DESCRIPTION OF DRAWINGS

[0021] Figure 1 It is a flowchart of a rice cultivation bed surface topography and tillage depth integrated measurement method.

[0022] Figure 2 It is a schematic diagram of the structure of the rotary tillage tool and the installation position of the dual-antenna GNSS and IMU.

[0023] Figure 3 It is a schematic diagram of the vehicle body coordinate system and the northeast sky coordinate system.

[0024] Figure 4 It is a schematic diagram of the spatial position vector of the deepest soil cutting point.

[0025] Figure 5 It is a schematic diagram of the spatial position vector of the field surface profiling point.

[0026] Figure 6 It is a grid point distribution diagram.

[0027] Figure 7 It is the estimation result of the field surface topography height.

[0028] Figure 8 It is the estimation result of the tillage depth.

[0029] Among them, 1 is a rack, 2 is a shell, 3 is a dual-antenna GNSS, 4 is an IMU, and 5 is a drag plate. DETAILED DESCRIPTION

[0030] The present application will be further described in detail below in conjunction with specific embodiments.

[0031] Example 1 This embodiment uses a rotary tiller as the measurement platform. The rotary tiller includes components such as a frame, a rotating cutter shaft, rotating blades, a cover, and a slide. The rotating cutter shaft is located below the frame and drives the rotating blades to rotate. The cover is fixedly connected to the frame and located above the rotating cutter shaft. The upper end of the slide is oscillatingly connected to the frame and located behind the rotating cutter shaft. The rotary tiller is as follows... Figure 2 As shown. In rotary tillage, rotating blades cut the soil and throw it backward. The soil impacts the cover and the drag plate, is broken up, and falls to the surface. The end of the drag plate contacts the field surface and moves in a contoured manner following the terrain.

[0032] like Figure 1 As shown in the figure, the specific method for integrating the measurement of rice cultivation seedbed topography and tillage depth in this embodiment is as follows: S1. Install dual-antenna GNSS and IMU on the frame and the trailer respectively to measure the heading angle, pitch angle, roll angle of the equipment, and the rotation angle of the trailer relative to the frame.

[0033] In this embodiment, the baseline direction of the dual-antenna GNSS (i.e., the direction from the main antenna to the secondary antenna) is perpendicular to the swath direction of the frame, and is used to measure the heading angle of the equipment. With pitch angle The X-axis or Y-axis of the IMU's internal coordinate system is parallel to the width direction of the frame and is used to measure the roll angle of the equipment. The rotation angle of the slide relative to the frame ,like Figure 3 As shown.

[0034] S2. Establish the vehicle coordinate system Taking the GNSS main antenna positioning point as the origin O, the direction of the equipment's movement as the X-axis, the left side of the direction of movement as the Y-axis, and the Z-axis as determined by the right-hand orthogonal criterion, as follows: Figure 3 As shown.

[0035] S3. Establish the spatial position vectors of the deepest soil cutting point of the rotating blade and the contour point of the trailer in the vehicle coordinate system.

[0036] In this embodiment, the spatial position vector of the deepest soil cutting point varies with the pitch angle of the rotary tiller. Changes, such as Figure 4 As shown. The position vector of the center point T of the rotary tool axis is set as... The radius of rotation of the rotary tiller blade is Establish the spatial location vector of the deepest soil point B. Its expression is as follows: .

[0037] The slide rotates in real time during operation, and the spatial position vector of the contour point changes accordingly, affected by the pitch angle of the rotary tiller. Rotation angle of the slide relative to the frame Together, such as Figure 5 As shown. The rotation center R position vector of the slide is set as... The distance between the contour point and the center of rotation is Establish the spatial position vector of the contour point C. Its expression is as follows: .

[0038] S4. During rotary tillage, the homogeneous coordinate transformation method is used to simultaneously measure the three-dimensional coordinates of the deepest incision point and the contour point under the northeast celestial coordinate system, and to construct the set of the deepest incision point and the set of contour points.

[0039] In this embodiment, the coordinates of the origin of the vehicle coordinate system in the northeast-northeast coordinate system are set as follows: The rotation matrix is The homogeneous coordinate transformation method was used to calculate the northeast-sky coordinates of the deepest incised soil point and the contour point. and for: .

[0040] S5. Extract the planar coordinates of the farmland boundary using the deepest cut point set or the contour point set, and arrange the planar grid points.

[0041] In this embodiment, taking the measured contour point set as an example, the specific steps are as follows: 1) Determine the direction of the long side of the farmland.

[0042] The number of contour points to be measured is set to m, and the set of plane coordinates of each contour point is as follows: .

[0043] in, Let X be the X coordinate of the i-th contour point. Let be the Y-coordinate of the i-th contour point.

[0044] Principal component analysis (PCA) was used to analyze the correlation between variables X and Y and to determine the direction of maximum correlation. The direction of maximum correlation is the direction of the largest eigenvalue of the covariance matrix, representing the direction of the longer side of the field. The formula for calculating the covariance matrix is ​​as follows: , .

[0045] The eigenvalues ​​and eigenvectors of the covariance matrix are calculated using the singular value decomposition algorithm: , in, are all eigenvectors of the covariance matrix, and the eigenvectors are sorted by eigenvalue size; is a diagonal matrix, whose diagonal elements are the square roots of the eigenvalues of the covariance matrix; is an orthogonal matrix.

[0046] 2) Rotate the point set: Express the two-dimensional point set in matrix form : , Rotate the two-dimensional point set to align the long and short directions of the farmland with the EN coordinate axes: .

[0047] 3) Arrange the grid points: Calculate the maximum and minimum values of the point set in the X and Y directions ), respectively, and establish the farmland boundary. Set the spacing of adjacent grid points in the X and Y directions to and , respectively, and arrange the grid point set as: , , Arrange the grid points on the local boundary of the farmland: , Merge the grid points: , Rotate the grid point set to restore the long and short directions of the farmland to their original directions: , The grid points are distributed along the long and short directions of the farmland, and the distribution of the grid points needs to meet the subsequent operation requirements. Specifically, the operation heading of the agricultural machinery is usually consistent with the long direction of the farmland, and the spacing of adjacent grid points in the short direction of the farmland is determined by the operation width, as shown in Figure 6 .

[0048] S6. Estimate the field terrain height of each planar grid point using the profiling point set as the data sample, and estimate the plow bottom layer height of each planar grid point using the deepest soil point set as the data sample, and calculate the plowing depth of each grid point.

[0049] ​In this embodiment, according to the characteristics of rotary tillage operation, a sample approximation Gaussian process regression algorithm (SA-GPR) is proposed to estimate the terrain height and plowing depth of any grid point. Specifically, by dividing the region of interest (ROI) related to the terrain height of the grid point, and approximating the ROI point set to the grid point under the premise of lossless accuracy. Based on this, taking the optimized ROI point set as the observation sample, the terrain height and plowing depth of the grid point are estimated by Gaussian process regression. Taking the point cloud of the field terrain as an example, the implementation process is as follows: With the rotary tillage operation width as the radius, the ROI affecting each grid point terrain height estimation is divided. The ROI terrain point set is extracted: , wherein is any point of the point set .

[0050] According to the characteristics of rotary tillage operation, the multiple profiling points measured at the same time have spatial collinearity. Therefore, the time variable is added to define the profiling point , and the collinear points are determined by the time variable . If there is no independent point in the ROI, the point is removed. According to the collinear points, the plane straight line equation is established, and the perpendicular line of the grid point to the straight line is drawn , and the two straight lines intersect at the nearest point . The positional relationship between the nearest point and the straight line is determined, as follows: .

[0051] If the nearest point meets the above conditions, the terrain height of the point is calculated according to the spatial linear relationship. At the same time, the point is added in the ROI, and the corresponding collinear point is removed. On the contrary, only the collinear point closest to the grid point is retained. The plane coordinates of the optimized ROI point set are rotated: .

[0052] Assuming that the terrain height is composed of a Gaussian process and a Gaussian noise term: , wherein is a Gaussian process model, representing the true terrain height at the input point ; is an independent and identically distributed Gaussian noise, is the noise variance. ​

[0053] Output value Follows a multivariate Gaussian distribution: , in, It is the covariance matrix of the training samples, whose elements are determined by the kernel function. Calculated; It is the covariance matrix of the observation noise.

[0054] Radial basis functions (RBFs) are suitable for terrains that are smooth and continuously varying, consistent with the topographic characteristics of the cultivated subsurface and field surface. The kernel function is defined as: , in, It is the signal variance; It is a length dimension parameter.

[0055] This embodiment optimizes model parameters using maximum likelihood estimation. , , .

[0056] For each grid point function value Terrain height relative to training samples Follows a joint Gaussian distribution: , in, and It is the covariance matrix between the training data and the grid points; It is the covariance scalar of the grid points themselves.

[0057] Based on the properties of the joint Gaussian distribution, the conditional distribution of grid points is as follows: .

[0058] Similarly, using the deepest soil point of the optimized ROI as the observation sample, the SA-GPR algorithm is used to estimate the topographic height of the cultivated subsurface at each grid point. Set the estimated height of the field terrain at the grid points to be... Then the tillage depth is: .

[0059] like Figure 7As shown, the true coordinates of 20 known measurement points are selected as input, and the terrain height is estimated. By comparing the estimated value of the field terrain height with the true value, the change trend of the terrain height estimation curve and the true curve is significantly consistent, and the error is less than 30mm. Statistical analysis results show that the average error of terrain height estimation is 17.95mm, and the root mean square error is 17.13mm, which verifies the accuracy of the method in terrain height estimation.

[0060] As shown in Figure 8 The change trend of the plowing depth estimation curve and the true curve is consistent, and most of the errors are less than 20mm. Statistical analysis shows that the average error of plowing depth estimation is 14.53mm, and the root mean square error is 16.50mm, indicating that the method can accurately estimate the plowing depth.

[0061] The estimation accuracy of plowing depth and terrain height is restricted by GNSS measurement accuracy, synchronous measurement accuracy and estimation accuracy of plowing bottom and field terrain. The results show that the error of plowing depth estimation is slightly lower than that of terrain height estimation. This is because the plowing depth is the relative vertical height between the plowing bottom and the field surface, which reduces the influence of GNSS measurement error on its estimation.

[0062] Therefore, the method of the present application realizes the integrated measurement of field terrain and plowing depth, and performs excellently in measurement accuracy.

[0063] Example two A rice cultivation seedbed preparation device adopts a rotary tiller, and implements the integrated measurement method of the field terrain and plowing depth of the rice cultivation seedbed of example one.

[0064] The above examples are the preferred embodiments of the present application, but the embodiments of the present application are not limited by the above examples, and any changes, modifications, substitutions, combinations, simplifications made without departing from the spirit and principles of the present application are equivalent replacement methods, and are all included in the protection scope of the present application.

Claims

1. A method for integrating the measurement of rice cultivation seedbed topography and tillage depth, using a rotary tiller as the measurement platform. The rotary tiller includes a frame, a rotating cutter shaft, rotating blades, a cover, and a drag plate. During operation, the rotating cutter shaft drives the rotating blades to cut the soil and throw it backward. The soil impacts the cover and drag plate, is broken up, and falls to the surface. The end of the drag plate contacts the field surface and moves in a contour-following manner with the terrain. The method is characterized by... Includes the following steps, S1. Install dual-antenna GNSS and IMU on the frame and the trailer respectively to measure the heading angle, pitch angle and roll angle of the equipment, as well as the rotation angle of the trailer relative to the frame; S2. Establish the vehicle coordinate system With the GNSS main antenna positioning point as the origin O, the direction of the equipment's movement as the X-axis, the left side of the direction of movement as the Y-axis, and the Z-axis determined according to the right-hand orthogonal criterion; S3. Establish the spatial position vectors of the deepest soil cutting point of the rotating blade and the contour point of the trailing plate in the vehicle coordinate system; S4. During rotary tillage, the homogeneous coordinate transformation method is used to simultaneously measure the three-dimensional coordinates of the deepest incision point and the contour point under the northeast celestial coordinate system, and to construct the set of the deepest incision point and the set of contour points. S5. Merge the deepest cut soil point set and the contour point set, extract the planar coordinates of the farmland boundary, and arrange the planar grid points; S6. Using the contour point set as data samples, estimate the field terrain height of each planar grid point; Using the deepest soil point set as data sample, the topographic height of the cultivated layer at each planar grid point is estimated, and the cultivation depth at each grid point is calculated.

2. The integrated measurement method for rice cultivation seedbed topography and tillage depth according to claim 1, characterized in that: In step S1, the baseline direction of the dual-antenna GNSS is from the main antenna to the secondary antenna, and the baseline direction is perpendicular to the swath direction of the frame, used to measure the heading angle of the equipment. With pitch angle The X-axis or Y-axis of the IMU's internal coordinate system is parallel to the width direction of the frame and is used to measure the roll angle of the equipment. The rotation angle of the slide relative to the frame .

3. The integrated measurement method for rice cultivation seedbed topography and tillage depth according to claim 2, characterized in that: In step S3, the spatial position vector of the deepest soil cutting point varies with the pitch angle of the rotary tiller. Change; Set the position vector of the center point of the rotary tool axis as The radius of rotation of the rotary tiller blade is Establish the spatial location vector of the deepest soil incision point. Its expression is as follows: 。 4. The integrated measurement method for rice cultivation seedbed topography and tillage depth according to claim 3, characterized in that: In step S3, the slide rotates in real time during operation, and the spatial position vector of the contour point changes accordingly, affected by the pitch angle of the rotary tiller. Rotation angle of the slide relative to the frame Together; the rotation center position vector of the slide is set as The distance between the contour point and the center of rotation is Establish the spatial position vector of the contouring point Its expression is as follows: 。 5. The integrated measurement method for rice cultivation seedbed topography and tillage depth according to claim 4, characterized in that: In step S4, the coordinates of the origin of the vehicle coordinate system in the northeast-central coordinate system are set as follows: The rotation matrix is The homogeneous coordinate transformation method was used to calculate the northeast-sky coordinates of the deepest incised soil point and the contour point. and for: 。 6. The integrated measurement method for rice cultivation seedbed topography and tillage depth according to claim 1, characterized in that: In step S5, the long and short sides of the farmland are determined based on the deepest cut point set or the contour point set, so that the grid points are distributed along the long and short sides of the farmland. The distribution of the grid points meets the navigation requirements of subsequent agricultural machinery operations, and the spacing between adjacent grid points in the short side direction of the farmland is determined by the working width.

7. The integrated measurement method for rice cultivation seedbed topography and tillage depth according to claim 6, characterized in that: In step S5, principal component analysis is used to analyze the correlation between variables X and Y and determine the direction of maximum correlation. The direction of maximum correlation is the direction of the largest eigenvalue of the covariance matrix, which represents the direction of the long side of the farmland. The singular value decomposition algorithm is used to calculate the eigenvalues ​​and eigenvectors of the covariance matrix.

8. The integrated measurement method for rice cultivation seedbed topography and tillage depth according to claim 1, characterized in that: In step S6, for the same grid point, the height of the field surface topography and the height of the topography of the cultivated bottom are estimated to ensure the accuracy of the tillage depth calculation and avoid the error caused by the non-vertical distribution of the height points of the field surface topography and the topography of the cultivated bottom in traditional tillage depth measurement.

9. The integrated measurement method for rice cultivation seedbed topography and tillage depth according to claim 8, characterized in that: In step S6, based on the characteristics of rotary tillage, a sample approximation Gaussian process regression algorithm is used to estimate the field surface topography height and the topography height of the tillage layer at any grid point.

10. A rice cultivation seedbed preparation device, characterized in that: A rotary tillage machine is used to implement the integrated measurement method of rice cultivation seedbed topography and tillage depth as described in any one of claims 1-9.

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