A leaf vegetable harvester header profiling adjusting device and adjusting method

Abstract

The present application provides a kind of leaf vegetable harvester header profiling adjustment device and adjusting method, by analyzing complete ultrasonic reflection signal, the measurement of ridge distance and ridge roughness is carried out;The height and attitude angle of the header are calculated by constructing the ridge distance measured by ultrasonic sensor and the structure of harvester, which are used as input parameters, the height adjustment fuzzy controller of header and the attitude angle adjustment fuzzy controller of header are designed, the roughness of soil surface is used as the basis for adaptive adjustment of header height target, the extension amount of two electric cylinders is determined, and the adaptive profiling of header height and header attitude angle is realized. Through the measurement of ridge distance and ridge roughness, the influence of random interference such as soil block size, soft soil bed and vegetable stubble on measurement accuracy is avoided when non-contact measurement is carried out, the stability of measurement accuracy is guaranteed, the accuracy of header profiling adjustment is improved, and the quality of leaf vegetable harvesting is improved.

Description

TECHNICAL FIELD

[0001] The present application belongs to the technical field of automatic control of vegetable harvesting machines, and particularly relates to a leafy vegetable harvester header profiling adjustment device and method. BACKGROUND

[0002] The mechanization degree of the ploughing, seedling raising, sowing, transplanting and plant protection links of leafy vegetable production is relatively high, and the harvesting link is still mainly in the manual picking mode, which is low in efficiency, high in labor intensity and cost.

[0003] Header profiling is an important technology to ensure the performance of leafy vegetable harvesting. The existing leafy vegetable harvester header adjustment is mainly through manual adjustment of the height of the header from the ground, which depends on the operation experience of the operator, and has poor stability. If the position of the header is too high, it will cause the leafy vegetables to be missed or not cut, and if the position of the header is too low, it will easily cause the cutting tool to dig the soil, resulting in cutting tool collapse, stone stuck, etc. At present, some researches on the profiling adjustment of the leafy vegetable harvester header mainly use profiling wheels or profiling plates to measure the height of the header from the ground, that is, the profiling wheels or profiling plates are in contact with the ridge surface, and the height from the ground is obtained according to the position or deformation thereof.

[0004] However, in actual harvesting operation, the ridge surface is not flat due to the influence of factors such as long-term soil settlement and wind erosion. Contact measurement inevitably causes deformation of the soil on the ridge surface, especially in the soft soil bed environment, which is also affected by random interference such as soil blocks and vegetable stubble, and it is difficult to ensure the measurement accuracy, and the stability of the header profiling control is low.

[0005] At present, there are also laser non-contact measurement methods, which measure the distance from a certain point on the ridge surface to the sensor, and are also easily affected by factors such as soil blocks and stubble, and cannot guarantee the actual measurement accuracy. SUMMARY

[0006] In view of the above technical problems, one of the purposes of one mode of the present application is to provide a leafy vegetable harvester header profiling adjustment device, which detects the ridge surface information through an ultrasonic sensor on the frame of the harvesting component, and a controller can adjust the extension amount of an electric cylinder to realize two-degree-of-freedom adjustment of the height and attitude angle of the header, and complete the profiling adjustment when the header harvests leafy vegetables.

[0007] One of the objects of one embodiment of the present application is to provide a leaf vegetable harvester header profiling adjustment method, which measures the ridge distance and the ridge roughness by analyzing complete ultrasonic reflection signals, constructs the ridge distance measured by the ultrasonic sensor and the harvester structure to calculate the height and attitude angle of the header, takes the height and attitude angle of the header as input parameters, designs a header height adjustment fuzzy controller and a header attitude angle adjustment fuzzy controller, and adjusts the header height target adaptively based on the soil surface roughness to determine the extension amount of the two electric cylinders, so as to realize adaptive profiling of the header height and the header attitude angle. Through the measurement of the ridge distance and the ridge roughness, the influence of random interference such as the size of soil clumps, soft soil bed and vegetable stubble on the measurement accuracy during non-contact measurement is avoided, the stability of the measurement accuracy is ensured, the accuracy of the header profiling adjustment is improved, and the quality of the leaf vegetable harvesting is improved.

[0008] Note that the description of these objects does not hinder the existence of other objects. One embodiment of the present application does not need to achieve all the above-mentioned objects. The objects other than the above-mentioned objects can be extracted from the description, drawings, and claims.

[0009] The present application achieves the above technical objects through the following technical means.

[0010] A leaf vegetable harvester header profiling adjustment device includes a chassis walking part, a harvesting part rack, and a controller.

[0011] The harvesting part rack is arranged on the chassis walking part.

[0012] The harvesting part rack is provided with a cutter, and the bottom of the harvesting part rack is provided with a first ultrasonic sensor and a second ultrasonic sensor.

[0013] One end of the harvesting part rack is connected to the front end of the chassis walking part through a first electric cylinder and a second electric cylinder, and the other end of the harvesting part rack is connected to the rear end of the chassis walking part.

[0014] The controller is connected with the first electric cylinder, the second electric cylinder, the first ultrasonic sensor, and the second ultrasonic sensor, respectively, obtains the vertical distance d of the ridge P and the roughness SSR of the ridge P through the echo information of the detection information of the first ultrasonic sensor and the second ultrasonic sensor, and adjusts the piston rod length of the first electric cylinder and the second electric cylinder.

[0015] In the above scheme, the controller obtains the vertical distance d of the ridge P and the roughness SSR of the ridge P according to the echo information detected by the first ultrasonic sensor and the second ultrasonic sensor, establishes a plane equation of the harvesting component rack according to the installation positions of the first ultrasonic sensor and the second ultrasonic sensor, thereby determining the height and attitude angle of the cutting knife, then establishes a relationship equation of the first electric cylinder and the second electric cylinder and the height and attitude angle of the cutting knife, and finally adjusts the piston rod extension length of the first electric cylinder and the second electric cylinder through the cutting platform attitude angle control model and the cutting platform height control model, so as to adjust the height and attitude angle of the cutting knife.

[0016] A method for adjusting the profiling adjustment device of the leaf vegetable harvester cutting platform, comprising the following steps:

[0017] Step S1: The controller calculates the vertical distance d of the ridge P and the roughness SSR of the ridge P according to the echo signals of the first ultrasonic sensor and the second ultrasonic sensor;

[0018] Step S2: According to the distances of the first ultrasonic sensor and the second ultrasonic sensor from the ridge P detected in step S1, a coordinate system is established, and a plane equation of the harvesting component rack in the coordinate system is obtained;

[0019] Step S3: According to the plane equation of the harvesting component rack in the coordinate system obtained in step S2, a straight line equation of the axis L of the cutting knife 1 is established, the included angle between the axis L and the ridge P, i.e. the attitude angle α, and the vertical distance between the center position of the axis L and the ridge P, i.e. the cutting height H, are obtained;

[0020] Step S4: The piston rod length l1 of the first electric cylinder and the piston rod length l2 of the second electric cylinder are obtained, and according to the attitude angle α and the cutting height H obtained in step S3, a relationship equation of the attitude angle α and the cutting height H and the piston rod length l1 of the first electric cylinder and the piston rod length l2 of the second electric cylinder is established;

[0021] Step S5: A cutting platform attitude angle control model and a cutting platform height control model are established;

[0022] Step S6: According to the roughness SSR of the ridge P obtained in step S1, the target cutting height H0 is adjusted;

[0023] Step S7: According to the target cutting height H0 obtained in step S6, the height adjustment amount ΔH is calculated according to the cutting platform attitude angle control model, and the cutting platform attitude angle adjustment amount Δα is calculated according to the cutting platform attitude angle fuzzy controller;

[0024] Step S8: According to the height adjustment amount ΔH and the cutting head posture angle adjustment amount Δα obtained in step S7, the adjustment amounts of the first electric cylinder and the second electric cylinder are obtained through the relationship equation of the posture angle α and the cutting height H and the first electric cylinder piston rod length l1 and the second electric cylinder piston rod length l2, and adjustment is performed.

[0025] In the above scheme, when the step S1 detects the vertical distance of the first ultrasonic sensor and the second ultrasonic sensor from the ridge P and the roughness SSR of the ridge P, the reflected wave peak value time interval T p , the reflected wave intensity period integral E r , the median time width T m , and the reflected wave peak value V max are extracted respectively.

[0026] Further, when the step S1 detects the vertical distance of the first ultrasonic sensor and the second ultrasonic sensor from the ridge P, the following formula is used:

[0027] d=k·T p

[0028] Wherein, k is a constant coefficient related to the ultrasonic wave propagation speed.

[0029] Further, when the step S1 detects the roughness SSR of the ridge P, the following steps are used:

[0030] Step S1.1: Measure the point cloud information of the ridge P by the laser scanner, and calculate the surface roughness SSR according to the following formula:

[0031]

[0032] Wherein, v i is the distance between the laser scanner and the measurement point, is the average distance between the laser scanner and all measurement points;

[0033] Step S1.2: Repeat step S1 to establish a surface roughness sample library SSR i ;

[0034] Step S1.3: According to the ridge P information detected by the ultrasonic sensor, a sample library {T p , T m , T m , V max} p is established. m m max i ;

[0035] ​​​Step S1.4: Add the sample library {T} p T m T m V max} i The surface roughness sample library SSR is used as input to the adaptive fuzzy neural network. i The adaptive fuzzy neural network is trained using its output until the error of the adaptive fuzzy neural network meets the set range.

[0036] Step S1.5: The time interval T between the peak values ​​of the reflected waves detected by the first ultrasonic sensor and the second ultrasonic sensor is... p The periodic integral of the reflected wave intensity E r Median time width T m and the peak value of the reflected wave V max The input is fed into the trained adaptive fuzzy neural network to obtain the soil surface roughness (SSR).

[0037] In the above scheme, the relationship equations between the attitude angle α and the cutting height H in step S4 and the length l1 of the first electric cylinder piston rod and the length l2 of the second electric cylinder piston rod are as follows:

[0038]

[0039] In the above scheme, the attitude angle control model in step S5 is a two-dimensional fuzzy control model, and the input of the attitude angle control model is the cutting table attitude angle deviation E. α and the rate of change of the attitude angle deviation of the cutter head EC α The cutting table attitude angle deviation E α and the rate of change of the attitude angle deviation of the cutter head EC α Based on real-time cutting height H t The real-time cutting attitude angle α is calculated. t Then, it is compared with the target cutting attitude angle to obtain the result;

[0040] The cutting table attitude angle deviation E α The range of variation includes seven levels: [-45°, -10°], [-10°, -5°], [-5°, -2°], [-2°, 2°], [2°, 5°], [5°, 10°], and [10°, 45°].

[0041] The rate of change of the cutting table attitude angle deviation EC α Based on the sampling frequency and the set E α The range of variation is obtained; the rate of change of the cutting table attitude angle deviation ECa = (the cutting table attitude angle deviation Ea at the previous moment - the cutting table attitude angle deviation Ea at this moment) / sampling frequency;

[0042] The output of the attitude angle control model is a header attitude angle adjustment amount Δα.

[0043] In the above scheme, the header height control model in step S5 is a two-dimensional fuzzy control model, and the input of the header height control model is a header height deviation E H and a header height deviation change rate EC H The header height deviation E H and the header height deviation change rate EC H are compared with a real-time cutting height H t and a target cutting height H0.

[0044] The header height deviation E H has a change range including seven levels, i.e., [-H0, -0.5H0], [-0.5H0, -0.25H0], [-0.25H0, -0.1H0], [-0.1H0, 0.1H0], [0.1H0, 0.25H0], [0.25H0, H0] and [H0, 5H0].

[0045] The header height deviation change rate EC H is obtained from a sampling frequency and the target cutting height H0; the header height deviation change rate EC H = (a header height deviation E H at a previous time - a header height deviation E H at this time) / a sampling frequency.

[0046] The output of the header height control model is a header attitude angle adjustment amount Δα.

[0047] In the above scheme, the target cutting height H0 adjusted in step S6 adopts the following formula:

[0048] H0 = H'0 + ω·SSR

[0049] wherein H'0 is the target cutting height before adjustment, ω is a setting coefficient, and ω > 0.

[0050] Compared with the prior art, the present application has the following beneficial effects:

[0051] According to one mode of the present application, ultrasonic sensors are installed on both sides of a chassis frame of a leaf vegetable harvester to non-contact measure the roughness of a soil surface of a ridge and the average distance between the ridge and the header, since the detection range of the ultrasonic sensors is a certain circular area, compared with single-point distance measurement, the circular area detected can better represent the actual characteristics of the measured soil surface, can reduce the randomness of the measurement results caused by the unevenness of the ridge, and improve the measurement stability.

[0052] According to one mode of the present application, the present application adjusts the target value of the height of the cutting platform from the ground and the input parameter range of the height of the cutting platform fuzzy controller according to the roughness of the soil surface detected by the ultrasonic sensor, so as to adjust the height of the cutting platform from the ground adaptively according to the soil surface, improve the performance of the machine in the profiling harvesting operation in different soil surface roughness operation environment, and have wide applicability.

[0053] Note that the description of these effects does not preclude the presence of other effects. One mode of the present application does not necessarily have all of the above-mentioned effects. Effects other than the above-mentioned effects can be clearly seen and extracted from the description, drawings, claims, and the like. BRIEF DESCRIPTION OF DRAWINGS

[0054] Figure 1 is a schematic diagram of the structure of the leaf harvester cutting platform profiling adjustment device according to one mode of the present application.

[0055] Figure 2 is a schematic diagram of the structure of the harvesting component rack according to one mode of the present application.

[0056] Figure 3 is a schematic diagram of the connection relationship between the harvesting component rack and the chassis traveling component according to one mode of the present application.

[0057] Figure 4 is a schematic diagram of the leaf harvester cutting platform profiling adjustment method according to one mode of the present application.

[0058] Figure 5 is a schematic diagram of the ultrasonic sensor detection signal according to one mode of the present application, wherein Figure 5 (a) is a schematic diagram of the ultrasonic reflection wave signal of the flat ridge surface, Figure 5 (b) is a schematic diagram of the ultrasonic reflection wave signal of the rough ridge surface.

[0059] Figure 6 is a schematic diagram of the planar equation in the coordinate system of the harvesting component rack according to one mode of the present application.

[0060] Figure 7 is a schematic diagram of the ridge surface laser scanning according to one mode of the present application.

[0061] Figure 8 is a schematic diagram of the adaptive fuzzy neural network structure according to one mode of the present application.

[0062] In the figure: 1, cutting knife; 2, inclined conveying belt; 3, straw support; 4, harvesting component rack; 5, first ultrasonic sensor; 6, first lifting lug; 7, third lifting lug; 8, second lifting lug; 9, second ultrasonic sensor; 10, chassis rack; 11, third bearing; 12, first electric cylinder; 13, first bearing; 14, second electric cylinder; 15, second bearing. DETAILED DESCRIPTION

[0063] Embodiments of the present application are described in detail below with reference to the attached drawing figures, wherein the same or like component have the same or similar designations. The embodiments described below are presented by way of example to explain the present application, and are not intended to limit the present application.

[0064] In the description of the present application, it is to be understood that the orientations or positional relationships indicated by the terms "center", "longitudinal", "lateral", "length", "width", "thickness", "front", "back", "left", "right", "up", "down", "axial", "radial", "vertical", "horizontal", "inner", "outer", etc. are based on the orientations or positional relationships shown in the drawings, and are only for the purpose of facilitating the description of the present application and simplifying the description, and therefore cannot be understood as indicating or implying that the devices or elements indicated must have a particular orientation, be constructed and operated in a particular orientation, and therefore cannot be understood as limiting the present application. In addition, the terms "first", "second" are only for the purpose of description, and cannot be understood as indicating or implying relative importance or implicitly indicating the number of the technical features indicated. Therefore, the features defined as "first", "second" can explicitly or implicitly include one or more of the features. In the description of the present application, the meaning of "a plurality of" is two or more, unless otherwise explicitly specified and limited.

[0065] In the present application, unless otherwise explicitly specified and limited, the terms "mounting", "connection", "connecting", "fixing" and the like should be understood broadly, for example, can be fixed connection, can also be detachable connection, or integrally connected; can be mechanical connection, can also be electrical connection; can be directly connected, can also be indirectly connected through an intermediate medium, can be internal communication of two elements. For those skilled in the art, the specific meaning of the above terms in the present application can be understood according to the specific circumstances.

[0066] Embodiment 1

[0067] Figures 1-3 A preferred embodiment of the leaf vegetable harvester header profiling adjustment device is shown, comprising a chassis walking part, a harvesting part frame and a controller;

[0068] The harvesting part frame is arranged on the chassis walking part; the chassis walking part comprises a chassis frame 10;

[0069] The harvesting part frame is arranged on the chassis walking part; the chassis walking part comprises a chassis frame 10;

[0070] One end of the harvesting component frame 4 is connected with the front end of the chassis walking component through the first electric cylinder 12 and the second electric cylinder 14, and the other end of the harvesting component frame 4 is connected with the rear end of the chassis walking component; 1;

[0071] The first electric cylinder 12 is connected with the front end of the chassis walking component through the lug and the first bearing 13, and the second electric cylinder 14 is connected with the front end of the chassis walking component through the lug and the second bearing 15; the harvesting component frame is also connected with the rear end of the chassis walking component through the lug and the third bearing 11;

[0072] The controller is connected with the first electric cylinder 12, the second electric cylinder 14, the first ultrasonic sensor 5 and the second ultrasonic sensor 9 respectively, detects information through the first ultrasonic sensor 5 and the second ultrasonic sensor 9, and adjusts the piston rod length of the first electric cylinder 12 and the second electric cylinder 14.

[0073] According to the embodiment, preferably, the first electric cylinder 12 is a left electric cylinder, and the second electric cylinder 14 is a right electric cylinder; the first ultrasonic sensor 5 is a left ultrasonic sensor, and the second ultrasonic sensor 9 is a right ultrasonic sensor; the controller controls the left driver to adjust the piston rod length of the left electric cylinder and controls the right driver to adjust the piston rod length of the right electric cylinder through the echo signals of the left ultrasonic sensor and the right ultrasonic sensor.

[0074] According to the embodiment, preferably, the harvesting component frame 4 further comprises an inclined conveying belt 2 and a straw supporting device 3, the cutting knife 1, the inclined conveying belt 2 and the straw supporting device 3 keep relative positions fixed on the harvesting component frame 4, and constitute a cutting and conveying component.

[0075] According to the embodiment, preferably, the first bearing 13, the second bearing 15 and the third bearing 11 are fisheye bearings.

[0076] According to the embodiment, preferably, the first bearing 13 and the second bearing 15 are respectively located on both sides of the front end of the chassis walking component, and the third bearing 11 is located in the middle of the rear end of the chassis walking component.

[0077] According to the embodiment, preferably, the measurement directions of the first ultrasonic sensor 5 and the second ultrasonic sensor 9 are perpendicular to the ridge surface.

[0078] According to the embodiment, preferably, the harvesting component frame 4 is fixedly installed with a first lug 6, a second lug 8 and a third lug 7, the first lug 6, the second lug 8 and the third lug 7 are respectively connected with the first bearing 13, the second bearing 15 and the third bearing 11 through pin connections, so that the cutting and conveying component is obliquely supported on the chassis frame 10.

[0079] According to the embodiment, preferably, first displacement sensors and second displacement sensors are further included;

[0080] The first displacement sensor is used to detect the length of the piston rod of the first electric cylinder 12;

[0081] The second displacement sensor is used to detect the length of the piston rod of the second electric cylinder 14.

[0082] The controller obtains the vertical distance d of the ridge P and the roughness SSR of the ridge P according to the echo information detected by the first ultrasonic sensor 5 and the second ultrasonic sensor 9, establishes the plane equation of the harvesting component rack 4 according to the installation positions of the first ultrasonic sensor 5 and the second ultrasonic sensor 9, determines the height and attitude angle of the cutting knife 1, then establishes the relationship equation of the heights and attitude angles of the first electric cylinder 12 and the second electric cylinder 14 and the cutting knife 1, and finally adjusts the piston rod extension lengths of the first electric cylinder 12 and the second electric cylinder 14 through the cutting table attitude angle control model and the cutting table height control model, so as to adjust the height and attitude angle of the cutting knife 1.

[0083] The embodiment detects the ridge information through the ultrasonic sensors on the harvesting component rack 4, the controller can adjust the extension lengths of the electric cylinders, realizes the two-degree-of-freedom adjustment of the cutting table height and attitude angle, and completes the profiling adjustment when the cutting table harvests leaf vegetables.

[0084] Embodiment 2

[0085] As shown in Figure 4 An adjustment method of the profiling adjustment device of the cutting table of the leaf vegetable harvester according to embodiment 1, comprising the following steps:

[0086] Step S1: The controller calculates the vertical distance d of the ridge P and the roughness SSR of the ridge P according to the echo signals of the first ultrasonic sensor 5 and the second ultrasonic sensor 9;

[0087] Step S2: According to the distances of the first ultrasonic sensor 5 and the second ultrasonic sensor 9 from the ridge P detected in step S1, a coordinate system is established, and the plane equation of the harvesting component rack in the coordinate system is obtained;

[0088] As shown in Figure 6 The first ultrasonic sensor 5 and the second ultrasonic sensor 9 are fixedly installed on the harvesting component rack 4, and it is assumed that the vertical distances from the ridge measured by them are z1 and z2. In the ridge P coordinate system, according to the mutual relationship among the coordinates (x1, y1, z1) of the first ultrasonic sensor 5, the coordinates (x2, y2, z2) of the second ultrasonic sensor 9, and the coordinates (x3, y3, z3) of the third lifting lug 7, the plane equation of the harvesting component rack 4 in the ridge P coordinate system can be determined.

[0089] Step S3: According to the equation of the plane of the coordinate system obtained in step S2, the straight line equation of the axis L of the cutting knife 1 is established, the angle between the axis L and the ridge surface P, i.e. the attitude angle α, is obtained, and the vertical distance between the center position of the axis L and the ridge surface P, i.e. the cutting height H, is obtained;

[0090] Step S4: The length l1 of the piston rod of the first electric cylinder 12 and the length l2 of the piston rod of the second electric cylinder 14 are obtained, and the relationship equation between the attitude angle α and the cutting height H and the length l1 of the piston rod of the first electric cylinder 12 and the length l2 of the piston rod of the second electric cylinder 14 is established according to the attitude angle α and the cutting height H obtained in step S3;

[0091] Step S5: The cutting table attitude angle control model and the cutting table height control model are established;

[0092] Step S6: The target cutting height H0 is adjusted according to the roughness SSR of the ridge surface P obtained in step S1;

[0093] Step S7: The height adjustment amount ΔH is calculated according to the cutting table attitude angle control model and the cutting table attitude angle adjustment amount Δα is calculated according to the cutting table attitude angle fuzzy controller according to the target cutting height H0 obtained in step S6;

[0094] Step S8: The adjustment amounts of the first electric cylinder 12 and the second electric cylinder 14 are obtained through the relationship equation between the attitude angle α and the cutting height H and the length l1 of the piston rod of the first electric cylinder 12 and the length l2 of the piston rod of the second electric cylinder 14 according to the height adjustment amount ΔH and the cutting table attitude angle adjustment amount Δα obtained in step S7, and the adjustment is performed.

[0095] When the first ultrasonic sensor 5 and the second ultrasonic sensor 9 detect the vertical distance from the ridge surface P and the roughness SSR of the ridge surface P in step S1, the reflected wave peak value time interval T p , the reflected wave intensity period integral E r , the median time width T m , and the reflected wave peak value V max are extracted, respectively.

[0096] As shown in Figure 5 , the horizontal coordinate is time and the vertical coordinate is output voltage, the ultrasonic reflected wave signal of the flat ridge surface is shown in Figure 5 (a), and the ultrasonic reflected wave signal of the rough ridge surface is shown in Figure 5 (b).

[0097] At t0, the ultrasonic sensor emits an ultrasonic beam, the transmitted wave is not affected by external factors such as diffusion, attenuation, absorption, etc., therefore, the intensity of the transmitted wave is the largest, and the voltage value of the analog voltage signal output by the ultrasonic sensor is also the largest. The echo signal is the transmitted ultrasonic beam propagating through the air, being reflected by the soil and being accepted by the sensor, at t1, the ultrasonic sensor outputs a voltage signal. In this process, the sound intensity of the ultrasonic wave decreases after being absorbed by the air and reflected by the irregular surface of the soil, and the output voltage signal of the ultrasonic sensor also decreases.

[0098] Reflection wave signal feature extraction:

[0099] According to the experiments and induction analysis of the ultrasonic sensor under different installation heights and different ridge surface roughness, four characteristics of the reflection wave are extracted.

[0100] (1) Peak time interval T p :

[0101] The time length from the starting moment t0 of the transmitted wave echo signal to the moment t2 when the analog voltage of the soil reflection wave signal reaches the peak value. The ultrasonic beam has a certain emission angle, and it propagates to the soil surface as a circular area. When the output voltage of the ultrasonic sensor reaches the maximum, it indicates that the reflection wave intensity in this circular area reaches the maximum, therefore, the size of T p can be used to represent the average distance between the circular area and the ultrasonic sensor.

[0102] (2) Reflection wave intensity period integral E r :

[0103] The integral of the output voltage of the sensor with respect to time in the first period,

[0104]

[0105] where v out is the output voltage. Different ridge surface roughness has abnormal emission and scattering characteristics on the ultrasonic beam, which will cause changes in the overall reflection wave intensity, i.e., the change of E r .

[0106] (3) Median time width T m :

[0107] The median value V m of the output voltage of the ultrasonic sensor in the first period is defined as V th + V max ) / 2, V th is the minimum output voltage, and V max is the maximum output voltage, the output voltage of the ultrasonic sensor exceeds the median voltage V mThe time length is denoted as T m . The roughness of the ridge surface is different, and the ultrasonic beam will be repeatedly refracted on the ridge surface, resulting in a difference in the time of receiving the reflected wave by the ultrasonic sensor, which is manifested as a change in T m .

[0108] (4) The peak value V max of the reflected wave:

[0109] The peak value V max of the reflected wave mainly depends on two factors: one is the distance between the ultrasonic sensor and the ridge surface, and the other is the roughness of the soil surface. In the case of the same roughness of the soil surface, the greater the distance between the ultrasonic sensor and the ridge surface, the longer the propagation process of the ultrasonic wave in the air, the greater the absorption of the ultrasonic wave by the air, and the smaller the sound intensity of the ultrasonic wave, resulting in the decrease of V max . When the height of the ultrasonic sensor from the soil surface is consistent, the rougher the soil surface, the greater the randomness of the reflection direction of the ultrasonic wave, the more dispersed the sound beam reflected to the ultrasonic sensor, and the smaller the sound intensity, resulting in the decrease of V max .

[0110] When the step S1 detects the vertical distance between the first ultrasonic sensor 5 and the second ultrasonic sensor 9 and the ridge surface P, the following formula is used:

[0111] d=k·T p

[0112] wherein k is a constant coefficient related to the propagation speed of the ultrasonic wave.

[0113] When the step S1 detects the roughness SSR of the ridge surface P, the following steps are used:

[0114] Step S1.1: As shown in Figure 7 , the point cloud information of the ridge surface P is measured by a laser scanner, and the surface roughness SSR is calculated according to the following formula:

[0115]

[0116] wherein v i is the distance between the laser scanner and the measurement point, is the average distance between the laser scanner and all measurement points;

[0117] Step S1.2: Repeat step S1 to establish a surface roughness sample library SSR i .

[0118] Step S1.3: According to the ridge surface P information detected by the ultrasonic sensor, the peak time interval T p , the median time width T m , and the median time width Tm and the peak value of the reflected wave V max The sample library {T p T m T m V max} i ;

[0119] Step S1.4: Add the sample library {T} p T m T m V max} i The surface roughness sample library SSR is used as input to the adaptive fuzzy neural network. i As the output of the adaptive fuzzy neural network, the adaptive fuzzy neural network is trained until the error of the adaptive fuzzy neural network meets the set range;

[0120] like Figure 8 As shown, the adaptive fuzzy neural network consists of five layers:

[0121] The first layer: fuzzification, responsible for fuzzifying the input signal, has 12 nodes, and each node has an output function: or or

[0122] Where x i Let x1, x2, x3, and x4 be the inputs to the nodes, where i is 1, 2, 3, or 4, and x4 are the values ​​of T. p V max T m E r , is the input of the node, A i 1 A i 2 A i 3 It is a fuzzy subset. For membership function, That is A i 1 A i 2 A i 3 The membership function value indicates that x1, x2, x3, x4 belong to A. i 1 A i 2 A i 3 The degree of membership. A Gaussian function is chosen as the membership function:

[0123]

[0124] in, and These represent the center and width of the membership function, also known as the antecedent parameter, and j represents the order.

[0125] Layer 2: Rule Applicability. This layer has 12 nodes, and each node in this layer is responsible for multiplying the input signals. The output of each node in this layer... This indicates the credibility of the rule:

[0126]

[0127] Layer 3: Normalized applicability, with 12 nodes. The applicability w of the i-th rule is calculated for the i-th node. i Sum of applicability of all rules ratio Output of this layer This is called normalized fitness.

[0128]

[0129] Layer 4: Calculates the output for each rule. There are 12 nodes in total, and the i-th node has an output.

[0130]

[0131] here For the output of the third layer, p i q i u i v i r i For subsequent parameters.

[0132] Level 5: Summation, summing the outputs for each output to obtain the total output.

[0133]

[0134] Step S1.5: The time interval T between the peak reflected waves detected by the first ultrasonic sensor 5 and the second ultrasonic sensor 9 is recorded. p The periodic integral of the reflected wave intensity E r Median time width T m and the peak value of the reflected wave V max The input is fed into the trained adaptive fuzzy neural network to obtain the soil surface roughness (SSR).

[0135] The relationship between the attitude angle α and the cutting height H in step S4 and the piston rod length l1 of the first electric cylinder 12 and the piston rod length l2 of the second electric cylinder 14 is as follows:

[0136]

[0137] The posture angle control model in the step S5 is a two-dimensional fuzzy control model. In order to make the cutting knife parallel to the ridge surface and ensure the consistency of the stubble, the target posture angle a0=0 is set. The input of the posture angle control model is the cutting platform posture angle deviation E α and the cutting platform posture angle deviation change rate EC α The cutting platform posture angle deviation E α and the cutting platform posture angle deviation change rate EC α are calculated by the real-time cutting height H t , and the real-time cutting posture angle a t is calculated. Then, the real-time cutting posture angle a t is compared with the target cutting posture angle to obtain the result.

[0138] The cutting platform posture angle deviation E α has a change range including seven levels, i.e., [-45°, -10°], [-10°, -5°], [-5°, -2°], [-2°, 2°], [2°, 5°], [5°, 10°] and [10°, 45°]. The corresponding fuzzy language variables are NB (negative big), NM (negative medium), NS (negative small), ZE (zero), PS (positive small), PM (positive medium) and PB (positive big). The fuzzy control rule table of the posture angle is shown in Table 1.

[0139] Table 1 Fuzzy control rule table of posture angle

[0140]

[0141] The cutting platform posture angle deviation change rate EC α is obtained by the sampling frequency and the set E α . The cutting platform posture angle deviation change rate ECa=(cutting platform posture angle deviation Ea at the last time-cutting platform posture angle deviation Ea at this time) / sampling frequency.

[0142] The output of the posture angle control model is the cutting platform posture angle adjustment amount a.

[0143] The cutting platform height control model in the step S5 is a two-dimensional fuzzy control model. The cutting platform height target is set as H0. The input of the cutting platform height control model is the cutting platform height deviation E H and the cutting platform height deviation change rate EC H The cutting platform height deviation E H and the cutting platform height deviation change rate EC H are calculated by the real-time cutting height H t and the target cutting height H0.

[0144] The cutting platform height deviation E HThe variation range of the cutterbar height deviation E includes seven levels, namely [-H0, -0.5H0], [-0.5H0, -0.25H0], [-0.25H0, -0.1H0], [-0.1H0, 0.1H0], [0.1H0, 0.25H0], [0.25H0, H0] and [H0, 5H0]; the corresponding fuzzy language variables are NB (negative big), NM (negative medium), NS (negative small), ZE (zero), PS (positive small), PM (positive medium) and PB (positive big); the fuzzy control rule table of the cutterbar height is shown in Table 2.

[0145] Table 2 Fuzzy control rule table of cutterbar height

[0146]

[0147] The cutterbar height deviation variation rate EC H The variation range thereof is derived from the sampling frequency and the target cutting height H0; the cutterbar height deviation variation rate EC H = (cutterbar height deviation of the last time E H - cutterbar height deviation of this time E H ) / sampling frequency;

[0148] The output of the cutterbar height control model is the cutterbar posture angle adjustment amount Δα.

[0149] The average distance between the ridge surface and the ultrasonic sensor is measured by the ultrasonic sensor, since the ridge surface is uneven, the actual distance between the ridge surface and the sensor is a dynamic value, and the greater the unevenness of the ridge surface, the greater the fluctuation range of the distance. In order to avoid the shovel of the cutter, it is proposed to adjust the set cutterbar height target H0 adaptively according to the measured ridge surface smoothness SSR, and the set target cutting height H0 is adjusted by using the following formula:

[0150] H0 = H'0 + ω·SSR

[0151] Wherein, H'0 is the target cutting height before adjustment, and ω is a set coefficient, ω > 0.

[0152] After the adjustment of H0, the input parameter range of the cutterbar height fuzzy controller is also adjusted, so as to realize that in the case of small ridge surface roughness, H0 is small, the cutterbar can be finely adjusted, closely adhere to the ridge surface for harvesting operation, and the stubble height is reduced; when the ridge surface roughness is large, H0 is large, and the cutter is kept a certain distance from the ridge surface to avoid the shovel of the cutter. The harvesting performance of the whole machine is comprehensively improved in different soil surface roughness operation environments.

[0153] During actual operation, the controller acquires the analog signal output voltage of the first ultrasonic sensor 5 and the second ultrasonic sensor 9 in real time through the ADC signal acquisition module. By setting the refresh frequency of the timer to 20kHz, an interrupt is generated when the timer count overflows. In the interrupt service function, an event flag is set. When the event occurs, the event flag is set to 1, and the analog signal output voltage acquired by the ADC signal is saved to a signal array of 250 values. When the data saving is completed, the event flag is set to 0 and the system waits for the next event to occur.

[0154] like Figure 4 As shown, the controller processes the signal array, extracts signal features, calculates the ground clearance heights d1 and d2 on the left and right sides of the header and the surface roughness SSR1 and SSR2 of the ridge surface, and calculates the ground clearance height H of the header based on the transformation matrix F. t and the angle α of the cutter stand;

[0155] The controller integrates a fuzzy controller for the header height and a fuzzy control algorithm for the header attitude angle, and controls the header height H above the ground. t The inverse matrix F is obtained by taking the header attitude angle α as input and outputting the header height adjustment ΔH and header attitude angle adjustment Δα as outputs, and then performing decoupled calculations based on the dimensional parameters of the leafy vegetable harvester mechanism to obtain F. -1 Thus, the extension and retraction amounts l1 and l2 of the electric cylinders on both sides are obtained;

[0156] Based on the extension and retraction signal of the electric cylinder output by the control, the piston of the electric cylinder is extended and retracted to change the attitude angle α and cutting height H of the harvesting component frame 4 of the leafy vegetable harvester.

[0157] An interrupt is generated by the overflow of the timer count value, and the above adjustment process is repeated to achieve continuous contour adjustment.

[0158] This invention measures ridge distance and ridge roughness by analyzing complete ultrasonic reflection signals. It constructs a ridge distance measurement system using ultrasonic sensors and calculates the header height and attitude angle based on the harvester structure. Using these as input parameters, it designs fuzzy controllers for header height and attitude angle adjustment. Soil surface roughness is used as a basis for adaptive adjustment of the header height target. The extension and retraction of the two electric cylinders are determined to achieve adaptive contouring of the header's ground clearance and attitude angle. By measuring ridge distance and ridge roughness, the invention avoids the influence of random interference such as soil clod size, loose soil beds, and vegetable stubble left on measurement accuracy, as is common in non-contact measurements. This ensures the stability of measurement accuracy, improves the precision of header contouring adjustment, and ultimately improves the quality of leafy vegetable harvesting.

[0159] It should be understood that although the present specification is described in terms of various embodiments, each of which describes only one implementation, the specification is intended to cover all possible implementations that are within the scope of the application, which is defined by the claims. One skilled in the art will readily recognize from the disclosure herein, that alternative embodiments of the present application can be constructed from a number of approaches already known in the art, which do not depart from the spirit and scope of the present application. The individual features of the various embodiments of this application each will be recognized by one of ordinary skill in the art to be an innovative application that alone would entitle the applicant to a patent, but the present application is intended to cover each and every combination of the individual features disclosed herein and any other innovative feature that would be recognized by those of ordinary skill in the art to be an innovative application that alone would entitle the applicant to a patent.

[0160] The foregoing detailed description has set forth various embodiments of the devices and / or processes via the use of specific terminology. However, embodiments thereof can be practiced with the exact description not being presented in detail in this disclosure. It should be understood that various operations are described which can be implemented in one embodiment by one or more specific circuits or circuitry or by one or more processes of a computer. Thus, the broader practice of various embodiments can include computer processes and machine circuits which execute specific operations in conjunction with physical manipulations of physical quantities. The embodiments can therefore be generally described as transactional between a computer or computers and a human operator, or as a variety of input / output and processing relationships. The various embodiments described herein can

Claims

1. A contour-following adjustment device for the header of a leafy vegetable harvester, characterized in that, Includes chassis walking components, harvesting component frame (4) and controller; The harvesting component frame (4) is mounted on the chassis walking component; The harvesting component frame (4) is equipped with a cutter (1), and the bottom of the harvesting component frame (4) is equipped with a first ultrasonic sensor (5) and a second ultrasonic sensor (9). One end of the harvesting component frame (4) is connected to the front end of the chassis walking component through the first electric cylinder (12) and the second electric cylinder (14), and the other end of the harvesting component frame (4) is connected to the rear end of the chassis walking component; The controller is connected to the first electric cylinder (12), the second electric cylinder (14), the first ultrasonic sensor (5), and the second ultrasonic sensor (9) respectively. It obtains the vertical distance d of the ridge surface P and the roughness SSR of the ridge surface P through the echo information detected by the first ultrasonic sensor (5) and the second ultrasonic sensor (9), and adjusts the piston rod length of the first electric cylinder (12) and the second electric cylinder (14). The controller obtains the vertical distance d of the ridge surface P and the roughness SSR of the ridge surface P based on the echo information detected by the first ultrasonic sensor (5) and the second ultrasonic sensor (9), and establishes the planar equation of the harvesting component frame (4) based on the installation position of the first ultrasonic sensor (5) and the second ultrasonic sensor (9), thereby determining the height and attitude angle of the cutter (1). Then, it establishes the relationship equation between the height and attitude angle of the first electric cylinder (12) and the second electric cylinder (14) and the cutter (1), and uses the soil surface roughness as a basis to adaptively adjust the target height of the cutting platform. Then, it adjusts the piston rod extension length of the first electric cylinder (12) and the second electric cylinder (14) through the cutting platform attitude angle control model and the cutting platform height control model, thereby adjusting the height and attitude angle of the cutter (1).

2. A method for adjusting the profile of the header of a leafy vegetable harvester according to claim 1, characterized in that, Includes the following steps: Step S1: The controller calculates the vertical distance d of the ridge surface P and the roughness SSR of the ridge surface P based on the echo signals from the first ultrasonic sensor (5) and the second ultrasonic sensor (9). Step S2: Based on the distances between the first ultrasonic sensor (5) and the second ultrasonic sensor (9) detected in step S1 and the ridge surface P, establish a coordinate system and obtain the plane equation of the harvesting component frame in the coordinate system. Step S3: Based on the plane equation of the harvesting component frame in the coordinate system obtained in step S2, establish the straight line equation of the axis L of the cutter 1, and obtain the angle between the axis L and the ridge surface P, i.e., the attitude angle α, and the vertical distance between the center position of the axis L and the ridge surface P, i.e., the cutting height H. Step S4: Obtain the piston rod length l1 of the first electric cylinder (12) and the piston rod length l2 of the second electric cylinder (14). Based on the attitude angle α and cutting height H obtained in step S3, establish the relationship equation between the attitude angle α and cutting height H and the piston rod length l1 of the first electric cylinder (12) and the piston rod length l2 of the second electric cylinder (14). Step S5: Establish the header attitude angle control model and the header height control model; Step S6: Adjust the set target cutting height H0 according to the roughness SSR of the ridge surface P obtained in step S1. Step S7: Based on the target cutting height H0 obtained in step S6, calculate the height adjustment amount ΔH according to the header attitude angle control model, and calculate the header attitude angle adjustment amount Δα according to the header attitude angle fuzzy controller. Step S8: Based on the height adjustment amount ΔH and the cutting table attitude angle adjustment amount Δα obtained in step S7, the adjustment amount of the first electric cylinder (12) and the second electric cylinder (14) is obtained by using the relationship equation between the attitude angle α and the cutting height H and the piston rod length l1 of the first electric cylinder (12) and the piston rod length l2 of the second electric cylinder (14), and then the adjustment is performed.

3. The method for adjusting the header of a leafy vegetable harvester according to claim 2, characterized in that, In step S1, when detecting the perpendicular distance between the first ultrasonic sensor (5) and the second ultrasonic sensor (9) and the ridge surface P, and the roughness SSR of the ridge surface P, the peak time interval T of the reflected wave is extracted respectively. p The periodic integral of the reflected wave intensity E r Median time width T m and the peak value of the reflected wave V max .

4. The method for adjusting the header of a leafy vegetable harvester according to claim 3, characterized in that, When detecting the perpendicular distance between the first ultrasonic sensor (5) and the second ultrasonic sensor (9) and the ridge surface P in step S1, the following formula is used: ； Where k is a constant coefficient related to the speed of ultrasonic wave propagation.

5. The method for adjusting the header of a leafy vegetable harvester according to claim 3, characterized in that, The following steps are used in step S1 to detect the roughness SSR of the ridge surface P: Step S1.1: Measure the point cloud information of the ridge surface P using a laser scanner, and calculate the surface roughness SSR according to the following formula: ； Among them, v i The distance between the laser scanner and the measurement point. This is the average distance between the laser scanner and all measurement points; Step S1.2: Repeat step S1 to establish the surface roughness sample library SSR. i ; Step S1.3: Based on the information P on the ridge surface detected by the ultrasonic sensor, establish the peak time interval T. p Median time width T m Median time width T m and the peak value of the reflected wave V max The sample library {T p T m T m V max } i ; Step S1.4: Add the sample library {T} p T m T m V max } i The surface roughness sample library SSR is used as input to the adaptive fuzzy neural network. i As the output of the adaptive fuzzy neural network, the adaptive fuzzy neural network is trained until the error of the adaptive fuzzy neural network meets the set range; Step S1.5: The time interval T between the peak reflected waves detected by the first ultrasonic sensor (5) and the second ultrasonic sensor (9) is recorded. p The periodic integral of the reflected wave intensity E r Median time width T m and the peak value of the reflected wave V max The input is fed into the trained adaptive fuzzy neural network to obtain the soil surface roughness (SSR).

6. The method for adjusting the header of a leafy vegetable harvester according to claim 2, characterized in that, The relationship between the attitude angle α and the cutting height H in step S4 and the piston rod length l1 of the first electric cylinder (12) and the piston rod length l2 of the second electric cylinder (14) is as follows: F is the transformation matrix.

7. The method for adjusting the header of a leafy vegetable harvester according to claim 2, characterized in that, In step S5, the attitude angle control model is a two-dimensional fuzzy control model, and the input to the attitude angle control model is the cutter attitude angle deviation E. α and the rate of change of the attitude angle deviation of the cutter head EC α The cutting table attitude angle deviation E α and the rate of change of the attitude angle deviation of the cutter head EC α Based on real-time cutting height H t The real-time cutting attitude angle α is calculated. t Then, it is compared with the target cutting attitude angle to obtain the result; The cutting table attitude angle deviation E α The range of variation includes seven levels: [-45°, -10°], [-10°, -5°], [-5°, -2°], [-2°, 2°], [2°, 5°], [5°, 10°], and [10°, 45°]. The rate of change of the cutting table attitude angle deviation EC α Based on the sampling frequency and the set E α The range of variation is obtained; the rate of change of the cutting table attitude angle deviation ECa = (the cutting table attitude angle deviation Ea at the previous moment - the cutting table attitude angle deviation Ea at this moment) / sampling frequency; The output of the attitude angle control model is the attitude angle adjustment amount Δα of the cutter.

8. The method for adjusting the header of a leafy vegetable harvester according to claim 2, characterized in that, In step S5, the cutter height control model is a two-dimensional fuzzy control model, and the input to the cutter height control model is the cutter height deviation E. H and the rate of change of the header height deviation EC H The cutting table height deviation E H and the rate of change of the header height deviation EC H Based on real-time cutting height H t This is obtained by comparing it with the target cutting height H0; The cutting table height deviation E H The range of variation includes seven levels, namely [-H0, -0.5H0], [-0.5H0, -0.25H0], [-0.25H0, -0.1H0], [-0.1H0, 0.1H0], [0.1H0, 0.25H0], [0.25H0, H0] and [H0, 5H0]; The rate of change of the cutting platform height deviation EC H The variation range is derived from the sampling frequency and the target cutting height H0; the rate of change of the cutting table height deviation EC H = (Previous moment's cutter height deviation E) H -The height deviation of the cutting platform at this moment E H ) / sampling frequency; The output of the cutter height control model is the cutter attitude angle adjustment amount Δα.

9. The method for adjusting the header of a leafy vegetable harvester according to claim 2, characterized in that, In step S6, the target cutting height H0 is adjusted using the following formula: ； in, To adjust the previous target cutting height, To set coefficients, > 0.

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