阅读说明：本技术 一种基于驾驶数据的履带式联合收割机前进速度控制方法及装置 (Driving data-based crawler-type combine harvester advancing speed control method and device ) 是由 路恩 马征 唐忠 徐立章 张明燕 李颜刚 王志鹏 魏晨曦 于 2021-07-30 设计创作，主要内容包括：本发明提供了一种基于驾驶数据的履带式联合收割机前进速度控制方法及装置,该装置包括嵌入式控制系统、前进速度控制系统、前进速度检测系统、割台高度检测系统、沉陷深度检测系统、滚筒轴径向位移检测系统、前进速度预测调控模型、工控机和作物图像检测系统；履带式联合收割机在田间进行收获作业时,通过采集的驾驶数据计算与前进速度关联的作业状态数据,结合隐马尔科夫模型建立前进速度预测调控模型,预测下一个阶段履带式联合收割机需要的前进速度控制模式,通过前进速度控制系统实现履带式联合收割机前进速度的控制；本发明较好地解决了履带式联合收割机在田间收获作业时前进速度的自动调控。(The invention provides a method and a device for controlling the advancing speed of a crawler-type combine harvester based on driving data, wherein the device comprises an embedded control system, an advancing speed detection system, a header height detection system, a sinking depth detection system, a drum shaft radial displacement detection system, an advancing speed prediction regulation and control model, an industrial personal computer and a crop image detection system; when the crawler-type combine harvester performs harvesting operation in the field, the operation state data related to the advancing speed is calculated through the collected driving data, an advancing speed prediction regulation model is established by combining a hidden Markov model, an advancing speed control mode required by the crawler-type combine harvester at the next stage is predicted, and the advancing speed of the crawler-type combine harvester is controlled through an advancing speed control system; the invention better solves the problem of automatic regulation and control of the advancing speed of the crawler-type combine harvester during the field harvesting operation.)

1. The method for controlling the advancing speed of the crawler-type combine harvester based on driving data is characterized by comprising the following steps:

when the crawler-type combine harvester harvests in the field, calculating operation state data Y associated with the advancing speed through the collected driving data, establishing an advancing speed prediction regulation model by combining a hidden Markov model, predicting an advancing speed control mode required by the crawler-type combine harvester at the next stage, and realizing the control of the advancing speed of the crawler-type combine harvester through an advancing speed control system;

the work state data Y related to the forward speed is calculated by utilizing comprehensive grey correlation degree and fuzzy reasoning;

the comprehensive grey correlation degree of the forward speed is as follows:

wherein: x is the number of_h(k) Is the k characteristic value, x, of the header height_d(k) K characteristic value, x, of the depth of subsidence_s(k) The k characteristic value, x, of the radial displacement of the drum axis_p(k) The kth eigenvalue, x, of the spike-head pixel fraction_v(k) A k-th characteristic value of the forward speed, where k is 1, 2.. multidot.m, and m represents the number of characteristic values; gamma ray_h1(x_h(k)，x_v(k) Is the degree of shape similarity of header height to forward speed, gamma_d1(x_d(k)，x_v(k) Gamma) is the degree of shape similarity of the depth of subsidence to the speed of advancement_s1(x_s(k)，x_v(k) Is the gray correlation, γ, of the shape similarity of the drum axis radial displacement to the advance speed_p1(x_p(k)，x_v(k) Is the gray correlation, γ, of the shape similarity of the drum axis radial displacement to the advance speed_h2(x_h(k)，x_v(k) Grey correlation, gamma, of the distance similarity of header height to forward speed_d2(x_d(k)，x_v(k) Is the distance similarity gray correlation of the depth of subsidence to the forward speed, γ_s2(x_s(k)，x_v(k) Is the gray correlation, γ, of the distance similarity of the drum axis radial displacement to the advance speed_p2(x_p(k)，x_v(k) Is the distance similarity gray correlation of drum axis radial displacement and forward speed;

the process of acquiring the operation state data Y comprises the following steps: according to the header height, the sinking depth, the drum shaft radial displacement, the spike head pixel ratio and the respective changes, a fuzzy reasoning module is used for estimating the value of the next moment based on empirical knowledge respectively, and the value of the next moment is y_h、y_d、y_s、y_pCombining the values of the estimated next moment by utilizing the forward speed and the gray correlation degree to obtain the operation related to the forward speedState data Y:

2. a method of controlling the forward speed of a tracked combine based on driving data as claimed in claim 1, wherein said γ is a measure of the speed of the vehicle_h1(x_h(k)，x_v(k))、γ_d1(x_d(k)，x_v(k))、γ_s1(x_s(k)，x_v(k) And γ)_p1(x_p(k)，x_v(k) Satisfy:

wherein: Δ x_h(k)、Δx_d(k)、Δx_s(k)、Δx_p(k) The difference of the kth characteristic value of header height, sinking depth, drum shaft radial displacement, spike head pixel ratio and the kth characteristic value in the forward speed is respectively represented, and:

3. a method of controlling the forward speed of a tracked combine based on driving data as claimed in claim 1, wherein said γ is a measure of the speed of the vehicle_h2(x_h(k)，x_v(k))、γ_d2(x_d(k)，x_v(k))、γ_s2(x_s(k)，x_v(k) And γ)_p2(x_p(k)，x_v(k) Satisfy:

wherein:respectively represent the normalized value of the kth eigenvalue of header height, sinking depth, drum shaft radial displacement, spike head pixel ratio and the kth eigenvalue ratio in the forward speed, and:

wherein: respectively representing the ratio of the kth characteristic value of the header height, the sinking depth, the drum shaft radial displacement and the spike head pixel ratio to the kth characteristic value in the advancing speed,a maximum value of a ratio of a kth characteristic value representing a header height to a kth characteristic value in an advance speed,a minimum value of a ratio of a kth eigenvalue representing the header height to a kth eigenvalue in the forward speed,the maximum value of the ratio of the kth characteristic value representing the depth of subsidence to the kth characteristic value in the forward speed,a minimum value of a ratio of a kth characteristic value representing a depth of subsidence to a kth characteristic value in a forward speed,the maximum value of the ratio of the kth characteristic value representing the radial displacement of the drum shaft to the kth characteristic value in the forward speed,a minimum value of a ratio of a k-th characteristic value representing a radial displacement of the drum shaft to a k-th characteristic value in the forward speed,the maximum value of the ratio of the kth characteristic value representing the percentage of the ear pixels to the kth characteristic value in the advancing speed,and the minimum value of the ratio of the kth characteristic value representing the ratio of the spike head pixels to the kth characteristic value in the advancing speed.

4. A device for realizing the advancing speed control method of the crawler-type combine harvester based on the driving data according to any one of claims 1 to 3, which is characterized by comprising an embedded control system (1), an advancing speed control system (2), an advancing speed detection system (3), a header height detection system (4), a sinking depth detection system (5), a drum shaft radial displacement detection system (6), an advancing speed prediction regulation and control model (7), an industrial personal computer (8) and a crop image detection system (9); the advancing speed detection system (3), the header height detection system (4), the sinking depth detection system (5) and the drum shaft radial displacement detection system (6) send acquired data to the embedded control system (1), and the embedded control system (1) encodes the acquired data and sends the encoded data to the industrial personal computer (8); the data acquired by the crop image detection system (9) is directly sent to an industrial personal computer (8); the industrial personal computer (8) establishes an advancing speed prediction regulation and control model (7) of the crawler-type combine harvester (10) and sends the advancing speed prediction regulation and control model to the embedded control system (1), and the embedded control system (1) realizes advancing speed control of the crawler-type combine harvester (10) through the advancing speed control system (2).

5. The device according to claim 4, characterized in that the forward speed control system (2) comprises a stepping motor (2-1), a stepping motor driver (2-2), a gear (2-3), a hydraulic stepless transmission (2-4) and a sector (2-5), wherein the gear (2-3) arranged on the output shaft of the stepping motor (2-1) is meshed with the sector (2-5) rigidly connected with the operating rod (11) of the hydraulic stepless transmission (2-4); the embedded control system (1) is connected with the stepping motor driver (2-2), and the stepping motor driver (2-2) controls the stepping motor (2-1) to rotate.

6. The device according to claim 4, characterized in that the forward speed detection system (3) comprises a speed measuring radar I (3-1), a speed measuring radar II (3-2) and a frequency measuring module (3-3), wherein the speed measuring radar I (3-1) and the speed measuring radar II (3-2) are both connected with the frequency measuring module (3-3), and the frequency measuring module (3-3) is connected with the embedded control system (1).

7. The device according to claim 4, characterized in that the header height detection system (4) comprises an ultrasonic sensor I (4-1), an ultrasonic sensor II (4-2) and a conditioning circuit I (4-3), and both the ultrasonic sensor I (4-1) and the ultrasonic sensor II (4-2) are connected with the embedded control system (1) through the conditioning circuit I (4-3).

8. The device according to claim 4, characterized in that the depression depth detection system (5) comprises an ultrasonic sensor III (5-1), an ultrasonic sensor IV (5-2) and a conditioning circuit II (5-3), the ultrasonic sensor III (5-1) and the ultrasonic sensor IV (5-2) being connected with the embedded control system (1) through the conditioning circuit II (5-3).

9. The device according to claim 4, wherein the drum shaft radial displacement detection system (6) comprises an eddy current sensor I (6-1), an eddy current sensor II (6-2), a drum shaft (6-3) and a conditioning circuit III (6-4), the eddy current sensor I (6-1) and the eddy current sensor II (6-2) are respectively arranged on the central lines of the horizontal direction and the vertical direction of the drum shaft (6-3) and are connected with the embedded control system (1) through the conditioning circuit III (6-4).

Technical Field

The invention belongs to the technical field of vehicle forward speed control, and particularly relates to a method and a device for controlling the forward speed of a crawler-type combine harvester based on driving data.

Background

The crawler-type combine harvester has the advantages of small grounding pressure, large adhesive force, good trafficability and the like, has irreplaceable advantages when working in wet and rotten field blocks, and related researches on the working performance of the crawler-type combine harvester are paid more and more attention by people. The density, the moisture content, the terrain and the like of field crops can influence the change of the feeding amount of the crawler-type combine harvester, and the change of the feeding amount can influence the threshing separation performance of the threshing cylinder, so that the operation performance of the crawler-type combine harvester is influenced. In order to maintain the crawler-type combine harvester in a stable harvesting operation state, the advancing speed of the crawler-type combine harvester needs to be adjusted according to the front crop density, the roller load and the like. The current automatic control method for the advancing speed of the crawler-type combine harvester is realized based on a single control index and a modern control theory, and the improvement of the operation performance of the crawler-type combine harvester is seriously restricted in the face of the problem of insufficient adaptability of a complex field environment. The operator, familiar with the performance of the tracked combine being driven and the condition of the crop to be harvested, will empirically adjust the forward speed of the tracked combine to maintain it in a better, stable operating condition. Therefore, driving data is integrated to establish a forward speed prediction regulation model of the crawler-type combine harvester, forward speed control modes of the crawler-type combine harvester under different working conditions are determined according to the collected driving data and the forward speed prediction regulation model during field harvesting, automatic control of the forward speed of the crawler-type combine harvester is achieved, and the crawler-type combine harvester has a great improvement effect on the working performance of the crawler-type combine harvester.

Disclosure of Invention

In view of the above, the invention provides a method and a device for controlling the advancing speed of a crawler-type combine harvester based on driving data, and solves the problem of insufficient adaptability of the existing method for automatically controlling the advancing speed of the crawler-type combine harvester.

The present invention achieves the above-described object by the following technical means.

The method for controlling the advancing speed of the crawler-type combine harvester based on the driving data specifically comprises the following steps:

when the crawler-type combine harvester harvests in the field, calculating operation state data Y associated with the advancing speed through the collected driving data, establishing an advancing speed prediction regulation model by combining a hidden Markov model, predicting an advancing speed control mode required by the crawler-type combine harvester at the next stage, and realizing the control of the advancing speed of the crawler-type combine harvester through an advancing speed control system;

the work state data Y related to the forward speed is calculated by utilizing comprehensive grey correlation degree and fuzzy reasoning;

the comprehensive grey correlation degree of the forward speed is as follows:

wherein: x is the number of_h(k) Is the k characteristic value, x, of the header height_d(k) K characteristic value, x, of the depth of subsidence_s(k) The k characteristic value, x, of the radial displacement of the drum axis_p(k) The kth eigenvalue, x, of the spike-head pixel fraction_v(k) The k-th characteristic value of the forward speed, where k is 1,2, …, m and m represents the number of characteristic values; gamma ray_h1(x_h(k)，x_v(k) Is the degree of shape similarity of header height to forward speed, gamma_d1(x_d(k)，x_v(k) Gamma) is the degree of shape similarity of the depth of subsidence to the speed of advancement_s1(x_s(k)，x_v(k) Is the gray correlation, γ, of the shape similarity of the drum axis radial displacement to the advance speed_p1(x_p(k)，x_v(k) Is the gray correlation, γ, of the shape similarity of the drum axis radial displacement to the advance speed_h2(x_h(k)，x_v(k) Is prepared fromDistance similarity gray correlation, gamma, of header height to heading speed_d2(x_d(k)，x_v(k) Is the distance similarity gray correlation of the depth of subsidence to the forward speed, γ_s2(x_s(k)，x_v(k) Is the gray correlation, γ, of the distance similarity of the drum axis radial displacement to the advance speed_p1(x_p(k)，x_v(k) Is the distance similarity gray correlation of drum axis radial displacement and forward speed;

the process of acquiring the operation state data Y comprises the following steps: according to the header height, the sinking depth, the drum shaft radial displacement, the spike head pixel ratio and the respective changes, a fuzzy reasoning module is used for estimating the value at the next moment to be y respectively based on empirical knowledge_h、y_d、y_s、y_pAnd combining the numerical values of the estimated next moment by utilizing the forward speed comprehensive gray correlation degree to obtain the operation state data Y related to the forward speed:

further, γ is_h1(x_h(k)，x_v(k))、γ_d1(x_d(k)，x_v(k))、γ_s1(x_s(k)，x_v(k) And γ)_p1(x_p(k)，x_v(k) Satisfy:

wherein: Δ x_h(k)、Δx_d(k)、Δx_s(k)、Δx_p(k) The difference of the kth characteristic value of header height, sinking depth, drum shaft radial displacement, spike head pixel ratio and the kth characteristic value in the forward speed is respectively represented, and:

further, γ is_h2(x_h(k)，x_v(k))、γ_d2(x_d(k)，x_v(k))、γ_s2(x_s(k)，x_v(k) And γ)_p2(x_p(k)，x_v(k) Satisfy:

wherein:respectively represent the normalized value of the kth eigenvalue of header height, sinking depth, drum shaft radial displacement, spike head pixel ratio and the kth eigenvalue ratio in the forward speed, and:

wherein: respectively representing the ratio of the kth characteristic value of the header height, the sinking depth, the drum shaft radial displacement and the spike head pixel ratio to the kth characteristic value in the advancing speed,a maximum value of a ratio of a kth characteristic value representing a header height to a kth characteristic value in an advance speed,a minimum value of a ratio of a kth eigenvalue representing the header height to a kth eigenvalue in the forward speed,indicating depth of subsidenceThe maximum value of the ratio of the kth characteristic value of the degree to the kth characteristic value in the forward speed,a minimum value of a ratio of a kth characteristic value representing a depth of subsidence to a kth characteristic value in a forward speed,the maximum value of the ratio of the kth characteristic value representing the radial displacement of the drum shaft to the kth characteristic value in the forward speed,a minimum value of a ratio of a k-th characteristic value representing a radial displacement of the drum shaft to a k-th characteristic value in the forward speed,the maximum value of the ratio of the kth characteristic value representing the percentage of the ear pixels to the kth characteristic value in the advancing speed,and the minimum value of the ratio of the kth characteristic value representing the ratio of the spike head pixels to the kth characteristic value in the advancing speed.

A crawler-type combine harvester advancing speed control device based on driving data comprises an embedded control system, an advancing speed detection system, a header height detection system, a sinking depth detection system, a drum shaft radial displacement detection system, an advancing speed prediction regulation and control model, an industrial personal computer and a crop image detection system; the advancing speed detection system, the header height detection system, the sinking depth detection system and the drum shaft radial displacement detection system send acquired data to the embedded control system, and the embedded control system encodes the acquired data and sends the encoded data to the industrial personal computer; the data acquired by the crop image detection system is directly sent to an industrial personal computer; the industrial personal computer establishes an advancing speed prediction regulation model of the crawler-type combine harvester and sends the advancing speed prediction regulation model to the embedded control system, and the embedded control system realizes advancing speed control of the crawler-type combine harvester through the advancing speed control system.

In the above technical solution, the forward speed control system comprises a stepping motor, a stepping motor driver, a gear, a hydraulic stepless transmission and a sector, wherein the gear mounted on an output shaft of the stepping motor is meshed with the sector rigidly connected to an upper operating lever of the hydraulic stepless transmission; the embedded control system is connected with a stepping motor driver, and the stepping motor driver controls the stepping motor to rotate.

In the technical scheme, the advancing speed detection system comprises a speed measuring radar I, a speed measuring radar II and a frequency measuring module, wherein the speed measuring radar I and the speed measuring radar II are both connected with the frequency measuring module, and the frequency measuring module is connected with the embedded control system.

In the technical scheme, the header height detection system comprises an ultrasonic sensor I, an ultrasonic sensor II and a conditioning circuit I, wherein the ultrasonic sensor I and the ultrasonic sensor II are connected with the embedded control system through the conditioning circuit I.

In the technical scheme, the subsidence depth detection system comprises an ultrasonic sensor III, an ultrasonic sensor IV and a conditioning circuit II, wherein the ultrasonic sensor III and the ultrasonic sensor IV are connected with the embedded control system through the conditioning circuit II.

In the technical scheme, the drum shaft radial displacement detection system comprises an eddy current sensor I, an eddy current sensor II, a drum shaft and a conditioning circuit III, wherein the eddy current sensor I and the eddy current sensor II are respectively arranged on the central line of the drum shaft in the horizontal direction and the central line of the drum shaft in the vertical direction and are connected with the embedded control system through the conditioning circuit III.

The invention has the beneficial effects that: the method comprises the steps of collecting driving data of the crawler-type combine harvester, carrying out normalization processing, establishing a comprehensive grey correlation degree of the header height, the sinking depth, the drum shaft radial displacement, the spike head pixel ratio and the advancing speed of the normalized data, estimating the operation state data of the crawler-type combine harvester by combining fuzzy control, establishing an advancing speed prediction regulation model based on a hidden Markov model, and realizing the control of the advancing speed of the crawler-type combine harvester; the invention has the advantages of strong environment adaptability, high reliability, good stability and the like.

Drawings

FIG. 1 is a schematic structural diagram of a device for controlling the forward speed of a crawler-type combine harvester based on driving data, which is disclosed by the invention;

FIG. 2 is a schematic diagram of a forward speed control system according to the present invention;

FIG. 3 is a schematic diagram of a forward speed detection system according to the present invention;

fig. 4 is a schematic structural diagram of a header height detection system according to the present invention;

FIG. 5 is a schematic structural view of a system for detecting a depth of a depression according to the present invention;

FIG. 6(a) is a schematic top view of a tracked combine of the present invention;

FIG. 6(b) is a diagrammatic side view of a tracked combine of the present invention;

FIG. 7 is a schematic view of the drum shaft radial displacement detection system according to the present invention;

FIG. 8 is a schematic view of the installation of the crop image inspection system of the present invention;

FIG. 9 is a flow chart of the forward speed integrated gray correlation establishment described in this disclosure;

FIG. 10 is a flow chart of the forward speed predictive control model building of the present invention;

FIG. 11 is a flow chart of forward speed control according to the present invention;

in the figure: 1-an embedded control system, 2-an advancing speed control system, 3-an advancing speed detection system, 4-a header height detection system, 5-a sinking depth detection system, 6-a drum shaft radial displacement detection system, 7-an advancing speed prediction regulation and control model, 8-an industrial personal computer, 9-a crop image detection system, 10-a crawler-type combine harvester, 11-a control lever, 2-1-a stepping motor, 2-2-a stepping motor driver, 2-3-a gear, 2-4-a hydraulic stepless speed changer, 2-5-a sector, 3-1-a speed measuring radar I, 3-2-a speed measuring radar II, 3-3-a frequency measuring module and 3-4-a power supply module, 4-1-ultrasonic sensor I, 4-2-ultrasonic sensor II, 4-3-conditioning circuit I, 5-1-ultrasonic sensor III, 5-2-ultrasonic sensor IV, 5-3-conditioning circuit II, 6-1-eddy current sensor I, 6-2-eddy current sensor II, 6-3-roller shaft, 6-4-conditioning circuit III and 9-1-monocular camera.

Detailed Description

The invention will be further described with reference to the following figures and specific examples, but the scope of the invention is not limited thereto.

As shown in fig. 1, a crawler-type combine harvester advancing speed control device based on driving data comprises an embedded control system 1, an advancing speed control system 2, an advancing speed detection system 3, a header height detection system 4, a sinking depth detection system 5, a drum shaft radial displacement detection system 6, an advancing speed prediction regulation and control model 7, an industrial personal computer 8 and a crop image detection system 9; the advancing speed detection system 3, the header height detection system 4, the sinking depth detection system 5 and the drum shaft radial displacement detection system 6 send acquired data to the embedded control system 1, and the embedded control system 1 encodes the acquired data and sends the encoded data to the industrial personal computer 8 in a unified manner; the data of the crop image detection system 9 is directly sent to the industrial personal computer 8; the industrial personal computer 8 establishes an advancing speed prediction regulation and control model 7 of the crawler-type combine harvester 10 and sends the advancing speed prediction regulation and control model to the embedded control system 1, and the embedded control system 1 realizes advancing speed control of the crawler-type combine harvester 10 through the advancing speed control system 2.

As shown in fig. 2, the forward speed control system 2 comprises a stepping motor 2-1, a stepping motor driver 2-2, a gear 2-3, a hydraulic stepless transmission 2-4 and a sector 2-5, wherein the gear 2-3 arranged on an output shaft of the stepping motor 2-1 is meshed with the sector 2-5 rigidly connected with a control lever 11 on the hydraulic stepless transmission 2-4; the embedded control system 1 is connected with a stepping motor driver 2-2 through a universal I/O port, the stepping motor driver 2-2 controls the stepping motor 2-1 to rotate, the operating rod 11 is driven to rotate, and the forward speed of the crawler-type combine harvester 11 is adjusted, so that the forward speed of the crawler-type combine harvester 10 can be controlled by controlling the rotating angle of the stepping motor 2-1.

As shown in figure 3, the forward speed detection system 3 comprises a speed measuring radar I3-1, a speed measuring radar II 3-2, a frequency measuring module 3-3 and a power supply module II 3-4, the speed measuring radar I3-1, the speed measuring radar II 3-2 and the frequency measuring module 3-3 are respectively connected with the power supply module 3-4, the speed measuring radar I3-1 and the speed measuring radar II 3-2 are both connected with the frequency measuring module 3-3, and the frequency measuring module 3-3 is connected with the embedded control system 1 through CAN communication.

As shown in figure 4, the header height detection system 4 comprises an ultrasonic sensor I4-1, an ultrasonic sensor II 4-2 and a conditioning circuit I4-3, wherein the ultrasonic sensor I4-1 and the ultrasonic sensor II 4-2 are connected with the embedded control system 1 through the conditioning circuit I4-3.

As shown in FIG. 5, the subsidence depth detection system 5 comprises an ultrasonic sensor III 5-1, an ultrasonic sensor IV 5-2 and a conditioning circuit II 5-3, wherein the ultrasonic sensor III 5-1 and the ultrasonic sensor IV 5-2 are connected with the embedded control system 1 through the conditioning circuit II 5-3.

The tracked combine harvester 10 has many disturbances during the harvesting operation, such as crop straw, weeds, etc., which affect the accuracy of the ultrasonic sensors in the header height detection system 4 and the sinking depth detection system 5. According to the ultrasonic propagation theory, when the size of the obstacle is smaller than 1/2 of the ultrasonic wavelength, diffraction of the ultrasonic wave occurs, and when the size of the obstacle is larger than 1/2 of the ultrasonic wavelength, reflection occurs. Assuming that the maximum value of the diameter of the crop straw to be harvested is a, the wavelength lambda of the ultrasonic wave needs to satisfy lambda <2a, and according to a relation formula of frequency and wavelength:

f＝v/λ (1)

in the formula: f is the ultrasonic frequency, v is the sound propagation speed in the air;

since λ <2a, the center frequencies of the selected ultrasonic sensor I4-1, ultrasonic sensor II 4-2, ultrasonic sensor III 5-1 and ultrasonic sensor IV 5-2 should be greater than v/2 a.

As shown in fig. 6(a) and (b), a speed measuring radar I3-1 is installed at the lower right of the tail of the crawler-type combine harvester 11, a speed measuring radar II 3-2 is installed at the lower left of the tail of the crawler-type combine harvester 11, the speed measuring radar I3-1 detects the speed at the left side of the crawler-type combine harvester 10, the speed measuring radar II 3-2 detects the speed at the right side of the crawler-type combine harvester 10, and the running speed of the crawler-type combine harvester 10 is equal to half of the sum of two detection values; the ultrasonic sensor I4-1 is arranged at the right lower part of a cutting table of the crawler-type combine harvester 11, the ultrasonic sensor II 4-2 is arranged at the left lower part of the cutting table of the crawler-type combine harvester 11, the ultrasonic sensor I4-1 detects the height from the left side of the cutting table of the crawler-type combine harvester 10 to the ground, the ultrasonic sensor II 4-2 detects the height from the right side of the cutting table of the crawler-type combine harvester 10 to the ground, and the height of the cutting table of the crawler-type combine harvester 10 is equal to half of the sum of two detection values; the ultrasonic sensor III 5-1 is arranged at the right lower part of the front part of the chassis of the crawler-type combine harvester 11, the ultrasonic sensor III 5-2 is arranged at the left lower part of the front part of the chassis of the crawler-type combine harvester 11, the ultrasonic sensor III 5-1 detects the sinking depth of a left side crawler of the crawler-type combine harvester 10, the ultrasonic sensor IV 5-2 detects the sinking depth of a right side crawler of the crawler-type combine harvester 10, and the sinking depth of the crawler-type combine harvester 10 is equal to half of the sum of two detection values.

The eddy current sensor is used for detecting the radial displacement of the roller shaft, and the change of the radial displacement of the roller shaft can reflect the load condition of the roller. As shown in fig. 7, the drum shaft radial displacement detection system 6 includes an eddy current sensor i 6-1, an eddy current sensor ii 6-2, a drum shaft 6-3, and a conditioning circuit iii 6-4, wherein the eddy current sensor i 6-1 and the eddy current sensor ii 6-2 are respectively installed on the central line of the drum shaft 6-3 in the horizontal direction and the vertical direction, and are connected with the embedded control system 1 through the conditioning circuit iii 6-4; the distances from the installation positions of the eddy current sensor I6-1 and the eddy current sensor II 6-2 to the end face of the roller shaft 6-3 are detected, the detection values in the vertical direction and the horizontal direction under the static condition are a and b respectively, the detection values in the vertical direction and the horizontal direction of the crawler-type combine harvester 10 during harvesting operation are a 'and b' respectively, and the radial displacement d of the roller shaft of the crawler-type combine harvester can be calculated by the following formula:

d＝|a′-a|+|b′-b| (2)

as shown in fig. 8, the crop image detection system 9 adopts a monocular camera 9-1, and the monocular camera 9-1 is installed in front of the advancing direction of the crawler-type combine harvester 11 and above the crawler-type combine harvester 10; the monocular camera 9-1 collects images of crops in front of the crawler-type combine harvester 11 and transmits the images to the industrial personal computer 8 through the net opening.

As shown in fig. 9, the industrial personal computer 8 identifies the heading in the image of the crop to be harvested through an edge detection algorithm, and further calculates the proportion of the heading pixels in the image to the total pixels, wherein the heading pixel proportion reflects the density of the crop to be harvested in front of the crawler-type combine harvester 10. And then, judging the similarity degree of the header height, the sinking depth, the drum shaft radial displacement and the header pixel ratio data change and the advancing speed change data sequence by a grey correlation analysis method. The method specifically comprises the following steps:

firstly, normalization processing is carried out on the header height, the sinking depth, the drum shaft radial displacement, the spike head pixel ratio and the advancing speed by adopting a (0,1) normalization method, the maximum value and the minimum value in each line of data are recorded and are used as base numbers, and the normalization processing formula is as follows:assuming that the header height, sinking depth, drum shaft radial displacement, spike head pixel ratio and advancing speed data characteristic vectors after normalization processing are respectively as follows: x_H＝[x_h(1),x_h(2),…x_h(k),…x_h(m)]、X_D＝[x_d(1),x_d(2),…x_d(k),…x_d(m)]、X_S＝[x_s(1),x_s(2),…x_s(k),…x_s(m)]、X_P＝[x_p(1),x_p(2),…x_p(k),…x_p(m)]、X_V＝[x_v(1),x_v(2),…x_v(k),…x_v(m)]Where m denotes the dimensionality of the data and k is 1,2, …, m.

Secondly, calculating the difference value of the kth characteristic value according to the header height, the sinking depth, the radial displacement of the roller shaft, the spike head pixel ratio and the normalized data of the advancing speed:

in the formula: Δ x_h(k)、Δx_d(k)、Δx_s(k)、Δx_p(k) And the difference values of the kth characteristic value of the header height, the sinking depth, the drum shaft radial displacement and the spike head pixel ratio and the kth characteristic value of the advancing speed are respectively expressed.

The difference in the kth eigenvalue in the normalized data, the header height, the depth of subsidence, the drum axis radial displacement, the percentage of spike pixels, and the degree of shape similarity gray correlation with the forward speed may be expressed as follows:

then, calculating the ratio of the kth characteristic value according to the header height, the sinking depth, the radial displacement of the roller shaft, the spike head pixel ratio and the normalized data of the advancing speed:

in the formula:respectively representing the ratio of the kth characteristic value of the header height, the sinking depth, the drum shaft radial displacement and the spike head pixel ratio to the kth characteristic value of the advancing speed; normalizing the ratio data by adopting a (0,1) normalization method, recording the maximum value and the minimum value of the ratio, and taking the maximum value and the minimum value as a base number, then:

wherein:k-th characteristic value and advancing speed representing header heightThe maximum value of the k-th eigenvalue ratio,a minimum value of a ratio of a kth eigenvalue representing the header height to a kth eigenvalue in the forward speed,the maximum value of the ratio of the kth characteristic value representing the depth of subsidence to the kth characteristic value in the forward speed,a minimum value of a ratio of a kth characteristic value representing a depth of subsidence to a kth characteristic value in a forward speed,the maximum value of the ratio of the kth characteristic value representing the radial displacement of the drum shaft to the kth characteristic value in the forward speed,a minimum value of a ratio of a k-th characteristic value representing a radial displacement of the drum shaft to a k-th characteristic value in the forward speed,the maximum value of the ratio of the kth characteristic value representing the percentage of the ear pixels to the kth characteristic value in the advancing speed,and the minimum value of the ratio of the kth characteristic value representing the ratio of the spike head pixels to the kth characteristic value in the advancing speed.

The header height, the depth of subsidence, the drum shaft radial displacement, the distance similarity gray correlation of the spike pixel fraction to the forward speed may be expressed as follows:

and finally, calculating the comprehensive grey correlation degree of the header height, the sinking depth, the drum shaft radial displacement, the spike head pixel ratio and the advancing speed:

as shown in fig. 10, in the process of field operation, the crawler-type combine harvester 10 collects images of crops to be harvested in front, the industrial personal computer 8 identifies the spike heads in the images through an edge detection algorithm, and calculates the spike head pixel ratio and the spike head pixel ratio change; according to the height of the header, the sinking depth, the radial displacement of the roller shaft, the percentage of the spike head pixels and the change of the spike head pixels, a fuzzy reasoning module is used for estimating values (including the height of the header, the sinking depth, the radial displacement of the roller shaft and the percentage of the spike head pixels) at the next moment based on empirical knowledge respectively, and the values are y_h、y_d、y_s、y_p(ii) a Combining the values of the estimated next moment by using the comprehensive grey correlation degree of the advancing speed to obtain the working state data Y of the crawler-type combine harvester 10 related to the advancing speed, wherein the working state data Y is as follows:

based on the operation state data Y of the crawler-type combine harvester 10, a forward speed prediction regulation and control model 7 is established by utilizing a hidden Markov model, and an observation sequence of the hidden Markov model is the operation state data Y. In the hidden markov forward speed predictive control model λ ═ (N, M, pi, a, B), N represents the number of hidden states of the forward speed of the tracked combine 10, and can be set as necessary, for example: dividing the forward speed mode into 5, and then, N is 5; m represents the number of job status data associated with the forward speed, which may be set as desired, for example: dividing observation data of the hidden Markov model into 5 states, wherein M is 5; pi represents an initial probability distribution; a ═ a_ij]_N×MRepresenting a state transition probability matrix, i.e. a transition matrix of the crawler combine forward speed mode, wherein a_ij＝P(Z_j|Z_i) The hidden Markov model state at the time t-1 is represented as Z_iAt time t, the state is transferred to Z_jThe probability of (d); b ═ B_j(i)]_M×NProbability matrix representing job status data, wherein b_j(i) Is shown in state Z_iUnder the condition of the appearance of the observation sequence Y_jThe probability of (c).

As shown in fig. 11, when the crawler-type combine harvester 10 performs harvesting operation in the field, the operation state data Y associated with the current forward speed is calculated according to the collected driving data, and the built forward speed prediction regulation model 7 is combined to predict the hidden state variable value Z corresponding to the operation state data Y by using a Viterbi (Viterbi) algorithm, that is, the forward speed control mode required by the crawler-type combine harvester 10 at the next stage is predicted, so that the embedded control system 1 controls the rotation of the stepping motor 2-1 through the stepping motor driver 2-2 in the forward speed control system 2, and drives the joystick 11 to rotate to realize the control of the forward speed of the crawler-type combine harvester 10.

The present invention is not limited to the above-described embodiments, and any obvious improvements, substitutions or modifications can be made by those skilled in the art without departing from the spirit of the present invention.