Method for controlling tensioning degree of crawler belt of crawler-type combine harvester for soil compaction and reduction

Abstract

The invention discloses a crawler belt tensity control method of a crawler belt type combined harvester for soil compaction and reduction, belongs to the field of agricultural machinery control, and aims to solve the problem that the existing control on the soil compaction degree lacks self-adaptability and flexibility. The method comprises the following steps that 1, the current soil compaction degree is obtained based on monitoring data of a soil compaction monitoring sensor group; 2, according to the error, obtained in the step 1, between the current soil compaction degree and the target soil compaction degree, the crawler belt tension degree adjustment amount is obtained through a PID control algorithm; and step 3, the actuator adjusts the crawler belt in a stepping mode according to the crawler belt tensity adjustment amount obtained in the step 2 until the crawler belt tensity target value is reached.

Description

Technical Field

[0001] The invention relates to a crawler tension control method of a crawler type combine harvester for reducing soil compaction, and belongs to the field of agricultural machinery control. Background Art

[0002] With the advancement of agricultural mechanization, crawler harvesters are increasingly used in agricultural production. Crawler machinery has strong traction and stability, but due to its own weight and track tension, this type of equipment often compacts the soil during operation. This soil compaction phenomenon not only reduces the permeability and air permeability of the soil, but also affects the growth of plant roots, thereby reducing the yield and quality of crops.

[0003] Existing technologies mainly reduce soil compaction problems by fixing track tension, but this method does not fully consider the dynamic changes of soil and external environmental factors. For example, soil moisture, compressive strength, soil type, etc. will affect the degree of compaction, and traditional track tension control methods often cannot adapt to these changes in real time, resulting in over-compaction or under-compaction.

[0004] Therefore, there is an urgent need for an intelligent control system that can dynamically adjust the tension of the combine harvester track according to soil compaction characteristics (such as compaction strength, moisture, load, etc.). Such a system can not only reduce the harm of soil compaction, but also improve the efficiency of mechanical operations, ensure the health of the soil, and thus promote sustainable agricultural production.

[0005] At present, although some advanced soil monitoring systems can monitor the compaction degree of soil in real time, most systems still use traditional fixed control methods, which lack adaptability and flexibility. How to accurately adjust the track tension according to multiple factors such as the real-time state of the soil, the working environment of the machine, and the track load is still a major technical challenge. Summary of the invention

[0006] In view of the problem that the existing control of soil compaction degree lacks adaptability and flexibility, the present invention provides a crawler tension control method for a crawler type combine harvester for reducing soil compaction.

[0007] The crawler tension control method of a crawler-type combine harvester for reducing soil compaction according to the present invention comprises the following steps:

[0008] Step 1: obtaining the current soil compaction degree based on the monitoring data of the soil compaction monitoring sensor group;

[0009] Step 2: according to the error between the current soil compaction degree and the target soil compaction degree obtained in step 1, the track tension adjustment amount is obtained by using the PID control algorithm;

[0010] Step 3: The actuator adjusts the track in a step-by-step manner according to the track tension adjustment amount obtained in step 2 until the track tension target value is reached.

[0011] Preferably, the process of obtaining the current soil compaction degree p(t) in step 1 is:

[0012] Step 11, the soil compaction monitoring sensor group monitors the original data of soil moisture w′(t), deadweight f′(t), steering ratio time z′(t) and track speed v′(t);

[0013] Step 12: standardize the monitoring data obtained in step 11 to obtain dimensionless data w(t), f(t), z(t), and v(t);

[0014] The standardization formula is:

[0015] Where X'(t) is the original data, X'(t) refers to the soil moisture content w'(t), deadweight f'(t), steering time z'(t) or track speed v'(t);

[0016] X(t) is dimensionless data, X(t) refers to w(t), f(t), z(t) or v(t);

[0017] μ(t) is the mean of X'(t);

[0018] σ(t) is the standard deviation;

[0019] Step 13: Calculate the current soil compaction degree p(t) according to the following formula:

[0020]

[0021] Where, α1, α2, α3, α4, α5 are soil type correlation coefficients;

[0022] s(t) is the quantitative index of soil type. Soil types include sandy soil, clay soil and loam. The quantitative index of sandy soil is 0.2, the quantitative index of clay soil is 0.3, and the quantitative index of loam is 0.5.

[0023] β1, β2, β3, and β4 are the influence indexes of each factor.

[0024] Preferably, the process of obtaining the track tension adjustment amount in step 2 is:

[0025] Step 21: Obtain the current soil compaction degree p(t) and the target soil compaction degree p according to step 1. m The error c(t) of (t) is:

[0026] c(t)=p m (t)-p(t)

[0027] Step 22: Based on the error c(t), use the PID control algorithm to obtain the track tension adjustment u(t):

[0028]

[0029] Among them, K p (t), K i (t), K d (t) are proportional gain, integral gain, and differential gain respectively, Δt is the integration time, and Δt is set to 1 second.

[0030] Preferably, in step 3, the actuator performs stepwise adjustment on the tension of the crawler belt according to the following formula:

[0031] b m (t) = b(t) + u(t)·φ(t)·Δt

[0032] Where b(t) is the current track tension, b m (t) is the target value of track tension;

[0033] φ(t) is the dynamic adjustment factor,

[0034] Where k(t) is soil compression resistance, k(t)=χ0·(1-w(t))+χ1·s(t), χ0,χ1 are the coefficients of soil moisture content and soil type on compression resistance; δ1 represents the adjustment rate coefficient related to soil compression resistance.

[0035] Preferably, the track tension adjustment amount u(t) is limited to [u min ,u max ] range, u min ,u max They are the lower and upper limits of the track tension adjustment respectively.

[0036] Preferably, the track tension target value b m (t) is limited to [b min ,b max ] range, [b min ,b max ] are the lower and upper limits of the track tension target value respectively.

[0037] Preferably, the method further comprises step 4, performing adaptive learning through the historical data obtained from steps 1 to 3 to continuously optimize the PID parameters.

[0038] Preferably, adaptive learning is performed as follows:

[0039] K p ′(t)=K p (t)+ε1·c(t)

[0040]

[0041] In the formula, K p ′(t), K i ′(t), K d '(t) is the optimized proportional gain, integral gain and differential gain;

[0042] ε1, ε2, and ε3 are the learning rates of the adaptive learning of proportional gain, integral gain, and differential gain, respectively.

[0043] Beneficial effects of the present invention:

[0044] The present invention provides a track tension adjustment system and method based on adaptive PID control, which can accurately adjust the track tension according to the changes in soil compaction characteristics and dynamic feedback during mechanical operation, thereby reducing the negative impact of soil compaction. Compared with the prior art, the present invention has significant advantages in many aspects, especially in soil protection, operation efficiency, system intelligence and adaptability, and has broad application prospects and significant social and economic benefits.

[0045] The core innovation of the present invention lies in its adaptive PID control system, which can dynamically adjust the track tension in real time according to the soil's compaction strength, humidity, compression resistance, track load and other characteristics. Through real-time monitoring and analysis of soil compaction characteristics, the system can determine whether the track tension needs to be adjusted, avoiding the problem of excessive or insufficient track tension in traditional methods. Through adaptive learning and feedback mechanisms, the system can not only accurately control the track tension, but also automatically optimize the control strategy according to the real-time changes of the soil and operating conditions, thereby effectively avoiding the negative effects of soil compaction, such as soil structure damage, root growth stunting and reduced water retention capacity.

[0046] The present invention can not only effectively protect the soil, but also improve the operating efficiency of agricultural machinery. In traditional mechanical operations, the track tension is often fixed, which may lead to low operating efficiency and even unnecessary compaction of the soil. Through adaptive PID control, the present invention can adjust the track tension according to real-time feedback to ensure that the machinery always maintains the best working state under different soil conditions, thereby improving operating efficiency and reducing unnecessary energy consumption and operating time. The system can automatically adjust the track tension according to multiple factors such as soil moisture, compression resistance, and compaction degree, avoiding low working efficiency caused by excessive or insufficient track tension, and significantly reducing operating costs.

[0047] The adaptive PID control system of the present invention not only dynamically adjusts the track tension according to the real-time state of the soil and the operating conditions, but also continuously optimizes the gain parameters of the PID controller through historical data analysis and adaptive learning. Through the system real-time monitoring and analysis of soil changes, the parameters of the PID controller (will be intelligently adjusted according to factors such as soil type, humidity, and compaction strength, thereby maintaining the best control effect of the system. This adaptive learning mechanism ensures that the system can continuously optimize the control strategy as the operating environment changes, and improve the response speed and stability of the system.

[0048] In order to avoid system instability caused by over-adjustment, the present invention introduces an over-adjustment suppression mechanism and a track tension limiting mechanism. By setting the error threshold and the adjustment limit range, the system can automatically stop adjustment when the error is small, preventing mechanical vibration or damage caused by too frequent adjustments. The limiting mechanism ensures that the track tension is always within a reasonable range, avoiding mechanical damage caused by over-tensioning or loosening, and ensuring the long-term stable operation of agricultural machinery. BRIEF DESCRIPTION OF THE DRAWINGS

[0049] Figure 1 is a flow chart of a method for controlling track tension of a tracked combine harvester for reducing soil compaction according to the present invention;

[0050] Figure 2 It is a schematic diagram of the track tension control structure of a combine harvester;

[0051] Figure 3 It is the schematic diagram of the tension adjustment mechanism.

[0052] Figure numerals: 1-driving wheel, 2-track, 3-track tension adjustment mechanism, 4-tensioning wheel, 5-track support wheel, 6-road wheel. DETAILED DESCRIPTION

[0053] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0054] It should be noted that, in the absence of conflict, the embodiments of the present invention and the features in the embodiments may be combined with each other.

[0055] The present invention will be further described below in conjunction with the accompanying drawings and specific embodiments, but they are not intended to limit the present invention.

[0056] Specific implementation method 1: The following is combined Figures 1 to 3The present embodiment is described. The method for controlling the track tension of a crawler-type combine harvester for reducing soil compaction in the present embodiment comprises the following steps:

[0057] Step 1: obtaining the current soil compaction degree based on the monitoring data of the soil compaction monitoring sensor group;

[0058] Step 2: according to the error between the current soil compaction degree and the target soil compaction degree obtained in step 1, the track tension adjustment amount is obtained by using the PID control algorithm;

[0059] Step 3: The actuator adjusts the track in a step-by-step manner according to the track tension adjustment amount obtained in step 2 until the track tension target value is reached.

[0060] The process of obtaining the current soil compaction degree p(t) in step 1 is:

[0061] Step 11, the soil compaction monitoring sensor group monitors the original data of soil moisture w′(t), deadweight f′(t), steering ratio time z′(t) and track speed v′(t);

[0062] Step 12: standardize the monitoring data obtained in step 11 to obtain dimensionless data w(t), f(t), z(t), and v(t);

[0063] The standardization formula is:

[0064] Where X'(t) is the original data, X'(t) refers to the soil moisture content w'(t), deadweight f'(t), steering time z'(t) or track speed v'(t);

[0065] X(t) is dimensionless data, X(t) refers to w(t), f(t), z(t) or v(t);

[0066] μ(t) is the mean of X'(t);

[0067] σ(t) is the standard deviation;

[0068] Step 13: Calculate the current soil compaction degree p(t) according to the following formula:

[0069]

[0070] Where, α1, α2, α3, α4, α5 are soil type correlation coefficients;

[0071] s(t) is the quantitative index of soil type. Soil types include sandy soil, clay soil and loam. The quantitative index of sandy soil is 0.2, the quantitative index of clay soil is 0.3, and the quantitative index of loam is 0.5.

[0072] β1, β2, β3, and β4 are the influence indexes of each factor.

[0073] The process of obtaining the track tension adjustment amount in step 2 is as follows:

[0074] Step 21: Obtain the current soil compaction degree p(t) and the target soil compaction degree p according to step 1. m The error c(t) of (t) is:

[0075] c(t)=p m (t)-p(t)

[0076] Step 22: Based on the error c(t), use the PID control algorithm to obtain the track tension adjustment u(t):

[0077]

[0078] Among them, K p (t), K i (t), K d (t) are proportional gain, integral gain, and differential gain respectively, Δt is the integration time, and Δt is set to 1 second.

[0079] Track tension adjustment u(t) is limited to [u min ,u max ] range, u min ,u max They are the lower and upper limits of the track tension adjustment respectively.

[0080] The track tension adjustment u(t) must be limited within a certain range to avoid excessive or insufficient track tension, which may lead to mechanical damage or over-compaction. The formula for the limiting mechanism is:

[0081] u(t)=u(t) min ≤u(t)≤u max

[0082] u(t)=u max u(t)>u max

[0083] u(t)=u min u(t)<u max

[0084] In step 3, the actuator adjusts the tension of the track in steps according to the following formula:

[0085] b m (t) = b(t) + u(t)·φ(t)·Δt

[0086] Where b(t) is the current track tension, b m (t) is the target value of track tension;

[0087] φ(t) is the dynamic adjustment factor,

[0088] Where k(t) is soil compression resistance, k(t)=χ0·(1-w(t))+χ1·s(t), χ0,χ1 are the coefficients of soil moisture content and soil type on compression resistance; δ1 represents the adjustment rate coefficient related to soil compression resistance.

[0089] Track tension target value b m (t) is limited to [b min ,b max ] range, [b min ,b max ] are the lower and upper limits of the track tension target value respectively.

[0090] The track tension must also be limited within a certain range. The formula for the limiting mechanism is:

[0091] b m (t) = b m (t) b min ≤ b m (t)≤b max

[0092] b m (t) = b max b m (t)>b max

[0093] b m (t) = b min b m (t)>b min

[0094] The adjustment process of this step is dynamic, not a fixed increment. The incremental part u(t)·φ(t)·Δt is related to the degree of soil compaction and soil compression resistance, not fixed control, which overcomes the disadvantages of the traditional track tension control method using fixed control.

[0095] See also Figure 2 and Figure 3 When adjusting the track tension, the track tension adjustment mechanism 3 includes a hydraulic cylinder and an embedded control module made by the control method of the present invention. The control module uses PID to calculate the track tension adjustment amount and drives the hydraulic cylinder to work. The driving adjustment shaft of the hydraulic cylinder pulls / presses the tensioning wheel to achieve track tension adjustment.

[0096] The method also includes step 4, performing adaptive learning based on the historical data obtained from steps 1 to 3 to continuously optimize the PID parameters.

[0097] Follow the formula to perform adaptive learning:

[0098] K p ′(t)=K p (t)+ε1·c(t)

[0099]

[0100] In the formula, K p ′(t), K i ′(t), K d '(t) is the optimized proportional gain, integral gain and differential gain;

[0101] ε1, ε2, and ε3 are the learning rates of the adaptive learning of proportional gain, integral gain, and differential gain, respectively.

[0102] The gain parameters of the PID controller are continuously optimized through historical data analysis and adaptive learning. Through real-time monitoring and analysis of soil changes by the system, the parameters of the PID controller (will be intelligently adjusted according to factors such as soil type, moisture, compaction strength, etc.) to maintain the best control effect of the system. This adaptive learning mechanism ensures that the system can continuously optimize the control strategy as the operating environment changes, improving the system's response speed and stability.

[0103] Although the present invention is described herein with reference to specific embodiments, it should be understood that these embodiments are merely examples of the principles and applications of the present invention. It should therefore be understood that many modifications may be made to the exemplary embodiments and that other arrangements may be devised without departing from the spirit and scope of the present invention as defined by the appended claims. It should be understood that the various dependent claims and features described herein may be combined in a manner different from that described in the original claims. It should also be understood that the features described in conjunction with a single embodiment may be used in other described embodiments.

Claims

1. A method for controlling the track tension of a crawler combine harvester for reducing soil compaction, characterized in that: The method comprises the following steps: Step 1: obtaining the current soil compaction degree based on the monitoring data of the soil compaction monitoring sensor group; Step 2: according to the error between the current soil compaction degree and the target soil compaction degree obtained in step 1, the track tension adjustment amount is obtained by using the PID control algorithm; Step 3: The actuator adjusts the track in a step-by-step manner according to the track tension adjustment amount obtained in step 2 until the track tension target value is reached.

2. The method for controlling the track tension of a crawler combine harvester for reducing soil compaction according to claim 1, characterized in that: The process of obtaining the current soil compaction degree p(t) in step 1 is: Step 11, the soil compaction monitoring sensor group monitors the original data of soil moisture w′(t), deadweight f′(t), steering ratio time z′(t) and track speed v′(t); Step 12: standardize the monitoring data obtained in step 11 to obtain dimensionless data w(t), f(t), z(t), and v(t); The standardization formula is: Where X'(t) is the original data, X'(t) refers to the soil moisture content w'(t), deadweight f'(t), steering time z'(t) or track speed v'(t); X(t) is dimensionless data, X(t) refers to w(t), f(t), z(t) or v(t); μ(t) is the mean of X'(t); σ(t) is the standard deviation; Step 13: Calculate the current soil compaction degree p(t) according to the following formula: Where, α1, α2, α3, α4, α5 are soil type correlation coefficients; s(t) is the quantitative index of soil type. Soil types include sandy soil, clay soil and loam. The quantitative index of sandy soil is 0.2, the quantitative index of clay soil is 0.3, and the quantitative index of loam is 0.

5. β1, β2, β3, and β4 are the influence indexes of each factor.

3. The method for controlling the track tension of a crawler combine harvester for reducing soil compaction according to claim 2, characterized in that: The process of obtaining the track tension adjustment amount in step 2 is: Step 21: Obtain the current soil compaction degree p(t) and the target soil compaction degree p according to step 1. m The error c(t) of (t) is: c(t)=p m (t)-p(t) Step 22: Based on the error c(t), use the PID control algorithm to obtain the track tension adjustment u(t): Among them, K p (t), K i (t), K d (t) are proportional gain, integral gain, and differential gain respectively, Δt is the integration time, and Δt is set to 1 second.

4. The method for controlling the track tension of a crawler combine harvester for reducing soil compaction according to claim 3, characterized in that: In step 3, the actuator adjusts the tension of the track in steps according to the following formula: b m (t)=b(t)+u(t)·φ(t)·Δt Where b(t) is the current track tension, b m (t) is the target value of track tension; φ(t) is the dynamic adjustment factor, Where k(t) is soil compression resistance, k(t)=χ0·(1-w(t))+χ1·s(t), χ0,χ1 are the coefficients of soil moisture content and soil type on compression resistance; δ1 represents the adjustment rate coefficient related to soil compression resistance.

5. The method for controlling the track tension of a crawler combine harvester for reducing soil compaction according to claim 3 or 4, characterized in that: Track tension adjustment u(t) is limited to [u min ,u max ] range, u min ,u max They are the lower and upper limits of the track tension adjustment respectively.

6. The method for controlling the track tension of a crawler combine harvester for reducing soil compaction according to claim 4, characterized in that: Track tension target value b m (t) is limited to [b min ,b max ] range, [b min ,b max ] are the lower and upper limits of the track tension target value respectively.

7. The method for controlling the track tension of a crawler combine harvester for reducing soil compaction according to claim 4, characterized in that: The method also includes step 4, performing adaptive learning based on the historical data obtained from steps 1 to 3 to continuously optimize the PID parameters.

8. The method for controlling the track tension of a crawler combine harvester for reducing soil compaction according to claim 7, characterized in that: Follow the formula to perform adaptive learning: K p ′(t)=K p (t)+ε1·c(t) In the formula, K p ′(t), K i ′(t), K d '(t) is the optimized proportional gain, integral gain and differential gain; ε1, ε2, and ε3 are the learning rates of the adaptive learning of proportional gain, integral gain, and differential gain, respectively.

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