A method and system for adaptive adjustment of the soil entry angle of the vibratory shovel of a kudzu harvester

Abstract

This application relates to the field of kudzu harvester technology, specifically disclosing a method and system for adaptive adjustment of the soil entry angle of a vibratory shovel in a kudzu harvester. The method includes collecting intrinsic soil data and initial soil entry angle of the current working area; determining soil characteristic parameters, target vibration parameters, and target reference resistance corresponding to the intrinsic soil data based on a preset soil frequency resistance mapping table; inputting the soil characteristic parameters, target vibration parameters, and target reference resistance into a preset angle dynamic correction model, and outputting the target soil entry angle of the vibratory shovel; adjusting the angle of the vibratory shovel according to the difference between the target soil entry angle and the initial soil entry angle; and collecting the actual soil entry angle of the vibratory shovel in real time during the adjustment process, and dynamically correcting the adjustment deviation by combining a proportional-integral-differential error correction algorithm to adaptively adjust the soil entry angle of the vibratory shovel. The method achieves the high-efficiency and low-consumption operation requirements of the harvester by adaptively adjusting the soil entry angle for soils of different hardness.

Description

Technical Field

[0001] This application relates to the field of kudzu harvester technology, and in particular to a method and system for adaptive adjustment of the soil entry angle of the vibratory shovel of a kudzu harvester. Background Technology

[0002] As an important economic crop with both medicinal and edible properties, kudzu roots grow vertically in the soil at a depth of 30-60cm. To achieve high harvesting efficiency, kudzu harvesters are currently the main method of excavation. The harvesters are equipped with vibrating shovels that break up the soil by entering the soil and loosen the substrate by high-frequency vibration, thus separating the kudzu roots from the soil.

[0003] However, the inventors discovered that soil hardness (cohesion strength), as a key environmental variable, directly determines the soil penetration resistance and digging effect of the vibratory shovel. Furthermore, due to the significant differences in soil types in the main kudzu producing areas, ranging from red soil in the south and heavy clay soil in the central region to sandy loam in the north, the hardness covers a wide range. The same entry angle exhibits drastically different operating effects in soils of different hardness. In high-hardness heavy clay soil, an excessively small entry angle will make it difficult for the shovel tip to penetrate the soil, causing a surge in the forward resistance of the harvester, increasing the energy consumption per unit area, and even causing overload of the harvester's power system. In low-hardness loose soil, an excessively large entry angle will cause excessive soil agitation, increasing the kudzu damage rate, while also increasing ineffective energy consumption and reducing the harvester's operating efficiency.

[0004] Currently, the angle adjustment of the vibratory shovel of kudzu harvester is mainly based on manual preset or fixed angle design, lacking a dynamic adaptation mechanism with soil hardness: some equipment achieves 2-3 fixed angle switching or continuous angle adjustment through mechanical gears, relying on the operator's experience to judge soil conditions, which cannot match changes in soil hardness in real time, resulting in low adjustment accuracy and difficulty in meeting the high-efficiency and low-consumption operation requirements of harvesters under soils of different hardness. Summary of the Invention

[0005] Based on this, the present application provides a method and system for adaptive adjustment of the vibratory shovel's soil entry angle of a kudzu harvester, which aims to at least solve the technical problem that the adjustment of the vibratory shovel's soil entry angle of kudzu harvesters mainly adopts manual preset or fixed angle design, which makes it difficult to meet the high-efficiency and low-consumption operation requirements of harvesters under soils of different hardness.

[0006] In a first aspect, embodiments of this application provide a method for adaptively adjusting the soil entry angle of the vibratory shovel of a kudzu harvester, including: The intrinsic soil data of the current working area is collected based on the sensor array on the kudzu harvester. The intrinsic soil data includes soil cohesion strength and soil moisture, as well as the initial soil entry angle of the vibratory shovel collected by the microelectromechanical system tilt sensor. Based on a preset soil frequency resistance mapping table, a clustering matching algorithm is used to traverse the soil frequency resistance mapping table to determine the soil characteristic parameters, target vibration parameters, and target reference resistance corresponding to the soil intrinsic data. The soil frequency resistance mapping table is constructed jointly by discrete element orthogonal simulation experiments and field experiments. The soil characteristic parameters, target vibration parameters and target reference resistance are input into a preset angle dynamic correction model, and the target soil entry angle of the vibratory shovel is output. Based on the difference between the target entry angle and the initial entry angle, the vibratory shovel is driven by the actuator to adjust the angle. During the adjustment process, the actual entry angle of the vibratory shovel is collected in real time, and the adjustment deviation is dynamically corrected by combining the proportional-integral-derivative error correction algorithm, so as to adaptively adjust the entry angle of the vibratory shovel.

[0007] In some embodiments, the step of using a clustering matching algorithm to traverse a preset soil frequency resistance mapping table to determine the soil characteristic parameters, target vibration parameters, and target reference resistance corresponding to the intrinsic soil data, based on the preset soil frequency resistance mapping table, includes the following steps: The preset soil frequency resistance mapping table in the parameter association database is invoked, wherein the soil frequency resistance mapping table is used to characterize the quantitative correspondence between soil type, vibration parameters, reference resistance and soil intrinsic parameters; The intrinsic soil data were sequentially filtered, denoised, and standardized preprocessed, and features were extracted from the preprocessed intrinsic soil data to obtain soil feature vectors. A clustering matching algorithm is used to traverse the soil frequency resistance mapping table based on the soil feature vector and calculate the similarity between the soil feature vector and each group of data in the soil frequency resistance mapping table. Based on the similarity calculation results, the associated data group with the highest similarity is selected, and the corresponding soil type, vibration parameters and reference resistance are extracted, which are respectively used as the target soil type, the target vibration parameters and the target reference resistance.

[0008] In some embodiments, the step of calling the preset soil frequency resistance mapping table in the parameter association database includes creating the soil frequency resistance mapping table as follows: The intrinsic soil parameters and characteristic soil parameters under different soil types are obtained. The intrinsic soil parameters include soil cohesion strength and soil moisture, and the characteristic soil parameters include Poisson's ratio, density and shear modulus. Under different soil types, the initial vibration parameters and initial reference resistance were determined by combining discrete element orthogonal simulation experiments with field measurements. The soil intrinsic parameters, soil characteristic parameters, initial vibration parameters, and initial reference resistance corresponding to each soil type are structurally correlated and mapped to construct the soil frequency resistance mapping table with multi-dimensional parameter coupling and correlation characteristics.

[0009] In some embodiments, the step of determining the initial vibration parameters and initial reference resistance under different soil types by linking discrete element orthogonal simulation experiments with field measurements includes: Under different soil types, multiple sets of corresponding soil penetration resistance parameters were determined based on different test vibration parameters and different test soil penetration angles of the vibrating shovel. Linear fitting was performed based on multiple sets of the experimental vibration parameters, the experimental soil entry angle, and the soil entry resistance parameters to obtain linear correlation models for different soil types. Based on the linear fluctuation trend of the linear correlation model, the vibration parameters corresponding to the minimum soil penetration resistance under each soil type are determined as initial vibration parameters, and the minimum soil penetration resistance is used as the initial reference resistance.

[0010] In some embodiments, the step of inputting the soil characteristic parameters, target vibration parameters, and target reference resistance into a preset angle dynamic correction model and outputting the target entry angle of the vibratory shovel includes the following data processing steps for the angle dynamic correction model: Based on the soil Poisson's ratio, soil density, and soil shear modulus among the soil property parameters, the weighting coefficients of the soil entry angle factor, vibration frequency factor, and vibration amplitude factor in the angle dynamic correction model are calibrated; and the target reference resistance and the target vibration parameters are input into the angle dynamic correction model with the weighting coefficients configured, and the target soil entry angle of the vibratory shovel is output.

[0011] In some embodiments, the process of constructing the angle dynamic correction model includes: A coupled simulation model including kudzu root, heavy clay soil, and a vibrating shovel was constructed using the discrete element method. Based on the principle of particle agglomeration modeling, spherical discrete element particles of different sizes were combined according to the actual morphology and mechanical properties of kudzu root to construct a kudzu root simulation model. The kudzu root model was arranged at intervals along the harvester's working direction in the center of the soil trough in the simulated soil area. Simultaneously, a vibrating shovel simulation model was created and set on one side of the soil trough. Its motion parameters included vibration frequency, vibration amplitude, and working forward speed. Based on the bonding contact model, the Poisson's ratio, density and shear modulus of soil and kudzu, the collision recovery coefficient, static friction coefficient and rolling friction coefficient of soil-soil, soil-kudzu, vibratory shovel-soil and vibratory shovel-kudzu, and the normal stiffness, tangential stiffness, normal strength and tangential strength of the soil bonding system were calibrated respectively. After parameter calibration, orthogonal experimental design method is adopted to set the parameters of the vibratory shovel's soil entry angle, vibration frequency and vibration amplitude according to multi-level gradient. Multiple sets of coupled simulation tests are carried out to obtain soil entry resistance data corresponding to each set of parameter combinations, and to determine the sample dataset covering multi-parameter coupled working conditions. Based on the sample dataset, a dynamic mapping relationship between soil penetration angle, vibration frequency, vibration amplitude and soil penetration resistance was constructed by using a multivariate nonlinear regression algorithm combined with soil mechanical property correlation analysis. The dynamic correction mechanism of soil Poisson's ratio, density and shear modulus on the model parameters was incorporated to obtain the angle dynamic correction model.

[0012] In some embodiments, the calculation expression of the angle dynamic correction model is:

[0013] in, Let C be the angle at which the vibratory shovel enters the soil, and let C be a constant term. The influence coefficient of the soil entry angle. This is the coefficient representing the influence of vibration frequency on drag. The vibration frequency of the vibratory shovel in response to resistance. This is the coefficient representing the influence of vibration amplitude on drag. Let F be the vibration amplitude of the vibratory shovel, and F be the soil penetration resistance.

[0014] Compared with the prior art, the technical solution provided in the first aspect of this application includes at least the following beneficial effects or advantages: The adjustment method provided in this application acquires soil intrinsic data such as soil cohesion strength and soil moisture in real time through a sensor array, and obtains the initial soil entry angle of the vibratory shovel through a microelectromechanical system tilt sensor, achieving accurate perception of soil characteristics and the initial state of the equipment. Based on a preset soil frequency resistance mapping table, a clustering matching algorithm is used to determine the corresponding soil characteristic parameters, target vibration parameters, and target reference resistance, ensuring the accuracy of parameter matching. The matched soil characteristic parameters, target vibration parameters, and target reference resistance are input into the angle dynamic correction model to calculate the above parameters and output the target soil entry angle. Through an actuator combined with a proportional-integral-differential error correction algorithm, the dynamic adjustment and deviation calibration of the vibratory shovel's soil entry angle are realized, achieving real-time adjustment and adaptation of the vibratory shovel for different soil types. This improves the operational adaptability and digging efficiency of the kudzu harvester under different soil types, achieving efficient and low-consumption kudzu harvesting operations.

[0015] Secondly, this application provides an adaptive adjustment system for the soil entry angle of the vibratory shovel of a kudzu harvester, comprising: The acquisition module is configured to collect intrinsic soil data of the current working area based on the sensor array on the kudzu harvester. The intrinsic soil data includes soil cohesion strength and soil moisture, as well as the initial soil entry angle of the vibratory shovel collected by the microelectromechanical system tilt sensor. The first determining module is configured to traverse the soil frequency resistance mapping table based on a preset soil frequency resistance mapping table using a clustering matching algorithm to determine the soil characteristic parameters, target vibration parameters, and target reference resistance corresponding to the soil intrinsic data. The soil frequency resistance mapping table is jointly constructed by discrete element orthogonal simulation experiments and field experiments. The second determining module is configured to determine the target soil entry angle of the vibratory shovel based on a preset angle dynamic correction model, with the optimization objective of minimizing the deviation between the actual soil entry resistance and the target reference resistance, and in combination with the constraints formed by the target soil type and the target vibration parameters. The angle adjustment module is configured to drive the vibratory shovel to adjust the angle based on the difference between the target entry angle and the initial entry angle, and to collect the actual entry angle of the vibratory shovel in real time during the adjustment process, and to dynamically correct the adjustment deviation by combining the proportional-integral-derivative error correction algorithm, so as to adaptively adjust the entry angle of the vibratory shovel.

[0016] Thirdly, embodiments of this application also provide an electronic device, including: At least one processor; and A memory communicatively connected to the at least one processor; wherein, The memory stores instructions executable by the at least one processor, which, when executed by the at least one processor, enables the at least one processor to perform the steps of the adaptive adjustment method for the vibratory shovel entry angle of the kudzu harvester as described in any of the first aspects above.

[0017] Fourthly, embodiments of this application also provide a computer-readable storage medium storing computer program instructions thereon, which, when executed by a processor, implement the steps of the adaptive adjustment method for the vibratory shovel entry angle of the kudzu harvester described in any of the first aspects.

[0018] It is understood that the beneficial effects of the technical solutions provided in the second, third and fourth aspects above can be found in the relevant descriptions in the first aspect above, and will not be repeated here.

[0019] Additional aspects and advantages of this application will be set forth in part in the description which follows, and in part will be obvious from the description, or may be learned by practice of this application. Attached Figure Description

[0020] To more clearly illustrate the technical solutions of the embodiments of this application, the drawings used in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0021] Figure 1 A flowchart of the adaptive adjustment method for the soil entry angle of the vibratory shovel of the kudzu harvester provided in the embodiments of this application; Figure 2 This is a schematic diagram of the structure of the vibrating shovel of the kudzu harvester provided in an embodiment of this application; Figure 3 A schematic diagram of the coupled simulation model of the kudzu harvester provided in the embodiments of this application; Figure 4 This is a first schematic diagram illustrating the simulation process of the coupled simulation model of the kudzu harvester provided in the embodiments of this application; Figure 5 A second schematic diagram illustrating the simulation process of the coupled simulation model of the kudzu harvester provided in the embodiments of this application; Figure 6 A third schematic diagram illustrating the simulation process of the coupled simulation model of the kudzu harvester provided in this application embodiment; Figure 7 This application provides a structural block diagram of an adaptive adjustment system for the soil entry angle of a vibratory shovel in a kudzu harvester. Figure 8 This is a structural block diagram of an electronic device provided in an embodiment of this application. Detailed Implementation

[0022] To facilitate understanding of this application, a more complete description will be provided below with reference to the accompanying drawings, which illustrate several embodiments of the present application. However, the present application can be implemented in many different forms and is not limited to the embodiments described herein. Rather, these embodiments are provided so that the disclosure of this application will be thorough and complete.

[0023] It should be noted that when a component is said to be "fixed to" another component, it can be directly on the other component or there may be an intervening component. When a component is said to be "connected to" another component, it can be directly connected to the other component or there may be an intervening component. The terms "vertical," "horizontal," "left," "right," and similar expressions used in this document are for illustrative purposes only.

[0024] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs. The terminology used herein in the specification of this application is for the purpose of describing particular embodiments only and is not intended to be limiting of the application. The term "and / or" as used herein includes any and all combinations of one or more of the associated listed items.

[0025] Please see Figures 1 to 6 ,in, Figure 1 The flowchart illustrates the implementation of an adaptive adjustment method for the soil entry angle of a vibratory shovel of a kudzu harvester provided in this application embodiment. This embodiment provides an adaptive adjustment method for the soil entry angle of a vibratory shovel of a kudzu harvester, specifically including steps S100 to S400.

[0026] Step S100: Collect soil intrinsic data of the current working area based on the sensor array on the kudzu harvester. The soil intrinsic data includes soil cohesion strength and soil moisture, as well as the initial soil entry angle of the vibratory shovel collected by the microelectromechanical system tilt sensor. First, it needs to be explained that the kudzu harvester is a specialized agricultural piece of equipment developed specifically for the growth characteristics of kudzu, a crop that is both medicinal and edible. It is designed to dig up kudzu rhizomes that grow vertically in the soil at a depth of 30-60cm, and its core working component is a vibrating shovel. In actual operation, the vibrating shovel first enters the soil to break up the soil structure, and then uses high-frequency vibration to loosen the soil matrix, thereby achieving efficient separation of the kudzu rhizomes from the soil. This significantly reduces the labor intensity of manual digging and improves the efficiency and mechanization level of large-scale kudzu harvesting.

[0027] In practical applications, traditional kudzu harvesters face several challenges. First, kudzu is grown in a wide area with diverse soil types, including red soil in the south, heavy clay soil in the central region, and sandy loam in the north. The hardness and cohesion of these soils vary considerably, resulting in drastically different working effects for the same entry angle. In high-hardness, heavy clay soils, a small entry angle makes it difficult for the shovel tip to penetrate, significantly increasing the harvester's forward resistance. This not only increases energy consumption per unit area but can also lead to overload and shutdown of the harvester's power system. Conversely, in low-hardness, loose soils, an excessive entry angle causes excessive soil agitation, increasing the damage rate to kudzu roots and reducing harvest quality. This also increases ineffective energy consumption and negatively impacts the harvester's efficiency. On the other hand, most traditional kudzu harvesters adopt manual preset or fixed angle design. Although some equipment can switch between several fixed angles or adjust the angle continuously through mechanical gears, they rely entirely on the operator's experience to judge the soil conditions. They lack a dynamic adaptation mechanism with key parameters such as soil hardness and moisture. The adjustment accuracy is low and the response speed is slow. They cannot match the changes in soil characteristics during operation in real time and cannot meet the needs of harvesters for efficient and low-consumption digging operations in soils of different hardness.

[0028] In this embodiment, the kudzu harvester includes a vibratory shovel and a traction device. The traction device, serving as the power source and walking platform for the entire machine, can be a wheeled tractor, a tracked agricultural machinery chassis, or a dedicated kudzu harvester frame. It primarily provides forward propulsion for the vibratory shovel. Sensors for collecting intrinsic soil data can include an array of soil moisture sensors and soil cohesion strength sensors. The sensor installation location must allow for direct and sufficient contact with the soil; the specific installation location is not limited here. The microelectromechanical system (MEMS) tilt sensor can be fixed to the end of the vibratory shovel's rotating shaft using a waterproof metal bracket. The bracket is coaxially connected to the rotating shaft, and the sensor's sensitive axis is aligned with the shovel's soil entry direction to ensure accurate angle acquisition. It is also equipped with a waterproof sealed housing to adapt to damp field operating environments. The specific sensor model can be obtained according to actual needs.

[0029] For example, when the raw data collected by the sensor can be transmitted to the main controller of the harvester via the CAN bus, the main controller performs sliding window averaging filtering on the soil bonding strength and moisture data. The window size is set to 5-10 sets of sampled values ​​to eliminate impact interference signals. At the same time, Kalman filtering can be performed on the data collected by the tilt sensor to eliminate angle fluctuations caused by machine vibration. Finally, stable and accurate intrinsic soil data (bonding strength, moisture) and initial soil entry angle are output.

[0030] Step S200: Based on the preset soil frequency resistance mapping table, a clustering matching algorithm is used to traverse the soil frequency resistance mapping table to determine the soil characteristic parameters, target vibration parameters and target reference resistance corresponding to the soil intrinsic data. The soil frequency resistance mapping table is jointly constructed by discrete element orthogonal simulation experiment and field experiment. In this step, the soil frequency resistance mapping table is used to characterize the quantitative correspondence between soil type, vibration parameters, reference resistance, and intrinsic soil parameters. The soil frequency resistance mapping table can be pre-stored in a parameter association database. Data can be read by calling the pre-set soil frequency resistance mapping table in the parameter association database. The process of determining soil characteristic parameters, target vibration parameters, and target reference resistance may include sequentially performing filtering, noise reduction, and standardization preprocessing on the intrinsic soil data, and extracting features from the preprocessed intrinsic soil data to obtain soil feature vectors. A clustering matching algorithm is used to traverse the soil frequency resistance mapping table based on the soil feature vectors, calculating the similarity between the soil feature vectors and each group of data in the soil frequency resistance mapping table. Based on the similarity calculation results, the associated data group with the highest similarity is selected, and the corresponding soil type, vibration parameters, and reference resistance are extracted as the target soil type, target vibration parameters, and target reference resistance, respectively.

[0031] It should be noted that for filtering and noise reduction, for data collected by the soil cohesion strength sensor, the impact of the shovel body on the soil clods at the moment of entry can generate pulse interference. A sliding window averaging filter algorithm can be used for processing. For example, the window size can be set to 8 sets of sampling values, and the continuously collected raw data can be slid sequentially through the window. The arithmetic mean of the data in each window can be calculated and the raw data at the center of the window can be replaced to remove abnormal peaks caused by the impact. For soil moisture sensor data, there are random fluctuations due to the vibration of agricultural machinery, so a Kalman filter algorithm can be used for optimization. At the same time, since soil cohesion strength (unit: kPa) and soil moisture (unit: %RH) have different dimensions, direct matching will lead to weight imbalance. Therefore, a standardization preprocessing method can be used, such as Z-score standardization, for uniform processing.

[0032] In some embodiments, the creation of a soil frequency resistance mapping table may include: obtaining soil intrinsic parameters and soil property parameters for different soil types, wherein the soil intrinsic parameters include soil cohesion strength and soil moisture, and the soil property parameters include Poisson's ratio, density, and shear modulus; determining initial vibration parameters and initial reference resistance for different soil types by linking discrete element orthogonal simulation experiments with field measurements; and constructing a soil frequency resistance mapping table with multi-dimensional parameter coupling and correlation characteristics by performing structured correlation mapping on the soil intrinsic parameters, soil property parameters, initial vibration parameters, and initial reference resistance corresponding to each soil type.

[0033] It should be noted that multiple methods can be used for different soil types, such as red soil, central heavy clay soil, or sandy loam. The experimental process can employ a combination of discrete element method (DEM) simulation and field trials. In the DEM simulation stage, a three-dimensional coupled model can be built using EDEM software. The intrinsic soil parameters and characteristic soil parameters for different soil types can be obtained from relevant literature or historical experience, thereby determining multiple vibration parameters and multiple reference resistances for different soil types. In the field trial stage, typical soil types such as southern red soil, central heavy clay soil, and northern sandy loam are selected. Field operations are carried out in each soil region according to the simulation parameter combinations. The measured soil penetration resistance is collected by a tension sensor installed at the connection between the shovel and the frame. Simultaneously, soil samples are collected using a soil sampler, and soil characteristic parameters are measured in the laboratory to supplement the deficiencies of the simulation data. Finally, the simulation and measured data, i.e., the intrinsic soil parameters, characteristic soil parameters, vibration parameters, and reference resistance corresponding to each soil type, are structurally correlated and mapped to construct a soil frequency resistance mapping table with multi-dimensional parameter coupling and correlation characteristics. The soil frequency resistance mapping table data needs to be normalized to eliminate dimensional differences.

[0034] Furthermore, the initial vibration parameters and initial reference resistance are obtained as follows: For different types of soil, multiple sets of differentiated experimental vibration parameters (including vibration frequency and vibration amplitude) and multiple sets of differentiated vibratory shovel test entry angles are set. The entry resistance parameters corresponding to each combination of the experimental vibration parameters and entry angles are obtained through experiments, forming a correlated dataset of multiple sets of experimental vibration parameters, entry angles, and entry resistance parameters. Based on this correlated dataset, with the experimental vibration parameters (vibration frequency and vibration amplitude) and entry angles as independent variables and the entry resistance parameters as dependent variables, a multiple linear regression algorithm is used for linear fitting: First, the fitting objective is to construct a linear expression between the independent and dependent variables. Then, the least squares method is used to minimize the difference between the actual observed value of the dependent variable and the model prediction. The sum of squared residuals between the values ​​is used to solve for the regression coefficients of the linear correlation model, which includes the coefficients and constant terms corresponding to each independent variable. This allows for the construction of linear correlation models for different soil types. These models are used to quantify the linear mapping relationship between experimental vibration parameters, experimental entry angle, and entry resistance parameters. Based on these linear correlation models, the linear fluctuation trend of each independent variable on the entry resistance parameter is analyzed. Within a preset parameter constraint range (determined based on the hardware operating limits, operational safety, and kudzu harvesting quality requirements of the kudzu harvester), a target vibration parameter that minimizes the entry resistance parameter is selected. This target vibration parameter is then defined as the initial vibration parameter for the corresponding soil type, and the minimized entry resistance parameter is defined as the initial reference resistance for the corresponding soil type.

[0035] It should be noted that vibration parameters are a key factor affecting soil penetration resistance parameters, and changes in their values ​​directly lead to corresponding fluctuations in these parameters. This embodiment designs multiple sets of differentiated experimental vibration parameters and soil penetration angles, and through experimental back-calculation, obtains multiple sets of corresponding soil penetration resistance parameters, forming a complete correlation dataset covering key working conditions. Based on this dataset, multiple linear fitting is performed. Statistical modeling can isolate the independent influence and coupling effects of each parameter, ensuring that the constructed linear correlation model accurately reflects the true linear relationship between the parameters. This provides reliable theoretical and data support for the accurate acquisition of initial vibration parameters and initial reference resistance.

[0036] Step S300: Input the soil characteristic parameters, target vibration parameters and target reference resistance into the preset angle dynamic correction model, and output the target soil entry angle of the vibratory shovel. In some embodiments, the data processing procedure for the angle dynamic correction model includes: Based on soil property parameters such as Poisson's ratio, soil density, and soil shear modulus, the weighting coefficients of the entry angle factor, vibration frequency factor, and vibration amplitude factor in the dynamic angle correction model are determined. The target reference resistance and target vibration parameters are then input into the dynamically corrected angle model with the weighted coefficients configured, outputting the target entry angle of the vibratory shovel. It should be noted that actual experiments have shown that soil density reflects the compaction of soil particles; the higher the density, the stronger the compressive resistance of the soil on the shovel, and the weight of the entry angle factor needs to be increased accordingly. Soil shear modulus reflects the soil's ability to resist shear deformation; the higher the shear modulus, the more difficult the soil is to break up, and the weights of the vibration frequency and amplitude factors need to be appropriately increased to strengthen the counteracting effect of vibration parameters on the entry resistance. Soil Poisson's ratio characterizes the lateral deformation characteristics of the soil under pressure; the higher the Poisson's ratio, the more significant the lateral expansion of the soil under pressure, and the greater the lateral resistance to the shovel. In this embodiment, the angle dynamic correction model is used to calibrate the weighting coefficients of the soil entry angle factor, vibration frequency factor, and vibration amplitude factor based on soil characteristic parameters such as Poisson's ratio, soil density, and soil shear modulus. This can further improve the accuracy of the angle dynamic correction model in predicting the entry angle and allow the model's weighted calculation logic to match the actual mechanical behavior of the soil. This avoids deviations in the target entry angle due to ignoring the essential mechanical properties of the soil, ultimately ensuring that the vibratory shovel can achieve efficient and low-consumption operation under different soil types.

[0037] In some embodiments, the calculation expression for the angle dynamic correction model is:

[0038] in, Let C be the angle at which the vibratory shovel enters the soil, and let C be a constant term. The influence coefficient of the soil entry angle. This is the coefficient representing the influence of vibration frequency on drag. The vibration frequency of the vibratory shovel in response to resistance. This is the coefficient representing the influence of vibration amplitude on drag. Let F be the vibration amplitude of the vibratory shovel, and F be the soil penetration resistance.

[0039] In some embodiments, the construction process of the angle dynamic correction model includes: constructing a coupled simulation model of kudzu root, heavy clay soil, and a vibrating shovel using the discrete element method (DEM), wherein, based on the principle of particle aggregate modeling, spherical discrete element particles of different sizes are combined according to the actual morphology and mechanical properties of kudzu root to construct a kudzu root simulation model, and the kudzu root model is arranged at intervals along the harvester's operating direction at the center of the soil trough in the simulated soil area; and simultaneously creating a vibrating shovel simulation model, which is set on one side of the soil trough, and its motion parameters include vibration frequency, vibration amplitude, and operating forward speed; and calibrating the Poisson's ratio, density, and shear modulus of soil and kudzu root based on the adhesive contact model, and determining the soil-soil, soil-kudzu root, vibrating shovel-soil, and vibrating shovel-kudzu root collisions. Impact recovery coefficient, static friction coefficient, and rolling friction coefficient, as well as the normal stiffness, tangential stiffness, normal strength, and tangential strength of the soil bonding system; after parameter calibration, an orthogonal experimental design method was used to set the parameters of the vibratory shovel's entry angle, vibration frequency, and vibration amplitude according to multi-level gradients, and multiple sets of coupled simulation tests were conducted to obtain the entry resistance data corresponding to each parameter combination, and to determine the sample dataset covering the multi-parameter coupled working conditions; based on the sample dataset, a multivariate nonlinear regression algorithm combined with soil mechanical property correlation analysis was used to construct the dynamic mapping relationship between entry angle, vibration frequency, vibration amplitude, and entry resistance, and to incorporate the dynamic correction mechanism of soil Poisson's ratio, density, and shear modulus on the model parameters, to obtain the angle dynamic correction model.

[0040] For example, please refer to Figures 3 to 6 In constructing the angle dynamic correction model, the EDEM discrete element method software was used to establish a simulation model of the kudzu-heavy clay soil composite. Considering the soil's high moisture and high viscosity, the Hertz-Mindlin Bonding model was used to characterize the soil properties. The soil parameters were determined based on the characteristics of heavy clay soil in Jiangxi Province and by consulting relevant literature. The kudzu model was formed by combining spherical particles of different sizes, which were evenly distributed at the center of the soil trough along the direction of the kudzu harvester. The vibrating shovel was located on one side of the soil trough, and its motion parameters, including vibration frequency, vibration amplitude, and forward speed, were set to realize the forward movement of the vibrating shovel and the harvesting of kudzu.

[0041] For setting simulation parameters, including the intrinsic parameters of soil and kudzu root, as well as the contact parameters between soil, kudzu root, and the digging shovel, please refer to Table 1 below for examples. Table 1 shows the simulation parameter settings.

[0042] Based on the above simulation settings, the structural and motion parameters of the entry shovel were optimized, including the entry angle, vibration frequency, and vibration amplitude. According to the existing mechanical structure of vibratory shovels, the entry angle can be set to -20° to 20°, the vibration frequency to 10Hz to 100Hz, and the vibration amplitude to 2mm to 10mm. Table 2 shows the arrangement of the experimental factors.

[0043] Table 2. Optimization factors and levels of the experiment

[0044] Based on the above experimental factors and levels, the experimental scheme and the corresponding trenching resistance were determined through orthogonal experiments, as shown in the table below.

[0045]

[0046] Based on the above experimental scheme, a regression model was established, and the relationship between resistance and penetration angle, vibration frequency, and amplitude is as follows: F=3190 8.17θ 6.02f 67.6a Where θ, f, and α are the soil penetration angle, vibration frequency, and vibration amplitude, respectively.

[0047] As shown in the formula, the trenching resistance is minimized when the entry angle is 20 degrees and the vibration frequency and amplitude are 100 Hz and 10 mm, respectively. The vibration frequency and amplitude determine the vibration energy of the shovel. When the vibration frequency and amplitude are at their maximum, the shovel's vibration energy is at its maximum, resulting in the strongest soil-breaking ability and effectively weakening the soil's cohesion. At an entry angle of 20°, the shovel's entry process reduces the contact resistance between the soil and the shovel, facilitating successful shovel entry.

[0048] It should be understood that the above expression is only a regression model for one type of soil. The calculation expression of the angle dynamic correction model is obtained by conducting multiple simulation experiments under different soil types and solving them inversely.

[0049] In step S400, based on the difference between the target entry angle and the initial entry angle, the vibratory shovel is driven by the actuator to adjust the angle. During the adjustment process, the actual entry angle of the vibratory shovel is collected in real time, and the adjustment deviation is dynamically corrected by combining the proportional-integral-derivative error correction algorithm to adaptively adjust the entry angle of the vibratory shovel.

[0050] In this step, the actuator can be composed of an electric push rod combined with a linkage transmission mechanism. The electric push rod is installed below the crossbeam of the harvester frame via a high-strength hinge. The telescopic end of the push rod is hinged to the rotating arm of the vibratory shovel via a ball joint (the ball joint can eliminate lateral forces during the adjustment process and avoid jamming). The rotating arm is rigidly connected to the rotating shaft of the vibratory shovel, forming a mechanical transmission chain that adjusts the shovel angle through push rod telescopic extension and rotation of the rotating arm. The electric push rod has a built-in position sensor that can provide real-time feedback on its telescopic extension, thereby indirectly reflecting the angle change of the vibratory shovel. When a target entry angle command is received, the main controller calculates the required telescopic stroke of the electric push rod based on the difference between the initial entry angle and the target angle, sends a PWM drive signal to the electric push rod to control the telescopic extension and extension, driving the rotating arm to rotate around the rotating shaft, thus achieving coarse adjustment of the vibratory shovel's entry angle. During the adjustment process, the telescopic speed of the electric push rod can be dynamically adjusted according to the angle difference.

[0051] Simultaneously, during angle adjustment, the MEMS tilt sensor continuously collects the actual soil entry angle of the vibratory shovel and transmits it to the main controller in real time. The main controller compares the actual angle with the target angle and calculates the angle deviation. The proportional-integral-derivative (PID) error correction algorithm operates as follows: the proportional (P) component outputs an immediate correction amount based on the magnitude of the deviation; the larger the deviation, the larger the correction, quickly reducing the angle difference. The integral (I) component integrates the deviation value to eliminate long-term small static deviations and avoid angle drift. The derivative (D) component predicts the deviation trend based on the rate of change of the deviation value and outputs a reverse correction amount in advance to suppress overshoot during angle adjustment. The correction amounts output by the three components are weighted and summed to convert into fine-tuning commands for the electric actuator, dynamically adjusting the extension and retraction of the actuator to correct the angle of the vibratory shovel. The entire process forms a closed-loop control from drive adjustment, real-time detection, deviation calculation to precise correction, ensuring that the deviation between the actual soil entry angle and the target angle of the vibratory shovel is controlled within the allowable error range, achieving adaptive and precise adjustment.

[0052] Please see Figure 7 , Figure 7 This embodiment illustrates an adaptive adjustment system for the vibratory shovel's soil entry angle of a kudzu harvester. In this embodiment, the adaptive adjustment system 200 for the vibratory shovel's soil entry angle is used to perform the above-mentioned... Figure 1 The steps in the corresponding embodiments. Please refer to the details. Figure 1 as well as Figure 1 The relevant descriptions in the corresponding embodiments are shown below. For ease of explanation, only the parts relevant to this embodiment are shown. See also... Figure 7 The 200-type adaptive adjustment system for the vibratory shovel's soil entry angle of the kudzu harvester includes: The acquisition module 210 is configured to acquire soil intrinsic data of the current working area based on the sensor array on the kudzu harvester. The soil intrinsic data includes soil cohesion strength and soil moisture, as well as the initial soil entry angle of the vibratory shovel acquired by the microelectromechanical system tilt sensor. The first determining module 220 is configured to traverse the soil frequency resistance mapping table based on a preset soil frequency resistance mapping table using a clustering matching algorithm to determine the soil characteristic parameters, target vibration parameters and target reference resistance corresponding to the soil intrinsic data. The soil frequency resistance mapping table is jointly constructed by discrete element orthogonal simulation experiment and field experiment. The second determining module 230 is configured to determine the target soil entry angle of the vibratory shovel based on a preset angle dynamic correction model, with the optimization objective of minimizing the deviation between the actual soil entry resistance and the target reference resistance, and in combination with the constraint conditions formed by the target soil type and the target vibration parameters. The angle adjustment module 240 is configured to drive the vibratory shovel to adjust the angle based on the difference between the target entry angle and the initial entry angle, and to collect the actual entry angle of the vibratory shovel in real time during the adjustment process, and to dynamically correct the adjustment deviation by combining the proportional-integral-derivative error correction algorithm, so as to adaptively adjust the entry angle of the vibratory shovel.

[0053] The system provided in this embodiment collects soil intrinsic data such as soil cohesion strength and soil moisture in real time through a sensor array, and obtains the initial soil entry angle of the vibratory shovel through a microelectromechanical system tilt sensor, achieving accurate perception of soil characteristics and the initial state of the equipment. Based on a preset soil frequency resistance mapping table, a clustering matching algorithm is used to determine the corresponding soil characteristic parameters, target vibration parameters, and target reference resistance, ensuring the accuracy of parameter matching. The matched soil characteristic parameters, target vibration parameters, and target reference resistance are input into the angle dynamic correction model to calculate the above parameters and output the target soil entry angle. Through the actuator combined with the proportional-integral-differential error correction algorithm, the dynamic adjustment and deviation calibration of the vibratory shovel's soil entry angle are realized, enabling real-time adjustment and adaptation of the vibratory shovel to different soil types. This improves the operational adaptability and digging efficiency of the kudzu harvester under different soil types, while reducing the kudzu damage rate, achieving efficient and low-consumption kudzu harvesting operations.

[0054] It should be understood that, Figure 2 The structural block diagram of the adaptive adjustment system for the vibratory shovel's soil entry angle of the kudzu harvester is shown. Each module is used to execute the steps in the corresponding embodiment. Figure 1 The steps in the corresponding embodiments have been explained in detail in the above embodiments. Please refer to them for details. Figure 1 as well as Figure 1 The relevant descriptions in the corresponding embodiments will not be repeated here.

[0055] In some embodiments, an electronic device is also provided, including: at least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores instructions executable by the at least one processor, the instructions being executed by the at least one processor to enable the at least one processor to perform the steps of the adaptive adjustment method for the vibratory shovel entry angle of the kudzu harvester described in the above embodiments.

[0056] Please see Figure 8 , Figure 8 This diagram illustrates the structure of an electronic device provided in this embodiment. The ward-round robot of this embodiment may include an electronic device. The server 500 of this electronic device includes a processor 501, a memory 502, and a computer program 503 stored in the memory 502 and executable on the processor 501, such as a program for an adaptive adjustment method of the vibratory shovel's soil entry angle of a kudzu harvester. When the processor 501 executes the computer program 503, it implements the steps of the adaptive adjustment method of the vibratory shovel's soil entry angle of the kudzu harvester in the above embodiments, for example... Figure 1 Steps S100 to S400 in the corresponding embodiment. Alternatively, the processor 501 executes the computer program 503 to implement the above. Figure 7 The functions of each module in the corresponding embodiments, for example, Figure 7 For details on the functions of the modules shown (e.g., module 210), please refer to [link / reference]. Figure 7 The relevant descriptions in the corresponding embodiments are not repeated here.

[0057] For example, computer program 503 can be divided into one or more units, one or more units are stored in memory 502 and executed by processor 501 to complete the technical solution provided in the above embodiments. One or more units can be a series of computer program instruction segments capable of performing a specific function, which are used to describe the execution process of computer program 503 in server 500.

[0058] The electronic device may include, but is not limited to, a processor 501 and a memory 502. Those skilled in the art will understand that... Figure 8 This is merely an example of server 500 in an electronic device and does not constitute a limitation on server 500. It may include more or fewer components than shown, or combine certain components, or different components. For example, a turntable terminal device may also include input / output terminal devices, network access terminal devices, buses, etc.

[0059] The processor 501 may be a Central Processing Unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. A general-purpose processor may be a microprocessor or any conventional processor.

[0060] The memory 502 can be an internal storage unit of the server 500, such as the server 500's hard drive or memory. The memory 502 can also be an external storage terminal device of the server 500, such as a plug-in hard drive, Smart Media Card (SMC), Secure Digital (SD) card, or Flash Card equipped on the server 500. Furthermore, the memory 502 can include both internal storage units and external storage terminal devices of the server 500. The memory 502 is used to store computer programs and other programs and data required by the turntable terminal device. The memory 502 can also be used to temporarily store data that has been output or will be output.

[0061] In one embodiment, a computer-readable storage medium is also provided, the computer-readable storage medium storing a computer program, which, when executed by a processor, implements the steps of the method for adaptive adjustment of the vibratory shovel entry angle of a kudzu harvester as described in the above embodiments.

[0062] Furthermore, the functional units in the various embodiments of this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.

[0063] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. The computer-readable storage medium can be non-volatile or volatile. Based on this understanding, all or part of the processes in the methods of the above embodiments can also be implemented by a computer program instructing related hardware. The computer program can be stored in a computer-readable storage medium, and when executed by a processor, it can implement the steps of the various method embodiments described above. The computer program includes computer program code, which can be in the form of source code, object code, executable files, or certain intermediate forms. The computer-readable storage medium can include: any entity or device capable of carrying computer program code, recording media, USB flash drives, portable hard drives, magnetic disks, optical disks, computer memory, read-only memory (ROM), random access memory (RAM), electrical carrier signals, telecommunication signals, and software distribution media, etc.

[0064] The terms "first," "second," "third," etc., in the specification, claims, and accompanying drawings of this application are used to distinguish different objects and not to describe a particular order. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion. For example, it may include a series of steps or units, or optionally, steps or units not listed, or other steps or units inherent to these processes, methods, products, or devices.

[0065] The accompanying drawings show only the portions relevant to this application, not all of them. Before discussing exemplary embodiments in more detail, it should be noted that some exemplary embodiments are described as processes or methods depicted as flowcharts. Although the flowcharts describe operations (or steps) as sequential processes, many of these operations may be performed in parallel, concurrently, or simultaneously. Furthermore, the order of the operations may be rearranged. The process may be terminated when its operation is completed, but may also have additional steps not included in the drawings. The process may correspond to a method, function, procedure, subroutine, subprogram, etc.

[0066] The terms “component,” “module,” “system,” “unit,” etc., used in this specification are used to refer to computer-related entities, hardware, firmware, combinations of hardware and software, software, or software in execution. For example, a unit can be, but is not limited to, a process running on a processor, a processor, an object, an executable file, a thread of execution, a program, and / or distributed between two or more computers. Furthermore, these units can be executed from various computer-readable media on which various data structures are stored. Units can communicate, for example, via local and / or remote processes based on signals having one or more data packets (e.g., data from a second unit interacting with another unit between a local system, a distributed system, and / or a network; for example, the Internet interacting with other systems via signals).

[0067] In the description of this specification, the references to terms such as "one embodiment," "some embodiments," "illustrative embodiment," "example," "specific example," or "some examples," etc., refer to specific features, structures, materials, or characteristics described in connection with that embodiment or example, which are included in at least one embodiment or example of this application. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example.

[0068] Obviously, the described embodiments are only a part of the embodiments of this application, and not all of the embodiments. The reference to "embodiment" herein means that a specific feature, structure, or characteristic described in connection with an embodiment can be included in at least one embodiment of this application. The appearance of this phrase in various places in the specification does not necessarily indicate the same embodiment, nor is it an independent or alternative embodiment mutually exclusive with other embodiments. It will be explicitly and implicitly understood by those skilled in the art that the embodiments described herein can be combined with other embodiments. All other embodiments obtained by those skilled in the art based on the embodiments of this application without inventive effort are within the scope of protection of this application.

[0069] Other embodiments of this application will readily occur to those skilled in the art upon consideration of the specification and practice of the disclosure herein. This application is intended to cover any variations, uses, or adaptations of this application that follow the general principles of this application and include common knowledge or customary techniques in the art not disclosed herein. The specification and examples are to be considered exemplary only, and the true scope and spirit of this application are indicated by the following claims.

Claims

1. A method for adaptively adjusting the soil entry angle of the vibratory shovel of a kudzu harvester, characterized in that, include: The intrinsic soil data of the current working area is collected based on the sensor array on the kudzu harvester. The intrinsic soil data includes soil cohesion strength and soil moisture, as well as the initial soil entry angle of the vibratory shovel collected by the microelectromechanical system tilt sensor. Based on a preset soil frequency resistance mapping table, a clustering matching algorithm is used to traverse the soil frequency resistance mapping table to determine the soil characteristic parameters, target vibration parameters, and target reference resistance corresponding to the soil intrinsic data. The soil frequency resistance mapping table is constructed jointly by discrete element orthogonal simulation experiments and field experiments. The soil characteristic parameters, target vibration parameters and target reference resistance are input into a preset angle dynamic correction model, and the target soil entry angle of the vibratory shovel is output. Based on the difference between the target entry angle and the initial entry angle, the vibratory shovel is driven by the actuator to adjust the angle. During the adjustment process, the actual entry angle of the vibratory shovel is collected in real time, and the adjustment deviation is dynamically corrected by combining the proportional-integral-derivative error correction algorithm, so as to adaptively adjust the entry angle of the vibratory shovel.

2. The adaptive adjustment method for the soil entry angle of the vibratory shovel of the kudzu harvester according to claim 1, characterized in that, The method, based on a preset soil frequency resistance mapping table, employs a clustering matching algorithm to traverse the table and determine the soil characteristic parameters, target vibration parameters, and target reference resistance corresponding to the intrinsic soil data. The step of constructing the soil frequency resistance mapping table jointly from discrete element orthogonal simulation experiments and field experiments includes: The preset soil frequency resistance mapping table in the parameter association database is invoked, wherein the soil frequency resistance mapping table is used to characterize the quantitative correspondence between soil type, vibration parameters, reference resistance and soil intrinsic parameters; The intrinsic soil data were sequentially filtered, denoised, and standardized preprocessed, and features were extracted from the preprocessed intrinsic soil data to obtain soil feature vectors. A clustering matching algorithm is used to traverse the soil frequency resistance mapping table based on the soil feature vector and calculate the similarity between the soil feature vector and each group of data in the soil frequency resistance mapping table. Based on the similarity calculation results, the associated data group with the highest similarity is selected, and the corresponding soil type, vibration parameters and reference resistance are extracted, which are respectively used as the target soil type, the target vibration parameters and the target reference resistance.

3. The adaptive adjustment method for the soil entry angle of the vibratory shovel of the kudzu harvester according to claim 2, characterized in that, In the step of calling the parameter association database of the preset soil frequency resistance mapping table, the creation of the soil frequency resistance mapping table includes: The intrinsic soil parameters and characteristic soil parameters under different soil types are obtained. The intrinsic soil parameters include soil cohesion strength and soil moisture, and the characteristic soil parameters include Poisson's ratio, density and shear modulus. Under different soil types, the initial vibration parameters and initial reference resistance were determined by combining discrete element orthogonal simulation experiments with field measurements. The soil intrinsic parameters, soil characteristic parameters, initial vibration parameters, and initial reference resistance corresponding to each soil type are structurally correlated and mapped to construct the soil frequency resistance mapping table with multi-dimensional parameter coupling and correlation characteristics.

4. The adaptive adjustment method for the soil entry angle of the vibratory shovel of the kudzu harvester according to claim 3, characterized in that, The steps for determining initial vibration parameters and initial reference resistance under different soil types through a combination of discrete element orthogonal simulation experiments and field measurements include: Under different soil types, multiple sets of corresponding soil penetration resistance parameters were determined based on different test vibration parameters and different test soil penetration angles of the vibrating shovel. Linear fitting was performed based on multiple sets of the experimental vibration parameters, the experimental soil entry angle, and the soil entry resistance parameters to obtain linear correlation models for different soil types. Based on the linear fluctuation trend of the linear correlation model, the vibration parameters corresponding to the minimum soil penetration resistance under each soil type are determined as initial vibration parameters, and the minimum soil penetration resistance is used as the initial reference resistance.

5. The adaptive adjustment method for the soil entry angle of the vibratory shovel of the kudzu harvester according to claim 1, characterized in that, The step of inputting the soil characteristic parameters, target vibration parameters, and target reference resistance into a preset angle dynamic correction model and outputting the target soil entry angle of the vibratory shovel includes the following data processing steps of the angle dynamic correction model: Based on the soil Poisson's ratio, soil density, and soil shear modulus among the soil property parameters, the weighting coefficients of the soil entry angle factor, vibration frequency factor, and vibration amplitude factor in the angle dynamic correction model are calibrated; and the target reference resistance and the target vibration parameters are input into the angle dynamic correction model with the weighting coefficients configured, and the target soil entry angle of the vibratory shovel is output.

6. The adaptive adjustment method for the soil entry angle of the vibratory shovel of the kudzu harvester according to claim 5, characterized in that, The construction process of the angle dynamic correction model includes: A coupled simulation model including kudzu root, heavy clay soil, and a vibrating shovel was constructed using the discrete element method. Based on the principle of particle agglomeration modeling, spherical discrete element particles of different sizes were combined according to the actual morphology and mechanical properties of kudzu root to construct a kudzu root simulation model. The kudzu root model was arranged at intervals along the harvester's working direction in the center of the soil trough in the simulated soil area. Simultaneously, a vibrating shovel simulation model was created and set on one side of the soil trough. Its motion parameters included vibration frequency, vibration amplitude, and working forward speed. Based on the bonding contact model, the Poisson's ratio, density and shear modulus of soil and kudzu, the collision recovery coefficient, static friction coefficient and rolling friction coefficient of soil-soil, soil-kudzu, vibratory shovel-soil and vibratory shovel-kudzu, and the normal stiffness, tangential stiffness, normal strength and tangential strength of the soil bonding system were calibrated respectively. After parameter calibration, orthogonal experimental design method is adopted to set the parameters of the vibratory shovel's soil entry angle, vibration frequency and vibration amplitude according to multi-level gradient. Multiple sets of coupled simulation tests are carried out to obtain soil entry resistance data corresponding to each set of parameter combinations, and to determine the sample dataset covering multi-parameter coupled working conditions. Based on the sample dataset, a dynamic mapping relationship between soil penetration angle, vibration frequency, vibration amplitude and soil penetration resistance was constructed by using a multivariate nonlinear regression algorithm combined with soil mechanical property correlation analysis. The dynamic correction mechanism of soil Poisson's ratio, density and shear modulus on the model parameters was incorporated to obtain the angle dynamic correction model.

7. The adaptive adjustment method for the soil entry angle of the vibratory shovel of the kudzu harvester according to claim 5 or 6, characterized in that, The calculation expression for the angle dynamic correction model is: in, Let C be the angle at which the vibratory shovel enters the soil, and let C be a constant term. The influence coefficient of the soil entry angle. This is the coefficient representing the influence of vibration frequency on drag. The vibration frequency of the vibratory shovel in response to resistance. This is the coefficient representing the influence of vibration amplitude on drag. Let F be the vibration amplitude of the vibratory shovel, and F be the soil penetration resistance.

8. An adaptive adjustment system for the soil entry angle of a vibratory shovel in a kudzu harvester, characterized in that, include: The acquisition module is configured to collect intrinsic soil data of the current working area based on the sensor array on the kudzu harvester. The intrinsic soil data includes soil cohesion strength and soil moisture, as well as the initial soil entry angle of the vibratory shovel collected by the microelectromechanical system tilt sensor. The first determining module is configured to traverse the soil frequency resistance mapping table based on a preset soil frequency resistance mapping table using a clustering matching algorithm to determine the soil characteristic parameters, target vibration parameters, and target reference resistance corresponding to the soil intrinsic data. The soil frequency resistance mapping table is jointly constructed by discrete element orthogonal simulation experiments and field experiments. The second determining module is configured to determine the target soil entry angle of the vibratory shovel based on a preset angle dynamic correction model, with the optimization objective of minimizing the deviation between the actual soil entry resistance and the target reference resistance, and in combination with the constraints formed by the target soil type and the target vibration parameters. The angle adjustment module is configured to drive the vibratory shovel to adjust the angle based on the difference between the target entry angle and the initial entry angle, and to collect the actual entry angle of the vibratory shovel in real time during the adjustment process, and to dynamically correct the adjustment deviation by combining the proportional-integral-derivative error correction algorithm, so as to adaptively adjust the entry angle of the vibratory shovel.

9. An electronic device, characterized in that, include: At least one processor; as well as A memory communicatively connected to the at least one processor; wherein, The memory stores instructions that can be executed by the at least one processor, which, when executed by the at least one processor, enables the at least one processor to perform the steps of the method for adaptive adjustment of the vibratory shovel entry angle of the kudzu harvester as described in any one of claims 1-7.

10. A computer-readable storage medium having computer program instructions stored thereon, characterized in that, When the computer program instructions are executed by the processor, they implement the steps of the method for adaptive adjustment of the soil entry angle of the vibratory shovel of the kudzu harvester as described in any one of claims 1-7.

Images