Cutter parameter design method and system for rape furrow opening machine

Abstract

The invention provides a cutterhead parameter design method and system for a rape furrowing machine, and relates to the technical field of cutterhead parameter design, and the method specifically comprises the steps: collecting a plurality of groups of cutterhead characteristic parameters and blade parameters, taking the angle between a vertical plate and an arc-shaped plate and the ground clearance of a soil scraping plate as constant equipment parameters, constructing an initial population, and setting the initial population as an initial population; establishing a collapse risk assessment model, determining a risk coefficient by using an expert scoring method, training and verifying the model, performing data processing and correlation analysis, and generating a soil bearing coefficient and a soil uniformity coefficient, so as to assess the stability of the surrounding ditch and maximize a comprehensive assessment coefficient as a target. And iteratively optimizing the cutterhead parameters through a genetic algorithm, and extracting optimal cutterhead parameters. Based on a multi-objective optimization scheme, when the cutter parameters are designed, accurate optimization of the cutter parameters is realized, so that a uniform soil treatment effect is generated, the operation effect is improved, and positive influences on soil health and crop growth are also generated.

Description

Technical Field

[0001] The invention relates to the technical field of cutter disc parameter design, and in particular to a cutter disc parameter design method and system for a rapeseed trenching machine. Background Art

[0002] At present, the depths of the three trenches (side trench, waist trench and surrounding trench) in rapeseed planting are basically the same, which leads to slow drainage of water in the field. Therefore, the depth of the surrounding trench must be deepened. However, the digging of surrounding trenches is mainly done manually, and there is a lack of machines for digging surrounding trenches. Considering the labor costs, economic benefits and actual conditions of production, accelerating the development of rapeseed surrounding trench digging technology and equipment is of great significance to reducing yield losses and lowering production costs.

[0003] The existing technology only focuses on the stability of the ditch wall in the design of the cutter disc parameters of the ditch machine, and does not include the soil uniformity and bearing capacity of the ditch surface into the evaluation system. This single goal setting leads to inaccurate optimization of the cutter disc parameters during the design of the cutter disc parameters, resulting in uneven soil treatment effects, which not only affects the operating results, but also has a negative impact on soil health and crop growth.

[0004] The above information disclosed in this Background section is only for enhancement of understanding of the background of the present disclosure and therefore it may contain information that does not constitute the prior art that is already known to one of ordinary skill in the art. Summary of the invention

[0005] The object of the present invention is to provide a method and system for designing parameters of a cutter head for a rapeseed trenching machine, so as to solve the problems raised in the above-mentioned background technology.

[0006] To achieve the above object, the present invention provides the following technical solutions: A method for designing parameters of a cutter head for a rapeseed trenching machine, the specific steps comprising: S1. Collect multiple sets of known cutter disc parameters of the trenching machine, wherein the cutter disc parameters include cutter disc characteristic parameters and blade parameters on the cutter disc, and obtain the angle between the vertical plate and the curved plate of the trenching machine and the height of the scraper plate above the ground, and use the angle between the vertical plate and the curved plate of the trenching machine and the height of the scraper plate above the ground as constant equipment parameters. The cutter disc characteristic parameters include the rotation speed of the cutter disc, the outer diameter of the cutter disc, the vibration frequency of the cutter disc and the amplitude of the cutter disc. The blade parameters include the horizontal distance between the inner circle blades, the vertical distance between the inner circle blades and the outer circle blades, the spacing between the inner circle blades, the spacing between the outer circle blades, the inner circle blade angle and the outer circle blade angle. Multiple sets of known cutter disc parameters and constant equipment parameters are spliced ​​to construct individuals in the initial population; S2. Construct a collapse risk assessment model, take the rotation speed, outer diameter, vibration frequency and amplitude of the cutter disc of the individuals in multiple groups of initial populations as input, determine the trench wall collapse risk coefficient by the expert group scoring method, and train the collapse risk assessment model with the trench wall collapse risk coefficient as a label; S3. The horizontal distance between the inner ring blades, the vertical distance between the inner ring blades and the outer ring blades, the spacing between the inner ring blades, the spacing between the outer ring blades, the angle of the inner ring blades and the angle of the outer ring blades of the individuals in the initial population are processed and correlation analyzed to generate a soil bearing coefficient for evaluating the soil bearing capacity; the rotation speed of the cutter disc, the angle between the vertical plate and the arc plate and the height of the scraper plate from the ground of the individuals in the initial population are processed and correlation analyzed to generate a soil uniformity coefficient for evaluating the uniformity of the surface of the ditch opened by the ditch opener; the ditch wall collapse risk factor, the soil bearing coefficient and the soil uniformity coefficient are processed and correlation analyzed to generate a comprehensive evaluation coefficient for evaluating the stability of the ditch opened by the ditch opener; S4. Taking the maximization of the comprehensive evaluation coefficient as the objective function, and constructing the constraints of the cutter parameters and constant parameters, the individuals in the initial population are iteratively optimized through the genetic algorithm under the constraints to obtain the optimal individuals. Based on the optimal individuals, the optimal values ​​of the cutter parameters are extracted.

[0007] Furthermore, multiple sets of known cutter parameters and constant equipment parameters are spliced ​​together to construct individuals in the initial population. The specific process is as follows: Collect known cutterhead parameters, including cutterhead speed , outer diameter of the cutter disc , the vibration frequency of the cutter head , Amplitude of the cutter head , horizontal distance between inner ring blades , the vertical distance between the inner ring blade and the outer ring blade , the spacing between the inner ring blades , the spacing between the outer ring blades , Inner blade angle And outer blade angle , the constant device parameter combination is calibrated as ,and , , They represent the angles of the vertical plate and the curved plate and the height of the scraper plate from the ground in the constant equipment parameter combination, and the initial population formed by splicing is calibrated as , and the initial population , is the first Individuals, is the index of the individual in the initial population, and , m is the number of individuals in the initial population, ; in, Respectively The rotation speed of each individual cutter disc, the outer diameter of the cutter disc, the vibration frequency of the cutter disc, the amplitude of the cutter disc, the horizontal distance between the inner ring blades, the vertical distance between the inner ring blades and the outer ring blades, the spacing between the inner ring blades, the spacing between the outer ring blades, the inner ring blade angle and the outer ring blade angle.

[0008] Furthermore, the collapse risk assessment model is composed of a deep neural network based on a multilayer perceptron, wherein the deep neural network of the multilayer perceptron includes an input layer, a first hidden layer, a second hidden layer, a third hidden layer and an output layer, wherein the first hidden layer, the second hidden layer and the third hidden layer each have at least two neurons, and each uses ReLU as an activation function; The process of training the collapse risk assessment model is as follows: According to the known individual cutter disc speed, cutter disc outer diameter, cutter disc vibration frequency and cutter disc amplitude in the initial population, the corresponding ditch wall collapse risk coefficient is determined based on the expert scoring method. The larger the ditch wall collapse risk coefficient, the higher the ditch collapse risk, indicating that the stability of the ditch is worse. The rotation speed, outer diameter, vibration frequency and amplitude of the cutter disc of the individuals in the initial population are used as input, and the risk coefficient of trench wall collapse is used as the output label for training. The mean square error is used as the loss function. When the mean square error is When the collapse risk assessment model is within the range, the training of the collapse risk assessment model is completed.

[0009] Furthermore, the horizontal distance between the inner blades, the vertical distance between the inner blades and the outer blades, the spacing between the inner blades, the spacing between the outer blades, the inner blade angles and the outer blade angles of the individuals in the initial population are processed and correlation analyzed to generate a soil bearing coefficient for evaluating the soil bearing capacity, based on the following formula: ; in, is the soil bearing coefficient, is the exponential factor of the distance between the inner and outer ring blades, , is the optimum spacing between the inner ring blades, is the optimal spacing between the outer ring blades, The best angle for the inner blade. The optimum angle for the outer blade.

[0010] Furthermore, the rotation speed of the cutter disc, the angle between the vertical plate and the curved plate, and the height of the scraper plate from the ground of the individuals in the initial population are processed and correlated to generate a soil uniformity coefficient for evaluating the uniformity of the ditch surface opened by the ditch opener, based on the following formula: ; in, is the soil uniformity coefficient, is the angle between the vertical plate and the curved plate, is the height of the scraper board from the ground, , are constants, is the weight coefficient of the cutter head speed, is the weight coefficient of the angle between the vertical plate and the curved plate, is the weight coefficient of the height of the scraper board from the ground, is the optimal rotation speed of the cutter disc, is the optimal angle between the vertical board and the curved board. The best height of the scraper board from the ground. , .

[0011] Furthermore, the ditch wall collapse risk factor, soil bearing coefficient and soil uniformity coefficient are processed and correlated to generate a comprehensive evaluation coefficient for evaluating the stability of the ditch opened by the ditch opener, based on the following formula: ; in, is the comprehensive evaluation coefficient, is the risk factor of trench wall collapse, is the weight coefficient of soil bearing coefficient, is the weight coefficient of soil uniformity coefficient, is the weight coefficient of the ditch wall collapse risk factor.

[0012] Furthermore, the specific process of step S4 is as follows: A balance point is sought between the ditch wall collapse risk factor, soil bearing factor and soil uniformity factor to maximize the comprehensive evaluation factor. Maximization is the optimization goal, for the initial population Perform iterative optimization, that is, the initial population The individuals in the selection, crossover and mutation operations are performed. In the iterative optimization process, constraints should be set, that is, the rotation speed of the cutter head should be set. , outer diameter of the cutter disc , the vibration frequency of the cutter head , Amplitude of the cutter head , horizontal distance between inner ring blades , the vertical distance between the inner ring blade and the outer ring blade , the spacing between the inner ring blades , the spacing between the outer ring blades , Inner blade angle And outer blade angle The maximum and minimum values ​​of the cutter head speed , outer diameter of the cutter disc , the vibration frequency of the cutter head , Amplitude of the cutter head , horizontal distance between inner ring blades , the vertical distance between the inner ring blade and the outer ring blade , the spacing between the inner ring blades , the spacing between the outer ring blades , Inner blade angle And outer blade angle Within the constraints of Iterative optimization, specifically, select the individuals with the highest comprehensive evaluation coefficient as the parent generation, exchange and combine the genes of the parent individuals through crossover operation, generate new individuals, and then adjust the rotation speed of the cutterhead in the newly generated individuals. , outer diameter of the cutter disc , the vibration frequency of the cutter head , Amplitude of the cutter head , horizontal distance between inner ring blades , the vertical distance between the inner ring blade and the outer ring blade , the spacing between the inner ring blades , the spacing between the outer ring blades , Inner blade angle And outer blade angle After the genes are mutated, the selection, crossover, and mutation operations are repeated until the predetermined number of iterations is reached; In the initial population After iterative optimization, the optimal individual is calibrated as The optimal value of the cutterhead parameter is the cutterhead speed , outer diameter of the cutter disc , the vibration frequency of the cutter head , Amplitude of the cutter head , horizontal distance between inner ring blades , the vertical distance between the inner ring blade and the outer ring blade , the spacing between the inner ring blades , the spacing between the outer ring blades , Inner blade angle And outer blade angle .

[0013] To achieve the above object, the present invention also provides the following technical solutions: A system for designing parameters of a cutter disc for a rapeseed trenching machine, the system being used to execute any of the above-mentioned methods for designing parameters of a cutter disc for a rapeseed trenching machine, comprising: A data collection and population construction module is used to collect multiple sets of known cutter disc parameters of the trenching machine, wherein the cutter disc parameters include cutter disc characteristic parameters and blade parameters on the cutter disc, and obtain the angle between the vertical plate and the curved plate of the trenching machine and the height of the scraper plate above the ground, and use the angle between the vertical plate and the curved plate of the trenching machine and the height of the scraper plate above the ground as constant equipment parameters. The cutter disc characteristic parameters include the rotation speed of the cutter disc, the outer diameter of the cutter disc, the vibration frequency of the cutter disc and the amplitude of the cutter disc. The blade parameters include the horizontal distance between the inner circle blades, the vertical distance between the inner circle blades and the outer circle blades, the spacing between the inner circle blades, the spacing between the outer circle blades, the inner circle blade angle and the outer circle blade angle. Multiple sets of known cutter disc parameters and constant equipment parameters are spliced ​​to construct individuals in the initial population; The risk assessment module is used to construct a collapse risk assessment model. The rotation speed, outer diameter, vibration frequency and amplitude of the cutter disc of the individuals in multiple groups of initial populations are used as inputs. The trench wall collapse risk coefficient is determined by the expert group scoring method. The trench wall collapse risk coefficient is used as a label to train the collapse risk assessment model. The data processing and analysis module is used to process the horizontal distance between the inner ring blades, the vertical distance between the inner ring blades and the outer ring blades, the spacing between the inner ring blades, the spacing between the outer ring blades, the angle of the inner ring blades and the angle of the outer ring blades of the individuals in the initial population, and perform correlation analysis to generate a soil bearing coefficient for evaluating the soil bearing capacity, process the rotation speed of the cutter disc, the angle between the vertical plate and the arc plate, and the height of the scraper plate from the ground of the individuals in the initial population, and perform correlation analysis to generate a soil uniformity coefficient for evaluating the uniformity of the surface of the surrounding ditch opened by the surrounding ditch opening machine, process the ditch wall collapse risk factor, the soil bearing coefficient and the soil uniformity coefficient, and perform correlation analysis to generate a comprehensive evaluation coefficient for evaluating the stability of the surrounding ditch opened by the surrounding ditch opening machine; The parameter optimization module is used to maximize the comprehensive evaluation coefficient as the objective function and construct the constraints of the cutter parameters and constant parameters. Under the constraints, the individuals in the initial population are iteratively optimized through the genetic algorithm to obtain the optimal individuals. Based on the optimal individuals, the optimal values ​​of the cutter parameters are extracted.

[0014] Compared with the prior art, the present invention has the following beneficial effects: The present invention collects multiple sets of known cutter disc parameters of the trenching machine, obtains the angle between the vertical plate and the curved plate of the trenching machine, and the height of the scraper plate from the ground, takes the angle between the vertical plate and the curved plate of the trenching machine, and the height of the scraper plate from the ground as constant equipment parameters, splices multiple sets of known cutter disc parameters and constant equipment parameters, constructs individuals in the initial population, constructs a collapse risk assessment model, obtains the ditch wall collapse risk coefficient, obtains the soil bearing coefficient and the soil uniformity coefficient according to the parameters of the individuals in the initial population, performs data processing on the ditch wall collapse risk coefficient, the soil bearing coefficient and the soil uniformity coefficient, generates a comprehensive evaluation coefficient, takes the maximization of the comprehensive evaluation coefficient as the objective function, iteratively optimizes the individuals in the initial population through a genetic algorithm, and extracts the optimal value of the cutter disc parameters. Therefore, based on the multi-objective optimization scheme, when designing the cutter disc parameters, the accurate optimization of the cutter disc parameters is achieved, thereby producing a uniform soil treatment effect, which not only improves the operation effect, but also has a positive impact on soil health and crop growth. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] Figure 1 It is a schematic diagram of the overall method flow of the present invention; Figure 2 This is a block diagram of the module composition of the present invention. DETAILED DESCRIPTION

[0016] In order to make the objectives, technical solutions and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with specific embodiments.

[0017] It should be noted that, unless otherwise defined, the technical terms or scientific terms used in the present invention should be understood by people with ordinary skills in the field to which the present invention belongs. The words "first", "second" and similar words used in the present invention do not indicate any order, quantity or importance, but are only used to distinguish different components. "Include" or "comprise" and similar words mean that the elements or objects appearing before the word include the elements or objects listed after the word and their equivalents, without excluding other elements or objects. "Connect" or "connected" and similar words are not limited to physical or mechanical connections, but may include electrical connections, whether direct or indirect. "Up", "down", "left", "right" and the like are only used to indicate relative positional relationships. When the absolute position of the described object changes, the relative positional relationship may also change accordingly.

[0018] Embodiment 1: See also Figure 1 , the present invention provides a technical solution: A method for designing parameters of a cutter head for a rapeseed trenching machine, the specific steps comprising: S1. Collect multiple sets of known cutter disc parameters of the trenching machine, wherein the cutter disc parameters include cutter disc characteristic parameters and blade parameters on the cutter disc, and obtain the angle between the vertical plate and the curved plate of the trenching machine and the height of the scraper plate above the ground, and use the angle between the vertical plate and the curved plate of the trenching machine and the height of the scraper plate above the ground as constant equipment parameters. The cutter disc characteristic parameters include the rotation speed of the cutter disc, the outer diameter of the cutter disc, the vibration frequency of the cutter disc and the amplitude of the cutter disc. The blade parameters include the horizontal distance between the inner circle blades, the vertical distance between the inner circle blades and the outer circle blades, the spacing between the inner circle blades, the spacing between the outer circle blades, the inner circle blade angle and the outer circle blade angle. Multiple sets of known cutter disc parameters and constant equipment parameters are spliced ​​to construct individuals in the initial population; The parameters of the cutter head, the angles of the vertical plate and the curved plate of the trenching machine, and the height of the scraper plate from the ground can be found in the original equipment manual; S2. Construct a collapse risk assessment model, take the rotation speed, outer diameter, vibration frequency and amplitude of the cutter disc of the individuals in multiple groups of initial populations as input, determine the trench wall collapse risk coefficient by the expert group scoring method, and train the collapse risk assessment model with the trench wall collapse risk coefficient as a label; S3. The horizontal distance between the inner ring blades, the vertical distance between the inner ring blades and the outer ring blades, the spacing between the inner ring blades, the spacing between the outer ring blades, the angle of the inner ring blades and the angle of the outer ring blades of the individuals in the initial population are processed and correlation analyzed to generate a soil bearing coefficient for evaluating the soil bearing capacity; the rotation speed of the cutter disc, the angle between the vertical plate and the arc plate and the height of the scraper plate from the ground of the individuals in the initial population are processed and correlation analyzed to generate a soil uniformity coefficient for evaluating the uniformity of the surface of the ditch opened by the ditch opener; the ditch wall collapse risk factor, the soil bearing coefficient and the soil uniformity coefficient are processed and correlation analyzed to generate a comprehensive evaluation coefficient for evaluating the stability of the ditch opened by the ditch opener; S4. Taking the maximization of the comprehensive evaluation coefficient as the objective function, and constructing the constraints of the cutter parameters and constant parameters, the individuals in the initial population are iteratively optimized through the genetic algorithm under the constraints to obtain the optimal individuals. Based on the optimal individuals, the optimal values ​​of the cutter parameters are extracted.

[0019] On the basis of the above embodiment, multiple groups of known cutter head parameters and constant equipment parameters are spliced ​​to construct individuals in the initial population. The specific process is as follows: Collect known cutterhead parameters, including cutterhead speed , outer diameter of the cutter disc , the vibration frequency of the cutter head , Amplitude of the cutter head , horizontal distance between inner ring blades , the vertical distance between the inner ring blade and the outer ring blade , the spacing between the inner ring blades , the spacing between the outer ring blades , Inner blade angle And outer blade angle , the constant device parameter combination is calibrated as ,and , , They represent the angles of the vertical plate and the curved plate and the height of the scraper plate from the ground in the constant equipment parameter combination, and the initial population formed by splicing is calibrated as , and the initial population , is the first Individuals, is the index of the individual in the initial population, and , m is the number of individuals in the initial population, ; in, Respectively The rotation speed of each individual cutter disc, the outer diameter of the cutter disc, the vibration frequency of the cutter disc, the amplitude of the cutter disc, the horizontal distance between the inner ring blades, the vertical distance between the inner ring blades and the outer ring blades, the spacing between the inner ring blades, the spacing between the outer ring blades, the inner ring blade angle and the outer ring blade angle.

[0020] On the basis of the above embodiment, the collapse risk assessment model is composed of a deep neural network based on a multilayer perceptron, and the deep neural network of the multilayer perceptron includes an input layer, a first hidden layer, a second hidden layer, a third hidden layer and an output layer, and the first hidden layer, the second hidden layer and the third hidden layer each have at least two neurons, and each uses ReLU as an activation function; In this embodiment, the input features of the deep learning network of the multilayer perceptron include four features: the rotation speed of the cutter disc, the outer diameter of the cutter disc, the vibration frequency of the cutter disc, and the amplitude of the cutter disc.

[0021] The structure of the deep learning network of multi-layer perceptron is: Input layer: receives input of 4 features; The first hidden layer has 64 neurons and uses ReLU as the activation function. The second hidden layer has 32 neurons and also uses the ReLU activation function. The third hidden layer has 16 neurons and uses the ReLU activation function. Output layer: has a single neuron, the risk factor of groove wall collapse.

[0022] The process of training the collapse risk assessment model is as follows: According to the known individual cutter disc speed, cutter disc outer diameter, cutter disc vibration frequency and cutter disc amplitude in the initial population, the corresponding ditch wall collapse risk coefficient is determined based on the expert scoring method. The larger the ditch wall collapse risk coefficient, the higher the ditch collapse risk, indicating that the stability of the ditch is worse. The rotation speed, outer diameter, vibration frequency and amplitude of the cutter disc of the individuals in the initial population are used as input, and the risk coefficient of trench wall collapse is used as the output label for training. The mean square error is used as the loss function. When the mean square error is When the collapse risk assessment model is within the range, the training of the collapse risk assessment model is completed.

[0023] Based on the above embodiment, the correlation between the horizontal distance between the inner ring blades, the vertical distance between the inner ring blades and the outer ring blades, the spacing between the inner ring blades, the spacing between the outer ring blades, the inner ring blade angle, the outer ring blade angle and the soil bearing capacity is as follows: The horizontal distance between the inner ring blades is positively correlated with the soil bearing capacity, because when the horizontal distance increases, the cutting area of ​​the blade increases, which can disturb the soil more comprehensively, help to increase the looseness of the soil and enhance the soil's compressive resistance.

[0024] The vertical distance between the inner and outer blades is positively correlated with the soil bearing capacity, because the increase in vertical distance means that the blades can penetrate deeper into the soil and perform more effective cutting, especially in harder or dense soils. Deeper cutting can bring more soil disturbance, which helps improve the soil structure and increase the porosity of the soil, thereby improving its bearing capacity.

[0025] Within a certain range, the spacing between the inner blades, the spacing between the outer blades and the soil bearing capacity are positively correlated. Because the spacing between the blades increases, the overlapping area can be increased, and the overlapping area makes the cutting process more continuous, so that the cutting areas of each blade overlap each other, avoiding the uncut soil area, thereby improving the soil bearing capacity as a whole; After exceeding the optimal spacing, the spacing between the inner ring blades, the spacing between the outer ring blades and the soil bearing capacity are negatively correlated. This is because the increase in the spacing between the blades leads to uneven cutting, which damages the soil structure and reduces the bearing capacity.

[0026] Within a certain range, the inner blade angle, outer blade angle and soil bearing capacity are positively correlated. As the blade angle increases, the cutting force increases, which improves the cutting effect, thereby improving the soil structure and the overall stability and bearing capacity of the soil. After exceeding the optimal angle, the inner blade angle, outer blade angle and soil bearing capacity are negatively correlated. This is because the increase in blade angle increases the cutting force, which in turn leads to excessive cutting of the soil, causing the destruction of soil particles and loose structure, thereby reducing soil stability and bearing capacity.

[0027] Therefore, according to the correlation between the horizontal distance between the inner ring blades, the vertical distance between the inner ring blades and the outer ring blades, the spacing between the inner ring blades, the spacing between the outer ring blades, the inner ring blade angle, the outer ring blade angle and the soil bearing capacity, the horizontal distance between the inner ring blades, the vertical distance between the inner ring blades and the outer ring blades, the spacing between the inner ring blades, the spacing between the outer ring blades, the inner ring blade angle and the outer ring blade angle of the individuals in the initial population are processed and correlation analyzed to generate a soil bearing coefficient for evaluating soil bearing capacity, based on the following formula: ; in, is the soil bearing coefficient, is the exponential factor of the distance between the inner and outer ring blades, , is the optimum spacing between the inner ring blades, is the optimal spacing between the outer ring blades, The best angle for the inner blade. The optimum angle for the outer blade.

[0028] Design a series of experiments to gradually adjust the inner and outer blade spacing, inner and outer blade angles, and evaluate the soil bearing capacity and cutting effect under each configuration; Spacing experiment: Fixed the outer ring blade spacing, inner ring and outer ring blade angles, tested the soil bearing capacity and cutting effect of different inner ring blade spacings, and drew a relationship diagram between different inner ring blade spacings and soil bearing capacity based on the soil bearing capacity and cutting effect to determine the optimal spacing between the inner ring blades. ; Fixed the inner ring blade spacing, inner ring and outer ring blade angles, tested the soil bearing capacity and cutting effect of different outer ring blade spacings, and based on the soil bearing capacity and cutting effect, drew a relationship diagram between different outer ring blade spacings and soil bearing capacity to determine the optimal spacing between the outer ring blades. .

[0029] Angle experiment: Fix the outer ring blade angle and the distance between the inner and outer ring blades, test the soil bearing capacity and cutting effect of different inner ring blade angles, draw a relationship diagram between different inner ring blade angles and soil bearing capacity based on the soil bearing capacity and cutting effect, and determine the optimal angle of the inner ring blade ; Fixed the inner ring blade angle and the distance between the inner ring and outer ring blades, tested the soil bearing capacity and cutting effect of different outer ring blade angles, and based on the soil bearing capacity and cutting effect, drew a relationship diagram between different outer ring blade angles and soil bearing capacity to determine the best angle of the outer ring blade .

[0030] Soil bearing factor The value range is ; when When it is close to 0, it means that the blade configuration is unreasonable, resulting in ineffective soil cutting, and the soil bearing capacity is low; when When it is close to 1, it means that the blade configuration has reached the optimal state, and the cutting and load-bearing capacity is maximum.

[0031] Therefore, the soil bearing factor The larger it is, the greater the soil bearing capacity.

[0032] The reason why the above function form is used to express the functional relationship between the horizontal distance between the inner ring blades, the vertical distance between the inner ring blades and the outer ring blades, the spacing between the inner ring blades, the spacing between the outer ring blades, the inner ring blade angle and the outer ring blade angle and the soil bearing capacity is as follows: First, the formula for the soil bearing coefficient uses a fractional form because when the blade spacing and angle are within the optimal range, the multiplication form is used to emphasize the joint influence of various factors; after exceeding the optimal value, the denominator form is used to reduce the bearing capacity.

[0033] Second, when the horizontal or vertical distance between the blades increases, the increase in the soil's bearing capacity will gradually decrease, and the logarithmic function It can effectively express this "diminishing marginal effect", that is, the rate of increase in soil carrying capacity slows down with increasing distance.

[0034] Third, using exponential function , The value of is between 0 and 3. When the blade spacing changes, the influence on soil bearing capacity is lower. When the blade spacing is changed, the influence on soil bearing capacity is higher, and the influence of the spacing on soil bearing capacity can be flexibly controlled, which reflects the complex relationship between blade spacing, cutting force and soil bearing capacity.

[0035] Fourth, sine function It is periodic and can well describe the change of angle. When the angle of the blade changes between 0° and 90°, the sine function can show how this change affects the cutting effect. The value range of the sine function is [0,1], which means that no matter how the angle changes, the value of the function always remains within this range. This feature can limit the impact of the angle to a reasonable range, thereby avoiding unreasonable extreme values ​​of the cutting effect due to angle changes.

[0036] Based on the above embodiment, the correlation between the rotation speed of the cutter head, the angle between the vertical plate and the curved plate, the height of the scraper plate from the ground and the uniformity of the trench surface is as follows: Within a certain speed range, the speed of the cutter disc is positively correlated with the uniformity of the trench surface. This is because when the speed increases, the cutting and handling capabilities of the cutter disc are enhanced, which can more effectively distribute the soil evenly, reduce soil accumulation and unevenness, and thus improve the uniformity of the trench surface. When the rotation speed exceeds the optimal speed, the rotation speed of the cutter disc is negatively correlated with the uniformity of the trench surface. This is because the excessively high rotation speed will cause the soil to turn over quickly, resulting in uneven mixing of the surface and bottom layers of soil, increasing soil disturbance and instability, resulting in inconsistent height differences on the trench surface and reducing uniformity.

[0037] Within a certain range, the angle between the vertical plate and the curved plate is positively correlated with the uniformity of the trench surface. This is because the increase in the angle between the vertical plate and the curved plate can help improve the fluidity and cutting efficiency of the soil, help distribute the soil more evenly, reduce accumulation, and improve the uniformity of the trench surface.

[0038] After exceeding the optimal angle, the angle between the vertical plate and the curved plate is negatively correlated with the uniformity of the trench surface. Because the blade cannot effectively cut into the soil due to the excessively large angle, some soil is not cut or ignored, resulting in uneven soil distribution in the trench. Too large an angle causes soil to accumulate in certain areas. Because the cutting effect is not enough to remove the soil evenly, the accumulation phenomenon will directly affect the flatness and uniformity of the trench surface.

[0039] Within a certain range, the height of the scraper blade from the ground is positively correlated with the uniformity of the trench surface. This is because the increase in the height of the scraper blade from the ground enables the scraper blade to cut the soil deeper, which helps to remove soil and debris more effectively, thereby improving the uniformity of the trench surface, ensuring that the soil is fully processed and reducing uneven distribution.

[0040] When the optimal height is exceeded, the height of the scraper blade from the ground is negatively correlated with the uniformity of the trench surface. This is because if the height from the ground is too high, the cutting effect will be weakened, the soil cannot be effectively removed, and even soil will accumulate in certain areas, causing the trench surface to become uneven.

[0041] Therefore, according to the correlation between the rotation speed of the cutter disc, the angle between the vertical plate and the curved plate, the height of the scraper plate from the ground and the uniformity of the ditch surface, the rotation speed of the cutter disc, the angle between the vertical plate and the curved plate and the height of the scraper plate from the ground of the individuals in the initial population are processed and correlation analysis is performed to generate the soil uniformity coefficient for evaluating the uniformity of the ditch surface opened by the ditch opener, based on the following formula: ; in, is the soil uniformity coefficient, is the angle between the vertical plate and the curved plate, is the height of the scraper board from the ground, , are constants, is the weight coefficient of the cutter head speed, is the weight coefficient of the angle between the vertical plate and the curved plate, is the weight coefficient of the height of the scraper board from the ground, is the optimal rotation speed of the cutter disc, is the optimal angle between the vertical board and the curved board. The optimum height of the scraper board from the ground.

[0042] Design a series of experiments to gradually adjust the angles of the vertical plate and the curved plate, and the height of the scraper plate from the ground, and evaluate the uniformity of the trench surface opened by the trencher under each configuration; Setting multiple speeds , Angle between vertical board and curved board , Height of scraper board from ground ; Under controlled conditions (such as the same soil type and moisture), experiments were conducted with different cutter head speeds, vertical plate angles, and scraper board heights. In each configuration, the trencher was operated on the same length of soil, and the uniformity of each operation was recorded. Plot the relationship between different cutter head speeds, riser angles, and scraper board heights and uniformity to identify the optimal speed ,angle ,high .

[0043] Soil uniformity coefficient The value range is ; when When it is close to 0, it means that the cutter head speed, vertical plate angle and scraper board height are not configured properly, and the uniformity of the ditch surface is low; when When it is close to 1, it means that the cutter head speed, vertical plate angle and scraper board height configuration have reached the optimal state, and the ditch surface is highly uniform.

[0044] Therefore, the soil uniformity coefficient The larger it is, the more uniform the surface of the ditch is.

[0045] The reason why the above function form is used to express the functional relationship between the rotation speed of the cutter head, the angle between the vertical plate and the curved plate, the height of the scraper plate from the ground and the soil uniformity coefficient is as follows: First, use the fractional form (such as ), which is used to illustrate that with the increase of rotation speed, the soil uniformity shows a linear enhancement trend, but at the same time, the constant It can prevent the unreasonable situation that excessive uniformity is excessively improved due to excessive rotation speed, and ensure reasonable results.

[0046] Second, the periodicity of angle changes. When the angle of the blade changes within a certain range (such as 0° to 30°), the sine function can show how this change affects the uniformity of the soil. As the angle increases, the uniformity of the soil will gradually increase. The value range of the sine function is between [0,1], which can limit the impact of the angle on the uniformity coefficient within a reasonable range and avoid the occurrence of extreme values.

[0047] Third, as the height of the scraper plate from the ground increases, the soil uniformity coefficient will gradually increase, but the increase will gradually decrease. The logarithmic function can effectively describe this diminishing marginal effect, reflecting that the effect of increasing height on improving soil uniformity gradually weakens.

[0048] Generally speaking, the cutter head speed has a greater impact on the uniformity of the soil, because it directly determines the soil force and cutting speed, and is often the key factor affecting the soil treatment effect. Therefore, the correlation between the cutter head speed and the uniformity of the soil is the greatest, and the weight coefficient of the cutter head speed is maximum; The angle between the vertical plate and the curved plate affects the cutting and disturbance mode of the soil. The appropriate cutting angle can optimize the turning and mixing of the soil, making the soil more uniform during the processing. Although the change of the angle between the vertical plate and the curved plate can effectively affect the disturbance of the soil, its effect is indirect and depends on the cutting force provided by the cutter head speed. The correlation between the angle between the vertical plate and the curved plate and the uniformity of the soil is lower than the cutter head speed. The weight coefficient of the angle between the vertical plate and the curved plate is Next is; The change of the height of the scraper plate above the ground has a relatively small effect on the uniformity of the soil, because it mainly plays an auxiliary role rather than directly changing the mechanism of soil cutting and disturbance. Its role is more reflected in the fine-tuning of the final effect rather than the main driving factor. The correlation between the height of the scraper plate above the ground and the uniformity of the soil is lower than the angle between the vertical plate and the curved plate. The weight coefficient of the height of the scraper plate above the ground is Minimum.

[0049] In summary, setting ,and .

[0050] On the basis of the above embodiment, the ditch wall collapse risk factor, soil bearing coefficient and soil uniformity coefficient are processed and correlated to generate a comprehensive evaluation coefficient for evaluating the stability of the ditch opened by the ditch opener, based on the following formula: ; in, is the comprehensive evaluation coefficient, is the risk factor of trench wall collapse, is the weight coefficient of soil bearing coefficient, is the weight coefficient of soil uniformity coefficient, is the weight coefficient of the ditch wall collapse risk factor.

[0051] When evaluating the stability of the trench opened by the trenching machine, more attention is paid to the soil bearing capacity, followed by the uniformity of the surface, and finally the risk of trench collapse. Therefore, the weight coefficient is set according to the following principles: Soil bearing capacity is prioritized: The soil bearing coefficient directly reflects the ability of the soil to support the ditch wall and is a key factor affecting the stability of the ditch wall. A higher weight coefficient is assigned to it. ; The uniformity of the cabin surface is second: uniform soil is more conducive to uniform stress and reduces the risk of local overload and collapse, but its impact is indirect, so it is assigned a medium weight coefficient. ; The risk of trench collapse is the lowest: the trench wall collapse risk factor directly measures the possibility of collapse and affects the safety of the trench. A high risk factor means a higher risk of collapse. This negative impact is reflected as a subtraction in the formula, and a lower weight coefficient is assigned to it. .

[0052] Based on the above embodiment, the specific process of step S4 is as follows: A balance point is sought between the ditch wall collapse risk factor, soil bearing factor and soil uniformity factor to maximize the comprehensive evaluation factor. Maximization is the optimization goal, for the initial population Perform iterative optimization, that is, the initial population The individuals in the selection, crossover and mutation operations are performed. In the iterative optimization process, constraints should be set, that is, the rotation speed of the cutter head should be set. , outer diameter of the cutter disc , the vibration frequency of the cutter head , Amplitude of the cutter head , horizontal distance between inner ring blades , the vertical distance between the inner ring blade and the outer ring blade , the spacing between the inner ring blades , the spacing between the outer ring blades , Inner blade angle And outer blade angle The maximum and minimum values ​​of the cutter head speed , outer diameter of the cutter disc , the vibration frequency of the cutter head , Amplitude of the cutter head , horizontal distance between inner ring blades , the vertical distance between the inner ring blade and the outer ring blade , the spacing between the inner ring blades , the spacing between the outer ring blades , Inner blade angle And outer blade angle Within the constraints of Iterative optimization, specifically, select individuals with the top comprehensive evaluation coefficient as parents, the top refers to individuals in the top 50% of the comprehensive evaluation coefficient, and exchange and combine the genes of the parent individuals through crossover operations to generate new individuals. The new individuals are used to generate new ditch wall collapse risk coefficients, soil bearing coefficients, and soil uniformity coefficients. The new ditch wall collapse risk coefficients, soil bearing coefficients, and soil uniformity coefficients are used to generate new comprehensive evaluation coefficients. Continue iterative optimization and adjust the cutter head speed in the newly generated individuals. , outer diameter of the cutter disc , the vibration frequency of the cutter head , Amplitude of the cutter head , horizontal distance between inner ring blades , the vertical distance between the inner ring blade and the outer ring blade , the spacing between the inner ring blades , the spacing between the outer ring blades , Inner blade angle And outer blade angle After the genes are mutated, the selection, crossover, and mutation operations are repeated until the predetermined number of iterations is reached; In the initial population After iterative optimization, the optimal individual is calibrated as The optimal value of the cutterhead parameter is the cutterhead speed , outer diameter of the cutter disc , the vibration frequency of the cutter head , Amplitude of the cutter head , horizontal distance between inner ring blades , the vertical distance between the inner ring blade and the outer ring blade , the spacing between the inner ring blades , the spacing between the outer ring blades , Inner blade angle And outer blade angle .

[0053] See also Figure 2 , the present invention provides a technical solution: A system for designing parameters of a cutter disc for a rapeseed trenching machine, the system being used to execute any of the above-mentioned methods for designing parameters of a cutter disc for a rapeseed trenching machine, comprising: A data collection and population construction module is used to collect multiple sets of known cutter disc parameters of the trenching machine, wherein the cutter disc parameters include cutter disc characteristic parameters and blade parameters on the cutter disc, and obtain the angle between the vertical plate and the curved plate of the trenching machine and the height of the scraper plate above the ground, and use the angle between the vertical plate and the curved plate of the trenching machine and the height of the scraper plate above the ground as constant equipment parameters. The cutter disc characteristic parameters include the rotation speed of the cutter disc, the outer diameter of the cutter disc, the vibration frequency of the cutter disc and the amplitude of the cutter disc. The blade parameters include the horizontal distance between the inner circle blades, the vertical distance between the inner circle blades and the outer circle blades, the spacing between the inner circle blades, the spacing between the outer circle blades, the inner circle blade angle and the outer circle blade angle. Multiple sets of known cutter disc parameters and constant equipment parameters are spliced ​​to construct individuals in the initial population; The risk assessment module is used to construct a collapse risk assessment model. The rotation speed, outer diameter, vibration frequency and amplitude of the cutter disc of the individuals in multiple groups of initial populations are used as inputs. The trench wall collapse risk coefficient is determined by the expert group scoring method. The trench wall collapse risk coefficient is used as a label to train the collapse risk assessment model. The data processing and analysis module is used to process the horizontal distance between the inner ring blades, the vertical distance between the inner ring blades and the outer ring blades, the spacing between the inner ring blades, the spacing between the outer ring blades, the angle of the inner ring blades and the angle of the outer ring blades of the individuals in the initial population, and perform correlation analysis to generate a soil bearing coefficient for evaluating the soil bearing capacity, process the rotation speed of the cutter disc, the angle between the vertical plate and the arc plate, and the height of the scraper plate from the ground of the individuals in the initial population, and perform correlation analysis to generate a soil uniformity coefficient for evaluating the uniformity of the surface of the surrounding ditch opened by the surrounding ditch opening machine, process the ditch wall collapse risk factor, the soil bearing coefficient and the soil uniformity coefficient, and perform correlation analysis to generate a comprehensive evaluation coefficient for evaluating the stability of the surrounding ditch opened by the surrounding ditch opening machine; The parameter optimization module is used to maximize the comprehensive evaluation coefficient as the objective function and construct the constraints of the cutter parameters and constant parameters. Under the constraints, the individuals in the initial population are iteratively optimized through the genetic algorithm to obtain the optimal individuals. Based on the optimal individuals, the optimal values ​​of the cutter parameters are extracted.

[0054] The above formulas are all dimensionless and numerical calculations. The formula is a formula for the most recent real situation obtained by collecting a large amount of data and performing software simulation. The preset parameters in the formula are set by technicians in this field according to actual conditions.

[0055] The above embodiments may be implemented in whole or in part by software, hardware, firmware or any other combination thereof. When implemented using software, the above embodiments may be implemented in whole or in part in the form of a computer program product. Those skilled in the art may appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein may be implemented by computer software, electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed by hardware or software depends on the specific application and design constraints of the technical solution.

[0056] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, and may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0057] The above description is only a specific implementation manner of the present application, but the protection scope of the present application is not limited thereto. Any technician familiar with the technical field can easily think of changes or substitutions within the technical scope disclosed in the present application, which should be included in the protection scope of the present application.

Claims

1. A method for designing parameters of a cutter head for a rapeseed trenching machine, characterized in that: The specific steps include: S1. Collect multiple sets of known cutter disc parameters of the trenching machine, wherein the cutter disc parameters include cutter disc characteristic parameters and blade parameters on the cutter disc, and obtain the angle between the vertical plate and the curved plate of the trenching machine and the height of the scraper plate above the ground, and use the angle between the vertical plate and the curved plate of the trenching machine and the height of the scraper plate above the ground as constant equipment parameters. The cutter disc characteristic parameters include the rotation speed of the cutter disc, the outer diameter of the cutter disc, the vibration frequency of the cutter disc and the amplitude of the cutter disc. The blade parameters include the horizontal distance between the inner circle blades, the vertical distance between the inner circle blades and the outer circle blades, the spacing between the inner circle blades, the spacing between the outer circle blades, the inner circle blade angle and the outer circle blade angle. Multiple sets of known cutter disc parameters and constant equipment parameters are spliced ​​to construct individuals in the initial population; S2. Construct a collapse risk assessment model, take the rotation speed, outer diameter, vibration frequency and amplitude of the cutter disc of the individuals in multiple groups of initial populations as input, determine the trench wall collapse risk coefficient by the expert group scoring method, and train the collapse risk assessment model with the trench wall collapse risk coefficient as a label; S3. The horizontal distance between the inner ring blades, the vertical distance between the inner ring blades and the outer ring blades, the spacing between the inner ring blades, the spacing between the outer ring blades, the angle of the inner ring blades and the angle of the outer ring blades of the individuals in the initial population are processed and correlation analyzed to generate a soil bearing coefficient for evaluating the soil bearing capacity; the rotation speed of the cutter disc, the angle between the vertical plate and the arc plate and the height of the scraper plate from the ground of the individuals in the initial population are processed and correlation analyzed to generate a soil uniformity coefficient for evaluating the uniformity of the surface of the ditch opened by the ditch opener; the ditch wall collapse risk factor, the soil bearing coefficient and the soil uniformity coefficient are processed and correlation analyzed to generate a comprehensive evaluation coefficient for evaluating the stability of the ditch opened by the ditch opener; S4. Taking the maximization of the comprehensive evaluation coefficient as the objective function, and constructing the constraints of the cutter parameters and constant parameters, the individuals in the initial population are iteratively optimized through the genetic algorithm under the constraints to obtain the optimal individuals. Based on the optimal individuals, the optimal values ​​of the cutter parameters are extracted.

2. The method for designing parameters of a cutter head for a rapeseed trenching machine according to claim 1, characterized in that: Multiple sets of known cutter parameters and constant equipment parameters are spliced ​​together to construct individuals in the initial population. The specific process is as follows: Collect known cutterhead parameters, including cutterhead speed , outer diameter of the cutter disc , the vibration frequency of the cutter head , Amplitude of the cutter head , horizontal distance between inner ring blades , the vertical distance between the inner ring blade and the outer ring blade , the spacing between the inner ring blades , the spacing between the outer ring blades , Inner blade angle And outer blade angle , the constant device parameter combination is calibrated as ,and , , They represent the angles of the vertical plate and the curved plate and the height of the scraper plate from the ground in the constant equipment parameter combination, and the initial population formed by splicing is calibrated as , and the initial population , is the first Individuals, is the index of the individual in the initial population, and , m is the number of individuals in the initial population, ; in, Respectively The rotation speed of each individual cutter disc, the outer diameter of the cutter disc, the vibration frequency of the cutter disc, the amplitude of the cutter disc, the horizontal distance between the inner ring blades, the vertical distance between the inner ring blades and the outer ring blades, the spacing between the inner ring blades, the spacing between the outer ring blades, the inner ring blade angle and the outer ring blade angle.

3. The method for designing parameters of a cutter head for a rapeseed trenching machine according to claim 2, characterized in that: The collapse risk assessment model is composed of a deep neural network based on a multilayer perceptron, wherein the deep neural network of the multilayer perceptron includes an input layer, a first hidden layer, a second hidden layer, a third hidden layer and an output layer, wherein the first hidden layer, the second hidden layer and the third hidden layer each have at least two neurons, and each uses ReLU as an activation function; The process of training the collapse risk assessment model is as follows: According to the known individual cutter disc speed, cutter disc outer diameter, cutter disc vibration frequency and cutter disc amplitude in the initial population, the corresponding ditch wall collapse risk coefficient is determined based on the expert scoring method. The larger the ditch wall collapse risk coefficient, the higher the ditch collapse risk, indicating that the stability of the ditch is worse. The rotation speed, outer diameter, vibration frequency and amplitude of the cutter disc of the individuals in the initial population are used as input, and the risk coefficient of trench wall collapse is used as the output label for training. The mean square error is used as the loss function. When the mean square error is When the collapse risk assessment model is within the range, the training of the collapse risk assessment model is completed.

4. The method for designing parameters of a cutter head for a rapeseed trenching machine according to claim 3, characterized in that: The horizontal distance between the inner blades, the vertical distance between the inner blades and the outer blades, the spacing between the inner blades, the spacing between the outer blades, the inner blade angles and the outer blade angles of the individuals in the initial population are processed and correlation analyzed to generate the soil bearing coefficient for evaluating the soil bearing capacity, based on the following formula: ； in, is the soil bearing coefficient, is the exponential factor of the distance between the inner and outer ring blades, , is the optimum spacing between the inner ring blades, is the optimal spacing between the outer ring blades, The best angle for the inner blade. The optimum angle for the outer blade.

5. The method for designing parameters of a cutter head for a rapeseed trenching machine according to claim 4, characterized in that: The data of the rotation speed of the cutter disc, the angle between the vertical plate and the curved plate, and the height of the scraper plate from the ground of the individuals in the initial population are processed and correlation analyzed to generate the soil uniformity coefficient used to evaluate the uniformity of the ditch surface opened by the ditch opener. The formula is as follows: ； in, is the soil uniformity coefficient, is the angle between the vertical plate and the curved plate, is the height of the scraper board from the ground, , are constants, is the weight coefficient of the cutter head speed, is the weight coefficient of the angle between the vertical plate and the curved plate, is the weight coefficient of the height of the scraper board from the ground, is the optimal rotation speed of the cutter disc, is the optimal angle between the vertical board and the curved board. The best height of the scraper board from the ground. , .

6. The method for designing parameters of a cutter head for a rapeseed trenching machine according to claim 5, characterized in that: The ditch wall collapse risk factor, soil bearing coefficient and soil uniformity coefficient are processed and correlated to generate a comprehensive evaluation coefficient for evaluating the stability of the ditch opened by the ditch opener. The formula is as follows: ； in, is the comprehensive evaluation coefficient, is the risk factor of trench wall collapse, is the weight coefficient of soil bearing coefficient, is the weight coefficient of soil uniformity coefficient, is the weight coefficient of the ditch wall collapse risk factor.

7. The method for designing parameters of a cutter head for a rapeseed trenching machine according to claim 6, characterized in that: The specific process of step S4 is as follows: A balance point is sought between the ditch wall collapse risk factor, soil bearing factor and soil uniformity factor to maximize the comprehensive evaluation factor. Maximization is the optimization goal, for the initial population Perform iterative optimization, that is, the initial population The individuals in the selection, crossover and mutation operations are performed. In the iterative optimization process, constraints should be set, that is, the rotation speed of the cutter head should be set. , outer diameter of the cutter disc , the vibration frequency of the cutter head , Amplitude of the cutter head , horizontal distance between inner ring blades , the vertical distance between the inner ring blade and the outer ring blade , the spacing between the inner ring blades , the spacing between the outer ring blades , Inner blade angle And outer blade angle The maximum and minimum values ​​of the cutter head speed , outer diameter of the cutter disc , the vibration frequency of the cutter head , Amplitude of the cutter head , horizontal distance between inner ring blades , the vertical distance between the inner ring blade and the outer ring blade , the spacing between the inner ring blades , the spacing between the outer ring blades , Inner blade angle And outer blade angle Within the constraints of Iterative optimization, specifically, selects individuals with the highest comprehensive evaluation coefficient as parents, exchanges and combines the genes of the parent individuals through crossover operations, generates new individuals, and adjusts the rotation speed of the cutterhead in the newly generated individuals. , outer diameter of the cutter disc , the vibration frequency of the cutter head , Amplitude of the cutter head , horizontal distance between inner ring blades , the vertical distance between the inner ring blade and the outer ring blade , the spacing between the inner ring blades , the spacing between the outer ring blades , Inner blade angle And outer blade angle After the genes are mutated, the selection, crossover, and mutation operations are repeated until the predetermined number of iterations is reached; In the initial population After iterative optimization, the optimal individual is calibrated as The optimal value of the cutterhead parameter is the cutterhead speed , outer diameter of the cutter disc , the vibration frequency of the cutter head , Amplitude of the cutter head , horizontal distance between inner ring blades , the vertical distance between the inner ring blade and the outer ring blade , the spacing between the inner ring blades , the spacing between the outer ring blades , Inner blade angle And outer blade angle .

8. A system for designing parameters of a cutter disc for a rapeseed trenching machine, the system being used to execute a method for designing parameters of a cutter disc for a rapeseed trenching machine according to any one of claims 1 to 7, characterized in that: include: A data collection and population construction module is used to collect multiple sets of known cutter disc parameters of the trenching machine, wherein the cutter disc parameters include cutter disc characteristic parameters and blade parameters on the cutter disc, and obtain the angle between the vertical plate and the curved plate of the trenching machine and the height of the scraper plate above the ground, and use the angle between the vertical plate and the curved plate of the trenching machine and the height of the scraper plate above the ground as constant equipment parameters. The cutter disc characteristic parameters include the rotation speed of the cutter disc, the outer diameter of the cutter disc, the vibration frequency of the cutter disc and the amplitude of the cutter disc. The blade parameters include the horizontal distance between the inner circle blades, the vertical distance between the inner circle blades and the outer circle blades, the spacing between the inner circle blades, the spacing between the outer circle blades, the inner circle blade angle and the outer circle blade angle. Multiple sets of known cutter disc parameters and constant equipment parameters are spliced ​​to construct individuals in the initial population; The risk assessment module is used to construct a collapse risk assessment model. The rotation speed, outer diameter, vibration frequency and amplitude of the cutter disc of the individuals in multiple groups of initial populations are used as inputs. The trench wall collapse risk coefficient is determined by the expert group scoring method. The trench wall collapse risk coefficient is used as a label to train the collapse risk assessment model. The data processing and analysis module is used to process the horizontal distance between the inner ring blades, the vertical distance between the inner ring blades and the outer ring blades, the spacing between the inner ring blades, the spacing between the outer ring blades, the angle of the inner ring blades and the angle of the outer ring blades of the individuals in the initial population, and perform correlation analysis to generate a soil bearing coefficient for evaluating the soil bearing capacity, process the rotation speed of the cutter disc, the angle between the vertical plate and the arc plate, and the height of the scraper plate from the ground of the individuals in the initial population, and perform correlation analysis to generate a soil uniformity coefficient for evaluating the uniformity of the surface of the surrounding ditch opened by the surrounding ditch opening machine, process the ditch wall collapse risk factor, the soil bearing coefficient and the soil uniformity coefficient, and perform correlation analysis to generate a comprehensive evaluation coefficient for evaluating the stability of the surrounding ditch opened by the surrounding ditch opening machine; The parameter optimization module is used to maximize the comprehensive evaluation coefficient as the objective function and construct the constraints of the cutter parameters and constant parameters. Under the constraints, the individuals in the initial population are iteratively optimized through the genetic algorithm to obtain the optimal individuals. Based on the optimal individuals, the optimal values ​​of the cutter parameters are extracted.

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