Intelligent control method and system for trenching and paving device

Abstract

The present invention relates to the field of intelligent control technology, and in particular to an intelligent control method and system for trenching and paving devices. The contents include: collecting real-time data of soil and terrain and preprocessing them, calculating trenching parameters based on the preprocessed data, and introducing a dynamic feedback mechanism to obtain optimal trenching parameters; based on the optimal trenching parameters, adjusting the trenching auger to excavate the trench, controlling the pressure delivery speed based on the actual trench shape data after the trenching is completed, laying biomass, obtaining the trench filling status data after the laying is completed, and planning the trenching path to obtain a preliminary planned path, optimizing the preliminary planned path to obtain the optimal planned path; converting the optimal planned path into a control instruction to intelligently control the trenching and paving device. The control method solves the problems of inaccurate calculation of the trenching auger depth and inclination angle, poor path planning and tracking adaptability, and low control accuracy in the traditional trenching and paving device control method.

Description

Technical Field

[0001] The present invention relates to the field of intelligent control technology, and in particular to an intelligent control method and system for a trenching and paving device. Background Art

[0002] In agricultural production, especially in low-lying areas in the south, the drainage demand for farmland is very prominent. In order to prevent crops from being waterlogged, farmers often need to dig drainage ditches in farmland to lower the groundwater level and maintain appropriate soil moisture. However, different types of soil (such as clay, loam and sand) have different water permeability and support stability, so the depth, slope and spacing requirements of the trenches are also different. Especially in farmland with heavy soil, the trench density is high, the earthwork volume is large during excavation, and more arable land is occupied. At the same time, traditional trenches are designed with a fixed depth, which cannot flexibly adjust the groundwater level according to the changes in the water demand of different crops during the growth cycle, making it difficult to dynamically optimize the drainage effect of the trenches.

[0003] In summary, the control method of the traditional trenching and paving device has technical problems such as inaccurate calculation of the trenching auger depth and inclination, poor path planning and tracking adaptation, and low control accuracy. Summary of the invention

[0004] The present invention provides an intelligent control method and system for a trenching and paving device, so as to solve the technical problems that a conventional trenching and paving device control method has inaccurate calculation of trenching auger depth and inclination angle, poor path planning and tracking adaptability, and low control accuracy.

[0005] The present invention provides an intelligent control method and system for trenching and laying devices, which specifically include the following technical solutions:

[0006] An intelligent control method for a trenching and laying device comprises the following steps:

[0007] S1. Collecting real-time data of soil and terrain, and preprocessing the real-time data to obtain preprocessed data; calculating trenching parameters based on the preprocessed data, and introducing a dynamic feedback mechanism to optimize the trenching parameters to obtain optimal trenching parameters;

[0008] S2. Based on the optimal trenching parameters, adjust the position and angle of the trenching auger to perform trench excavation and obtain the actual trench shape data after trenching is completed; based on the actual trench shape data after trenching is completed, control the pressure delivery speed and perform biomass laying to obtain the trench filling state data after laying is completed;

[0009] S3. Based on the trench filling status data after paving, the trenching path is planned through a multivariable adaptive path optimization algorithm to obtain a preliminary planned path; the deviation of the preliminary planned path is detected in real time, and the preliminary planned path is optimized to obtain the optimal planned path; the optimal planned path is converted into control instructions to intelligently control the trenching paving device.

[0010] Preferably, the S1 specifically includes:

[0011] Based on the preprocessed data, a data matrix is ​​constructed; all the data in the data matrix are normalized to obtain normalized data; a weight matrix of ditching parameters is introduced, and the weights of the normalized data are initialized to obtain ditching parameter weights; based on the ditching parameter weights, the ditching parameters are calculated.

[0012] Preferably, the S1 specifically includes:

[0013] The dynamic feedback mechanism is introduced to optimize the trenching parameters by defining the target loss function, minimizing the target loss function through the gradient descent method, optimizing the weight matrix of the trenching parameters, and obtaining the optimal trenching parameters; the target loss function The definition formula is as follows: in, , , are the actual trench depth, actual trench slope, and actual trench spacing, respectively, representing the actual trenching parameters; , , is the adaptive weight; is the regularization parameter; Indicates the normalized data Category The ditching parameter weight of each feature; are the groove depth, groove slope and groove spacing, respectively, representing the trenching parameters.

[0014] Preferably, the S2 specifically includes:

[0015] Based on the optimal trenching parameters, a nonlinear multivariable position-angle control algorithm is introduced to calculate the target depth position and target inclination angle of the trenching auger.

[0016] Preferably, the S2 specifically includes:

[0017] Based on the target depth position and the target inclination angle, the motor drive is controlled to obtain the control output of the motor drive; the depth error and the angle error are obtained by combining the current actual depth position and the actual inclination angle; based on the depth error and the angle error, the control output of the motor drive is adjusted.

[0018] Preferably, the S2 specifically includes:

[0019] Based on the actual groove shape data after ditching, the pressure feeding speed calculation formula is introduced to obtain the pressure feeding speed. The specific calculation formula is:

[0020] in, is the pressure delivery speed; is the volume of biomass required per unit time; , , is the speed adjustment parameter; They represent the actual groove depth, actual groove slope and actual groove spacing respectively; is the actual groove cross-sectional area, which is determined by the actual groove depth and actual groove spacing Calculated.

[0021] Preferably, the S3 specifically includes:

[0022] In the implementation process of the multivariable adaptive path optimization algorithm, the initial target path point is generated based on the trench filling status data after paving and the real-time positioning information of the trenching and paving device. The specific formula is as follows: in, is generated Initial target path points, It is The three-dimensional coordinates of the initial target path points; is the initial position of the trenching and laying device, is the three-dimensional coordinate of the initial position of the trenching and laying device; is the path planning step length; , , is along , , Actual groove slope of the shaft; is the uniformity adjustment factor; is the laying uniformity parameter; is the laying thickness; is the thickness attenuation parameter;

[0023] Based on the initial target path point, a preliminary planned path is obtained.

[0024] Preferably, the S3 specifically includes:

[0025] The deviation of the preliminary planned path is detected in real time. Based on the path deviation size and path deviation direction angle in the path deviation, the deviation control formula is introduced to adjust the initial target path point to obtain the optimized target path point; the deviation control formula is as follows: in, is the optimized target path point; is the initial target path point, It is The three-dimensional coordinates of the initial target path points; is the three-dimensional coordinate of the current position of the trenching and laying device; is the optimization gain coefficient; is the path deviation size; is the path deviation direction angle; , are used to control the uniformity of laying and laying thickness Adaptive adjustment coefficients of weights in path optimization;

[0026] Based on the optimized target path point, the next target path point is generated to obtain the optimal planning path.

[0027] Preferably, the S3 specifically includes:

[0028] When the trenching and paving device moves along the optimal planned path and reaches the optimized path point for trenching, the implementation process of steps S1 and S2 is repeated, and the trench filling status data after paving is fed back to the multivariable adaptive path optimization algorithm to form a path optimization closed loop.

[0029] An intelligent control system for a trenching and paving device includes the following parts:

[0030] Soil detection and data acquisition module, intelligent calculation and optimization module, ditching control module, biomass laying and pressure delivery module, automatic path planning control module, detection feedback module, crawler movement control module;

[0031] The soil detection and data acquisition module collects real-time data of soil and terrain, and pre-processes the real-time data to obtain pre-processed data; the pre-processed data is transmitted to the intelligent calculation and optimization module;

[0032] The intelligent calculation and optimization module calculates the ditching parameters based on the preprocessed data, and introduces a dynamic feedback mechanism to optimize the ditching parameters to obtain the optimal ditching parameters; the optimal ditching parameters are transmitted to the ditching control module;

[0033] The trenching control module adjusts the position and angle of the trenching auger based on the optimal trenching parameters to obtain the actual trench shape data after the trenching is completed; and transmits the actual trench shape data after the trenching is completed to the biomass laying and pressure delivery module;

[0034] The biomass laying and pressing module controls the pressing speed based on the actual groove shape data after the trenching is completed, lays the biomass, obtains the groove filling status data after the laying is completed; and transmits the groove filling status data after the laying is completed to the automatic path planning control module;

[0035] The automatic path planning control module plans the trenching path based on the trench filling status data after paving and the real-time positioning information of the trenching paving device to obtain a preliminary planned path; transmits the preliminary planned path to the detection feedback module; optimizes the preliminary planned path based on the path deviation to obtain the optimal planned path; converts the optimal planned path into a control command and sends it to the crawler movement control module;

[0036] The detection feedback module detects the deviation of the preliminary planned path in real time and obtains the path deviation; the path deviation is transmitted to the automatic path planning control module;

[0037] The crawler movement control module adjusts the speed and direction of the crawler tracks of the trenching and paving device based on the control instructions of the automatic path planning control module, and intelligently controls the trenching and paving device. When the trenching and paving device moves along the optimal planned path and reaches the optimized path point for trenching, it repeats the implementation process of the soil detection and data acquisition module, the intelligent calculation and optimization module, the trenching regulation module, and the biomass paving and pressure delivery module, and feeds back the trench filling status data after paving to the automatic path planning control module to form a path optimization closed loop.

[0038] The beneficial effects of the technical solution of the present invention are:

[0039] 1. A dynamic feedback mechanism is introduced to construct the target loss function by calculating the deviation between the actual ditching parameters and the calculated ditching parameters, and the gradient descent method is used to minimize the loss. The weight matrix of the ditching parameters is adjusted through real-time feedback to ensure the accuracy of the ditching parameters, prevent deviation and overfitting caused by unreasonable ditching parameter weights, and improve the adaptability of the ditching parameters in various environments.

[0040] 2. Use the nonlinear multivariable position-angle control algorithm to finely adjust the position and inclination of the trenching auger. Through real-time adjustment of the target depth position and target inclination, it is ensured that the trench slope and trench depth meet the optimal design requirements, improving the accuracy and stability of trench excavation and ensuring the overall effect of trenching and laying biomass concealed pipes.

[0041] 3. Utilize a multivariable adaptive path optimization algorithm to combine the path deviation size and path deviation direction angle, and achieve dynamic path adjustment through nonlinear optimization; the path deviation is expressed in polar coordinates, which not only takes into account the path distance deviation, but also corrects the deviation angle in real time, achieving high efficiency and accuracy of path optimization in three-dimensional space, ensuring that the trenching and paving device moves accurately along the planned path, avoiding deviation from the path, and enhancing the sensitivity and control accuracy of path tracking. BRIEF DESCRIPTION OF THE DRAWINGS

[0042] Figure 1 This is a structural diagram of an intelligent control system for a trenching and paving device according to the present invention;

[0043] Figure 2 This is a flow chart of the intelligent control method of the trenching and paving device described in the present invention. DETAILED DESCRIPTION

[0044] In order to further explain the technical means and effects adopted by the present invention to achieve the predetermined invention purpose, the technical scheme in the embodiment of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiment of the present invention. Obviously, the described embodiment is only a part of the embodiment of the present invention, not all the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0045] Unless defined otherwise, 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 invention belongs.

[0046] The specific scheme of the intelligent control method and system of the trenching and paving device provided by the present invention is described in detail below with reference to the accompanying drawings.

[0047] See attached Figure 1 , which shows a structure diagram of an intelligent control system for a trenching and paving device provided by an embodiment of the present invention, the system includes the following parts:

[0048] Soil detection and data acquisition module, intelligent calculation and optimization module, ditching control module, biomass laying and pressure delivery module, automatic path planning control module, detection feedback module, crawler movement control module;

[0049] The soil detection and data acquisition module collects real-time data of soil and terrain, and pre-processes the real-time data to obtain pre-processed data; the pre-processed data is transmitted to the intelligent calculation and optimization module;

[0050] The real-time data includes soil type, water permeability, soil density, water level, terrain slope, etc.;

[0051] The intelligent calculation and optimization module calculates the trenching parameters (such as trench depth, trench slope and trench spacing) based on the preprocessed data according to the crop type and farmland requirements, and introduces a dynamic feedback mechanism to optimize the trenching parameters to adapt to various soil types and terrains and obtain the optimal trenching parameters; the optimal trenching parameters are transmitted to the trenching control module;

[0052] The trenching control module calculates the target depth position and target inclination angle of the trenching auger based on the optimal trenching parameters, and adjusts the position and angle of the trenching auger by controlling the motor drive to achieve trench excavation of a specific depth and slope, and obtains the actual trench shape data after trenching is completed; the actual trench shape data after trenching (actual trench depth, actual trench slope, actual trench spacing) is transmitted to the biomass laying and pressure delivery module;

[0053] The biomass laying and pressure delivery module starts the extrusion auger based on the actual groove shape data after the trenching is completed, and evenly lays the crushed straw, biofertilizer and other materials at the bottom of the groove, and controls the pressure delivery speed according to the actual groove shape data after the trenching is completed, so as to realize the laying of the biomass blind pipe, and at the same time obtains the groove filling status data after the laying is completed (including laying thickness and laying uniformity); transmits the groove filling status data after the laying is completed to the automatic path planning control module;

[0054] The automatic path planning control module plans the trenching path based on the trench filling status data after paving and the real-time positioning information of the trenching paving device to obtain a preliminary planned path; transmits the preliminary planned path to the detection feedback module; optimizes the preliminary planned path based on the path deviation to obtain the optimal planned path; converts the optimal planned path into a control command and sends it to the crawler movement control module;

[0055] The detection feedback module detects the deviation of the preliminary planned path in real time and obtains the path deviation; the path deviation is transmitted to the automatic path planning control module;

[0056] The track movement control module adjusts the speed and direction of the track of the trenching and paving device based on the control instructions of the automatic path planning control module, so that the trenching and paving device moves along the optimal planned path, ensuring that the trenching and paving operations are carried out within the specified area; when the trenching and paving device moves along the optimal planned path and reaches the optimized path point for trenching, it repeats the implementation process of the soil detection and data acquisition module, the intelligent calculation and optimization module, the trenching regulation module, and the biomass paving and pressure delivery module, and feeds back the trench filling status data after paving to the automatic path planning control module to form a path optimization closed loop.

[0057] See attached Figure 2, which shows a flow chart of an intelligent control method for a trenching and paving device provided by an embodiment of the present invention, the method comprising the following steps:

[0058] S1. Collecting real-time data of soil and terrain, and preprocessing the real-time data to obtain preprocessed data; calculating trenching parameters based on the preprocessed data, and introducing a dynamic feedback mechanism to optimize the trenching parameters to obtain optimal trenching parameters;

[0059] After professional technicians select and lay out the sensors, real-time data of soil and terrain are collected through the sensors, including soil type data such as soil conductivity, pH value, humidity, density, permeability data, soil density, water level height, terrain slope, etc.; the real-time data is preprocessed such as filtering, data correction, formatting, etc. to obtain preprocessed data; the preprocessing process adopts technical means well known to those skilled in the art and will not be described in detail here.

[0060] Based on the preprocessed data, combined with crop types and farmland requirements, the ditching parameters (such as ditch depth, slope and spacing) are calculated, and a dynamic feedback mechanism is introduced to optimize the ditching parameters to obtain the optimal ditching parameters. The specific implementation process is as follows:

[0061] First, the preprocessed data, crop types and farmland requirements are used as initial data, and the initial data is dimensionless processed to prevent deviations caused by dimension differences. The dimensionless processing method uses existing technology and will not be described here; the initial data is converted into a data matrix using expert experience ,in Indicates Category The categories include soil characteristics, terrain characteristics, crop requirements, etc.; the characteristics include humidity, infiltration rate, initial slope, height change, root depth, waterlogging tolerance depth, etc.; all elements in the data matrix are further normalized to unify the data scale to obtain the normalized data. ;

[0062] Furthermore, the normalized data is weighted and the weight matrix of the ditching parameters is introduced. , Indicates the normalized data Category The ditching parameter weight of each feature. The weight initialization formula is as follows: ;

[0063] in, It is Category The ditching parameter weight of each feature; It is The number of features in the class; is the number of data categories. Through weight initialization, the influence of the ditching parameters is adjusted in the subsequent steps to balance the effects of different factors;

[0064] Furthermore, after the weight initialization is completed, the trenching parameters, such as trench depth, are calculated based on the expert experience method combined with the trenching parameter weights. , Groove slope , Groove spacing ;

[0065] After calculating the groove depth , Groove slope and groove spacing Finally, in order to obtain more accurate trenching parameters, a dynamic feedback mechanism is introduced to improve the accuracy and adaptability of trenching parameters. The dynamic feedback mechanism is implemented by defining the target loss function. The definition formula is as follows: ;

[0066] in, is the target loss function, which reflects the deviation between the calculated trenching parameters and the actual trenching parameters; , , are the actual trench depth, actual trench slope and actual trench spacing, i.e., actual trenching parameters; , , is an adaptive weight used to reasonably distribute the impact of different trenching parameters on the loss; It is a regularization parameter, which is used to control the weight of the ditching parameter, prevent the ditching parameter from being overly dependent on specific factors, and improve the adaptability under different terrain characteristics and crop requirements. The regularization term can prevent overfitting caused by excessive weight of the ditching parameter;

[0067] Finally, the objective loss function is minimized by gradient descent , the weight matrix for optimizing trenching parameters The objective loss function is the weight of the ditching parameters. The gradient of is calculated as: ;

[0068] in, is the learning rate, which is used to control the update step size; is the target loss function Weights for trenching parameters The partial derivative of Sensitivity to loss is used to adjust the ditching parameter weights to minimize the objective loss function; in each update, the objective loss function continues to be minimized, and the ditching parameter weight matrix The ditching parameters are optimized step by step according to the real-time feedback data to ensure their accuracy and adaptability. When the value of the target loss function is less than the loss threshold preset according to the expert experience method, the update is stopped and the optimized ditching parameter weights are obtained. Based on the optimized ditching parameter weights, the optimized ditching parameters (groove depth) are calculated according to the expert experience method. , Groove slope , Groove spacing ).

[0069] S2. Based on the optimal trenching parameters, adjust the position and angle of the trenching auger to perform trench excavation and obtain the actual trench shape data after trenching is completed; based on the actual trench shape data after trenching is completed, control the pressure delivery speed and perform biomass laying to obtain the trench filling state data after laying is completed;

[0070] According to the optimal trenching parameters, the target depth position and target inclination angle of the trenching auger are calculated using the nonlinear multivariable position-angle control algorithm, and the position and angle of the trenching auger are adjusted by controlling the motor drive to achieve trench excavation of a specific depth and slope; the specific implementation process is as follows:

[0071] First, calculate the target depth position of the trenching auger, the calculation formula is as follows: ;

[0072] in, is the target depth position, indicating the final depth position of the trenching auger; It is the initial position, indicating the initial height of the trenching auger before it goes down; is the position adjustment factor, which is used to control the coupling strength between the groove depth and the groove slope; is the depth correction factor, which is used to control the adaptability of the groove depth under different conditions; is the attenuation coefficient, which is used to control the effect of the exponential attenuation term and gradually reduce the groove depth adjustment under larger groove depth conditions;

[0073] Further, after determining the target depth position Then calculate the target inclination angle of the trenching auger. , in order to achieve the optimal trenching parameters trench slope The target inclination angle calculation formula is as follows: ;

[0074] in, is the target inclination angle, which indicates the inclination angle that the trenching auger needs to reach; is the initial inclination, which indicates the angle of the trenching auger before excavation; It is the depth-angle transition smoothing parameter, which is used to control the smooth transition between depth and angle to prevent large changes; It is the angle correction coefficient, which is used to adjust the adaptability of the angle, especially to enhance the control sensitivity when the terrain changes greatly;

[0075] Further, the target depth position and target inclination First, the vertical drive motor in the control motor drive is responsible for moving the trenching auger to the target depth position. , vertical drive motor output Depends on the current actual depth position Depth position of target The depth position deviation between the two is used to introduce a nonlinear control formula with gain and adaptive correction terms to calculate the output of the vertical drive motor: ;

[0076] in, It is the output of the vertical drive motor, used to adjust the depth position of the trenching auger; It is the position control gain parameter, which is used to control the response strength of the vertical drive motor to the depth position deviation; It is the current actual depth position, indicating the current depth position of the trenching auger; is the adaptive position correction coefficient, which is used to dynamically adjust the control force according to the change of depth position deviation;

[0077] At the same time, the angle drive motor in the control motor drive is used to realize the inclination control of the trenching auger to achieve the target inclination angle . Angle drive motor output Depends on the current actual inclination and target inclination To ensure the accuracy of angle adjustment, the following nonlinear control formula is introduced: ;

[0078] in, It is the output of the angle drive motor, which is used to adjust the inclination angle of the trenching auger; It is the angle control gain parameter, which is used to control the response strength of the angle drive motor to the angle deviation; is the current actual inclination angle, indicating the current inclination angle of the trenching auger; is the adaptive angle correction factor, which is used to dynamically adjust the sensitivity of the angle drive motor to angle deviation;

[0079] Furthermore, based on the vertical drive motor output and angle drive motor output , to conduct real-time error feedback and further accurately control the motor drive; set the current actual depth position and the actual inclination , calculate the depth error and angle error, and fine-tune the control output of the motor drive to make the depth error and angle error approach zero. Depth Error and angular error They are: ;

[0080] Based on the depth error and angle error, the control output of the motor drive is precisely fine-tuned: ,

[0081] in, is the feedback gain coefficient of the depth position, which is used to control the adjustment strength of the depth error feedback; is the feedback attenuation factor of the depth position, used to control the feedback effect when the depth error decreases to prevent over-adjustment; is the angle feedback gain coefficient, which is used to control the adjustment strength of the angle error feedback; is the angle feedback attenuation factor, used to control the feedback effect when the angle error decreases.

[0082] Finally, after completing the precise adjustment of the target depth position and the target inclination angle, the trenching auger enters the actual excavation stage and obtains the actual trench shape data (actual trench depth, actual trench slope, actual trench spacing) after trenching.

[0083] Furthermore, based on the actual trench shape data after trenching is completed, the extrusion auger is started to evenly spread the crushed straw, biofertilizer and other materials on the bottom of the trench, and the pressing speed is controlled according to the actual trench shape data after trenching is completed to realize the laying of biomass concealed pipes, and at the same time, the trench filling status data after laying is completed (including laying thickness and laying uniformity) is obtained.

[0084] In order to ensure that the biomass pipes are evenly laid in the trench, the pressure delivery speed According to the actual groove depth , Actual trench slope and actual groove spacing Calculate. Set the target laying thickness of the biomass underground pipe to , then the pressure delivery speed The calculation formula is: ;

[0085] in, is the pressure delivery rate, which indicates the pressure delivery rate of the biomass, used to lay the biomass evenly in the trench; is the volume of biomass required per unit time, determined by the target paving thickness and the actual groove shape data after trenching is completed; is the actual groove cross-sectional area, which is determined by the actual groove depth and actual groove spacing Calculated; , , It is a speed adjustment parameter, which is set through experiments to adapt to the pressure delivery requirements under different terrain conditions.

[0086] Furthermore, the laying of the biomass blind pipe is achieved according to the pressure delivery speed, and the trench filling status data after the laying is completed (including laying thickness and laying uniformity) is obtained.

[0087] S3. Based on the trench filling status data after paving, the trenching path is planned through a multivariable adaptive path optimization algorithm to obtain a preliminary planned path; the deviation of the preliminary planned path is detected in real time, and the preliminary planned path is optimized to obtain the optimal planned path; the optimal planned path is converted into control instructions to intelligently control the trenching paving device.

[0088] Based on the trench filling status data after paving is completed and the real-time positioning information of the trenching and paving device, a multivariable adaptive path optimization algorithm is used for planning to obtain a preliminary planned path. At the same time, the deviation of the preliminary planned path is detected in real time, and the path deviation is used as detection feedback to optimize the preliminary planned path to obtain the optimal planned path.

[0089] The multivariable adaptive path optimization algorithm is based on the trench filling status data after paving (such as paving thickness, paving uniformity) and the real-time positioning information of the trenching and paving device. It generates the path through a complex multivariable nonlinear relationship and performs adaptive optimization. It combines the size and direction angle of the path deviation, and uses multiple nonlinear terms and polar coordinates to express the path deviation, ensuring that the path optimization can consider the size of the path deviation in three-dimensional space and adjust the path deviation angle in real time. The specific implementation process is as follows:

[0090] First, the initial target path point is generated by the trench filling status data after paving and the real-time positioning information of the trenching paving device. Assume that the initial position of the trenching paving device is , initial target path point According to the path planning step length The target inclination angle of the groove is gradually generated, and multiple nonlinear terms are introduced to make the initial target path point adapt to the paving thickness and paving uniformity. The formula for generating the initial target path point is as follows:

[0091] ,

[0092] in, is generated Initial target path points, It is The three-dimensional coordinates of the initial target path points; It is the three-dimensional coordinate of the initial position of the trenching and paving device, which is used to set the starting position of the path; is the path planning step length, defined as the length of one step of the trenching and paving device, used to generate continuous path points; , , is along , , The actual groove slope of the axis is used to set the direction of the path point so that the path conforms to the slope and direction of the groove design; Is the uniformity adjustment factor, used to control the paving uniformity Impact on path generation; It is a laying uniformity parameter, which indicates the stability of the thickness during the trench filling process and is usually measured by detecting the fluctuation of the filling thickness; is the laying thickness, which indicates the actual laying thickness of the biomass concealed pipe in the trench; is the thickness attenuation parameter, which is used to control the thickness adaptability during path generation;

[0093] Based on the initial target path point, a preliminary planned path is obtained;

[0094] Furthermore, after generating the preliminary planned path, in order to ensure the accuracy of the path, the path deviation of the trenching and paving device needs to be detected in real time to obtain the path deviation. The path deviation is described in polar coordinate form, including the path deviation size and path deviation angle , in order to improve the detection accuracy. The current position of the trenching and laying device is , the initial target path point is , path deviation size and path deviation angle The calculations are as follows: ;

[0095] in, Is the path deviation size, indicating the current position of the trenching and paving device The initial target path point The distance between It is the path deviation angle, indicating the direction of the current path deviation, ensuring accurate control of the path deviation in three-dimensional space. By simultaneously detecting the path deviation size and path deviation angle, it ensures that the path optimization can not only dynamically adjust the distance according to the actual deviation of the trenching and paving device, but also correct the direction in real time;

[0096] Further, in obtaining the path deviation size and path deviation angle After that, the deviation control formula is introduced to calculate the initial target path point The position is adjusted, and the calculation formula is as follows: ;

[0097] in, is the optimized target path point; is the initial target path point, It is The three-dimensional coordinates of the initial target path points; is the three-dimensional coordinate of the current position of the trenching and laying device; is the optimization gain coefficient, which is used to control the amplitude of path adjustment; , are adaptive adjustment coefficients, which are used to control the paving uniformity. and laying thickness The weight in path optimization. The above formula is introduced by The term implements nonlinear path correction, responding to the magnitude of path deviation , while passing the direction vector The target path point is adjusted in the direction of the path deviation to ensure that the spatial position correction of the target path point is more accurate.

[0098] Further, based on the optimized target path point , generate the next target path point , in order to gradually realize the dynamic update of the target path and obtain the optimal planning path. The update formula is as follows:

[0099] ;

[0100] in, is the next target path point after update; is the path planning step length; , is the step length correction factor, which is used to control the path planning step length to ensure that the path is gradually stabilized when the path deviation is reduced; It is the three-dimensional direction vector of the target path point, ensuring that the path is updated in the direction of the path deviation. With the introduction of , the update formula not only considers the path planning step length, but also adjusts the path direction according to the change of path deviation, so that the path of the trenching and paving device tends to be stable when the deviation gradually decreases, and finally the path is gradually optimized.

[0101] To ensure that the generated path is optimal, the final path must meet the following conditions:

[0102] Path deviation is stable: if in continuous The path deviation size is If both are smaller than the deviation threshold, it is considered that the path has stabilized; the deviation threshold is set by expert experience.

[0103] Paving uniformity meets: Paving uniformity during path optimization It needs to be kept within the target range to ensure uniformity of biomass pipe laying; the target range is set by expert experience.

[0104] Furthermore, the optimal planned path is converted into a control instruction, and the speed and direction of the trenching and paving device track are calculated based on the control instruction according to the existing speed and direction calculation method, so that the trenching and paving device moves along the optimal planned path, thereby realizing intelligent control of the trenching and paving device.

[0105] When the trenching and paving device moves along the optimal planned path and reaches the optimized path point for trenching, the implementation process of steps S1 and S2 is repeated, and the trench filling status data after paving is fed back to the multivariable adaptive path optimization algorithm to form a path optimization closed loop.

[0106] In summary, an intelligent control method and system for a trenching and paving device have been completed.

[0107] The order of the embodiments of the invention is for description only and does not represent the advantages and disadvantages of the embodiments. The processes depicted in the drawings do not necessarily require the specific order or continuous order shown to achieve the desired results. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0108] The various embodiments in this specification are described in a progressive manner, and the same or similar parts between the various embodiments can be referenced to each other, and each embodiment focuses on the differences from other embodiments.

[0109] The above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit the same. Although the present invention has been described in detail with reference to the above embodiments, those skilled in the art should understand that the technical solutions described in the above embodiments may still be modified, or some of the technical features may be replaced by equivalents. Such modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present invention, and should be included in the protection scope of the present invention.

Claims

1. An intelligent control method for a trenching and laying device, characterized in that: The following steps are involved: S1. Collecting real-time data of soil and terrain, and preprocessing the real-time data to obtain preprocessed data; Based on the preprocessed data, the ditching parameters are calculated, and a dynamic feedback mechanism is introduced to optimize the ditching parameters by defining the target loss function. The target loss function is minimized by the gradient descent method, and the weight matrix of the ditching parameters is optimized to obtain the optimal ditching parameters. The definition formula is as follows: ； in, , , are the actual trench depth, actual trench slope, and actual trench spacing, respectively, representing the actual trenching parameters; , , is the adaptive weight; is the regularization parameter; Indicates the normalized data Category The ditching parameter weight of each feature; are trench depth, trench slope and trench spacing, respectively, representing trenching parameters; S2. Based on the optimal trenching parameters, the position and angle of the trenching auger are adjusted to perform trench excavation, and the actual trench shape data after trenching is completed is obtained; based on the actual trench shape data after trenching is completed, the pressure delivery speed calculation formula is introduced to control the pressure delivery speed, and biomass is laid to obtain the trench filling state data after laying is completed; the pressure delivery speed calculation formula is: ； in, is the pressure delivery speed; is the volume of biomass required per unit time; , , is the speed adjustment parameter; They represent the actual groove depth, actual groove slope and actual groove spacing respectively; is the actual groove cross-sectional area, which is determined by the actual groove depth and actual groove spacing Calculated; S3. Based on the trench filling status data after paving and the real-time positioning information of the trenching and paving device, the initial target path point is generated through a multivariable adaptive path optimization algorithm. The specific formula is as follows: ; in, is generated Initial target path points, It is The three-dimensional coordinates of the initial target path points; is the initial position of the trenching and laying device, is the three-dimensional coordinate of the initial position of the trenching and laying device; is the path planning step length; , , is along , , Actual groove slope of the shaft; is the uniformity adjustment factor; is the paving uniformity parameter; is the laying thickness; is the thickness attenuation parameter; Based on the initial target path point, a preliminary planned path is obtained; the deviation of the preliminary planned path is detected in real time, and based on the path deviation size and path deviation direction angle in the path deviation, a deviation control formula is introduced to adjust the initial target path point to obtain the optimized target path point; the deviation control formula is as follows: ； in, is the optimized target path point; is the initial target path point, It is The three-dimensional coordinates of the initial target path points; is the three-dimensional coordinate of the current position of the trenching and laying device; is the optimization gain coefficient; is the path deviation size; is the path deviation direction angle; , are used to control the uniformity of laying and laying thickness Adaptive adjustment coefficients of weights in path optimization; Based on the optimized target path point, the next target path point is generated to obtain the optimal planned path; the optimal planned path is converted into control instructions to perform intelligent control of the trenching and paving device.

2. The intelligent control method for trenching and laying device according to claim 1, characterized in that: The S1 specifically includes: Based on the preprocessed data, a data matrix is ​​constructed; all the data in the data matrix are normalized to obtain normalized data; a weight matrix of ditching parameters is introduced, and the weights of the normalized data are initialized to obtain ditching parameter weights; based on the ditching parameter weights, the ditching parameters are calculated.

3. The intelligent control method for trenching and laying device according to claim 1, characterized in that: The S2 specifically includes: Based on the optimal trenching parameters, a nonlinear multivariable position-angle control algorithm is introduced to calculate the target depth position and target inclination angle of the trenching auger.

4. The intelligent control method for trenching and laying device according to claim 3, characterized in that: The S2 specifically includes: Based on the target depth position and the target inclination angle, the motor drive is controlled to obtain the control output of the motor drive; the depth error and the angle error are obtained by combining the current actual depth position and the actual inclination angle; based on the depth error and the angle error, the control output of the motor drive is adjusted.

5. The intelligent control method for trenching and laying device according to claim 1, characterized in that: The S3 specifically includes: When the trenching and paving device moves along the optimal planned path and reaches the optimized path point for trenching, the implementation process of steps S1 and S2 is repeated, and the trench filling status data after paving is fed back to the multivariable adaptive path optimization algorithm to form a path optimization closed loop.

6. An intelligent control system for trenching and paving devices, applied to an intelligent control method for trenching and paving devices as claimed in claim 1, characterized in that: Includes the following parts: Soil detection and data acquisition module, intelligent calculation and optimization module, ditching control module, biomass laying and pressure delivery module, automatic path planning control module, detection feedback module, crawler movement control module; The soil detection and data acquisition module collects real-time data of soil and terrain, and pre-processes the real-time data to obtain pre-processed data; Transfer the preprocessed data to the intelligent computing and optimization module; The intelligent calculation and optimization module calculates the ditching parameters based on the preprocessed data, and introduces a dynamic feedback mechanism to optimize the ditching parameters to obtain the optimal ditching parameters; the optimal ditching parameters are transmitted to the ditching control module; The trenching control module adjusts the position and angle of the trenching auger based on the optimal trenching parameters to obtain the actual trench shape data after trenching is completed; The actual groove shape data after the trenching is completed is transmitted to the biomass laying and pressure delivery module; The biomass laying and pressing module controls the pressing speed based on the actual groove shape data after the trenching is completed, lays the biomass, obtains the groove filling status data after the laying is completed; and transmits the groove filling status data after the laying is completed to the automatic path planning control module; The automatic path planning control module plans the trenching path based on the trench filling status data after paving and the real-time positioning information of the trenching paving device to obtain a preliminary planned path; Transmitting the preliminary planned path to the detection feedback module; The preliminary planned path is optimized based on the path deviation to obtain the optimal planned path; Convert the optimal planned path into control instructions and send them to the crawler movement control module; The detection feedback module detects the deviation of the preliminary planned path in real time and obtains the path deviation; the path deviation is transmitted to the automatic path planning control module; The crawler movement control module adjusts the speed and direction of the crawler tracks of the trenching and paving device based on the control instructions of the automatic path planning control module, and intelligently controls the trenching and paving device. When the trenching and paving device moves along the optimal planned path and reaches the optimized path point for trenching, it repeats the implementation process of the soil detection and data acquisition module, the intelligent calculation and optimization module, the trenching regulation module, and the biomass paving and pressure delivery module, and feeds back the trench filling status data after paving to the automatic path planning control module to form a path optimization closed loop.

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