1872 results about "Farm machine" patented technology

The invention provides an automatic driving agricultural machinery marshalling operation control method and system, and relates to the technical field of agricultural machinery control, and the method comprises the steps: determining the function type and number configuration of needed agricultural machinery according to the farming task type, farmland scale and terrain parameters; based on the agricultural machinery operation capability parameter set and the farmland space features, generating agricultural machinery cooperation groups; planning an operation path containing space-time collision avoidance constraint for each agricultural machine group, and establishing a time sequence scheduling strategy matched with the task load; based on farmland environment data, agricultural machinery working condition data and operation quality data which are acquired in real time, agricultural machinery marshalling topology and operation parameters are dynamically reconstructed, through dynamic grouping, intelligent path planning and real-time state feedback and reconstruction, the flexibility, efficiency and robustness of agricultural machinery collaborative operation are remarkably improved, and the development requirements of precision and intelligence of modern agriculture are met.

The invention relates to the technical field of agricultural machinery automation control, and discloses an agricultural machinery operation path intelligent planning method based on Beidou positioning. The method comprises the following steps: firstly, acquiring Beidou positioning data and a farmland geographic data set, and eliminating positioning noise by using a dynamic filtering algorithm to obtain a calibrated agricultural machine track sequence; performing rasterization processing on the farmland geographic data to generate a digital elevation model, and dividing a job priority region; generating an initial operation path by adopting a hybrid optimization algorithm, and dynamically adjusting the path based on real-time operation state information; and finally, a path conflict detection module is combined with obstacle coordinates to calculate a collision probability, and a final agricultural machine operation path is output. According to the method, various factors are comprehensively considered, real-time dynamic adjustment of the path can be realized, path conflicts are effectively avoided, the operation precision and efficiency of agricultural machinery are improved, energy consumption and equipment loss are reduced, and agricultural mechanization and intelligentization development is promoted.

The invention discloses a field unstructured road real-time segmentation system and method for agricultural machinery autonomous navigation, particularly relates to the field of agricultural machinery autonomous navigation, and is used for solving the problems of high precision and low delay of real-time segmentation of a driving area and an obstacle in a field unstructured road environment. The image stability under complex illumination is improved through brightness balance, and texture and contour features are extracted through lightweight multi-scale coding; texture deflection and contour focusing are normalized into probability distribution, direction consistency is analyzed based on modal competition fusion, direction embedding is dynamically adjusted, and deviation is avoided; guiding branch activation of a BiSeNet decoder by the direction perception tensor, and outputting a driving area probability graph and an edge heat graph; and continuous frame consistency filtering is used for eliminating instantaneous fluctuation, a stable segmentation mask and a boundary position vector are generated, and the path stability and operation continuity of navigation control are ensured.

The invention discloses an unmanned agricultural machine path navigation method based on farmland environment perception judgment, and relates to the technical field of path navigation, and the method comprises the steps: continuously perceiving farmland topographic relief features, gradient changes, and agricultural machine current attitude and wheel speed information before and during the operation of an agricultural machine; identifying a terrain disturbance potential risk area based on the sensing data, and predicting the offset and rollover risk value of the terrain fluctuation to the agricultural machine trajectory; according to the method, a pre-correction model fusing terrain prediction data and agricultural machinery dynamic characteristics is called, a pre-correction path containing the terrain compensation amount is generated, and navigation control parameters are adjusted in advance, so that the pre-correction path containing the terrain compensation amount is actively generated by sensing terrain fluctuation and predicting risk and offset in advance; the problem of causal malposition of risk prior to control is avoided from the source.

The invention provides a remote sensing image-based in-field agricultural machine driving efficiency suitability evaluation method. The method comprises the steps of S1, extracting fine field attribute information based on a high-resolution remote sensing image; s2, extracting field obstacle information and field terrain information based on the field attribute information; s3, constructing a key evaluation index set influencing the running efficiency of the agricultural machinery in the field; s4, index weighting based on a geographical weighted attention mechanism; s5, establishing an in-field agricultural machine driving efficiency suitability evaluation model, and positioning key negative impact indexes; and S6, grading the suitability level of the agricultural machine driving efficiency based on a natural breakpoint method. The invention further provides a system for evaluating the suitability of the running efficiency of the agricultural machinery in the field based on the remote sensing image. According to the method, the field-level key index set is constructed, the geographical weighted regression and the attention mechanism are innovatively combined, the regional difference and the field characteristics are fully considered, and the scientificity and the practicability of evaluation are greatly improved.

The invention provides an agricultural machinery multi-source data fusion and collaborative operation method based on edge calculation. The method comprises the following steps: step 1, dividing a multi-source sensor group into three units to collect data; 2, constructing a data fusion and collaborative operation model through four parts of space-time calibration, dynamic weight data fusion, a real-time decision engine and multi-agricultural machinery collaborative operation; 3, realizing practical application of the data fusion and collaborative operation model in the step 2 through edge-cloud collaboration; and 4, performing test detection on the data fusion and collaborative operation model. According to the invention, real-time collection and fusion of agricultural machine multi-source data are realized through an edge computing architecture, and the data transmission delay is significantly reduced; the heterogeneous computing architecture design greatly reduces the power consumption of edge nodes, and meets the long-time operation requirement; and the edge-cloud collaboration mechanism supports incremental updating and exception verification of model parameters, so that the reliability and the expandability of the model are ensured.

The invention provides a multi-dimensional data fusion soil fertilizer application system and method, and relates to the technical field of soil fertilizer application, and the system comprises a data collection module which is used for collecting multi-source original data including soil, weather, crops and fertilizer in real time; the data preprocessing module is used for preprocessing the multi-source original data; the data fusion module is used for generating a comprehensive index reflecting the soil fertility state and the crop demand; the fertilization decision module is used for generating an optimal fertilization scheme; the execution control module is used for controlling the variable fertilizer applicator and the drip irrigation equipment to execute precise fertilization operation; and the effect monitoring and feedback module is used for evaluating the decision effect and optimizing the nutrient leaching model. According to the invention, through multi-objective optimization based on the nutrient leaching model and the genetic algorithm, the fertilizer cost, the environmental risk and the agricultural machinery operation constraint are considered while the fertilizer requirement rule of crops is met, and the optimal fertilization scheme considering both the economical efficiency and the ecological property is output.

The invention relates to the field of agricultural fertilization, in particular to a corn straw returning-to-field and fertilization operation path collaborative scheduling optimization method, which comprises the following steps: performing standardization processing on farmland multi-source original data to obtain a field piece unit standardization feature vector; performing imbalance degree analysis on the feature dimension distance component to obtain a feature contribution balance factor; performing activeness evaluation on neighborhood membership distribution of the field units to obtain a spatial membership smoothing factor; obtaining adaptive distance measurement by combining a feature contribution balance factor and a space membership smoothing factor; and performing hardening processing on the final membership matrix to obtain an agricultural machinery path collaborative scheduling instruction set, thereby solving the problems of misalignment of a zoning result, fragmentation of a management boundary and unreasonable agricultural machinery path scheduling in an abnormal straw accumulation region based on a standard FCM clustering algorithm in the prior art.

The invention relates to a navigation control method and device of agricultural machinery, electronic equipment, a medium and the agricultural machinery, and the method comprises the following steps: acquiring a positioning point coordinate, course information, real-time vehicle speed and yaw rate information of the agricultural machinery at the current moment, and calculating the navigation of the agricultural machinery according to the positioning point coordinate, course information, real-time vehicle speed and yaw rate information at the current moment; calculating transverse deviation, course deviation and estimated values of the front wheel turning angle between the agricultural machine and a preset target path point according to the geometrical relationship, calculating an expected value of the front wheel turning angle at the next moment of the current moment according to the transverse deviation, the course deviation and the estimated values of the front wheel turning angle, and calculating the expected value of the front wheel turning angle at the next moment according to the expected value of the front wheel turning angle at the next moment. The agricultural machine is controlled to advance. By means of the method, the expected value of the front wheel rotation angle at the next moment is optimized, so that accurate control over advancing of the agricultural machine is achieved, the path tracking accuracy of the agricultural machine is remarkably improved, deviation errors in the operation process can be effectively reduced, and it is ensured that the agricultural machine accurately travels according to the preset path.

The present invention discloses a self-propelled cyperus chinensis combine harvester, belonging to the field of agricultural machinery technology. The harvester comprises a vehicle body, the front end of which is connected to a digging platform; a conveyor plate chain is provided on the digging platform, the rear end of which is connected to an elevator chain mechanism fixedly connected to the vehicle body; the rear end of the elevator chain mechanism extends into the front portion of a screen drum; a rotatable shaft is provided at the center of the screen drum; a plurality of grass guide blades and a plurality of throw ropes are connected to the shaft; a reciprocating vibrating screen is connected to the vehicle body below the screen drum; the outlet end of the berry elevator is located above a storage bin fixedly connected to the vehicle body; and a plurality of small sieve holes are formed on the collecting plate, the chain belt of the conveyor plate chain, and the chain belt of the elevator chain mechanism. While the space of the self-propelled vehicle body is limited, the present invention includes a five-stage screening mechanism, which has a strong soil screening capacity and can effectively screen out clods of soil carried by cyperus chinensis roots, thereby improving the efficiency and quality of cyperus chinensis harvesting.

The invention provides an unmanned agricultural machine obstacle avoidance operation path optimization method and device in a farmland scene, and relates to the field of automatic driving and path planning, and the method comprises the steps: finding a collision risk strip through detecting whether there is an intersection point between an unmanned agricultural machine operation strip and an obstacle expansion range in a farmland; based on key parameters such as the machine tool size and the minimum turning radius of the agricultural machine, the minimum influence range of the obstacle repulsive force effect is restrained, and it is ensured that the obstacle avoiding path meets the actual obstacle avoiding requirements of the agricultural machine and the mounted machine tool of the agricultural machine in space; local obstacle avoidance path planning is carried out based on an artificial potential field method, the distance relation between sampling points on an operation strip and the center of an obstacle substance is introduced, deflection angle adjustment is carried out on the repulsive force direction in combination with the obstacle influence radius, and therefore potential field distribution is dynamically optimized. According to the method, the operation requirement, the path smoothness, the path continuity and the operation efficiency can be considered, and the application value of the unmanned agricultural machine in the complex environment in the field is improved.

A dynamic wind-resistant flexible photovoltaic power generation mount system, in which multiple photovoltaic panels are mounted astride a same load-bearing cable and connected in series to form a flat-plate-type photovoltaic power generation suspension cable. Each photovoltaic panel can sway with the wind around the load-bearing cable. The present application overcomes the defects of existing static wind-resistant technologies, pioneers a new dynamic wind-resistant approach, reduces wind resistance, and achieves an exceptionally strong wind-resistant effect. The present application allows for an increased span, reduces the number of pile foundations, and minimally interferes with large-scale agricultural machinery operation. The movement speed of shadows is rapid, so that crop photosynthesis is not affected, and instead, crop growth is stimulated and agricultural yield and income are increased.

The invention discloses an unmanned agricultural machine path tracking preset performance control method and system, and the method comprises the steps: collecting the pose information of an unmanned agricultural machine, building an unmanned agricultural machine path tracking error kinematic model, and designing a finite time preset performance function based on the unmanned agricultural machine path tracking error kinematic model. The constraint is converted through nonlinear mapping; based on the Lyapunov stability theory, adopting a backstepping method to recursively design an actual control law, and according to the actual control law, performing inverse transformation on the input of the unmanned agricultural machine tracking control system in the error kinematics model of the unmanned agricultural machine tracking control system to obtain the front wheel steering angle of the unmanned agricultural machine. According to the method, convergence is completed within finite time, and transient control performance and steady control performance of a path tracking control system are considered.

The invention discloses an agricultural machinery high-precision automatic driving intelligent control system, which belongs to the technical field of agricultural machinery vehicle automatic driving and comprises a data acquisition module, a path planning module, a control module and an instruction execution module. The data acquisition module is used for acquiring a dynamic data set in real time and transmitting the dynamic data set to the path planning module, and the path planning module is used for receiving and analyzing the dynamic data set and generating an optimal path; the control module is used for synchronously receiving the optimal path, the real-time vehicle body posture dynamic data and the environment change data and generating a control instruction set; the instruction execution module receives the control instruction set, synchronously adjusts the steering angle and the running speed of the agricultural machine, generates actual execution parameters and feeds back the actual execution parameters to the control module. Through arrangement of the control module, the data acquisition module, the path planning module and the instruction execution module, the collision hidden danger caused by insufficient environmental adaptability of a traditional fixed track algorithm is solved.

The invention discloses a farmland furrow three-dimensional point cloud data correction method and system based on a laser radar, and relates to the technical field of three-dimensional image processing based on the laser radar, in particular to a three-dimensional image geometric correction technology. The problems that original point cloud data directly obtained under the dynamic operation condition of an existing agricultural machine has geometric distortion, and the shape of a furrow cannot be truly reflected are solved; meanwhile, the problems that furrow quality evaluation seriously depends on low-efficiency manual means, the adaptability of an existing automatic technical scheme to an unstructured field environment is insufficient, and robust, real-time and high-precision perception of a real three-dimensional shape of a furrow cannot be achieved are solved. According to the method, dynamic tilt correction is carried out through real-time acquisition of point cloud and agricultural machine attitude information, boundary feature points are extracted, boundary lines are fitted, and a three-dimensional point cloud set of a single furrow is reconstructed by fusing a self-adaptive clustering algorithm of spatial prior. The method is suitable for the fields of farmland tillage and soil preparation quality detection, precision agricultural management, agricultural machinery intelligent operation and the like under the dynamic operation condition of agricultural machinery.

The invention discloses an unmanned aerial vehicle-unmanned agricultural machine collaborative operation staged scheduling method under energy consumption constraint, belongs to the technical field of intelligent scheduling, and innovatively designs a three-stage dynamic scheduling mechanism based on operation urgency, and realizes stage adaptive switching through real-time energy consumption monitoring. And an unmanned aerial vehicle-agricultural machinery energy consumption prediction model considering flight conditions and operation parameters is established, and accurate prediction of the residual endurance time is realized by using an LSTM network. An improved NSGA-II multi-objective optimization algorithm is provided, and under a three-objective Pareto optimization framework of total energy consumption minimization, task completion rate maximization and time cost minimization, an energy consumption perception auction mechanism is combined to realize intelligent distribution of emergency tasks to high-electric-quantity equipment. A distributed real-time scheduling system based on edge computing is developed, an edge server is deployed to run a lightweight algorithm, and a real-time scheduling algorithm and a dynamic task conflict resolution mechanism are combined, so that the task redistribution delay is controlled within 500ms, and the conflict resolution success rate is increased to 92.3%.

The invention discloses an agricultural machine navigation method and device, equipment and a storage medium. The method comprises the following steps: determining a visual path point of an agricultural machine at the current moment, acquiring an original farmland image of the agricultural machine looking forward at the visual path point through a camera, and acquiring farmland point cloud data of the agricultural machine looking forward at the visual path point through a laser radar; determining a fitting path line of a farmland furrow according to the farmland original image and the farmland point cloud data; determining the steering angle and the speed of the agricultural machine according to the fitting path line and the visual path point; and adjusting the steering and speed of the agricultural machine according to the steering angle and speed of the agricultural machine to realize navigation driving of the agricultural machine along the fitting path line. According to the technical scheme of the invention, vision is taken as a dominant, the navigation path of the agricultural machinery in the furrow environment is accurately extracted by fusing the camera and the laser radar sensor, and meanwhile, the navigation performance of the agricultural machinery is enhanced according to the navigation path and agricultural machinery motion control, so that the accurate navigation method for the agricultural machinery in the furrow layout environment is realized, and the robustness is high.

The utility model relates to the field of agricultural machinery, in particular to a residual film picking and recycling straw beating machine, which comprises a main frame, a traction frame and traveling wheels, and a straw beating device, a residual film picking roller, a packing device and a transmission device are arranged on the main frame. The plastic film residue picking roller is characterized by structurally comprising a track disc device, a roller body, a center transmission rotating shaft, a shaft disc, a roller side plate, a film picking elastic tooth set, a film picking crank and a crank roller. The machine is reasonable in structure, economical and practical, and can realize the combined operation of picking, recycling and packaging the residual films and smashing and returning the straws to the field; in the picking process, the residual film picking roller can be utilized, the burden is small, the overall flexibility of the picking roller can be effectively improved, and the residual film picking operation efficiency is greatly improved; the special suspension traction frame is utilized to solve the actual problem that an included angle formed between power input and a transmission shaft is too small, and backward transmission of the locomotive is not facilitated, and flexible connection steering and transmission between the traction locomotive and the operation agricultural machine can be achieved.

This application provides a strip photovoltaic power generation method that uses narrow flat photovoltaic panels to encapsulate a photovoltaic power generation strip. Many photovoltaic power generation strips are connected in series to form photovoltaic power generation cables, which can significantly reduce system costs. The strip photovoltaic power generation method of this application has a large span and few pile foundations, and it hardly interferes with the operation of large agricultural machinery. The shadow moves quickly, not only does it not affect crop photosynthesis, but it also increases production and income, allowing arable land to continue to be cultivated normally. This application opens up a vast new world where photovoltaic power generation does not interfere with arable land cultivation, and provides a unique technical solution for ensuring both energy and food security.

The invention belongs to the technical field of agricultural robots, and particularly relates to a multi-degree-of-freedom double-arm pear fruit picking robot based on an agricultural machinery and agricultural technology fusion idea, which comprises a walking chassis, a picking system, a fruit collecting system, a visual system, a control system and an endurance system, the walking chassis is mainly used for bearing mechanical parts and picked fruits, walking in a field and providing power for the whole picking robot, the picking system is carried on a picking robot body and mainly used for grabbing recognized pears capable of being picked, and the fruit collecting system is carried on the picking robot body and used for collecting the fruit collected by the fruit collecting system. The picking robot body is used for conveying the picked pears into the fruit collecting box, and the visual system is carried on the picking robot body. The device can adapt to the picking operation of standardized pear garden planting agriculture in different planting modes, is highly integrated and automatic, can effectively improve the pear fruit picking operation efficiency, greatly reduces the dependence on the labor cost, and achieves the intelligent upgrading of agricultural production.

The invention provides an agricultural machine four-wheel-drive control method and system for optimizing riding comfort, and relates to the technical field of agricultural machine control, and the method comprises the steps: building a dynamic model of a distributed four-wheel-drive agricultural machine based on basic parameters; an optimization model predictive control algorithm containing constraint conditions is constructed by taking the vehicle body acceleration and the driving stability as optimization targets; solving the dynamic model to obtain the optimal tire force distribution of each wheel of the distributed four-wheel-drive agricultural machine; on the basis of a tire magic formula model, through a reverse lookup table, converting the wheel longitudinal force in each optimal tire force distribution into a target wheel slip rate; designing a slip rate tracking controller to enable the actual wheel slip rate to track the target wheel slip rate; based on a tracking result of the slip rate tracking controller, calculating an independent driving torque instruction of each wheel of the distributed four-wheel-drive agricultural machine; independent drive torque commands are executed to control each wheel drive torque to track an optimal tire force distribution.

The invention discloses a greenhouse agricultural machinery data anomaly detection method and system based on an isolated forest algorithm, and the method is characterized in that the method comprises the following steps: S1, obtaining data, and carrying out the preprocessing of the data; s2, performing feature derivation calculation to form derived features; s3, performing feature screening to form data selection features; s4, constructing an isolated forest algorithm model; s5, greenhouse agricultural machine data detection: carrying out real-time detection work; and S6, result interpretation and fault location are carried out. The detection system comprises a data acquisition and preprocessing module, a feature derivation calculation module, a feature screening module, a model training and parameter adjustment module, a real-time detection deployment module and a result interpretation and fault positioning module. According to the method, the problem that the accuracy judgment of the abnormal node is influenced due to the defects that a detection method in the prior art is easy to leak real anomalies, detection fails in a high dimension, real-time streaming data is difficult to deal with and training is difficult due to lack of positive samples is solved.

The invention discloses an agricultural machinery intelligent path planning system and method based on multi-sensor fusion, and relates to the technical field of agricultural machinery automation control. Comprising an AI large model learning module, a visual identification module, a data analysis module and an intelligent control module. The AI large model learning module learns an operation instruction of the agricultural implement controller; the visual identification module collects and extracts agricultural implement controller panel feature information; the data analysis module analyzes, diagnoses and analyzes the feature information; and the intelligent control module transmits the analyzed data to an intelligent driving system of the tractor and executes corresponding control actions. The method solves the problems that the agricultural implements cannot be subjected to associated control under different communication protocols, and the existing scheme is high in cost, complex, low in efficiency and the like, has the advantages of high compatibility, low cost, high efficiency, high adaptability, high safety and the like, and can be widely applied to the field of modern agriculture.

The utility model provides a leveling and deviation-adjusting composite mechanism of agricultural machinery. The composite mechanism is used for connecting and adjusting the positions of a hilly and mountain tractor and an agricultural implement. The combined mechanism comprises a tractor connecting assembly, a machine tool connecting assembly and a posture adjusting assembly. The tractor connecting assembly comprises a tractor traction frame, the machine tool connecting assembly comprises a middle frame and a machine tool traction frame, and the middle frame can rotate relative to the tractor traction frame; the two ends of a leveling hydraulic cylinder and the two-way reciprocating deviation adjusting hydraulic cylinder of the posture adjusting assembly are connected with a tractor traction frame and a middle frame correspondingly, and the posture adjusting assembly stretches out and draws back to drive the middle frame to rotate. Telescopic piston rods are arranged at the two ends of the two-way reciprocating deviation adjusting hydraulic cylinder, and the two ends of the two-way reciprocating deviation adjusting hydraulic cylinder are connected with the two ends of the machine tool traction frame through connecting pieces to drive the machine tool traction frame to slide left and right; the leveling and deviation adjusting composite mechanism can achieve transverse dip angle adjustment of the agricultural implement and adjustment of the left-right position of the agricultural implement.

The invention discloses an automatic path tracking method and system for a crawler-type combine harvester, and belongs to the technical field of unmanned driving of agricultural machinery, and the method comprises the following steps: automatic on-line: obtaining a current position and a current course, carrying out transverse deviation calculation and judgment, adjusting the advancing direction of the harvester, and enabling the harvester to be on-line rapidly; linear path tracking: calculating a transverse deviation and a course deflection angle in real time and finely adjusting the harvester; performing current operation path termination judgment: performing distance judgment, angle judgment and area judgment on the current position of the harvester to obtain a current operation path termination judgment result, and determining whether the harvester reaches the terminal point of the current operation path or not; and right-angle turning: performing right-angle turning to realize accurate line feed operation of the harvester. According to the invention, the problem that the working efficiency is low due to the fact that the existing tracked vehicle cannot quickly go on line and control right-angle turning is solved. According to the method, high-precision path tracking is ensured, and meanwhile, the working efficiency and the stability of a control system are improved.

The invention belongs to the technical field of soil humidity prediction methods, and particularly relates to a soil deep humidity prediction system and method based on near infrared spectrum and federated learning. The system comprises a near infrared spectrum acquisition device, an auxiliary information acquisition module, an edge end data preprocessing module, a federated learning client module, a cloud federated aggregation server and a man-machine interaction and equipment control module. The method comprises the following steps: establishing a surface humidity estimation model by collecting soil surface near-infrared reflectivity and environment auxiliary information; a deep humidity prediction model is constructed in combination with a heat conduction equation and machine learning, and the accuracy is improved by adopting weighted fusion. A federal learning framework is introduced, local training and cloud aggregation of each agricultural machine are realized, data privacy is protected, and the model generalization ability is improved. The system does not need to destroy the soil structure, has the advantages of non-contact, high efficiency, safety and expandability, and is suitable for intelligent prediction of large-range deep humidity in farmland and linkage control of agricultural operation.

This invention relates to a device and method for in-situ detection of seeding spacing and depth based on magnetic field induction, belonging to the field of intelligent agricultural machinery equipment technology. It includes a mounting base at the rear end of a precision seeder, a vertical rod mounted on the mounting base, and a cutting shovel at the lower end of the vertical rod. The cutting shovel has two opposing cutting plates, and the opposing sides of the two cutting plates are respectively equipped with multi-dimensional high-precision magnetic sensing modules for detecting magnetic induction intensity information. It also includes a controller and a GPS wireless speed measuring device. The GPS wireless speed measuring device is used to measure the real-time operating speed of the precision seeder. The controller is electrically connected to both the GPS wireless speed measuring device and the multi-dimensional high-precision magnetic sensing modules. This application can solve the problems of current methods for detecting seeding spacing and depth after sowing operations, which rely on manual labor, have poor detection accuracy, and low detection efficiency.

The utility model belongs to the technical field of agricultural machinery assembly auxiliary equipment, and particularly relates to a roller welding device which comprises a machine frame and a middle frame, the middle frame is installed on the machine frame in a sliding mode, an upper layer frame is hinged to the middle frame, at least two sets of clamping units are arranged on the upper layer frame, and the clamping units are connected with the middle frame. The clamping unit comprises clamping mechanisms which are oppositely arranged, and the clamping mechanisms jointly clamp the roller ring. The middle frame is installed on the machine frame in a sliding mode, translation carrying before and after roller welding is achieved, the upper-layer frame is installed on the middle frame in a hinged mode, unloading after roller welding is achieved through overturning of the upper-layer frame around the hinged point, manual carrying is not needed, and the labor intensity of workers is greatly reduced. The roller ring is clamped during welding through the oppositely-arranged clamping mechanisms, the stability of the roller ring during welding is guaranteed, and therefore the welding quality is guaranteed.

The invention provides a control system and method for power distribution and power generation control of an extended-range agricultural machine based on intelligent identification of a working road surface and a hybrid tractor. The control system comprises the following steps: identifying a field type by collecting image information of a driving road, calculating required power of a vehicle range extender in a corresponding working scene based on the field type, and controlling a range extender assembly; and adjusting the torque of the driving motor and the driving motor based on the field type, the rotating speed of the driving motor and the vehicle speed. Based on field type recognition and historical working data, accurate distribution of driving force and efficient and stable power generation of the range extender can be achieved, the safety and the service life of a power battery are guaranteed, and the farmland operation efficiency of the tractor is improved.