1190 results about "Farm machine" patented technology

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 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 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 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 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 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.

The invention belongs to the field of land parcel information extraction technology, and provides an agricultural machinery operation suitability evaluation method comprising the following steps: S1, based on a remote sensing image and a digital elevation model, extracting field parcel geometric features, road features, field obstacle features and terrain parameters, and calculating field parcel indexes; and S2, a multi-dimensional environment correction factor is calculated, the obstacle influence function and the agricultural machinery operation efficiency loss are integrated, a multi-parameter weighted agricultural machinery operation suitability evaluation model is constructed, and an agricultural machinery operation suitability index is calculated. The invention also correspondingly provides an agricultural machinery operation suitability evaluation system. The method not only reflects the direct influence of field obstacles on agricultural machinery operation, but also objectively quantifies the efficiency loss in actual operation through path planning simulation, and provides a scientific basis for precise reconstruction of farmland and intelligent scheduling of agricultural machinery.

The invention discloses an agricultural machinery intelligent scheduling method based on reinforcement learning and dynamic game optimization, and aims to improve the working efficiency and resource utilization efficiency of agricultural machinery. According to the system, a millimeter wave radar, a 4G / 5G network module and a Beidou positioning system are arranged for agricultural machinery, so that real-time acquisition and primary processing of agricultural machinery position, operation state and environment data are realized, and the data are uploaded to a cloud for further analysis. Secondly, designing a multi-level decision-making mechanism comprising a deployment center, agricultural machinery and task points: in the first layer, the deployment center allocates tasks according to factors such as task priority, agricultural machinery load conditions and terrain resistance; in the second layer, a single agricultural machine optimizes path planning according to a specific terrain so as to realize obstacle avoidance. Besides, a revenue model comprehensively considering the job completion degree, the energy consumption and the delay time is constructed and converted into a reward function suitable for being used by a multi-agent reinforcement learning algorithm so as to promote the agents to make an optimal decision. Finally, the invention provides a set of complete intelligent agricultural machinery scheduling management system from data collection, on-line fine tuning, emergency processing and man-machine collaborative management, so that the agricultural production efficiency is effectively improved, manual intervention is reduced, and the development of intelligent agriculture is promoted.

The utility model relates to the technical field of agricultural machinery transmission system detection, and discloses an agricultural machinery transmission system intelligent running-in table which comprises an installation platform, a main power assembly is arranged on the rear side of the upper end of the installation platform, and a running-in tool is arranged in front of the output end of the main power assembly. A left loading assembly and a right loading assembly are arranged on the left side and the right side of the running-in tool respectively, a transmission axle to be tested is arranged on the running-in tool to be supported, the main power assembly is in transmission connection with the power input end of the transmission axle, and the two output ends of the transmission axle are in transmission connection with the left loading assembly and the right loading assembly respectively. According to the utility model, through the automatic design of the main power assembly, the left loading assembly and the right loading assembly, the full-process automatic operation from axle installation, power input to loading test is realized, and the main power assembly is driven by the first driving motor, the first gear and the first rack plate to automatically complete the butt joint with the input end of the axle. And the complexity and the time cost of manual operation are greatly reduced.

The invention relates to an agricultural machine safety control method and device and a computer readable storage medium. The method comprises the following steps: synchronously acquiring agricultural machine operation data through multiple sensors, extracting terrain, earth surface and motion features, constructing feature vectors, and identifying a geographic position category label of an agricultural machine by using a pre-training model; loading a corresponding exclusive safety control rule according to the label, wherein the rule comprises a specific sensor combination, a risk mapping matrix and a basic operation parameter; screening real-time data according to a rule to calculate a risk state vector, and linearly transforming the risk state vector into a control instruction correction through a mapping matrix; and finally, a control instruction is generated in combination with the basic parameters and is issued to an actuator, so that safety control based on environment category accurate perception and dynamic rule self-adaption is realized, and the operation safety, the environment adaptability and the operation efficiency of the agricultural machinery under complex terrains are effectively improved.

The utility model belongs to the technical field of agricultural machinery assembly, and particularly relates to a roller welding and positioning device which comprises a base, a shaft positioning and clamping assembly, an amplitude disc positioning mechanism, a roller positioning mechanism and a baffle positioning and clamping mechanism are arranged on the base, and the shaft positioning and clamping assembly comprises a rotary clamping mechanism and a rotary jacking mechanism. The rotary clamping mechanism and the rotary jacking mechanism are oppositely arranged, the rotary clamping mechanism comprises a rotary clamping support, a rotary disc and an index plate are rotationally arranged on the rotary clamping support, the rotary disc and the index plate synchronously rotate, a shaft clamping mechanism is arranged on the index plate, and the shaft clamping mechanism is arranged on the rotary clamping support. The shaft clamping mechanism is used for clamping one end of an intermediate shaft, a first positioning hole is formed in the index plate, a plurality of second positioning holes are evenly formed in the index plate in the axial direction, and a first positioning pin and a second positioning pin are arranged on the rotary clamping support. According to the utility model, the dynamic balance performance of the roller is improved, and the occurrence probability of unbalanced faults of the roller in operation is reduced.

The invention relates to an agricultural machinery operation range monitoring system, method and device based on a geofence, and relates to the technical field of agricultural machinery positioning and monitoring, and the system comprises a data acquisition module which is used for determining the contour information of an agricultural machinery based on the positioning information and pose information of the agricultural machinery; the geo-fence setting module is used for determining geo-fence setting information based on the coordinate point sequence of the fence boundary polygon; the real-time monitoring module is used for determining a geo-fence monitoring result of the agricultural machine based on the contour information of the agricultural machine, the geo-fence setting information and a preset fence monitoring algorithm; and the judgment and early warning module is used for determining that the agricultural machinery obtains a grading early warning strategy based on the geofence monitoring result, and performing early warning operation according to the grading early warning strategy. The technical effects that the operation range of the agricultural machine can be accurately monitored in real time, corresponding treatment measures are taken according to different border crossing conditions, graded early warning is achieved, and safe operation of the agricultural machine is guaranteed are achieved.

The invention belongs to the field of multi-machine collaborative operation path planning, and particularly relates to an agricultural machine multi-machine collaborative operation path planning method, which comprises the following steps: constructing environment perception; grid modeling is carried out; agricultural machine capability modeling; the local tasks are optimized and fragmented; agricultural machine operation paths are planned hierarchically; constructing an intention broadcast and carrying out conflict detection; remote feedback is carried out by setting online triggering conditions, and online learning is carried out according to the feedback; according to the invention, the unmanned agricultural machine can sense the environment around the operation in real time while operating according to the statically planned route, and dynamically adjust the operation path according to the feedback sensed in real time, thereby overcoming the defects of the traditional path planning, and feeding back the information to the central control system in real time, thereby adjusting the operation plan in time, and improving the working efficiency. And the problem of delayed response of a traditional method is avoided.

The invention provides a smart farm brain and natural language interaction system based on big data. The system comprises a land parcel selection module, a data perception module, an intelligent decision module, a job execution module and an AI question and answer module. The land parcel selection module is responsible for determining a target land parcel and crops, the data sensing module displays sensor data such as soil and weather of the land parcel according to the selected land parcel, then the intelligent decision-making module generates farming decision-making content according to the sensor data of the selected land parcel, and the operation execution module coordinates agricultural machinery group collaborative operation based on a decision-making result. The AI questions and answers provide natural language interactions with agricultural knowledge. The system can be widely applied to large and medium-sized digital farms and scientific research test farmlands, the farm management cost can be remarkably reduced, the farm operation efficiency is improved, and the agricultural intelligent upgrading and the village revitalizing development process are promoted.

The invention discloses an agricultural machinery braking performance detector based on a Beidou satellite single-point positioning mode, and belongs to the technical field of braking performance detection. The agricultural machinery braking performance detector comprises a signal collector and a host, and the signal collector is internally provided with a satellite signal receiving module compatible with a BDS and a GPS; a sequence parameter extraction module, an integral distance measurement module, an error correction module, a slope calculation module and a performance evaluation module are arranged in the host; the method comprises the following steps: collecting three-dimensional motion data of a detected agricultural machine, calculating an uncorrected braking distance by using a complex Simpson integral algorithm, obtaining an error correction distance caused by single-point positioning signal drift based on a back propagation neural network, calculating the braking distance of the agricultural machine in combination with a slope correction value, and finally judging that the braking performance of the detected agricultural machine is qualified. According to the method, a ground differential base station and an external supporting assembly do not need to be erected, the problem that field detection deployment is tedious is solved, signal drifting and road slope interference are eliminated, and detection convenience and accuracy are improved.

The invention discloses a crawler remote control type bag-controlled slow-release fertilizer applying device and a use method thereof, relates to the technical field of fertilizer applying devices, and solves the technical problem that a bag-controlled fertilizer is difficult to apply due to compression deformation or damp caking. The crawler remote control type bag-controlled slow-release fertilizer applying device comprises a chassis for an agricultural machine, the chassis for the agricultural machine is connected with a control remote controller through a wireless network, a fuel generator set is arranged on the front side of the upper end of the chassis for the agricultural machine, and a fertilizer applying processing device shell is fixedly connected to the middle of the upper end of the chassis for the agricultural machine; the front end of the chassis for the agricultural machine is fixedly connected with a soil shoveling bucket, and the rear end of the chassis for the agricultural machine is fixedly connected with a fixing frame. The fan at the upper end of the air duct operates to blow air into the air duct, the heating plate for separation at the lower end of the air duct is electrified to heat the air, hot air flows into the processing device shell through the through groove in the baffle plate to perform constant-temperature treatment on the fertilizer, and the fertilization efficiency of the bag-controlled slow-release fertilizer is improved.

The invention discloses an agricultural machinery operation scheduling method, device and equipment based on Beidou positioning, and a storage medium, and relates to the technical field of Beidou intelligent agricultural machinery scheduling, and the method comprises the steps: calculating the matching degree score of each agricultural machinery for each operation task based on an agricultural machinery operation capability dynamic evaluation model, and obtaining a matching degree score result; judging whether a score difference value of each agricultural machine for the same task in the matching degree score result is smaller than a preset confidence threshold value or not, and obtaining a judgment result; when the judgment result is that the score difference value is smaller than a preset confidence threshold value, a multi-machine collaborative conflict resolution mechanism is started to execute a bilateral matching algorithm on each agricultural machine and each operation task, and a target scheduling scheme is obtained; and generating an operation path according to the target scheduling scheme, sending the operation path to the agricultural machine positioning terminal to perform agricultural machine operation, and through conflict resolution and dynamic path correction, significantly reducing the empty driving range and improving the operation response speed.

The invention relates to the technical field of agricultural machinery control, and discloses a hill and mountain agricultural machinery all-terrain self-adaptive walking control method and system, and the method comprises the steps: carrying out the point cloud reconstruction of multi-source fusion data of an operation environment, and obtaining an environment terrain field; performing risk situation awareness on the environmental topographic field to obtain regional attribute information; based on the regional attribute information and the dynamic state of the target equipment, performing collaborative path planning on the target equipment to obtain a dynamic obstacle avoidance path; performing soil viscosity trend analysis on the dynamic obstacle avoidance path to obtain a soil adhesion prediction state set; based on the geometric characteristics of the dynamic obstacle avoidance path and the soil attachment prediction state set, performing rolling optimization on a dynamic control strategy of the target equipment to obtain a walking control strategy; controlling advancing and steering actions of the target equipment based on the walking control strategy; according to the invention, the all-terrain self-adaptive walking control efficiency of the hill and mountain agricultural machinery can be improved.

The invention discloses an agricultural machinery group operation task dynamic allocation method, belongs to the field of agricultural machinery scheduling, and aims to solve the problem that the existing static scheduling and single optimization algorithm are insufficient in coping with dynamic and multi-target agricultural machinery scheduling problems. The method comprises the following steps: S1, constructing an agricultural machine group operation task dynamic allocation model, wherein the model comprises a parameter system, decision variables, an objective function and constraint conditions; s2, on the basis of the agricultural machine group operation task dynamic allocation model, a multi-population co-evolution genetic algorithm is adopted for solving, and an initial task allocation scheme and an agricultural machine cooperation path are output; and S3, in the operation execution process of the agricultural machine, receiving the dynamic order in real time, and judging whether the dynamic order is inserted into the current operation route or not based on an improved saving algorithm so as to update a task allocation scheme.

The invention provides a bionic stubble cutting knife, a bionic stubble cutting knife device and a design method, and relates to the technical field of agricultural machinery, the bionic stubble cutting knife comprises a knife disc base body and a plurality of knife teeth uniformly distributed along the circumference of the knife disc base body in the same direction, each knife tooth comprises a main cutting edge, a tooth tip, a knife back and a tooth root reinforcing rib which are connected in sequence, and the angle of the main cutting edge imitates the upper jaw of a earwig. The outer contour curve of the cutter tooth is formed by sequentially connecting a main cutting edge curve, a tooth top curve, a cutter back curve and a tooth root reinforcing rib curve in a transition mode, and the connecting points of the curves are tangent. The bionic stubble cutting knife device comprises a bionic stubble cutting knife, a connecting structure, a vibration reduction structure, a connecting spring and a driving device, and the vibration reduction structure adopts a two-stage composite vibration reduction system. Through a bionic cutting structure, a two-stage vibration reduction system and a flexible adaptive design, cooperation of efficient cutting, stable operation, cost reduction, efficiency improvement and environmental protection is achieved, a better solution is provided for agricultural stubble cutting operation, and technological upgrading of agricultural machinery equipment is promoted.

The invention relates to the technical field of agricultural machinery operation, in particular to a field operation path planning method and system for agricultural machinery equipment in hilly and mountainous regions, and the method comprises the following steps: obtaining terrain data of the hilly and mountainous regions and operation data of the agricultural machinery equipment, so as to construct an environment equipment cooperation data set; analyzing the environment equipment collaborative data set to obtain a field operation segmentation area and a field operation priority as an agricultural machinery operation analysis result; based on the agricultural machinery operation analysis result, establishing a four-wheel steering kinematics model and an agricultural machinery trafficability constraint model as mechanical constraint conditions of agricultural machinery equipment; generating an initial agricultural machine operation path by combining the agricultural machine operation analysis result and the agricultural machine equipment mechanical constraint condition; and performing multi-target adaptive adjustment on the initial agricultural machine operation path according to an agricultural machine operation mode to obtain an optimal agricultural machine operation path. The method is combined with mechanical characteristics of agricultural machinery equipment, the accuracy of path planning is improved, and complex terrains of hills and mountains are effectively adapted.

The invention discloses a multi-modal open-field vegetable management decision method and device, electronic equipment and a storage medium, and the method comprises the steps: obtaining modal perception data corresponding to a target open-field vegetable field; determining a modal feature corresponding to each modal sensing data, determining a feature fusion weight corresponding to the modal feature of each time anchor point, and determining a global multi-modal fusion feature based on the feature fusion weight and the modal feature; and determining knowledge representation features from the agronomic knowledge spectrogram based on the modal perception data, and determining a target decision scheme according to the knowledge representation features and the global multi-modal fusion features. Various data sources such as weather, soil, crop states and agricultural machinery operation parameters are fused, space-time alignment and a self-adaptive weighting mechanism are adopted, a reinforcement learning technology is combined, an agricultural machinery operation strategy is dynamically adjusted according to real-time data, agricultural management measures such as fertilization, irrigation and pest control are optimized, the production efficiency is improved, and the economic benefit is increased. And the real-time performance and the accuracy of decision making are ensured.

The invention discloses an unmanned agricultural machine cluster path planning method based on multiple operation types, and relates to the technical field of agricultural automation, and the method comprises the steps: information acquisition and environment modeling: obtaining farmland, operation tasks and agricultural machine technical parameter information, and employing a grid method to construct a farmland environment model and operation models of different operation types; operation task planning: analyzing the operation tasks based on the operation model to determine the workload and the estimated time, determining the sequence of the operation types, and establishing a constraint rule, and carrying out the reasonable planning of the unmanned agricultural machinery cluster operation path through the comprehensive consideration of the sequence relation of different operation types. According to the method, unnecessary waiting time in the operation process of the agricultural machine is shortened, the phenomenon that the empty driving range is increased due to disordered operation sequences is avoided, meanwhile, in the path planning and optimizing link, multiple factors such as operation efficiency, cost and path length are comprehensively considered, the turning frequency and the running speed uniformity are optimized, and the path planning and optimizing efficiency is improved. And the energy consumption and abrasion of the agricultural machine are effectively reduced.

The invention relates to the technical field of agricultural intelligent equipment and autonomous operation machinery, in particular to a method and a system for simultaneously detecting an operation area and an obstacle. The method comprises the following steps: constructing a work scene data set, and marking non-work areas and obstacle categories for an image; a multi-task learning network YOLODS is constructed based on YOLOv5s, and non-operation area segmentation is realized by adding a network decoding segmentation module; the optimization network decoding detection module is used for respectively extracting target position and category information by adopting a decoupling head and fusing and outputting the target position and category information; and optimizing a loss function, and introducing Focal Loss to solve the problem of obstacle sample imbalance. The system comprises a front-end horizontal camera, a data processing module and a control module, the data processing module operates a YOLODS network to synchronously output an operation area segmentation map and an obstacle detection frame, and the control module plans an agricultural machine path and avoids obstacles according to the operation area segmentation map and the obstacle detection frame. Cooperative processing of operation area pixel-level boundary identification and obstacle instance detection is achieved, the segmentation mIoU on a test set reaches 0.964, the detection mAP at 50 reaches 0.968, and the real-time operation requirement of agricultural machinery is met.

The invention discloses an agricultural machine thin-wall part forming process based on multi-objective optimization. The agricultural machine thin-wall part forming process comprises the following steps that 1, agricultural machine thin-wall part forming basic parameters and multi-objective optimization indexes are determined; 2, an agricultural machine thin-wall part forming multi-physics field coupling numerical simulation model is constructed; 3, constructing a multi-objective optimization model based on an improved intelligent algorithm; step 4, determining a Pareto optimal solution and process parameters; and 5, batched forming and quality monitoring of the agricultural machine thin-wall parts are carried out. According to the technology, by building a multi-objective optimization model and combining numerical simulation and experimental verification, collaborative optimization of forming precision, mechanical properties and production economy is achieved, the forming quality and production efficiency of the agricultural machine thin-wall part are improved, and the production cost and resource consumption are reduced.

A vehicle-mounted support for conveniently replacing a wheel relates to the technical field of agricultural machinery accessories, and when the wheel needs to be replaced, only one person can lift an agricultural machine by using the vehicle-mounted support, so that the wheel replacement difficulty and workload are greatly reduced; comprising a mounting seat and a supporting bracket, and one end of the mounting seat is used for integrally mounting the vehicle-mounted bracket; a mounting hole is formed in the other end of the mounting seat, and one end of the supporting bracket is rotationally connected with the mounting seat through the mounting hole; the other end of the supporting bracket is a supporting end, and the supporting end extends towards the left side or the right side or any one side to form an extending supporting part.

The invention discloses an agricultural machinery driving fatigue grade division method based on multi-source physiological information, solves the problems of insufficient robustness and detection precision of the agricultural machinery driving fatigue grade division method, and belongs to the technical field of human-computer interaction, traffic safety and artificial intelligence cross application. The method comprises the steps that electrocardiosignals and face image data of a driver are collected, feature extraction is carried out, and a heart rate feature vector and a face feature vector of a current sliding window are obtained; fusing the standardized heart rate features and facial features to obtain fused feature representation; taking the fusion feature representation as an observation vector, inputting the observation vector into a time sequence model, and estimating potential fatigue strength; according to the standardized heart rate features and facial features, obtaining respective corresponding edge fatigue probabilities, and fusing the two edge fatigue probabilities into a joint fatigue confidence coefficient; and calibrating the potential fatigue strength by using the joint fatigue confidence, and carrying out ordered grading by using the calibrated fatigue strength to obtain a predicted fatigue grade.

The invention relates to an agricultural machine data transmission optimization system, method and device and a medium, and relates to the technical field of data transmission optimization, and the system comprises a data sensing and classification module which is used for obtaining a plurality of pieces of operation data of an agricultural machine, and determining the priority of each piece of operation data based on a preset data classification rule; the network state sensing module is used for carrying out network detection on a cloud server based on a preset period, obtaining network state parameters of the agricultural machine and determining the quality grade of the current network of the agricultural machine; the data transmission optimization module is used for acquiring the priority corresponding to each piece of operation data and the quality grade of the current network; and selecting and executing a corresponding data transmission strategy based on the priority corresponding to each piece of operation data and the current network quality grade. According to the invention, the problems of high data transmission delay, poor reliability and low bandwidth utilization rate in a weak network environment are solved, and the reliability and real-time performance of data transmission are improved.

The invention discloses a smart agricultural machinery collaborative scheduling method fusing Beidou PNT and Internet of Things data, and relates to the technical field of smart agricultural machinery collaborative scheduling, and the method comprises the steps: collecting agricultural machinery Beidou PNT dynamic data, Internet of Things sensor data and task demand data in real time, and transmitting the data to a scheduling platform; preprocessing the data, removing abnormal values and correcting time deviation; evaluating the health degree and the operation capability of the agricultural machine, the farmland operation progress, the adaptability and the environmental influence; decomposing tasks and sorting the tasks according to agricultural hour urgency, plot priority and agricultural machinery suitability; an improved A algorithm is adopted to plan a working path containing multiple constraints; agricultural machinery is dynamically dispatched, and faults, environment sudden changes and path conflicts are processed in real time; the position, progress, quality and safety of the agricultural machine are monitored, and early warning is performed when abnormity occurs; the scheduling strategy is iteratively optimized based on historical data, and the operation efficiency is improved. According to the method, multi-source data, real-time monitoring and early warning and iterative optimization strategies are fused, the operation efficiency and quality are improved, and agricultural production requirements are met.

A kind of based on four-wheel independent drive chassis's harvesting platform terrain simulation adjusting system and method belong to intelligent agricultural machinery technical field.Aiming at the problem that existing platform is difficult to adapt to complex terrain, the mapping relationship of vehicle pose, terrain elevation function and platform space posture is constructed in unified ground coordinate system, data is acquired in real time by terrain information acquisition module and vehicle posture measurement unit, three degrees of freedom adjustment of platform lifting, pitching and roll are realized by double independent electric push rod through coordinate transformation and geometric inverse solution.The system includes mobile platform, hanging module, harvesting and conveying module, collecting device and controller.The invention realizes high-precision profiling control under complex terrain such as hills and slopes, maintains constant ground clearance and set posture angle, significantly improves harvesting quality and operation safety.