89results about How to "Taking into account precision" patented technology

The invention provides a GNSS data quality prediction method and device based on a fisheye camera, and a medium, and belongs to the technical field of data processing, and the method comprises the steps: determining the satellite orbit information of a future time period with a to-be-evaluated observation station as a reference point based on ephemeris prediction; according to the fisheye sky image shot at the to-be-evaluated observation station and the satellite orbit information, determining satellite feature data of a future time period and the occlusion porosity of the future time period; respectively inputting the occlusion porosity of the future time period and at least part of satellite feature data of the future time period into a general prediction model and an observation station prediction model corresponding to the observation station to be evaluated for data quality evaluation, and obtaining a first data quality evaluation index and a second data quality evaluation index; and determining a data quality prediction result based on the first data quality evaluation index and the second data quality evaluation index. A general prediction model and an observation station exclusive prediction model are introduced to carry out double-model evaluation, and accurate prediction of GNSS observation data quality is realized.

The invention relates to a self-adaptive control method, system and device for environment test equipment, and the method comprises the following steps: S1, data collection: collecting environment detection data and data of a corresponding actuator according to a to-be-controlled physical quantity; s2, selecting or constructing a control object according to the physical quantity to be controlled; s3, performing online identification operation when an identification condition is met, otherwise, directly executing the step S4; s4, feedforward and feedback: calculating feedforward compensation and feedback compensation according to the value of the to-be-estimated quantity, and superposing the feedforward compensation and the feedback compensation to obtain a control instruction; and S5, performing constraint allocation on the actuator: performing saturation constraint processing on the control instruction to obtain a control quantity of the corresponding actuator. Joint online identification can be carried out on the to-be-estimated quantity only through perturbation excitation; different loads and test object states are automatically adapted; saturation constraint processing is adopted; the model and the algorithm are low in calculation amount, and precision, speed and engineering realizability are considered.

The invention discloses a blade aerodynamic robustness evaluation method based on a dual-fidelity collaborative neural network, and relates to the technical field of turbomachinery blade aerodynamic analysis. Acquiring a plurality of groups of uncertainty parameters influencing the aerodynamic characteristics of the blade; inputting the uncertainty parameters into the dual-fidelity collaborative neural network model, extracting feature vectors of the uncertainty parameters through a basic trend prediction module, and predicting low-fidelity aerodynamic performance; weighting the feature vector through a cross-fidelity attention fusion module, fusing the uncertainty parameter and the weighted feature vector, and inputting the fused vector into a residual error correction module to obtain a residual error prediction value; adding the residual prediction value and the prediction value of the low-fidelity aerodynamic performance to obtain a prediction value of the high-fidelity aerodynamic performance; and determining the robustness index of the blade according to the high-fidelity aerodynamic performance predicted values corresponding to the multiple groups of uncertainty parameters. According to the method, the calculation efficiency is ensured while the aerodynamic performance precision of the blade is improved.

The invention discloses a longitudinal driving method and device for automatic parking of a traditional fuel vehicle, the vehicle and a medium, a transmission control unit (TCU) is actively introduced into a control loop of a parking working condition, two interfaces of a longitudinal control signal and a target creeping speed are introduced to be respectively sent to an IPB and the TCU, and a staged arbitration mechanism is introduced into an engine controller (EMS), so that the automatic parking of the traditional fuel vehicle is realized. Smooth starting of the vehicle is ensured, backward sliding and accurate following of the target crawling speed are effectively prevented, and the common problems of unsmooth vehicle speed, rushing and the like in the automatic parking process of a traditional fuel vehicle are solved from the source.

This invention provides a clock discipline method and apparatus, relating to the field of time synchronization technology. The method first calculates the original time difference sequence, then filters it, then calculates the frequency increment based on the filtered time difference sequence, and finally performs calibration based on the frequency increment. This ensures that the frequency deviation information on which calibration depends is no longer affected by the random jitter of the BeiDou clock second pulse signal, thereby suppressing frequent oscillations in the calibration command. At the same time, because the time difference sequence on which calibration is based has become smooth and stable, the calibration process converges faster, avoiding phase disturbances introduced by repeated trial and error. Thus, without sacrificing the inherent short-term stability of the local crystal oscillator, it achieves continuous and stable correction of its long-term frequency drift, taking into account both the short-term stability and long-term frequency accuracy of the output clock.

The application is suitable for the technical field of unmanned ship, and provides an unmanned ship mapping method, an unmanned ship and a computer readable storage medium, which comprises the following steps: in the process of unmanned ship sailing, a plurality of first position points in a target environment where the unmanned ship is located are acquired by a monocular vision device of the unmanned ship; for any one of the first position points, a bearing angle sequence of the unmanned ship relative to the first position point is acquired by the monocular vision device; positioning information of the first position point is calculated according to the bearing angle sequence; and a map of the target environment is generated according to the positioning information of each first position point in the target environment. Through the above method, the problem that the unmanned ship cannot accurately map due to limited load can be solved.

The application relates to the technical field of battery rubberizing, and discloses a lithium battery pole piece rubberizing device which comprises a battery pole piece conveying assembly, a buffer assembly, a power assembly, an adjusting assembly and a burr cutting assembly. The battery pole piece conveying assembly conveys the battery pole piece. The buffer assembly and the power assembly are coordinated to realize seamless adaptation of continuous conveying and intermittent rubberizing, greatly improve production efficiency, the burr cutting assembly is integrated in a pre-rubberizing process, burrs on the pole piece are accurately removed, the risk of film breakage and battery short circuit is avoided, product quality is guaranteed, the adjusting assembly can flexibly adjust the cutting width, the pole piece is prevented from deviating, different specifications of pole pieces are adapted for processing, a waste material collecting structure realizes closed-loop recovery of burrs, and the working environment is kept clean. The overall device has high integration, is convenient to operate, considers precision and efficiency, significantly reduces production cost, and adapts to the automatic production demand of lithium batteries.

The invention relates to the technical field of mobile robot navigation, and discloses a robot adaptive motion control method and system, and the system comprises a step test module which is used for recording odometer data and control quantity data with a timestamp; the parameter fitting module is used for analyzing the odometer data and the control quantity data and establishing a mapping function of the control quantity and the movement speed; the delay compensation module is used for maintaining a historical control quantity queue and predicting the expected pose of the robot when the control instruction sent at the moment t is executed based on the control delay tau; the multi-objective optimization module is used for solving the optimal control quantity; and the online updating module is used for continuously collecting motion data in the motion process of the robot and dynamically updating the mapping function and the key parameters. According to the method, actual motion parameters are automatically obtained through step testing, different robot individuals and performance attenuation scenes are adapted, the problem of model mismatching is solved, and time delay compensation is controlled to reduce positioning deviation.

The present disclosure provides a data fitting method, device and computer equipment for application-specific integrated circuit, relates to the technical field of computer and artificial intelligence, and the scheme is: a self-defined floating-point number model is constructed; fitting control parameters are initialized; based on the self-defined floating-point number model and the fitting control parameters, segmented fitting processing is performed on a target continuous function to obtain a segmented fitting result; based on the self-defined floating-point number model and fitting related parameters, verification processing is performed on the segmented fitting result to obtain a verification result; iterative optimization processing is performed on the fitting related parameters to obtain optimized fitting related parameters; the segmented fitting result is updated based on the optimized fitting related parameters, and error compensation processing is performed on the segmented fitting result to obtain compensated fitting related parameters; and the compensated fitting related parameters are mapped to hardware implementation code, so that the precision, hardware cost and delay can be considered, and the function fitting and hardware implementation efficiency are improved.

The utility model relates to a shoe -pad and shoe sole convenient to dismount, including shoe -pad body and support board, the bottom of shoe -pad body is equipped with the accommodation groove, the support board is placed in the accommodation groove, the front end of above -mentioned support board is equipped with the guide slot and the round hole connected in the rear end of guide slot, the groove bottom of accommodation groove rear end is equipped with the locating post, and the one end of locating post is connected with the locating cap away from shoe -pad body, the side of above -mentioned support board rear end is equipped with the bayonet, and the groove bottom of accommodation groove rear end is equipped with the locking post of cooperation bayonet, and the lower end of this locking post is connected with the locking cap. The rectangular section design of the locating post of the application can limit the rotation of the support board around the locating post with the linear cooperation of the guide slot, further ensure the position accuracy of the support board in the accommodation groove, avoid the influence of the supporting effect due to the deviation of the support board, the user can complete the dismounting of the support board without the help of the tool, and precise positioning can be realized without repeated adjustment, the convenience and the precision are considered, and the operation is simple and convenient.

The application belongs to the technical field of integrated circuits, and particularly relates to a reconfigurable photonic sampling analog-digital converter control method, system and device, which comprises the following steps: S1, obtaining a starting safety configuration, performing an initialization self-check, and when the initialization self-check results all satisfy preset safety starting conditions, the initialization self-check is passed; S2, after the initialization self-check is passed, a target analysis frequency band is determined based on a target working interval, an initial sampling configuration is obtained, calibration samples corresponding to each activated channel are collected, and a coarse calibration configuration is obtained; S3, continuously sampling an analog signal to be converted to generate a performance state frame, performing deep learning analysis based on the performance state frame, and outputting an error estimation result; and S4, generating a candidate control vector according to the error estimation result, performing safety constraint auditing on the candidate control vector, taking the candidate control vector that passes the auditing as a system control vector, and performing target parameter soft updating in the system control vector. The application can be used for data conversion circuit design in a high-performance measurement system.

This invention relates to the field of digital biomechanical assessment technology, providing a method for inverse calculation of dynamic pressure distribution, including: S1: offline initialization, performing finite element discretization on a transparent flexible elastomer, constructing and preprocessing a global stiffness matrix; S2: online scanning and displacement boundary mapping, acquiring the initial height field of the elastomer under no-load conditions and the real-time height field of the bottom of the test part after the elastomer is pressed under load; S3: multi-layer medium refraction dynamic compensation, performing layered refraction correction on the laser beam path based on the surface normal vector of the elastomer after compression; S4: inverse finite element analysis (iFEA) pressure inverse calculation, inputting the corrected displacement field as boundary conditions into a preset mechanical model; S5: geometric-dynamic data fusion output, mapping high-precision three-dimensional geometric mesh and high-resolution pressure texture pixel by pixel. This simultaneously acquires high-precision three-dimensional foot morphology and sub-millimeter-level pressure data, solving the problems of scanning distortion and disconnection between shape and pressure data.

The application relates to a ceramic multi-material continuous forming light-curing additive manufacturing equipment and a process control method thereof. The application is applied to additive manufacturing of multi-material heterogeneous and complex-shaped ceramic components. The ceramic multi-material continuous forming light-curing additive manufacturing equipment comprises a vibration isolation table, a release film conveying module, a multi-material feeding module, a substrate rotating module and a DLP light machine projection displacement module, and each module is installed on the upper surface of the vibration isolation table; the vibration isolation table is a mounting base of the whole equipment and is used for reducing the influence of external vibration on printing precision; the release film conveying module is used for conveying paste and residual paste after curing; the multi-material feeding module is used for feeding different ceramic pastes and realizing material feeding switching; the substrate rotating module is used for bonding and curing ceramic blanks, realizing multi-layer printing and substrate cleaning during material replacement; and the DLP light machine projection displacement module is used for projecting slice patterns to cure the paste and realizing large-format splicing forming.

The application discloses a kind of based on reduced-order model retraining's fractured reservoir injection-production parameter optimization method, it is related to unconventional oil and gas development technical field, including: establishing fractured reservoir full-order numerical simulation model, setting initial injection-production control parameter, running main, vice training simulation;Snapshot matrix is executed singular value decomposition, and reduced-order basis matrix is constructed;Snapshot matrix and the gradient information of main training simulation are executed reduced-order preprocessing, and reduced-order model is constructed;Based on reduced-order model, injection-production parameter optimization iteration is executed and is dynamically judged, until cumulative adjustment step is not more than pre-set allowable value and has reached pre-set maximum iteration step number, then with current optimal injection-production parameter operation verification, output optimal injection-production parameter and objective function value, otherwise using current optimal injection-production parameter updates main training simulation and retraining reduced-order model.The application is through simulation, reduced-order, optimization, update closed loop process, ensure accuracy while greatly improving the calculation efficiency of fractured reservoir production optimization.

The application discloses a numerical simulation method for spray combustion of an aero-engine combustion chamber, and belongs to the technical field of simulation of spray combustion of an aero-engine combustion chamber. The numerical simulation method is based on an adaptive matching iterative solution control mechanism of liquid droplet and flow field motion scale to perform outer circulation; starting from mixed fraction definition and component transport, a coupling relationship between fuel evaporation and combustion is established by deducing mixed fraction source terms and component transport equation source terms under different definitions, so that the numerical simulation method has high-fidelity coupling simulation capability of flow-spray-combustion; the RCCE method is introduced to establish a flame surface database, a large number of components in a chemical reaction mechanism are mapped to a limited number of constraint variables for dimension reduction solution, and a constraint equilibrium state is obtained according to the maximum entropy principle, and finally, the concentration of each component is reconstructed by using a constraint potential energy; while ensuring the accuracy of key chemical thermodynamic coupling, the generation efficiency of a complex fuel chemical reaction database is improved.

The utility model discloses a carpet left front and right front and back carpet assembly testing fixture, which comprises a chassis, a testing fixture main body, an auxiliary positioning mechanism, a positioning clamping mechanism and a detection mechanism, and is characterized in that the testing fixture main body is fixedly arranged in the middle of the chassis, sliding rails are symmetrically and fixedly arranged on the chassis front and back, a sliding frame is slidably arranged on the sliding rails, and positioning buckets are symmetrically and fixedly arranged below one side of the sliding frame; a carpet assembly is plugged into the positioning hopper, positioning reference holes are formed in the four corners of the carpet assembly in a matched mode, detection grooves are symmetrically formed in the detection tool body, positioning reference columns are fixedly arranged at the four corners in the detection grooves in a matched mode, a positioning clamping mechanism is arranged below the other side of the sliding frame, and a detection mechanism is arranged below the other side of the sliding frame. According to the utility model, automatic guiding and positioning of the carpet assembly are realized through cooperation of the slide rail and the positioning hopper, the detection efficiency is obviously improved by combining accurate alignment of the positioning reference hole and the reference column, and the gap pressure change can be monitored in real time and the size can be accurately judged through the detection mechanism integrating the pressure sensor and the feeler gauge.

The application discloses a small sample geothermal resource prediction method and device, system and storage medium, comprising: learning the Bayesian prior knowledge with generalization ability from limited source data by meta-learning, migrating to a new small sample target area through a rapid adaptation mechanism, and utilizing multi-scale differential similarity calculation and mixed student distribution to realize high-precision point prediction and reliable uncertainty interval estimation. By adopting the technical scheme of the application, under the objective constraints of small sample, high cost and strong regional heterogeneity in geothermal resource exploration, high-precision, high-robustness and energy-based uncertainty reserve prediction can be realized.

This invention belongs to the field of pressure sensor technology and discloses a flexible thin-film resistive pressure sensor, comprising an upper flexible conductive thin film layer, a lower flexible conductive thin film layer, a spacer support structure, an elastic insulating isolation layer, and a protective layer. The upper surface of the upper flexible conductive thin film layer is provided with the protective layer. The spacer support structure is disposed between the upper and lower flexible conductive thin film layers, forming a cavity structure. The elastic insulating isolation layer covers the lower surface of the lower flexible conductive thin film layer. The upper and lower flexible conductive thin film layers are made of conductive polymer materials or metal nanowire composite materials, with a thickness of 10-200 μm. The resistance values ​​of the upper and lower flexible conductive thin film layers are greater than 1 MΩ under no-pressure conditions. This invention, through the use of a cavity structure, conductive particles, and a resistance gradient design, can achieve accurate detection from minute physiological signals to large mechanical pressures, while breaking through the limitations of traditional sensor ranges.

The invention discloses a dynamic modeling analysis system for combustion atmosphere data of a biomass oxygen-enriched combustion boiler, and relates to the technical field of dynamic modeling analysis. The system comprises a working condition self-adaptive feature extraction module, a time sequence maintaining model training module, an online self-adaptive correction module and an incremental model updating module. Through a working condition adaptive feature extraction module, a time sequence maintenance model training module, an online adaptive correction module and an incremental model updating module, adaptive feature vectors are generated through feature extraction, a basic model is obtained through training, and online correction and incremental updating are performed by combining feature vector verification threshold judgment. And finally, iterative upgrading is completed through an incremental learning fine tuning model, the reliability of dynamic modeling analysis of the combustion atmosphere data of the biomass oxygen-enriched combustion boiler is improved, and the problem that in the prior art, the reliability of dynamic modeling analysis of the combustion atmosphere data of the biomass oxygen-enriched combustion boiler is low is solved.

The invention discloses an airflow circulation optimization structure and an energy-saving control method of a large walk-in constant temperature and humidity laboratory, the airflow circulation optimization structure comprises a laboratory box body and an airflow circulation system arranged in the box body, and the airflow circulation system comprises two groups of air supply units and a group of air return units which are symmetrically arranged along the length direction of the box body. Through the combination of the symmetrically arranged air supply units and the rotational flow air supply outlets, a gear linkage adjusting mechanism and a particle swarm algorithm are matched, accurate and synchronous optimization of the angles of the air supply outlets is achieved, rotational flow full coverage is achieved, local dead angles are eliminated, the temperature and humidity uniformity in the box is greatly improved, and the reliability of test data is guaranteed. And a flow equalizing plate and a multi-probe sensor group of the main air return channel ensure the accuracy of monitoring data and provide reliable feedback for control.

The present application belongs to the technical field of digital publication processing, and provides a multi-modal PDF content purification and intelligent proofreading system and method based on visual perception enhancement, which comprises a visual perception module, a semantic understanding module and an intelligent decision module; the visual perception module eliminates physical layer interference by generating multi-resolution images, extracting fine structure features and locating invisible characters; the semantic understanding module constructs a knowledge graph and a DST-Transformer model to realize character recognition, semantic coding and image-text association repair; the intelligent decision module outputs a purified document through weighted confidence calculation, dynamic threshold adjustment and cross-platform verification; the method corresponds to the three module steps, realizes full-process processing from physical layer analysis to logical layer reconstruction and then to intelligent output, improves the PDF content purification accuracy and cross-platform compatibility, and is suitable for electronic document deep purification and proofreading.

This invention relates to a method and apparatus for tuning control parameters of magnetic levitation bearings, a storage medium, and an electronic device, belonging to the technical field of magnetic levitation control parameters. The tuning method includes: S1, constructing a mathematical model of a PID parameter optimization problem; S2, generating a Bayesian optimization sample set, fitting a Gaussian process surrogate model, and globally exploring to generate a PID parameter subspace; S3, executing a dung beetle optimization algorithm within the subspace to obtain the optimal point (x) within the subspace. db y db S4, add the optimal point to the Bayesian optimization sample set and update the Gaussian process model; S5, repeat steps S2 to S4 until the condition is met, and output the optimal PID parameter x. db * By combining the global exploration capability of Bayesian algorithms with the local development capability of the dung beetle algorithm, the Bayesian optimization reduces the dependence on the initial sample size, while the dung beetle algorithm accelerates convergence within the subspace, thus balancing efficiency and accuracy.

This invention belongs to the field of UAV defect detection technology, and discloses a UAV bridge defect detection method and related apparatus based on the CSG-DETR model. The method includes: acquiring bridge surface defect images using a UAV to obtain a UAV bridge defect detection dataset; inputting the trained CSG-DETR model into the UAV bridge defect detection dataset to obtain multi-scale features; performing feature fusion and enhancement mechanisms on the multi-scale features to obtain fused features containing structural and semantic information; generating target-level feature representations through global modeling; and detecting the target category and bounding box of bridge defects based on the target-level feature representations, outputting the UAV bridge defect detection results. This invention achieves the dual goals of improved accuracy and lightweight design, has broad application prospects, is suitable for UAV inspection scenarios, realizes real-time, high-precision detection of bridge surface defects, and reduces the cost and risk of manual inspection.

The invention relates to an optical parameter detection device and method, in particular to an optical system wavefront detection device and method based on phase modulation. In order to solve the problems in the prior art that a multi-frame acquisition strategy adopted by a phase recovery method based on a point spread function is difficult to adapt to a dynamic test scene, a single-frame acquisition strategy is difficult to stably invert wavefront with conjugate symmetry, and iterative inversion operation time is relatively long and may fall into a local optimal solution, the invention provides a phase recovery method based on a point spread function. The invention discloses an optical system wavefront detection device based on phase modulation. The optical system wavefront detection device comprises a module, a first imaging lens, a first plane mirror, a beam splitter, a microscope objective, a second plane mirror, a partition phase plate, a second imaging lens and a photoelectric detector, and asymmetric phase coding is achieved through the partition phase plate. Based on the device, according to the method, the unsupervised deep neural network is combined with the physical driving layer, so that accurate inversion of different optical systems to be detected is realized.

The invention discloses a power electronic module and system for a switch and a detection method. In the module, an insulating substrate is arranged in a packaging shell; the plurality of power semiconductor chip units are connected in parallel to the insulating substrate; the three-dimensional suspension type non-contact sensing structure is arranged in the packaging shell, and the sensor carrier plate is installed above a single target power chip in the multiple power semiconductor chip units in a crossing mode in a three-dimensional suspension mode through the insulating supporting piece and does not occupy a main power wiring area of the insulating substrate in the vertical projection direction. The chip-level current sensor is integrally mounted on one side, facing the single target power chip, of the sensor carrier plate in a surface-mounted manner and directly faces a bonding wire arching area of the single target power chip, and the chip-level current sensor is configured to acquire branch current flowing through the single target power chip in a non-contact magnetic coupling manner and output an analog voltage signal; and the analog signal output end of the chip-level current sensor is directly connected to the hardware straight-through protection terminal through a low-impedance straight-through path.

The application discloses a world time continuous solution method, comprising: obtaining and preprocessing the solution result files of each session in a predetermined time range; applying uniform constraints to each session after preprocessing, and performing parameter blocking and local parameter elimination; constructing a sliding time window in a target time range, parameterizing the world time by using a segmented linear function in the window, and establishing a session and time node mapping relationship; constructing a sliding time window on a global time axis, collecting sessions in the window, superimposing a session weight equation, adding a time node smoothing constraint, and jointly solving the world time residual increment; superimposing a priori on the joint solution result, recovering a tidal term, and generating a world time continuous sequence. The application solves the problems of the existing world time product, such as limited time resolution based on daily parameter level combination, insufficient utilization of session level observation geometry and equation information, sensitivity to modeling differences of different session types, and difficulty in adapting to the existing reference framework.

The present application provides a kind of light weight face emotion recognition method and system, it is related to computer vision technical field, the method includes: obtaining image sequence to be processed;Image sequence is carried out character region detection, and character region image is extracted;Main path pretreatment is executed to character region image, obtain the image data to be identified and input emotion recognition model, obtain first emotion label and its confidence, and main path pretreatment includes histogram equalization processing;When the confidence of first emotion label is lower than preset threshold, alternative path pretreatment is executed to character region image, obtain supplementary image data to be identified and input emotion recognition model again, obtain second emotion label as final emotion label;When the confidence is not lower than preset threshold, with first emotion label as final emotion label.The present application is through main path fast inference and alternative path on-demand precision inspection dual-path mechanism, in light weight deployment scene, the real-time performance and accuracy of face emotion recognition are considered.

The present application relates to a kind of navigation satellite orbit determination precision promotion method based on pseudo-range deviation correction, belong to satellite navigation field, the method is combined with global distribution ground station dual-frequency pseudo-range observation value and external precise orbit clock difference product constructs ionosphere-free combination observation equation, through precise point positioning calculation receiver coordinate and constructs posteriori pseudo-range residual equation;According to the grouping of receiver model and the application of zero-sum constraint, align receiver clock difference, through multi-epoch joint network least square batch processing each type receiver is solved to each navigation satellite dual-frequency ionosphere-free combination pseudo-range deviation value;According to the receiver model of ground station, select the pseudo-range deviation value of corresponding type, deduct from dual-frequency ionosphere-free combination pseudo-range observation, obtain the pseudo-range observation of correction;Using the pseudo-range observation of correction and carrier phase observation, joint solution navigation satellite precise orbit parameter.The present application has significantly improved the navigation satellite orbit determination precision and spatial reference consistency level.

This invention discloses a dual-channel spraying device for weed control during crop seedling stages, belonging to the field of agricultural pesticide application technology. It includes a frame and a spray boom mounted on the frame. The spray boom is equipped with a lifting mechanism to raise and lower the boom and maintain its stability. A foldable spray boom is mounted on the boom. Below the spray boom are a target nozzle array and a sealing nozzle array. The target nozzle array is used for targeted spraying of seedling weeds, while the sealing nozzle array is used for sealing spraying of the soil surface in the work zone. The target nozzles of this invention employ a small cone angle and close spacing, enabling precise, point-to-point spraying of weeds and avoiding the waste of pesticide and the risk of crop damage caused by uniform spraying across the entire area. The sealing nozzles employ a large fan angle and wider spacing, forming a continuous and uniform pesticide film through droplet overlap, ensuring consistent sealing effect. The two spraying modes complement each other on the same platform, balancing precision and comprehensiveness.

The application discloses a kind of tree sap flow prediction method and equipment combined with gradient promotion and time convolution, first acquisition includes the time series data of tree sap flow data, corresponding environmental factor and equipment parameter;And pretreatment is carried out;Then the key factor that is screened with the influence tree sap flow data using lightweight gradient promotion machine model;Then the multivariate time convolution prediction model of integrated gate feature fusion mechanism is constructed, and the multivariate time convolution prediction model constructed is trained;Again, the trained multivariate time convolution prediction model is used to carry out tree sap flow prediction;Finally, based on the post-processing of the prediction result of sliding quantile and environmental factor, the prediction result is converted into probabilistic output.The application realizes the efficient prediction of tree sap flow by the triple optimization strategy of "feature screening-model construction-postprocessing".The overall scheme considers accuracy and efficiency, and the supporting equipment is simple, low in power consumption, suitable for long-term monitoring and early warning application of tree sap flow.