1322 results about "Speed measurement" patented technology

The invention discloses an indoor water tank sediment starting speed measurement system and method, and aims to solve the technical problem that data accuracy is affected due to the fact that a sensor disturbs a flow field in an existing measurement method. The core of the technical scheme is that the non-contact measurement characteristic of the PIV technology is applied to the whole process from flow field construction to data acquisition. The device is mainly composed of an imaging unit, a laser lighting unit, a movable sliding frame, a water flow adjusting unit and a buffer plate. Optical measurement is carried out through the imaging unit and the laser illumination unit, a physical sensor does not need to be arranged in a flow field, and interference of a measuring instrument on a water flow structure and a sediment starting process is fundamentally avoided. The movable sliding frame which is integrally designed integrates the functions of sediment laying, particle throwing and measuring, so that a test area can be quickly positioned; and the buffer plate and the water inlet and drainage adjusting unit are combined, so that a gradually-changed flow field from weak to strong can be accurately and stably simulated.

The invention belongs to the technical field of intelligent traffic, and discloses a road vehicle speed and distance detection method, system and device based on unmanned aerial vehicle vision. The method comprises the steps of tracking a vehicle in a to-be-processed video aerially photographed by an unmanned aerial vehicle in real time through an improved YOLOv11 network and a BotSort algorithm to obtain a vehicle trajectory, and converting a vehicle pixel coordinate detected by each frame into a world coordinate in combination with a conversion matrix H of the pixel coordinate and the world coordinate to form a trajectory sequence of the vehicle in the world coordinate system; and for a certain vehicle i, according to the pixel coordinates at the t-th moment and the (t + t)-th moment in several continuous video frames, corresponding world coordinates are obtained through the conversion matrix H, the displacement between two points is calculated according to an Euclidean distance formula, and the average speed of the vehicle in the time period is calculated. According to the invention, efficient, stable and reliable vehicle speed measurement and vehicle distance calculation can be realized.

The invention provides an unmanned aerial vehicle real-time road condition monitoring method and system and a medium, the method relates to the field of image data processing, and the system comprises an unmanned aerial vehicle which comprises an image acquisition device and a sensor group and is used for acquiring aerial videos and flight parameters of the unmanned aerial vehicle in real time; the streaming media server is used for receiving and storing the aerial video transmitted by the unmanned aerial vehicle; analyzing the video stream into a frame-by-frame image sequence with aligned timestamps; performing target detection on each frame of image, and identifying a target vehicle by using a pre-trained deep learning model; carrying out target tracking on the target vehicle in the continuous frames based on an intersection-to-union ratio matching and trajectory prediction algorithm, and constructing a target motion trajectory; and calculating the displacement distance of the target vehicle in the image based on an optical flow method, feature point matching and a deep learning algorithm, and estimating the actual running speed of the vehicle in combination with the flight parameters of the unmanned aerial vehicle. According to the system, computer vision and sensor technologies are combined, and accurate speed measurement is realized through target detection, tracking and speed estimation.

Disclosed is a low-precision incremental encoder-based method for ultra-low speed control of a servo system. According to the present invention, a fast speed observer in an ultra-low-speed working state is achieved, only a sampling speed and load torque in an M / T method need to be observed, and position information of an electric motor does not need to be observed, such that the structure of the observer is simplified, and calculation is simple and fast; moreover, the influence of a friction force and cogging torque on a speed change is considered, such that the speed observation precision is further improved. The fast speed observer can reduce hysteresis and measurement dead zones, such that the speed response and the speed control precision in a low-speed working state are greatly improved, the problem in a traditional observer of a large position deviation caused by nonlinear factors such as an external load is avoided, improving the stability and robustness of the system. According to the present invention, the processing of sampling measurement time at a medium-high speed and the processing of switching the observer at a low speed in the M / T method can optimize the speed measurement precision at both the medium-high speed and the ultra-low speed, and can better satisfy the requirements of apparatuses such as a radar on rotating speed control.

The invention relates to the field of meteorological detection and analysis, and discloses a low-altitude complex wind field detection and inversion method based on a vehicle-mounted laser radar, and the method comprises the steps: determining a scanning point location based on the terrain, building distribution and simulation data; optimizing the driving path of the vehicle-mounted radar to cover the high-risk area; acquiring three-dimensional wind field data by adopting an RHI and PPI multi-mode scanning strategy; the influence of vehicle-mounted movement on speed measurement is corrected; calculating turbulence intensity and vortex nucleus position by using spectral width characteristics; and identifying the wind shear position and strength through a slope algorithm. According to the invention, low-cost and high-precision wind field detection is realized through maneuvering deployment and multi-mode cooperation, and reliable technical support is provided for safe flight of the unmanned aerial vehicle, low-altitude traffic management and meteorological early warning.

The invention provides a backup degradation train control system based on rail transit intelligent perception, the system comprises existing vehicle-mounted signal subsystems loaded at two ends of a train, a vehicle interface, a bridge and an intelligent perception subsystem, the intelligent perception subsystem comprises an ATO, an ATP, an ITE, a perception device and a speed measurement device; the sensing equipment is connected with the existing vehicle-mounted signal subsystem; the switching equipment is used for switching to the intelligent sensing subsystem to run in an autonomous sensing mode when the train with the CBTC is degraded due to a fault, and the existing vehicle-mounted signal subsystem is still maintained in an RM mode; when the train which autonomously perceives running runs to the area with the upgraded CBTC, the vehicle-mounted equipment is switched back to recover running of the train CBTC; the wireless communication device is used for being in wireless connection with the vehicle-mounted signal subsystem and the trackside device. The intelligent sensing subsystem operates when the CBTC breaks down and degrades, toughness is improved, and it is achieved that the train does not get off line in the peak period.

The invention relates to the technical field of video water flow velocity detection, and discloses a river video velocity measurement method and device based on a multi-feature fusion PSA-ResNet network, and a medium. The method comprises the following steps: constructing an STIA data set; extracting low-level textural features of the space-time image by using a CLBP multi-feature extraction algorithm, performing channel-level fusion on a feature map and an original RGB image to form a six-channel CLBP-STIA feature map, and constructing a CLBP-STIA data set according to the six-channel CLBP-STIA feature map; fusing a pyramid segmentation attention module PSA in a residual block of the residual network ResNet to construct an angle classification model, and training the model by using a CLBP-STIA data set; generating enhanced feature representation of the to-be-detected space-time image by referring to the above mode, then inputting the enhanced feature representation to the trained classification model, and outputting a corresponding texture principal direction angle; and acquiring the actual length of the velocity measurement line in the video image, and calculating the actual flow velocity of the surface flow feature on the velocity measurement line in combination with the texture main direction angle. The texture main direction is accurately estimated, so that the speed measurement precision and efficiency are improved.

The invention relates to the technical field of video monitoring, and provides an ectopic dual-camera intelligent vehicle speed measurement method and system based on deep optimization. The method comprises the following steps: acquiring images acquired by two cameras which are arranged at different positions on the same side of a road; extracting features of each vehicle based on each vehicle detected by the first image and the second image, and matching the features of the vehicles in the first image and the second image; when a target vehicle reaches a speed measurement point area, determining a three-dimensional geometric projection constraint residual error according to depth estimation values of the two cameras and three-dimensional geometric projection constraints of the target vehicle and the two cameras, constructing an error-minimized target function in combination with a depth consistency error, and optimizing the depth estimation values of the two cameras to obtain a target vehicle speed measurement result; obtaining depth estimation optimization values of the first camera and the second camera; and converting the two-dimensional track pixel coordinates of the target vehicle into three-dimensional world coordinates based on the depth estimation optimization values of the first camera and the second camera, and calculating the final speed of the target vehicle.

The invention discloses a method for calculating a vehicle speed based on a moving unmanned aerial vehicle video, and belongs to the technical field of vehicle speed calculation methods through videos, and the method comprises the steps: extracting global feature points of a video frame through employing an SIFT operator, calculating a homography matrix H through combining with an RANSAC algorithm, projecting a previous frame image to a current frame, and carrying out the calculation of the current frame image; the method effectively eliminates the interference of the motion (such as flight attitude change and displacement) of the unmanned aerial vehicle on the vehicle speed calculation, solves the problem of speed measurement failure caused by the deviation of the motion directions of the unmanned aerial vehicle and the vehicle in the traditional method, enables the algorithm to be suitable for complex scenes such as curves and multi-angle flight of the unmanned aerial vehicle, improves the adaptability of the system in a dynamic environment, and improves the reliability of the system. According to the method, the YOLOv5-1 model is combined with the DeepSORT algorithm, high-precision detection and stable tracking of the vehicle are achieved, even under the complex conditions that the vehicle is partially shielded, illumination changes and the like, continuous detection frame association can still be kept, and reliable time sequence data support is provided for vehicle displacement calculation.

The invention belongs to the field of unmanned aerial vehicle safety, and particularly relates to an unmanned aerial vehicle high-speed collision body safety evaluation test device, which comprises a collision protection cabin, a speed measurement device, a sabot separation mechanism, a special-shaped gun barrel, a rapid bomb loading device and a gas storage tank, the special-shaped gun barrel is cylindrical and horizontally arranged, the impact protection cabins are arranged on the outer side of the output end of the special-shaped gun barrel at intervals, and the speed measuring device is arranged between the impact protection cabins and the output end of the special-shaped gun barrel. The high-speed impact test of the unmanned aerial vehicle is realized by adopting the special-shaped gun barrel and the integrated sabot separation mechanism and adopting the 400mm large-diameter gas gun impact test device to accelerate the unmanned aerial vehicle to a specified speed, so that the reliability of a test result is ensured, and the test cost and the test difficulty are also remarkably reduced. Meanwhile, the method has wide applicability, can be used for the unmanned aerial vehicle, and is also suitable for impact damage evaluation of an object of 2 kg or above at the speed of 150 m / s.

The invention discloses a system parameter adjustment method. The method comprises the following steps: screening to-be-adjusted system parameters according to a preset strategy and sorting the system parameters; according to the default values of the system parameters, adjusting ranges corresponding to the system parameters are generated, and adjusting strategies corresponding to the types of the system parameters are obtained; selecting system parameters one by one according to the sorting result, and performing adjustment and speed measurement according to an adjustment range and an adjustment strategy corresponding to the system parameters so as to obtain an optimal adjustment value corresponding to the optimal speed measurement result; performing adjustment and speed measurement on the next system parameter based on the optimal adjustment value to obtain the optimal adjustment value corresponding to the next system parameter; and after the optimal adjustment values of the system parameters are obtained, combining the optimal adjustment values corresponding to the system parameters into a system parameter optimal adjustment set. By applying the technical scheme of the invention, each system parameter in the speed measurement system can be reasonably and efficiently adjusted, the optimal performance of the test system is realized, and the optimal speed measurement result is obtained.

The invention discloses a cascading filtering positioning method and device in a complex and severe environment of a well mine and a medium, and achieves a high-precision positioning function of a well mine unmanned vehicle based on a cascading filtering method. According to the method, the IMU, the wheel speed and the wheel rotation angle are subjected to data fusion through adaptive Kalman filtering, the influence of non-Gaussian noise on wheel speed measurement is reduced through non-Gaussian noise feature extraction, and robust prior positioning information is obtained. According to the method, a regular term representing feature degradation is constructed, a laser radar observation model based on a prior map and laser radar data is constructed, and finally, a result of the laser radar observation model and prior positioning information are fused according to the regular term under a regularization Kalman filtering framework to obtain posterior positioning information. The precision and robustness of the method meet the positioning requirements of the mine unmanned vehicle.

The invention relates to the technical field of mine ventilation, in particular to a mining optical fiber wind speed sensor and a detection system. The mining optical fiber wind speed sensor comprises a shell, wherein a main air channel, a first sub-air channel and a second sub-air channel which are communicated with one another are formed in the shell; the dust removal assembly is arranged in the main air duct and blocks the flowing direction of the air flow; the airflow is separated into first airflow and second airflow after flowing through the dust removal assembly, and the first airflow comprises impurities; the speed measuring assembly is arranged in the second sub-air duct and located on the outlet side of the second sub-air duct, and the speed measuring assembly is configured to measure the air speed of the second airflow; wherein airflow enters the shell through the inlet of the main air duct and is separated into first airflow and second airflow through the dust removal assembly, the first airflow flows out of the shell through the first sub air duct, and the second airflow flows out of the shell through the speed measurement assembly in the second sub air duct. Impurities in airflow flowing into the sensor are removed twice, so that the problem that the impurities damage the sensor is reduced.

The invention relates to the technical field of fabric testing, in particular to an experimental testing method and device for determining the impact resistance of fabric, and the method comprises the following steps: S1, initial calibration: installing the fabric to be tested on a fabric frame, adjusting the tension of the fabric to be tested to a set value through a first electric push rod, starting an electromagnetic suction table to compress a spring to an energy storage state, and starting a second electric push rod; the pressure sensor array module is impacted by a bullet launched in a no-load mode, the process is repeated three times, an impact force calibration value is obtained, and the speed measurement sensor is synchronously calibrated, and S2, testing position switching is conducted, and liquid agar gel is injected into the transparent gel cylinder. According to the invention, through a unique spring system, the linear transmission module is utilized to drive the electromagnetic suction table to move, and the stretching amount of the spring is accurately controlled, so that the accurate adjustment of the projectile launching speed is realized, and the impact at various speeds can be simulated when the impact resistance of the fabric is tested.

The invention relates to an arrangement for optical distance and / or speed measurement with a mode multiplexer in the coaxial transmission and reception path, wherein a different mode is used for transmission (i.e., light emission or the transmitter) than for the reception path. This eliminates the need for a circulator in the transmission path. The mode multiplexer thus assumes the function of branching the reception channel from the transmission channel and can be integrated as a PIC.

The invention discloses a train multi-source information fusion positioning method based on 5G positioning, which fuses multi-source data information such as 5G positioning information, satellite positioning information, speed sensor information, transponder information and the like, and provides more reliable train position and speed information through redundancy complementation of the multi-source data information. The defect that positioning depends on satellite positioning and is greatly influenced by terrains and environments is overcome, and the problems that in the prior art, in the environments where satellite signals are shielded in tunnels, valleys and the like, satellite positioning fails, a system only uses a wheel axle speed sensor for speed measurement and distance measurement, and errors are large are solved.

The invention relates to a train dormancy awakening method and system based on TACS fusion control, and the method comprises the following steps: before a train is dormant, an AOM stores the position information of the train; in the train dormancy process, the speed measurement positioning board card keeps power supply, the speed measurement positioning module continuously collects speed pulse signals, train position information is calculated, and the train position information obtained through calculation is sent to the AOM; before the train is awakened, the AOM compares the position information obtained from the speed measurement positioning module in real time with the position information stored before dormancy, and whether the train is allowed to be awakened or not is judged based on the comparison result. According to the method, power supply is kept for the speed measurement positioning module during the train sleep period, real-time monitoring of the train position during the sleep period is achieved, meanwhile, through position comparison before wakeup, the wakeup efficiency of the train is improved, and wrong wakeup operation caused by abnormal movement of the train is prevented.

The invention relates to a long-gap discharge leader development speed measurement method based on radiated electromagnetic wave detection. The method comprises a set of high-frequency antennas and a high-speed oscilloscope and a long-gap discharge leader development speed calculating method. The method adopts a certain antenna arrangement form; long-gap discharge radiated electromagnetic wave pulse time is detected simultaneously through the plurality of antennas; leader head position is positioned according to time difference of a signal arriving at different antennas; and furthermore, the long-gap discharge leader development speed can be calculated. The method can effectively improve the measurement precision of the discharge leader development speed, and resolution reaches the level of 0.1 ns.

The embodiment of the invention discloses a real-time tennis ball speed calculation method and system based on a sliding window, and the method comprises the steps: carrying out the data buffering through employing a 35-frame first-in first-out buffer region based on a three-dimensional track point, screening effective points, calculating the instantaneous speed according to a Euclidean distance formula and an inter-frame time interval, and obtaining the real-time tennis ball speed. And through a three-frame sliding window average smooth speed curve, abnormal values are filtered by using a 10-220km / h threshold value, and ball speed calculation is realized. Through three-dimensional track points, ball speed calculation is realized through the steps of data buffering, effective point screening, instantaneous speed calculation, sliding window averaging, threshold filtering and the like. Compared with traditional single-point speed measurement, the precision is improved by about 20% by means of three-frame sliding window and three-dimensional coordinate calculation, and single-frame errors are reduced; the robustness in a complex scene is enhanced through data screening, window averaging and threshold filtering; the process is simple, the calculated amount is small, and the real-time requirement of occupational competitions is met; a fixed 35-frame buffer area optimizes resources, and memory redundancy is avoided.

The invention discloses a flow velocity measurement system adopting bubble tracing, and the system comprises a circulation loop which is internally provided with a medium storage tank and a pump body; the air supply branch is connected into the circulation loop and provided with an air storage tank, and the air storage tank is used for supplying air to the circulation loop so that bubbles can be generated in the circulation loop; and the flow velocity measuring device is used for monitoring bubbles in the circulation loop. In conclusion, the flow velocity measurement device obtains the bubble motion information from the outside of the circulation loop, and a speed measurement device such as a sensor does not need to be inserted into the circulation loop, so that disturbance to a medium flow field in the circulation loop is avoided, the measurement is more real and reliable, and the accuracy is higher.

The invention discloses a speed measurement positioning method and device for a rack rail train, electronic equipment and a storage medium. Comprising the steps that when the rack rail train runs on the rack rail, a tooth number recognition sensor is used for continuously measuring the tooth number of the rack rail, the running time of the rack rail train passing through a preset interval is calculated, and the tooth number recognition sensor is arranged on the rack rail train; and the real-time speed of the rack rail train is determined according to the running time and the preset distance. Speed measurement of the rack rail train can be efficiently and accurately completed, and the problem that the speed measurement precision of the rack rail train is low is solved.

A vehicle positioning device, comprises a wireless communicator, at least one ultra-wideband transceiver and a signal processor. The ultra-wideband transceiver is disposed in a vehicle and configured to receive a pulse signal with source information from another ultra-wideband transceiver. The signal processor is connected to the at least one ultra-wideband transceiver and a speed measuring device of the vehicle, and configured to generate a position information according to the signal value of the pulse signal and the source information and transmit the position information and a vehicle speed information obtained from the speed measuring device through the wireless communicator to a server, and receive a driving information associated with the position information and the vehicle speed information from the server through the wireless communicator.

The invention discloses a speed measurement method of an optimized speed observer, relates to the technical field of vehicle power control, and solves the problem that a small negative value is easily taken as a large positive value or a small positive value is easily taken as a large negative value due to the fact that a deviation angle crosses a period in angle error calculation of an existing speed observer. The speed measurement method comprises the following steps: the acquisition and processing module acquires and processes a pulse signal of the encoder to obtain a feedback angle; an angle estimation value is calculated; taking the difference between the feedback angle and the angle estimation value as a deviation angle, and performing nonlinear compensation to obtain an angle deviation value; inputting a matrix operation framework of a speed observer, and outputting a linear acceleration estimated value; the pulse signal of the encoder is collected and processed again, a feedback angle is obtained, M-method operation and filtering processing are carried out on the feedback angle and the last feedback angle, and the feed-forward speed is obtained; and the speed observer performs weighted fusion operation on the linear acceleration estimated value, the angle deviation value and the feedback angle to obtain a final angular velocity estimated value, so that a final estimated angle is obtained, and velocity measurement is completed.

The utility model discloses a device used for detecting parameters of a mowing robot, comprising a workbench and a mowing robot, the workbench is provided with a test platform, the mowing robot is installed on the test platform, the device also comprises three-axis electrical parameter modules, the two sides of the test platform are both provided with the three-axis electrical parameter modules, and the three-axis electrical parameter modules are connected with the test platform. The three-axis electrical parameter module is used for detecting information of a wheel set and a cutter head of the mowing robot. The wheel set information of the mowing robot can be collected through the self-resetting wheel speed measurement module, the cutter information of the mowing robot can be collected through the photoelectric sensor, and the information can be collected through the PCB main control board.

The invention provides an intelligent traffic cone barrel anti-collision early warning method based on binocular vision, and aims to improve the safety of a road construction operation area. And accurate data are provided for subsequent detection and analysis through a binocular camera high-precision calibration technology based on circle detection. In combination with a data acquisition and enhancement technology, high-quality training data is provided for an improved RT-DETR algorithm, and the accuracy and efficiency of vehicle identification are significantly improved. A binocular vision depth perception and StrongSORT multi-target tracking algorithm is utilized to realize real-time speed measurement and distance measurement of a vehicle, and accurate input is provided for track prediction. Based on a GAN multi-modal trajectory prediction technology, a plurality of future trajectories are generated, and a multi-level early warning decision is realized through a comprehensive collision risk index (CRI). According to the method, the limitation of an existing prediction method in a complex road scene is effectively solved, the vehicle behavior intention is predicted and analyzed through the multi-modal trajectory, and reliable early warning information can be provided under various complex road conditions.

The invention discloses a hidden danger pre-diagnosis method of an elevator traction system, relates to the technical field of elevator safety monitoring, and is used for solving the technical problems of poor real-time performance, low accuracy and difficulty in defect positioning of hidden danger diagnosis of the elevator traction system in the prior art. The hidden danger pre-diagnosis method for the elevator traction system comprises the steps that multi-source data are synchronously collected, specifically, a current transformer is deployed in a power supply loop at the input end of an elevator traction motor to collect a three-phase current instantaneous value, a speed measurement encoder is used for measuring the speed, the elevator running state, the speed, the floor position and the time-variable load weight are synchronously obtained, and a time-space correlation data set is constructed; signal self-adaptive preprocessing: performing layered noise reduction, working condition alignment and dynamic normalization processing on the acquired current signals; multi-scale feature fusion extraction: current signal features are extracted from a basic feature layer, a time domain feature layer, a frequency domain and a time-frequency domain feature layer; and feature optimization and decision making: after feature screening and dimension reduction fusion, inputting a pre-training classification model to output hidden danger types, positions and risk levels.

The invention relates to the technical field of rail transit, and provides a multifunctional rail detection system, which comprises a multi-source data acquisition unit, an optical fiber inertial navigation sensor, a laser array module, a dual-mode camera group, a radar speed measurement module and a temperature and humidity sensor, the data acquisition module is used for synchronously acquiring track geometric parameters, three-dimensional surface topography, inertial navigation data, real-time vehicle speed and environmental parameters; the dynamic processing unit is arranged in the compartment and comprises a data fusion controller, a self-adaptive Kalman filtering module, an anomaly diagnosis engine and an edge computing host, and the data fusion controller integrates multi-source data through a multi-thread parallel processing technology. On the basis of self-adaptive Kalman filtering and vehicle speed-parameter dynamic mapping, the track gauge detection error under the variable speed working condition is reduced to + / -0.3 mm from + / -3 mm, and the curvature radius calculation error lt is obtained; and the predictive maintenance model prolongs the overhaul period of the track by 40%, and reduces the operation and maintenance cost by 35%.

The invention relates to a motor filtering speed measurement method based on an FPGA, and belongs to the technical field of motor speed measurement. The filtering speed measurement method comprises the following steps: detecting rotation of a motor through a Hall encoder and outputting a pulse signal, outputting the pulse signal to a digital quantity input interface of an FPGA (Field Programmable Gate Array), and realizing a filtering speed measurement algorithm in the FPGA in a hardware form; and performing data operation processing on the pulse signal by using an FPGA based on a filtering speed measurement algorithm to realize measurement of the rotating speed of the motor. Compared with a speed measurement method in the prior art, the method has the advantages that the FPGA is combined with a filtering speed measurement algorithm, so that the rotation speed of the motor can be measured, the problem of low speed measurement precision of the motor in an unstable state can be effectively solved, the anti-interference capability of motor speed measurement can be improved, and the response speed of a speed measurement system can be increased.

The utility model provides a speed measuring device for elevator detection, which relates to the technical field of elevator detection and comprises a mounting plate, and the top of the mounting plate is provided with two insertion grooves. When the running speed of an elevator is detected through the speed measuring device, vibration can be generated during running of the elevator car and transmitted to the mounting plate, meanwhile, under the action of a limiting plate, the speed measuring device and the mounting plate can be driven to move up and down, and under the action of a compression spring and a second damper, the speed measuring device and the mounting plate are driven to move up and down. According to the elevator speed measuring device, vibration borne by the mounting plate and the speed measuring device can be partially absorbed or eliminated, and then the vibration borne by the mounting plate and the speed measuring device can be further absorbed or eliminated under the action of an arc-shaped plate, a sliding block, a buffer spring and a first damper, so that the accuracy of an elevator running speed detection result by the speed measuring device is improved; and an electronic component in the speed measuring device is protected, so that the electronic component is prevented from being damaged due to long-time vibration.

The invention discloses a control method for controlling the follow-up speed change of a drip irrigation disc of a seeder based on Beidou speed measurement. The control method comprises the following steps: S1, collecting and preprocessing position information and speed information of a tractor; s2, inputting the preprocessed data into a fusion calculation unit, and executing space-time weight calibration; s3, inputting the fusion speed sequence into a speed prediction network, extracting multi-scale features, and generating a speed guide feature map; s4, generating a target rotating speed instruction according to the mapping function and operation parameter modulation; s5, inputting a target rotating speed instruction to a motor control unit, and generating a current signal through dual-channel torque regulation and control; s6, a motor is driven to rotate the drip irrigation disc, the actual rotating speed is collected, and an error sequence is constructed; and S7, inputting the error sequence into a calibration module, generating a correction parameter to update a current signal, and realizing synchronous control. According to the invention, high-precision synchronous control of the drip irrigation disc on the speed of the tractor is realized, and the drip irrigation consistency, the response speed and the operation stability are improved.