88results about How to "Improve dynamic adaptability" patented technology

The invention relates to the technical field of semiconductor test equipment, in particular to a full-automatic high-precision probe station, which utilizes multi-physics field coupling sensing and compensation to remarkably improve the positioning precision: by comprehensively collecting multi-physics field data such as a temperature field and a stress field and combining a coupling algorithm to optimize a compensation strategy, multi-factor interference is effectively counteracted, and the accuracy of the probe station is improved. The positioning repetition precision can reach + / -0.05 [mu] m, and the test requirement of the advanced semiconductor technology is met; a dynamic three-dimensional modeling technology and dynamic adaptability enhancement are achieved, a dynamic three-dimensional modeling system with the size affected by multi-physical field data can update the form of a test target in real time, test deviation caused by target deviation or surface fluctuation is avoided, and the adaptability of equipment to a complex test scene is improved. The automation degree is high, the testing efficiency is improved, the whole process of data acquisition, modeling, compensation and testing can be completed without manual intervention, the calibration process is simplified, the testing period is shortened, and the method is suitable for batch detection scenes.

The invention discloses a multi-delivery robot path collaborative optimization system and a scheduling method, and aims to solve the problems of non-uniform scheduling load, unsmooth path, weak conflict avoidance capability and poor dynamic adaptability of existing multi-robot scheduling. The system comprises a central scheduling module, a distribution robot terminal, an environment sensing module and a map management module, and realizes task analysis, state monitoring, path planning and conflict coordination. According to the method, region division and task balanced distribution are completed by improving a DARP algorithm, path coverage efficiency and smoothness are optimized by fusing a BA * algorithm, a cattle farming method and a TEB algorithm, multi-type path conflicts are solved by adopting a time window reservation and distributed negotiation strategy, and dynamic adjustment under new task access, robot faults and environment sudden change is supported. According to the method, the load balance, the path optimization effect and the conflict avoidance capability of multi-robot collaborative distribution can be remarkably improved, the efficient and stable execution of the distribution task is ensured, and the method is suitable for terminal distribution scenes such as communities and office buildings.

The invention discloses a blue army task planning method based on knowledge and data driving, and relates to the technical field of military simulation modeling and computer simulation, and the blue army task planning method comprises a sensing layer, a fusion layer, a reasoning layer, a planning layer, an optimization layer and an output layer. Bidirectional interaction between the layers is achieved through data interfaces, and deep fusion of knowledge and data in the whole process is ensured; by constructing a dynamically updated knowledge graph and a knowledge-data mapping mechanism, domain knowledge can guide data modeling in the whole process, meanwhile, the data can optimize a knowledge system in real time, the limitation of a single driving mode is solved, and through testing, in a complex military drill scene, the knowledge and data can be fully fused. The matching degree of the fusion-driven planning scheme and the actual situation reaches 92%, is improved by 25% compared with a knowledge-driven scheme, and is improved by 30% compared with a data-driven scheme.

The application discloses an adaptive tuning device and method of an anti-interference satellite communication antenna, and relates to the technical field of satellite communication, wherein the device comprises a multi-mode reconfigurable surface antenna module, an environment sensing module, a prediction module, a cooperative tuning module and a closed-loop feedback correction module; the application constructs a multi-mode radiation system through the multi-mode reconfigurable surface antenna module and the environment sensing module, obtains an electromagnetic environment and a link state, the prediction module predicts interference and signal deviation based on multi-source data, the cooperative tuning module synchronously executes radiation mode switching and array amplitude and phase pre-tuning according to a prediction result, preset nulls are formed before interference arrives, and the closed-loop feedback correction module collects signal quality in real time and corrects a prediction model and a tuning strategy, so that a prediction type, closed-loop self-optimizing active anti-interference tuning mechanism is formed, interference is not arrived, and tuning is performed in advance, and the anti-interference capability and communication stability under a dynamic complex electromagnetic environment are significantly improved.

This utility model relates to the field of high-voltage electrical system technology, and particularly to a DC copper busbar with single-phase conduction function, comprising: an input copper busbar, an output copper busbar, a power diode, and an insulating material; the input and output copper busbars are arranged in parallel, and the two copper busbars have an overlapping area in a direction perpendicular to the plane of the copper busbars, with a predetermined gap between the input and output copper busbars in the overlapping area; the power diode is disposed within the gap in the overlapping area of ​​the input and output copper busbars, and its two ends are electrically connected to the input and output copper busbars respectively; the insulating material fills the remaining gaps outside the power diode in the overlapping area of ​​the input and output copper busbars. This utility model solves the problems of high cost, reliance on manual operation, and complex structure of existing anti-reverse protection measures.

The invention discloses a multi-person picture synthesis method and device, equipment and a medium. The method comprises the following steps: splicing original images at multiple angles to obtain a panoramic image of a current target area; real-time tracking is carried out according to all face position information in the current frame, sound source information is collected synchronously, and a current spokesman in the target area is determined; and generating a multi-person synthetic picture according to the real-time motion picture of the current spokesman and the real-time motion pictures of other people. Multi-angle images are collected for feature point matching and image splicing, a high-quality panoramic image is generated, wide-area visual angle coverage is achieved, a more detailed image is obtained, all face positions are locked, corresponding sound source information is collected, a current spokesman is recognized, a multi-person synthetic picture which highlights the current spokesman and gives consideration to other people is generated, and the multi-person synthetic picture is obtained. The integrity of the panoramic information is guaranteed, meanwhile, the key content is clearly presented, the problems that the visual angle is limited and information is overloaded are solved, and the communication efficiency and watching experience of a teleconference are improved.

The present application relates to the technical field of intelligent control, and discloses a power plant low bypass steam direct heating network circulating water dynamic shunting system, comprising: a data acquisition module, which is used for collecting power plant operation parameters and heating network demand parameters in real time; a model solving module, which is used for inputting the collected parameters into a preset multi-objective optimization model, and obtaining an optimal steam shunting ratio through online calculation of the model; an instruction generation module, which is used for converting the optimal steam shunting ratio into real-time control instructions for a shunting regulating valve group; an execution adjusting module, which is used for adjusting the shunting regulating valve group according to the control instructions, dynamically changing the flow of low bypass steam injected into the heating network circulating water, and discharging the remaining steam according to the original bypass system; and a safety monitoring module, which is used for independently monitoring key safety parameters, and when a safety threshold is exceeded, interrupting the main control process and executing a preset highest priority safety interlocking action. Under the premise of guaranteeing the heating quality of the heating network, the economic benefits of low-grade waste heat recovery are maximized.

The application provides a grid synchronization control method, device, equipment and medium of a photovoltaic inverter, comprising: collecting three-phase voltage signals at a grid point of common connection in real time, and preprocessing the three-phase voltage signals to obtain q-axis voltage residuals; serializing sampling the q-axis voltage residuals to construct a short-time phase deviation time sequence; inputting the short-time phase deviation time sequence into a pre-trained recurrent neural network model to obtain a predicted phase angle increment; based on the predicted phase angle increment, combining a photovoltaic grid-connected working condition, and calculating a synchronization phase angle; and based on the synchronization phase angle, controlling the grid synchronization phase of the photovoltaic inverter. The phase deviation is predicted through the recurrent neural network, the phase error problem caused by the lag of the traditional PI control is overcome, and the accuracy and stability of the grid synchronization of the photovoltaic inverter are effectively improved.

The invention belongs to the technical field of artificial intelligence, and relates to an underwriting data verification method, which comprises the following steps: training a pre-constructed network model based on an annotation data set and an underwriting rule text, performing rule extraction on the underwriting rule text through the large language model, and obtaining an underwriting data verification result, the method comprises the steps of obtaining a prediction verification rule, constructing a verification instruction based on the prediction verification rule, inputting the verification instruction and an annotation data set into a lightweight model, outputting a prediction verification result, adjusting model parameters based on the prediction verification rule and a prediction loss value calculated by the prediction verification result, and obtaining a finally trained insurance policy verification model. And performing insurance policy verification by using the insurance policy verification model. The invention further provides an underwriting data verification device, computer equipment and a storage medium. The method can be applied to business management program systems such as financial science and technology, and the accuracy and efficiency of overall underwriting verification are improved.

This invention relates to the field of energy system optimization and intelligent scheduling technology, and particularly to a multi-domain economic scheduling method and system based on game theory and generative networks. The invention includes: constructing a master-slave game framework; using a conditional generative adversarial network to generate a sequence of predicted scenarios for future time periods and selecting typical scenarios; the slaves calculating their local optimal trading volume based on time-of-use pricing and typical scenarios; calculating a global consistency variable based on the local optimal trading volumes of all slaves, and dynamically adjusting the penalty factor of the alternating direction multiplier method according to scenario deviations; updating the dual variable based on the global consistency variable until the convergence condition is met, obtaining the converged trading result; evaluating the overall system benefit based on the converged trading result; if the preset target is not achieved, adjusting the master's strategy and re-triggering the game process until the preset target is achieved, outputting the final scheduling plan. This invention significantly improves the game model's ability to handle uncertainty and achieves high accuracy.

The invention relates to an adsorption method of an adsorption type unhooking robot, the adsorption type unhooking robot is used for carrying out unhooking operation on a car coupler on a train, the adsorption type unhooking robot comprises a fixing device and an unhooking mechanical arm, and the fixing device comprises a 3-PRS assembly, an adsorption base assembly, a clamping arm assembly, a worm reducer assembly, a controller and a motor lead screw assembly; the 3-PRS assembly is connected to the adsorption base assembly, and the adsorption base assembly is further connected with the worm reducer assembly and the motor lead screw assembly. The clamping arm assembly is connected with the worm reducer assembly, and the motor lead screw assembly is connected with the worm reducer assembly. The adsorption method comprises an adsorption stage and a fixing stage, and in the adsorption stage, the 3-PRS assembly is adsorbed and attached to an adsorbed object on a train under the action of the controller; in the fixing stage, the controller controls the motor lead screw assembly and the worm reducer assembly to act so that the clamping arm assembly can clamp an adsorbed object, the coupler on the train can be removed at the same time, automatic operation can be achieved, and the working efficiency is improved.

The application discloses an eye diagram data synchronization circuit and method and a serial-parallel converter receiving end, and belongs to the technical field of high-speed serial data communication; the circuit comprises: a calibration signal generation module for generating a phase calibration signal according to a phase difference between a data sampling signal and an offset sampling signal; two registers for respectively outputting the offset sampling signal and pre / post offset sampling signals; wherein the pre / post offset sampling signals are obtained by outputting the offset sampling signal in advance / delaying half a bit period; and a selection output module for selecting the offset sampling signal or the pre / post offset sampling signals as a synchronized offset sampling signal output according to the phase calibration signal, so that the synchronized offset sampling signal and the data sampling signal are in the same bit period. The application has wide application range, high synchronization precision and good dynamic performance.

The invention relates to a model quantitative deployment precision evaluation system and method, which adopts a WebSocket + JSON-RPC long connection protocol to be combined with Base64 standardized coding to realize efficient transmission of model files and image data, and defines a unified reasoning result serialization format to improve multi-model compatibility. And a flexible model context pool and an RPC method registry are designed, so that the multi-model dynamic adaptation capability is enhanced. A reasoning-post-processing collaborative architecture is constructed, division and collaboration of a lower computer and a client are realized, a post-processing acceleration interface is reserved in the lower computer, DSP resource occupation is reduced, and the overall efficiency of precision evaluation is improved. A refined resource management mechanism is perfected, independent context resources are established for each model, all associated resources are automatically released when the models are deleted, and resource leakage is avoided; memory is dynamically allocated according to the model size and reasoning requirements, and the hardware resource utilization rate is increased.

The invention discloses a real-time network security protection system based on big data analysis. The real-time network security protection system comprises the following steps: collecting real-time network data and constructing a dynamic network diagram data set; constructing a graph state space model based on the dynamic network graph and completing state space initialization; a parallel selective state scheduling mechanism is introduced into the state updating path, parallel analysis is carried out on network node states, and state importance parameters are generated; reconstructing a state updating process according to the state importance parameters, and only executing state updating on the network nodes meeting conditions; performing security judgment on the corresponding communication behavior based on the updated state space representation, and generating a security risk identifier; and generating and issuing a network security protection control instruction according to the security risk identifier, and updating a state scheduling parameter based on execution feedback. According to the invention, through parallel selective state scheduling and state updating reconstruction, the real-time performance and scheduling efficiency of security protection in a large-scale network environment are improved.

The invention discloses a dynamic detection method and system for a construction project site environment, relates to the field of engineering environment detection, and solves the problems that in the dynamic detection of the construction project site environment, a monitoring area is difficult to adaptively evolve along with the evolution of the construction site environment, and the detection efficiency is low. The technical problem of data distortion caused by high randomness of dust diffusion, non-uniform spatial distribution and monitoring limitation of a single sensor in a construction project site is difficult to solve; the method comprises the following steps: planning a conjoint analysis area on a construction project site, and determining a dynamic sampling frequency based on the number of people in the conjoint analysis area, the types of construction machines and the number of each type; collecting the dust concentration of each joint analysis area based on dynamic sampling; performing cross analysis on the dust concentration to obtain a calibration regulation factor, and regulating the dust concentration based on the calibration regulation factor; according to the invention, the flexibility and accuracy of engineering field environment dynamic detection can be improved.

The present application relates to the technical field of intelligent control of industrial robots, and particularly relates to a vision transfer mechanical arm dual-arm cooperative assembly control method and system. The method comprises the following steps: collecting the action posture of the mechanical arm dual arms and the relative pose information between the dual arms in real time; identifying the process switching node of the current assembly process stage; constructing the master-slave role dynamic control logic of the dual-arm cooperation, setting the initial motion control parameters of the dual-arm cooperation based on the collected dual-arm posture and relative pose information, and determining the initial master-slave role division of the dual arms. The present application realizes seamless connection of processes, adaptation to various tasks and high-precision stable assembly through posture node identification technology, dynamic adjustment cooperation technology and vision transfer technology, so as to improve the assembly process efficiency, the mechanical arm adaptation ability and the overall assembly quality.

This invention relates to the field of digital twin technology, and more particularly to a predictive maintenance platform for the entire lifecycle of a heat dissipation system based on digital twins. The platform includes: a data acquisition module; a model building module; a block partitioning module for determining whether to perform direct partitioning based on regional coupling strength or related partitioning based on heat exchange correlation, according to the fault propagation coefficient; a category analysis module for determining block categories based on temperature deviation and determining whether to adjust the block categories of the second-class blocks based on the contaminant deposition impact and fluid pressure anomaly of the second-class blocks, according to the maximum fluctuation cycle decay rate; an update analysis module for determining the update frequency of each updated block based on a comprehensive evaluation value; and an update optimization module for determining whether to perform optimization adjustments based on the block change coefficient. This invention can improve model update efficiency.

This invention proposes a simulation optimization method and system for gas-liquid two-phase flow fields in fixed dredging module pipelines, belonging to the field of simulation optimization technology for gas-liquid two-phase flow fields in dredging. Addressing the problems in existing technologies where the determination of aeration parameters largely relies on empirical values, leading to unstable dredging effects, high energy consumption, and a lack of dynamic control over aeration parameters under different flow conditions, this invention conducts multi-condition numerical simulations using a gas-liquid two-phase flow model. With the objectives of maximizing the disturbance range and minimizing unit energy consumption, multi-dimensional disturbance indices are extracted and combined with unit energy consumption indices to construct a multi-objective optimization evaluation function. A comprehensive performance score is calculated using a combination of Pareto front screening and congestion distance scoring. Closed-loop iterative correction is performed through physical model verification experiments, achieving dynamic adjustment of aeration parameters based on real-time flow velocity monitoring. This invention significantly improves the energy efficiency ratio, accuracy, and reliability of aeration parameters in dredging operations, while reducing reliance on manual operation and maintenance.

The application provides a UAV dynamic reasoning offloading method, device, equipment and medium, wherein the method comprises: inputting image data collected by a UAV into a neural network model to determine original intermediate features output at a candidate split layer; determining a target network layer capable of outputting the original intermediate features in each network level, screening candidate split nodes capable of meeting the adaptation of on-board end independent reasoning and cloud end continuous reasoning in the target network layer, and arranging the candidate split nodes in network level order to construct a candidate split point set; constructing a multi-dimensional task constraint parameter system according to flight state data, original intermediate features and a task instruction issued by a ground control end; taking the candidate split point set as a traversal range, fusing the constraint parameter system, screening an optimal split layer adapting to a current working condition through comprehensive cost evaluation; and performing adaptive switching of a reasoning mode based on a link quality index and the optimal split layer.

The application relates to the technical field of multi-source flexible grid connection, and discloses a storage multi-module cooperative energy conversion efficiency increasing system and method, the method comprising the following steps: high-frequency sampling of load change data at a load end, and collecting operation state data of each energy conversion unit; time scale analysis of energy change characteristics at the load end, and calculation of dynamic characteristic strength representing rapid energy change; judging whether there is significant energy fluctuation at the load end; if yes, constructing a dynamic response strategy for the load end, comprising the following steps: calculation of dynamic response adaptation indexes of each energy conversion unit; screening of response adjustment units, and calculation of adjustment task weights of each response adjustment unit; based on the corresponding adjustment task weights, controlling each response adjustment unit to perform dynamic response adjustment on the load end. The application can improve the overall conversion efficiency and operation stability of a solid-state transformer in the scene of flexible grid connection and multi-load direct connection.

This application provides a light and shadow control method, system, electronic device, and computer-readable storage medium, relating to the field of light and shadow control technology. The light and shadow control method includes: acquiring ambient light data, ultraviolet (UV) data, and user interaction commands; determining the current target scene mode based on the user interaction commands and / or the ambient light data; calculating the basic transmittance of an electrochromic film and the basic light and shadow parameters of a light-emitting device based on the target scene mode; determining whether the UV data exceeds a preset protection trigger threshold; if the UV data exceeds the preset protection trigger threshold, performing a gradient adjustment on the basic transmittance based on the UV data and adjusting the output spectrum of the light-emitting device to generate protection control parameters; wherein the protection control parameters are used to control the electrochromic film and the light-emitting device to perform actions.

This application discloses a port route planning method, system, device, and storage medium based on virtual lanes. First, based on a pre-built lane grid index, the starting and ending lanes of the target vehicle are quickly located. Second, based on the obstacle and structural information of the current lane, a set of key lane-changing points formed by obstacles and / or process constraints is extracted. Then, the actual lanes and the virtual lanes generated based on the key lane-changing points are used together as graph nodes, and a weighted topology graph is constructed with travel cost as the edge weight. Next, the optimal path from the starting lane to the ending lane, passing through all key virtual lane nodes in sequence, is obtained based on the shortest path algorithm. Finally, the optimal path is converted into an executable path point sequence containing the key lane-changing points. This method can efficiently adapt to the dynamic operating environment and process constraints of ports, improving the flexibility and efficiency of route planning.

The invention discloses an intelligent low-temperature-resistant collision buffering device suitable for an LNG (liquefied natural gas) floating transmission system, and relates to the technical field of safety protection of the LNG floating transmission system.The intelligent low-temperature-resistant collision buffering device comprises a composite buffering device, a shell and a bottom plate; an outer rigid supporting layer, a middle energy absorption layer and an inner flexible contact layer are sequentially arranged from outside to inside, the outer rigid supporting layer, the middle energy absorption layer and the inner flexible contact layer are fixedly connected into a whole in a gluing or integral forming mode, and the outer side of the composite buffering device and the outer side of the internal mechanism are wrapped with the shell. The protective shell is fixedly connected with the bottom plate to form a protective shell; through deep integration of material innovation, structure optimization and intelligent control, the technical problems of low-temperature failure, low energy absorption efficiency, poor posture adaptation, no intelligent regulation and control and the like of a traditional buffer device in an LNG floating transmission scene are comprehensively solved, and the reliability, the adaptability and the intelligent level of collision protection are remarkably improved.

The invention discloses a personalized accompanying method, system and equipment based on digital human twinning and a medium, and relates to the technical field of smart tourism and artificial intelligence. According to the method, a tourist portrait is constructed based on tourist preference and historical behavior data by creating a tourist exclusive digital human twinning agent, and a visual touring draft is generated through a multi-dimensional evaluation model and path optimization in combination with the tourist portrait, scenic spot static data and future prediction data before a tour; in the touring process, according to the real-time multi-mode environment of the scenic area and tourist state data, dynamic re-planning is carried out, a guide instruction is generated, and continuous and intelligent tour accompanying experience is provided. According to the invention, the technical problems that the traditional navigation service is passively split and the planning is lack of individuation and dynamic adaptability are solved.

The application discloses an AI cooperative hierarchical multi-agent industrial internet production scheduling method and system, relates to the technical field of industrial internet production scheduling, and comprises the following steps: uploading a scheduling task to a meta-controller for pre-evaluation, determining a task hierarchical agent architecture; receiving scheduling task execution low-dimensional embedding coding and scheduling trajectory decision, obtaining a prior task strategy; importing the prior task strategy into a scheduling optimizer, performing hierarchical cascade scheduling configuration based on the task hierarchical agent architecture, and fusing to obtain a task scheduling strategy; and performing automatic production scheduling management on the scheduling task according to the task scheduling strategy. The application solves the technical problems of existing industrial production scheduling, such as fixed hierarchical architecture, single optimization mode, poor hierarchical collaboration and insufficient dynamic adaptation capability, achieves hierarchical multi-agent adaptive scheduling and double-branch parallel optimization, and improves the technical effects of the collaboration and dynamic adaptation of industrial production scheduling.

This invention discloses a multi-sensor fusion-based method, control method, system, equipment, storage medium, and excavator for excavator stress and strain monitoring, relating to the field of engineering machinery control technology. The monitoring method includes: S1 sensor array data acquisition; S2 noise reduction processing; S3 fusion modeling and state assessment; and S4 load path analysis. The control method specifically includes: A1 graded threshold setting, A2 control strategy implementation, and A3 control strategy library matching. The system includes: a sensor array assembly, a data processing module, and a control module. This invention overcomes existing limitations through multi-dimensional sensing technology. By integrating multi-source data such as structural stress, hydraulic load, and operating posture, and employing a noise reduction fusion algorithm to eliminate environmental interference, it overcomes the limitations and data distortion problems of single-sensor monitoring, achieving real-time monitoring of the stress state of key excavator components and significantly improving the reliability of monitoring results under complex working conditions.

The present application belongs to the technical field of power transmission line engineering cableway design and construction, and particularly relates to a power transmission line cableway stockyard point mode recognition method and system based on slope compensation and road width dynamic correction, a storage medium and a computing device. The method comprises the following steps: S1, road feature extraction: including extracting road center line feature data, road final width feature data, and road unit direction feature data; S2, road feature enhancement processing; S3, calculating road curvature; S4, mode recognition classification: using a feature space dynamic weighting segmentation algorithm, through an iterative optimization process in a dynamic weighting road feature space, dynamically adjusting road feature weights, scaling the original road feature space, so that the left and right boundary points in the transformed space can be effectively separated by a hyperplane, realizing accurate two-classification of the stockyard points; S5, space topology consistency enhancement. The method can solve the problem of road width measurement distortion caused by steep slope terrain.

The invention discloses a large language model adaptive quantitative transaction system based on parallel game and strategy evolution. The large language model adaptive quantitative transaction system comprises an acquisition module, an evaluation module and an execution module. The acquisition module preprocesses the multi-source heterogeneous financial data to generate a structured market state; the evaluation module generates candidate transaction strategies in parallel based on a large language model, and selects a target execution strategy through comprehensive score function evaluation in combination with a disturbance mechanism; the execution module is converted into a transaction instruction for execution after being verified by a preset risk control rule, target strategy parameters are updated by adopting a strategy gradient algorithm based on a transaction result reward signal, and meanwhile candidate strategies are evolved through an evolutionary algorithm and the evaluation step is cycled. According to the system, the strategy generation efficiency and diversity are improved, and the dynamic adaptability of transaction decisions is enhanced.

The utility model relates to clothing rack technical field, and disclose a clothing rack for art design, including base and top frame, and the base is installed with a electric telescopic column between top frame, and the base is rotatably installed with the drive of the main drive swing frame through the transfer position motor, and the main drive swing frame is rotatably installed with the drive of the transmission bevel gear through servo motor, and the top frame is rotatably installed with driven swing frame, and a group of hanger module is installed between the main drive swing frame and driven swing frame, and the hanger module includes elastic ring carrier tape. The utility model passes through the multidimensional cooperation of mechanical drive, intelligent control and material innovation, and the core problem such as traditional clothing rack display angle limited, form rigid, dust difficult to clean and operation inefficiency is systematically solved. Its technical scheme has remarkable creativity in three-dimensional display, dynamic form adjustment, automatic dust removal and remote control etc.

The invention provides a lumbar puncture training simulator mixing a magnetorheological damper and a voice coil motor. The lumbar puncture training simulator is composed of the magnetorheological damper, the voice coil motor, a linear guide rail, a sliding block, a limiting block, a laser displacement sensor, a puncture holder, a cover plate and a laser displacement sensor support. The magnetorheological damper comprises a cylinder barrel, an end cover, a check ring, an MRD coil, a piston and a piston rod. And a liquid injection hole is formed in the damper cylinder barrel. The magneto-rheological damper and the voice coil motor are arranged in parallel, and under data feedback of the force sensor and the displacement sensor, a piston rod of the magneto-rheological damper and a rotor of the voice coil motor can output corresponding puncture force to the lumbar puncture needle and an operator. In the system, the MRD is responsible for generating passive force feedback, and the VCM generates active force feedback. The combined work of the two actuators forms a magnetoelectric hybrid driving system capable of providing accurate puncture force feedback. The lumbar puncture training device effectively simulates the change of puncture resistance in the lumbar puncture process and can be used as a lumbar puncture training device.