3937results about "Simulators" patented technology

The invention provides an interactive simulation teaching processing method and device for ship electromechanical guarantee, and relates to the technical field of interactive simulation teaching, and the method comprises the steps: building a ship electromechanical full-structure model in a virtual simulation platform, digitally mapping real equipment operation parameters into virtual parts with real-time response characteristics, and carrying out the real-time simulation of the virtual parts; synchronous acquisition and normalized calibration of operation instructions, equipment feedback and environment disturbance in a teaching scene are realized, and a unified teaching simulation data set is generated. State recognition, fault simulation and operation evaluation calculation are completed through multi-layer task scheduling, and real-time teaching feedback is generated and visually displayed on a terminal. Based on difference analysis of dynamic evaluation data and a standard operation template, operation deviation and abnormity are automatically identified, and a targeted guide prompt is generated. According to the invention, unified modeling and data linkage can be carried out on student operation behaviors, equipment dynamic responses and teaching feedback results, and the problems of teaching feedback lagging and lack of pertinence in operation correction are solved.

The invention discloses a road roller construction quality real-time monitoring system based on digital twinning, and relates to the technical field of road roller construction intelligent monitoring, and the road roller construction quality real-time monitoring system comprises a data acquisition module which uses a multi-modal fusion sensor network and edge calculation to comprehensively acquire and preprocess data; the digital twinborn model building module is used for modeling by combining physical-data dual drive with geological characteristics; the data transmission module is used for ensuring efficient and safe transmission by using a software defined network and a block chain; the real-time monitoring and analysis module is used for carrying out multi-scale space-time correlation analysis and generating virtual data; and the decision support module fuses deep reinforcement learning and a knowledge graph, supports man-machine cooperation decision, and provides intelligent suggestions for construction. According to the invention, the advantages are obvious, multi-modal acquisition and edge calculation ensure accurate and real-time data, a dual-drive model truly simulates construction, an advanced transmission technology ensures data safety, multi-scale analysis comprehensively evaluates quality, full-process coverage improves construction quality and management intelligence, and cost reduction and efficiency improvement are realized.

The invention discloses a disaster emergency rescue nursing skill training system based on virtual reality, and relates to the technical field of virtual reality. A high-simulation virtual disaster scene is constructed based on real data, diversified injury condition virtual objects matched with the scene are generated, a secondary disaster risk diffusion effect and emergency prompt information are overlaid in real time, physiological state changes such as blood pressure and respiration generated by nursing operation differences in the rescue process of wounded personnel are dynamically simulated, and the rescue effect of the wounded personnel is improved. The problems of single scene and fixed injury condition in traditional training are solved, real-time and multi-modal feedback of student operation is realized through accurate comparison and hierarchical identification of multi-dimensional operation characteristics, the defects of guidance lagging and general are overcome, a personalized and adaptive training scheme is generated according to a comprehensive evaluation result, the progress is dynamically adjusted, and the training efficiency is improved. And scene simulation, operation practice, accurate feedback and personalized improvement are integrated.

The invention discloses a PICC virtuality and reality combined simulation training system and method, solves the problems that puncture simulation training is not real enough and students cannot perform intensive training aiming at a puncture technology due to the fact that an existing venipuncture simulation platform lacks necessary puncture force feedback, and belongs to the technical field of virtual training. The system is composed of a personal information management module, a simulation training terminal, a virtual model management module and a man-machine interaction module, and student operation information is collected in real time based on a multi-dimensional sensor; the virtual model management module reconstructs real anatomical structures such as blood vessels and skin of a human body through a high-precision 3D modeling technology, a physical engine is matched to provide a vivid puncture hand feeling, students can experience a scene very close to real operation, and the simulation training terminal can simulate the real operation through a force feedback technology in a virtual scene. The trainee can feel the touch similar to that of real puncture, so that the understanding of the trainee on the puncture process and the control of the trainee on the puncture strength and angle are improved.

The invention provides a training and examination robot system based on a multi-modal large model, equipment and a computer program product, and aims to accelerate training transformation and upgrading and improve coping ability as basic appeals, and based on regular training work of teams, training and examination robot, sensor acquisition equipment and big data platform three-terminal equipment. A multi-modal data acquisition layer for realizing real-time attitude detection and motion capture by using an edge calculation algorithm, a data processing and analysis layer for finishing real-time image processing through localized edge calculation in a network-free or power-free environment, and system control functions for finishing intelligent decision making, evaluation, error correction and the like are provided; an intelligent decision-making and control layer of a training subject rewriting decision-making mechanism is established, cross-modal collaborative learning middleware is utilized to realize modal representation consistency while training subject transposition evaluation is realized, training and assessment operations of the same subject of multiple persons or different subjects of multiple persons are supported, and the training and assessment efficiency is remarkably improved.

The invention provides an anesthesia virtual simulation training system fusing knowledge, skills and a thinking closed loop. The anesthesia virtual simulation training system comprises a medical knowledge base module, a clinical thinking module, a skill training module, an examination question brushing module, a knowledge graph module and an intelligent platform bottom layer framework. The intelligent platform underlying architecture comprises a data middle platform, an AI engine and a 3D engine, collects student behavior data of each module, constructs a dynamic student ability portrait through a gradient boosting tree algorithm and a collaborative filtering recommendation model, analyzes knowledge blind areas and skill shortages, plans a personalized learning path and pushes targeted training content, and provides a personalized learning result. A closed-loop process of evaluation, learning, practice and re-evaluation is formed; and deep fusion of theoretical knowledge, clinical thinking and skill operation is realized through a cross-module collaboration mechanism. The problems that traditional anesthesia teaching is high in practical operation risk, scattered in resource and insufficient in individuation are solved, and the clinical comprehensive ability and teaching quality of anesthetists are effectively improved.

Systems and techniques are described for implementing autonomous control of earth-moving construction and / or mining vehicles, including to automatically determine and control autonomous movement of part or all of one or more such vehicles (e.g., a vehicle's arm(s) and / or attachment(s), such as a digging bucket, claw, hammer, blade, etc.) to move materials or perform other actions in a manner that is based at least in part on data from simulated operation of the vehicle(s). For example, the systems / techniques may include using data from simulated operation of the earth-moving vehicle(s) in various manners, such as for use in training one or more machine learning models that are used in implementing the autonomous operations, determining optimal or otherwise preferred hardware component configurations to use, determining optimal or otherwise preferred implementation plans to use for one or more tasks and / or multi-task jobs, enabling user what-if experimentation activities, etc.

A computer-implemented method for simulating an aircraft system in a closed-loop functional simulation environment is disclosed. The computer-implemented method may include: receiving, at a computer system, one or more control inputs from an interface; processing, by a control system model, the one or more control inputs to generate one or more system command signals; applying the one or more system command signals to one or more virtual system models; simulating a physical response of the aircraft based on output generated by the one or more virtual system models in response to application of the one or more system command signals; generating, responsive to monitoring the output generated by the one or more virtual system models, sensor data; transmitting the sensor data to the control system model; and outputting simulation results, wherein the simulation results at least comprise an indication of the physical response of the aircraft.

The invention relates to the technical field of auxiliary training, and discloses an AR auxiliary training system for improving the diagnosis and treatment capability of general practitioners on undifferentiated diseases, and an immersive training environment is constructed by adopting an augmented reality technology. The system comprises an environment sensing module, a space positioning module, a case data module, a virtual rendering module, an interactive acquisition module, an intelligent response module, a state control module and an evaluation calculation module. The environment sensing module adopts an RGB-D camera and an inertial measurement unit to collect environment and head movement data of a user; the spatial positioning module determines a virtual patient placement position based on an SLAM algorithm; the virtual rendering module renders a three-dimensional virtual patient in a real environment; the interaction acquisition module supports voice and gesture multi-mode interaction; the intelligent response module generates an intelligent patient answer; the evaluation calculation module carries out comprehensive evaluation from three dimensions. The invention provides a highly immersive and intelligent training environment, and has the advantages of low cost, reusability and high standardization degree.

The invention provides a control method, which is applied to an artificial intelligence experiment system, at least comprises a robot hardware platform, a controller, a wheeled robot chassis and an industrial mechanical arm, and the method comprises the following steps: starting an operation system and executing hardware self-inspection; loading a large language model service and a traditional AI model, wherein the traditional AI model comprises a speech recognition model, a target detection model and a semantic analysis model; a natural language instruction of a user is received, voice is converted into a structured text through a voice recognition model, an instruction intention is analyzed through a large language model and a semantic analysis model, robot control parameters are generated, and a multi-modal interaction control signal is obtained; based on the multi-mode interaction control signal, a camera is called to collect image data, the position and category of a target object to be grabbed by the robot are recognized through a target detection model, the moving path of the robot and the grabbing track of the mechanical arm are calculated in combination with laser radar data, and the wheeled robot chassis and the industrial mechanical arm are controlled to execute coordinated actions.

The invention discloses a whole-process vascular interventional operation training method and system based on a virtual reality technology, and the method comprises the steps: firstly, developing a vascular interventional mechanics and collision simulation module, and achieving the deformation simulation of a blood vessel and a guide wire through the combination of position dynamics, a region shape matching technology and a Cosseerat elastic rod model, the collision between the blood vessel and the guide wire is treated by adopting a wide-to-narrow three-layer progressive collision detection method; secondly, constructing an immersive virtual operation scene through model construction and rendering optimization; visual angle roaming, instrument operation and interface interaction are fused, and multi-mode interaction control driving intervention training is achieved; finally, based on a'module-event 'dual-drive framework, operation tasks such as anesthesia, puncture, radiography, intervention, stent release and hemostasis are sequentially connected in series through a unified state machine, and whole-process training is achieved. The accuracy and stability of blood vessel and guide wire simulation are improved, the training immersion sense is enhanced, interventional operation whole-process training is achieved, and high teaching and practical value is achieved.

The invention relates to the technical field of medical simulation training, in particular to an ultrasonic operation intelligent training method and device based on multiple modalities, and the method comprises the steps: obtaining real-time six-degree-of-freedom pose data of an ultrasonic probe held by an operator, and generating an ultrasonic image in real time through a first deep learning model in cooperation with scene parameters; wherein the first deep learning model is trained to learn and establish a continuous mapping relation from an ultrasonic probe pose space to an ultrasonic image space; performing section classification on the ultrasound image by using a second deep learning model, and determining deviation information for a non-standard section; and based on the real-time six-degree-of-freedom pose data and a division result of a preset standard section and an ultrasonic probe pose, generating visual guide information for guiding an operator to adjust the probe pose, and displaying the visual guide information. In this way, the problems that an existing virtual training image is discontinuous and guiding is inaccurate are solved, and meanwhile the training efficiency and the reality sense of ultrasonic operation are remarkably improved.

The invention discloses an intelligent network connection automobile active safety teaching control method based on digital twinning. The method comprises the steps that S1, multi-source sensor data are collected and preprocessed to generate a driving state data set; s2, inputting the state data into a digital twin model to drive a traffic scene and outputting a synchronous state; s3, based on Dueling-DDQN, executing strategy learning to generate an active safety control instruction; s4, the instruction response effect is simulated and verified in the virtual environment; s5, collecting driver operation behaviors, inputting the improved MHA-BiLSTM model to extract time sequence features, and outputting behavior features; and S6, comparing the driving behavior with a standard instruction item by item, calculating an operation deviation and a response difference, and generating a personalized active safety teaching task. According to the invention, efficient comparison and teaching feedback of the driving behavior and the active control strategy can be realized, and the intelligent level of driving training is improved.

The invention relates to the technical field of occupational simulation training evaluation, and discloses a system for college student occupational scene simulation training evaluation. The system comprises a task analysis unit, a dynamic behavior modeling unit, a multi-mode interaction management unit, a state evolution tracking unit, a strategy adaptation unit and a comprehensive evaluation generation unit. The system receives the initial scene description and generates a structured task framework, and behavior parameters are configured for student roles; constructing a multi-modal interaction atlas by fusing aligned voice, action and sight line data in real time; identifying a key decision node, and dynamically tracking a team state evolution path; matching and adjusting strategies in a behavior rule base according to the evolution sequence, and outputting an adaptive intervention scheme; and finally generating a multi-dimensional structured evaluation report. According to the system, deep insight and dynamic and objective intelligent evaluation of complex interaction behaviors in the simulation training process are realized.

The invention provides a power equipment three-dimensional dynamic updating method and system for virtual reality training, and the method comprises the steps: collecting the working state data of power equipment in real time through a sensor; processing the working state data based on a preset function model, and calculating the physical state change of the power equipment; according to the physical state change, adjusting physical attributes of the three-dimensional model of the power equipment in real time so as to simulate physical effects of thermal expansion, stress concentration or structural deformation; loading the adjusted three-dimensional model into a virtual reality environment, and performing real-time display through a virtual reality rendering platform; and after the user executes the interactive operation through the virtual reality equipment, the working state of the power equipment is updated, and the influence of the operation on the three-dimensional model of the equipment is dynamically fed back, so that a virtual-real linkage closed-loop training process is formed. The virtual model can change in real time along with the collected data, and the technical verisimilitude and operability of virtual training are remarkably improved.

The invention belongs to the technical field of customer service, and particularly relates to an intelligent customer service practical training system and method, and the system comprises a business scene digital reconstruction layer which is used for constructing a business training scene to form a training scene library, managing the business training scene library, and reconstructing a training scene according to scene configuration data; the AI simulation interaction core layer is used for receiving and recognizing voice and text input of students and generating behavior strategies of AI partner training according to input content on the basis of a current training scene; the training execution layer is used for generating scene configuration data according to a student selection instruction and sending the scene configuration data to the business scene digital reconstruction layer, and the scene configuration data content comprises a training scene, training difficulty and role setting; the training difficulty is dynamically adjusted according to the real-time performance of the trainee; and the quantitative evaluation layer is used for performing multi-dimensional analysis on the training data and generating a quantitative evaluation result and an improvement suggestion. The problems that existing customer service training is low in efficiency and high in cost are solved.

The invention provides a multi-scene intelligent manufacturing teaching practical training method and system based on a digital twinning technology, a storage medium and electronic equipment. The method comprises the steps of data acquisition and processing, intelligent manufacturing digital twinning model construction, multi-scene integration, practical training process development, resource issuing and sharing, teaching management and the like. A digital twinborn model of equipment, process and environment is constructed and integrated into a three-dimensional virtual scene, and a graphical process design tool and a cloud platform are combined, so that standardized development, online deployment and intelligent evaluation of teaching resources are realized. The method improves the flexibility and efficiency of practical training, and is suitable for the construction and management of intelligent manufacturing multi-type teaching practical training scenes.

The invention relates to the technical field of gastrointestinal tracts, in particular to a gastrointestinal tract ultrasonic virtual simulation nursing teaching platform which comprises a function module and a hardware configuration module. The function module comprises an anatomy learning module, an ultrasonic simulation module, a case training module and an examination and evaluation module; the hardware configuration comprises a VR head-mounted display, an ultrasonic simulator and an operation panel. The system has the advantages of safe and risk-free training, standardized process learning, immersive scene experience and instant feedback evaluation, a high-fidelity gastrointestinal tract ultrasonic virtual simulation teaching platform for critically ill patients is constructed, a 3D virtual model is constructed by using a virtual simulation technology, knowledge is presented dynamically and visually, real situations such as ICU wards and the like are simulated through VR, and real-time feedback evaluation of the gastrointestinal tracts of the critically ill patients is realized. The learning initiative and the sense of participation are stimulated; an ICU environment is virtualized, an unlimited'trial-and-error 'practice space is provided, the equipment cost is reduced, potential safety hazards are avoided, and space-time and safety barriers are broken.

The invention provides a financial practical training method, system and product based on a dynamic situation. The method comprises the following steps: generating a user portrait based on user state information; generating financial practical training scene data based on the user portrait and the knowledge graph; triggering a corresponding situation event based on the operation behavior data of the user, and updating a user portrait in real time; optimizing a triggering path of the situation event based on the updated user portrait and the knowledge graph, and returning to the step of triggering the corresponding situation event based on the operation behavior data of the user until a preset practical training target of the user is achieved; and after a preset practical training target of the user is achieved, generating a personalized evaluation report based on the latest user portrait. According to the financial practical training method provided by the invention, targeted financial practical training scene data is realized through fusion of the knowledge graph and the user portrait, and a situation event triggered in the financial practical training scene data is adjusted in real time according to user operation, so that the pertinence and timeliness of a financial education tool in a use process can be effectively enhanced.

In various examples, a simulation platform generates a simulated driving environment by processing road map data to derive the location of wear-related visual artifacts for sections of a lane surface. Using map data, the simulation platform generates texture maps for aesthetic road rendering, which are used to apply textures to a 3D polygon topology mesh. The simulation platform generates visual artifacts representing the wear and tear of the road surface based on a calculation of one or more lane feature distances derived from the map data. The simulation platform calculates distances associated with reference line data derived from an image to render a texture of one or more lane features.The spacing is used to determine how the appearance of the texel is adjusted to include wear-related visual artifacts when displayed on a lane of the simulated driving environment.

The invention discloses a temperature-controllable laser heating device and method, and relates to the technical field of laser heating, and the device comprises a laser generator which is used for generating a laser beam for heating; the triangular prism assembly is arranged on the same side of the laser generator and the detection control module and is used for refracting the laser beams to irradiate the power equipment for heating and refracting infrared radiation generated by the power equipment to irradiate the detection control module; the detection control module is used for detecting the infrared radiation so as to obtain the actual temperature of the heating point of the power equipment, and adjusting the output power of the laser generator based on the actual temperature and the preset temperature so as to control the deviation between the preset temperature and the actual temperature; the laser beam is refracted to irradiate the power equipment for heating, the actual temperature of the heating point is obtained, the output power of the laser generator is adjusted based on the actual temperature and the preset temperature, the device can be used without modification, and the problems of randomness of training content and concealment of examination content are solved.

A motion cueing system for a flight simulator includes a motion system controller configured to generate actuation commands for a movable simulator platform. The actuation commands are based on at least one of: an absolute attitude of a simulated aircraft; or a weighted function of a groundspeed of the simulated aircraft.

The invention relates to the technical field of virtual reality experiment teaching, and discloses an experiment teaching simulation method and system based on virtual reality. The method comprises the steps that a continuous behavior sequence generated by user operation is collected, and a teaching behavior chain is generated through discretization; constructing a state vector by identifying the space-time state of the behavior unit, and comparing the state vector with a standard template to mark an abnormal behavior unit; tracing the context to generate an abnormal behavior description block, and querying an error knowledge base to obtain error information; meanwhile, analyzing a state change event of the virtual experiment equipment; and finally, fusing the error information and the state event to generate a simulation teaching evaluation result. According to the method, refined multi-dimensional analysis of experimental operation behaviors and intelligent error influence quantitative evaluation are realized, and the accuracy and guidance of teaching feedback are improved.

The invention discloses a practical training evaluation method and system based on multi-modal data fusion. The method comprises the following steps: firstly, constructing a practical training task topology based on a knowledge graph, mapping elements such as knowledge points into nodes, and defining a relationship through directed edges; in response to task starting, dynamically deploying a multi-modal data fusion agent pre-loaded with a targeted model and a rule; in the operation process, the agent synchronously collects and processes original data from the machine vision and sensor network in real time, and a standardized feature flow is generated; then, on-line space-time correlation and reasoning are carried out on the multi-modal features based on a fusion strategy, and a task scene understanding model is dynamically constructed and maintained; after the task is completed, packaging a program code, a report and process abstract data exported by the model to form an enhanced practical training result package; and finally, multi-dimensional automatic comparison is carried out by calling the rule base and the case model, and an evaluation result is generated. According to the invention, intelligent perception and comprehensive evaluation of the whole practical training operation process are realized.

The invention discloses an intelligent experimental training system with a body based on a multi-modal large model, and the system comprises the following modules: a multi-modal sensing module collects visual, voice, motion and force sense data, and generates a state vector through synchronization and fusion; the semantic evaluation module is used for performing semantic matching and identifying knowledge blanks by using a multi-modal large model; the causal generation module generates a causal query after blank detection and forms a hypothetical experiment proposition; the tool body execution module executes an intervention action and collects multi-mode feedback; the effect verification module calculates causal effects before and after intervention and judges significance; the graph updating module generates new knowledge nodes and updates the causal relationship graph when verification is established; and the teaching management module performs causal chain visualization and result feedback according to the updated atlas. According to the method, a self intervention feedback mechanism is introduced into a multi-modal perception, semantic understanding and decision execution closed loop, so that the knowledge evolution and teaching intelligence level is remarkably improved.

The invention discloses a multifunctional hydraulic system experiment table, which relates to the technical field of hydraulic system experiment tables and comprises a time base line synchronous control module, a phase lock correction stability control module, a false peak identification and correction module, a multi-dimensional fault-tolerant judgment control module and a reverse energy slow-release anti-reverse module. And the time base line synchronous control module is used for establishing a cross-sensor unified time base line control structure, generating a synchronous reference surface by using a high-stability crystal oscillator signal, and executing nanosecond phase calibration on sampling signals of the pressure sensor and the flow sensor by taking the synchronous reference surface as a unified time reference. According to the invention, high-precision synchronous acquisition of pressure and flow signals is realized through unified time base line and phase locking correction, and high-pressure transient test data is ensured to be real and stable; and meanwhile, control logic is reconstructed, and an energy slow release strategy is introduced, so that the pressure relief process is stable and controllable, pump reverse rotation and structural impact are avoided, and the safety, reliability and self-healing stability of the experiment table are remarkably improved.

The invention aims to provide a washout algorithm based on a data-driven parameter prediction model, and belongs to the technical field of driving simulation, a vehicle longitudinal acceleration signal and a motion platform state parameter are acquired and input into a pre-trained multi-layer perceptron neural network model, a washout filter parameter combination adaptive to a current working condition is calculated and output, and the washout filter parameter combination is determined. And then real-time and dynamic adjustment of parameters of the high-pass acceleration filter and parameters of the low-pass inclination coordination filter along with the state of the vehicle and the motion platform is realized, so that online real-time optimization of a control instruction of the motion platform is completed, and finally optimization of driving motion feeling simulation fidelity is realized. A data-driven parameter prediction model breaks through the limitation that a traditional washout algorithm is fixed in parameter and poor in adaptability; offline optimization and online prediction are combined, and real-time performance and fidelity are balanced; the active centering controller compensates the longitudinal acceleration by using the pitch angle, improves the space utilization rate, introduces a comprehensive somatosensory error evaluation index, and accurately evaluates the somatosensory simulation effect.

The invention discloses a medical operation AR practical training system based on mixed reality and reinforcement learning and a training method thereof, and relates to the technical field of medical education and medical operation training. The system comprises an MR terminal presentation and interaction module, a case and scene management module, a multi-mode operation data acquisition and evaluation module, a reinforcement learning training strategy engine module, a practical training process control module, a training examination management module and the like, a vivid medical scene is constructed in an MR environment, and data such as operation tracks, force and step time sequences of students are acquired in real time; the evaluation result is coded into a state to be input into the reinforcement learning model, the case difficulty, the prompting mode and the training rhythm are adjusted in a self-adaptive mode, individualized, procedural and quantifiable skill training and assessment are achieved, and the method is suitable for various operations such as cardio-pulmonary resuscitation, endoscopic surgery and puncture catheterization.

The invention relates to the technical field of hemodialysis teaching systems, and discloses a hemodialysis teaching system based on AI intelligent pushing. The system comprises an operation feature extraction module, an instrument positioning analysis module, an operation step analysis module and a teaching strategy generation module. Operating a feature extraction module to obtain a hemodialysis teaching video stream, and extracting multi-modal features containing an instrument movement track sequence and physiological parameter simulation data; an instrument positioning analysis module calls a pre-training network for positioning and generates a coordinate data set containing instrument types and three-dimensional position coding mapping; the operation step analysis module analyzes the time sequence characteristics by means of an action segmentation model, and generates a result containing step integrity and an error operation mark; and the teaching strategy generation module inputs a result into the intelligent push model, plans a personalized teaching path, outputs a knowledge point sequence containing a student ability model and dynamic teaching elements of operation difficulty parameters, and assists the hemodialysis teaching to be precise and personalized.

The invention discloses a neurosurgical operation virtual simulation training system based on multi-modal data fusion, and relates to the technical field of operation simulation. The data acquisition and preprocessing module acquires data such as images and force feedback, and standardized storage is performed after filtering and registration; the multi-modal data fusion module performs weighted fusion on the data by using an attention algorithm to generate a three-dimensional model; the virtual operation scene construction module generates a high-fidelity environment through ray tracing and a physical engine; the surgical operation interaction simulation module realizes accurate interaction through positioning tracking and force feedback; the training evaluation and feedback module quantifies operation performance and provides guidance; and the system management and iteration module guarantees operation and supports data updating and optimization. According to the method, a high-reality scene is constructed through multi-modal fusion, interaction and multi-dimensional evaluation help skill improvement, dynamic difficulty and personalized paths are adaptive to different users, collaborative training and privacy data collaboration are supported, operation training standardization is promoted, and the risk of errors in an operation is reduced.