265 results about "Skills training" patented technology

The invention discloses a low-voltage transformer area examination meter practical training device and a fault simulation control method, and relates to the technical field of electric power practical training. The device aims at the problems of single scene, extensive evaluation and low skill improvement efficiency in traditional electric power practical training. The meter simulation module is compatible with various meters and is matched with a dual-communication protocol to realize efficient data transmission; the intelligent interaction module provides high-quality interaction experience through a high-definition touch screen and low-delay transmission; the data generation module can quickly switch customized scenes, and the fault simulation module can accurately inject various faults; the training management module depends on advanced technologies of knowledge maps, deep learning and fuzzy comprehensive evaluation to realize full-process closed-loop management from project design and operation guidance to evaluation feedback and intelligent optimization; all the modules cooperate efficiently, and the professionality, the accuracy and the efficiency of power failure troubleshooting and operation and maintenance skill training of trainees are remarkably improved.

The invention relates to the technical field of online network teaching, and discloses an online network teaching practice method based on a virtual technology, and the method comprises the steps: obtaining virtual scene data, and carrying out the integration and building of a dynamic knowledge graph and a multi-modal teaching resource library; learning behavior features are extracted according to the cognitive features of the learner, knowledge difficulty levels are divided, and immersive learning is guided; constructing a cognitive evaluation model, optimizing a learning path through hierarchical reinforcement learning, and generating a self-adaptive teaching instruction; collecting interaction track data to generate an operation thermodynamic diagram, and evaluating the skill mastering degree; complexity parameters of the virtual scene are dynamically adjusted, a virtual-real linkage experiment simulation environment is constructed, and skill training closed-loop feedback is achieved. The invention further relates to specific implementation modes of resource integration, cognitive feature extraction, learning path optimization and the like. According to the method, the personalized and immersive experience and skill training effect of online teaching are improved, and the method is suitable for the field of online network teaching.

The invention provides a CT guided liver puncture training method and system based on virtual reality, and relates to the technical field of virtual reality. A deformable liver model and a virtual CT reconstruction engine under respiration driving are constructed, needle body posture mapping and image fusion display are achieved by fusing an inertia-electromagnetic dual-mode sensor, path interaction control, tissue dynamic response and score feedback are supported, the scene difficulty is automatically adjusted based on a training result, and the accuracy and the reliability of the system are improved. Progressive puncture skill training of static breath-holding, shallow breath and free breath scenes is achieved, the sense of reality of training, operation feedback and teaching efficiency are improved, and the system is suitable for development and clinical teaching application of an interventional therapy training system under the guidance of medical images.

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 relates to the technical field of hydrological survey skill training, in particular to a construction method and system of a hydrological survey knowledge model based on a large model. The method comprises the following steps: acquiring multi-source hydrological data, and constructing a hydrological knowledge graph; generating a confusion sample corresponding to the hydrological knowledge graph, and performing adversarial training on the confusion sample; according to the confrontation training result and historical test questions in the multi-source hydrological data, obtaining bidirectional mapping test questions; inputting the bidirectional mapping test questions into a question setting interface of a hydrological survey learning platform; collecting answer data and student physiological data corresponding to the bidirectional mapping test questions in real time, and updating a student knowledge state according to the answer data and the student physiological data; constructing a hydrological survey knowledge model based on the updated student knowledge state; and generating a student recommendation learning scheme by using the hydrological survey knowledge model. According to the invention, the intellectualization and practicability of hydrological survey education can be 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.

The invention relates to the technical field of intelligent education, in particular to an AI-based nursing teaching scene construction and evaluation system. According to the system, a dynamic case script is generated through historical case data, and a virtual patient physiological model is constructed; creating three teaching scenes of community follow-up visit, emergency rescue and traditional Chinese medicine nursing fusion by using a mixed reality technology; a personalized learning portrait of the student is constructed through a pre-test, and accurate matching between the ability of the student and the teaching content is formed; a double-track system skill training module is built, and AI tutor guidance and teacher guidance are integrated; and an ability evaluation system based on operation data is established, and intelligent pushing of adaptive training content is realized. The problems that in traditional nursing teaching, scene authenticity is insufficient, personalized training is insufficient, and clinical thinking is difficult to cultivate are solved, and the clinical operation skill and decision judgment ability of students are improved.

The invention discloses a nursing medicine education system based on the Internet, and relates to the field of computer application technology and education management, and the system comprises a theory learning module which is used for achieving the online teaching and personalized learning pushing of nursing theory knowledge, the nursing skill training module is used for training and evaluating the standardized nursing operation ability of students, the virtual simulation practical training module is used for providing an immersive virtual clinical training environment, and the structured nursing document training module is used for improving the ability of the students to write standard nursing documents. The intelligent evaluation module is used for carrying out automatic, multi-dimensional and structured comprehensive evaluation on the learning and training process of students, and the system integration interface module is used for realizing data exchange and interaction between the teaching platform and an existing information system of a hospital. The system has the advantages of complete functions, closed-loop data and accurate intelligent evaluation, and can effectively improve the standardization, practicability and intelligent level of nursing education.

The invention relates to the technical field of artificial intelligence, in particular to a personalized soft skill training method and system based on artificial intelligence. The method comprises the following steps of performing evaluation by using a multi-dimensional questionnaire, and analyzing semantics of user answers in combination with a large language model to generate an initial user portrait; updating the initial user portrait; constructing a skill tree by using a word embedding technology and an improved Woltzz method; constructing and optimizing a global model based on the skill tree; and dynamically generating a personalized learning path according to the global model. By introducing an artificial intelligence large language model technology, a neural network word embedding algorithm and a graph theory algorithm and combining a'questionnaire-learning-practice 'closed-loop training mode, individuation, systematization and intelligentization of soft skill training are realized, the technical bottleneck of a traditional method in the aspect of subjective question type intelligent feedback is broken through, and the intelligent feedback of the subjective question type is realized. And the soft skill training effect and the user experience are obviously improved.

The invention discloses an unmanned aerial vehicle operation skill training system based on deep reinforcement learning, and the system comprises the following modules: an operation behavior data collection module which is used for constructing an operation behavior data set; the data preprocessing module is used for generating a time sequence joint input tensor; the behavior transformation module is used for outputting an operation behavior representation vector; the parameter updating module is used for carrying out non-momentum mode iteration updating on the training parameters of the behavior transformation Transform module based on a Lion optimizer; the disturbance adjusting module is used for obtaining disturbance behavior representation; the decoding module is used for decoding the disturbance behavior representation into a control action sequence; the reversible motivation generation network module is used for reasoning to obtain a reconstructed motivation vector; the motivation comparison module is used for identifying target cognitive deviation; and the training scheduling module is used for outputting a new training scene and a control strategy to the training simulation environment. According to the method, deep reinforcement learning and motivation modeling methods are fused, and personalized training of unmanned aerial vehicle operation skills is realized.

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 flight training, and particularly discloses an intelligent auxiliary training method and system for the driving skill of a helicopter pilot, and the method comprises the steps: deploying a plurality of sensors in a simulated helicopter cockpit for collecting operation, physiology, eye movement and other original data; after data standardization preprocessing, constructing a trainee training state comprehensive data model by using a multi-modal data fusion algorithm; dynamically generating a simulated flight scene by using VR and AR; carrying out comprehensive evaluation by adopting a multi-modal evaluation model based on deep learning in combination with multi-source data and student scene performance, and generating a multi-dimensional report; an evaluation result is fed back in real time through multiple channels such as voice and touch, and customized training resources are pushed; and formulating an exclusive training plan by using a personalized learning path planning algorithm based on multiple training data. Through multi-source data fusion and an intelligent algorithm, the training state of the trainee is comprehensively and accurately evaluated, a personalized training scheme is provided, and the driving skill training efficiency and quality of the helicopter pilot are effectively improved.

The invention provides a resource configuration and optimal scheduling method for supervision resources, and the method comprises the steps: building a cable laying three-dimensional visual model, enabling the attributes of supervision personnel to be matched with a supervision region, generating an initial configuration scheme, and carrying out the correlation analysis of a historical electrical engineering quality problem and the attributes of the supervision personnel, thereby achieving the optimal scheduling of the supervision resources. And dynamic adjustment of supervision personnel configuration is realized. And the construction process is monitored in real time by using the Internet of Things technology, and early warning and positioning are carried out on abnormal conditions. Quality of key processes is judged through image analysis, and professional supervisors are matched for disposal according to severity of problems. And skill training is carried out in combination with a virtual reality technology, and a personnel scheduling strategy is optimized. And through big data analysis, continuous evaluation and dynamic adjustment of supervision personnel configuration are carried out to form closed-loop optimization. According to the method, the supervisor and the supervision area are highly matched, the supervisor can quickly and efficiently complete the supervision work, the construction efficiency of the cable laying project is effectively improved, and the quality of the cable laying project is improved.

The invention discloses an electric power skill training and scoring evaluation method based on a large model algorithm, and belongs to the technical field of electric power skill training and scoring evaluation, and the method comprises the steps: collecting and processing student information data and historical operation behavior data, and integrating the processed data into a unified data warehouse for storage; analyzing the information data and the power skill post demand of each student by using a natural language processing technology to generate a demand analysis result; generating a training content scheme according to the demand analysis result based on a pre-selected large model; by analyzing learning behavior data, constructing a student learning style model, and further optimizing a training content scheme to obtain an optimal training scheme; a three-dimensional electric power working scene model is constructed by using computer graphics and VR / AR technologies; through establishing an operation evaluation model, real-time scoring evaluation is carried out on electric power skill operation of students, and an evaluation result of each student is obtained.

The invention relates to the technical field of medical care, in particular to a lung cancer chemotherapy patient resilience intervention system and application thereof. According to the intervention system based on the PERMA mode, intervention is implemented in stages through comprehensive measures such as acute symptom management, psychological construction strengthening, chemotherapy adverse reaction cognition, home nursing skill training, physical recovery training, social support linkage and treatment compliance improvement. The method comprises the following steps: quantifying pain by using digital scoring equipment, and assisting pressing to relieve symptoms by using acupoint diagrams; the psychological toughness is enhanced through the positive voice listening and the anti-cancer brave diary recording; an online and offline combined mode is adopted, group lectures, scene simulation video teaching and online community interaction are carried out, and social support of patients is enhanced; personalized exercise prescriptions and home safety lists are formulated, and treatment compliance is improved. The system can significantly improve the recovery of a patient, improve the life quality during chemotherapy, and provide a scientific basis for innovation of a tumor nursing mode.

The invention relates to the technical field of medical education, and discloses a virtual simulation method for an interactive anesthesia crisis skill training scene, and the method comprises the following steps: constructing a high-fidelity operating room and a crisis processing scene in a virtual environment; physiological parameter changes of the patient are simulated in real time and fed back to the student interface; recording and analyzing operation steps, decision-making time and physiological feedback of the trainee in training; and the learning path of the trainee is dynamically adjusted through a multi-objective optimization algorithm, so that the training effect is enhanced. According to the invention, through a personalized learning path and a real-time feedback mechanism, the effectiveness of anesthesia crisis skill training is improved. Students practice in a vivid virtual environment, and the clinical decision-making ability and the operation accuracy are enhanced. Meanwhile, the system is continuously updated to ensure that the training content is consistent with the latest medical practice, high-quality medical professionals are cultivated, and the medical service quality is comprehensively improved.

The invention provides an industrial assembly action recognition and error correction training method based on deep learning, and the method comprises the steps: achieving the synchronous collection of the whole assembly process through the deployment of a multi-mode perception collection system; a standard assembly database is constructed, a three-dimensional simulation platform is introduced, random disturbance is applied through a parameterized digital human body model, field disturbance is simulated, and a virtual sample enhancement training set is generated; based on real and virtual samples, constructing a deep neural network model, fusing a graph convolutional network, an LSTM and a convolutional network to extract skeleton, trajectory and mechanical features, and realizing assembly action recognition, anomaly detection and key frame positioning; and an assembly quality scoring function is constructed through the track consistency, the attitude offset and the mechanical anomaly index, multi-stage error correction feedback is generated, and personalized training is guided. The method is high in recognition precision of errors in assembly actions of assembly operators, can achieve timely and intelligent feedback, and is suitable for assembly quality optimization and skill training in an industrial scene.

The invention discloses a clinical skill training level evaluation method and device, equipment and a storage medium, and relates to the technical field of clinical medical education, and the method comprises the steps: collecting the current multi-modal data of the clinical skill operation of a target student in a clinical skill training process; preprocessing the current multi-modal data, and extracting features related to clinical skill operation of the target student in the preprocessed data to obtain an operation feature extraction result; and inputting the operation feature extraction result into a skill training level evaluation model obtained by training a multi-modal large model based on a dynamic space-time diagram attention network by using historical multi-modal data, so as to evaluate the clinical skill operation level of the target student based on the operation feature extraction result. And obtaining a skill training level evaluation result. The accuracy of clinical skill training level evaluation can be improved, and the evaluation efficiency is improved.

The invention relates to a force feedback simulation system and method based on a high refresh rate, the system comprises a tactile interaction device and a data processing feedback module, the tactile interaction device comprises an input signal acquisition unit used for acquiring information of the tactile interaction device and feeding back the information to the data processing feedback module; the feedback output unit is used for receiving the feedback signal and executing a simulation action; the data processing feedback module comprises a stress dynamic model which is used for respectively constructing a plurality of models according to different stages of simulation and determining and outputting a feedback signal after receiving the information of the mobile terminal; and the data acquisition refresh rate of the input signal acquisition unit is greater than or equal to 1000Hz. According to the method, the tactile fidelity, continuity and operation effect of operation simulation are remarkably improved, so that the method is closer to a real operation environment, the skill training and practice level of surgeons is improved, and the method is not only suitable for simple single-layer tissue puncture, but also supports complex multi-layer tissue simulation, and can be widely applied to minimally invasive operation training scenes.

The invention discloses an intelligent management system and method for vocational skill training, and relates to the technical field of vocational skill training management systems. The system comprises a student information management subsystem which integrates biological feature recognition, a dynamic password and SSO single sign-on to realize cross-platform secure access; a personal ability graph is constructed based on behavior logs and psychological assessment data, and attribute tags of unmarked nodes are automatically expanded by using a graph neural network. According to the system, attribute tags of unmarked nodes are automatically expanded through a graph neural network, a dynamic personal ability graph is constructed in combination with behavior logs and psychological assessment data, and accurate user portraits and personalized recommendation are supported; modeling time series data by using an LSTM neural network, and quantifying an attention concentration score; and student grades are divided based on a K-means clustering algorithm, and differentiated resource packages are pushed, so that individualized teaching is realized.

The invention discloses a doctor inquiry training system based on a generative AI technology, which comprises a medical document database and a processing unit in information interaction with the medical document database, the voice input module, the voice output module, the training module, the federation module, the vector database, the embedding module, the inspection module and the evaluation module are in information interaction with the processing unit. The system has the advantages that a real inquiry scene can be dynamically simulated to provide efficient and accurate inquiry ability training and evaluation support, and the problems that an existing inquiry training system is difficult to simulate real patient communication, the inquiry process cannot be deeply evaluated and continuously improved, a cross-hospital cooperative training mechanism is lacked, and the training effect is poor can be solved.

The invention relates to the technical field of medical simulation training, in particular to a simulation live wire treatment training method and system for high-risk orthopedic wounds, and the method comprises the following steps: calling preset explosion shock wave parameters, calculating the influence of shock waves on bones of multiple parts in combination with the stress-strain characteristics of bone tissues, and analyzing the mechanical response of the bone tissues, and simulating fracture injury conditions to obtain injury simulation data. According to the invention, through refined simulation of fracture injury and fracture complications, injury condition data are close to a real battlefield environment, students can visually understand dynamic evolution of wounds, and by collecting joint movement data of the students in real time and combining mechanical response of fracture parts, direct influence of treatment actions on the wounds is analyzed, so that the treatment effect of the wounds is improved. In the training process, wound state mapping is adjusted in real time, students are helped to understand operation feedback in real time, in combination with assessment of treatment skills, the skill level of the students is helped to be understood, a data basis is provided for adjusting training courses, and the skill training effect and efficiency are improved.

The invention discloses a clinical operation data analysis method based on virtual reality, and belongs to the field of virtual reality technology and medical skill training. Comprising the following steps: constructing a high-dimensional interaction data tensor covering space-time sequence features; establishing a three-dimensional space topological relation graph based on medical scene understanding, mapping various clinical operation skills into a three-dimensional model interaction sequence of a virtual medical device and an anatomical structure, and generating a multi-dimensional operation behavior feature vector matrix; virtual instrument operation sequence fragments with abnormal interaction efficiency or operation track deviation are identified, and dynamic loading priority weights of virtual medical scene resources are determined according to the virtual instrument operation sequence fragments; when the rendering frame rate of the virtual scene is lower than a specified threshold value, generating early warning information; and in a double-layer adaptive medical scene rendering optimization process, identifying performance bottleneck nodes and geometric processing conflicts in a three-dimensional rendering pipeline, and carrying out dynamic shader scheduling and model detail automatic switching according to a priority rule.

The invention discloses an intelligent switching control electrician practical training identification device, which belongs to the technical field of electrical detection and comprises a practical training platform, an operation panel, an electrical carrier plate and a built-in PLC (Programmable Logic Controller), the system integrates power input, a first conversion unit composed of a first isolation transformer and a first contactor, a second conversion unit composed of a second isolation transformer and a second contactor, a control unit, a data storage module, an operation input unit, a feedback unit and a load output unit. A dual-safety interlocking structure combining software interlocking and contactor hardware interlocking is realized through a PLC, and two paths of power outputs cannot be switched on at the same time. The device has the functions of intelligent mode switching, real-time voltage monitoring, fusing and sudden stop dual protection, operation state feedback and practical training data storage, meets industrial-grade and safety-grade practical training requirements, is compact in structure and high in safety, supports closed-loop control and data tracing, and is suitable for modern electrician skill training and intelligent examination and identification.

The invention discloses a police service vehicle rapid forward driving 180-degree U-turn driving training auxiliary method and system, and belongs to the field of police service vehicle special driving skill training. The method comprises the following steps: acquiring expert and coach successful operation data under different training condition parameters, and establishing a data model based on the data; obtaining training parameters of the current training task; according to the training parameters and the data model, a target operation time sequence is determined, and a synchronous operation prompt signal is sent to the trained driver through a signal prompt module; and recording the actual operation time sequence of the trained driver, comparing the actual operation time sequence with the target operation time sequence, and generating a training evaluation report containing deviation information. Through a data driving mode, a complex driving skill is deconstructed into a measurable, guidable and evaluable scientific process, personalized, standardized and intelligent assistance of special driving training is realized, and the training efficiency, the safety and the actual combat conversion rate are remarkably improved.

The invention discloses a basic nursing skill training system based on a large language model and deep learning, and belongs to the technical field of nursing skill training. The user terminal equipment is provided with a training system application program and is used for user login, training module selection and operation content display; the image acquisition equipment is used for acquiring video data of a simulation operation area in a user operation process in real time; the voice interaction device is used for collecting voice input of a user and playing voice feedback of a virtual patient; the processing control unit is used for running a large language model and a deep learning algorithm and realizing intelligent processing of visual identification and voice interaction of an operation process; and the evaluation feedback module is used for performing multi-dimensional evaluation on the operation normalization and communication performance of the user and generating a real-time feedback report. According to the invention, a complete intelligent teaching closed loop is realized. And full-process, multi-dimensional and granulated automatic evaluation can be carried out on three core capabilities, namely operation normalization, clinical thinking and communication effectiveness.

The invention belongs to the technical field of virtual training analysis, and particularly relates to an online virtual psychological training scoring system and a scoring method thereof. Comprising a training simulation module, a simulation evaluation module, a database module, a wide area network module, a management end and a student end. The training simulation module comprises a simulation server and a simulation output unit; the simulation evaluation module comprises an identity management unit, an index management unit and an evaluation unit; the database module is used for providing data support and processing service for each resource of the system and generated data; the wide area network module is used for establishing contact between equipment in the system and the management end and the student end; the management end is used for establishing an interface and a control mechanism related to system configuration management and system monitoring; and the student end is used for establishing a simulation training and student interaction operation mechanism. The virtual psychological training system is used for online virtual psychological training, meets the requirements of vocational skill training of related posts and the like, and enables learners to be familiar with and master basic knowledge, basic processes and practical operation skills of psychological training.

This invention relates to the field of intelligent education technology and discloses a tiered training method for editing skills based on deep learning. The method includes: constructing a training course library containing course units; using the course unit as the smallest learning unit, and based on the pre-dependencies of the course units, collecting real-time interactive operation data of learners to construct multi-dimensional feature vectors for learners; inputting the multi-dimensional feature vectors into a trained deep neural network model to output the learner's current assessed comprehensive course ability index; using a clustering method to divide all learners into three levels: basic, intermediate, and advanced; associating each level with a subset of course units, obtaining the matching degree between each learner's current assessed comprehensive course ability index and the difficulty coefficient, and generating a personalized course learning path recommendation for each learner. This invention achieves tiered training for learners' editing skills.

The present application relates to medical teaching aid technical field, especially intelligent feedback type thyroid ablation operation simulation training device. The model includes a simulation person, a cervical vertebra module, a thyroid module and a simulation nodule. The simulation nodule is made of a thermal response material, has a heating element inside, an ablation needle integrated with a temperature sensor, and a control unit triggers heating according to the sensor signal, so that the physical state of the nodule changes and the real ablation effect is simulated. The present application has a simple structure, can provide intuitive visual and tactile feedback, and is used for medical staff surgical skill training and objective examination.

The utility model discloses a coat surface inspection training device, relates to technical worker skill training technical field, the coat surface inspection training device comprises a frame, an operating platform and a control box, the operating platform comprises a mounting rack and a detection plate, the mounting rack is connected with the frame, the detection plate is connected with the mounting rack, the detection plate is provided with a functional area, and the functional area is connected with the control box. The functional area comprises a lamplight area and a paint surface detection area which are sequentially arranged in the first direction, a plurality of timing lamps are arranged on the lamplight area, and the control box can sequentially turn off the timing lamps in the second direction to form a paint surface detection path. According to the technical scheme of the utility model, the existing automobile door panel is adopted as the detection plate, so that the panel paint surface detection environment is actually restored, an efficient skill training means is provided for new employees, the sense of reality of training is greatly enhanced, the adaptation period of the new employees after the new employees are on duty is reduced, the training is more effective, and the working efficiency is improved. Students can more quickly adapt to the requirements of actual working posts.