30 results about "Emergency training" patented technology

The invention discloses a railway modularized intelligent emergency training system based on a TRIZ theory, and belongs to the technical field of railway emergency training. The system is composed of a data acquisition module, a scene simulation module, an intelligent interaction module, a practical training evaluation module and a modular management unit. The data acquisition module acquires railway operation data and historical emergency case data in real time; the scene simulation module constructs a vivid and parameter-adjustable practical training scene by using VR, AR and other technologies; the intelligent interaction module realizes natural interaction and real-time feedback between trainees and scenes; the practical training evaluation module scientifically evaluates the practical training performance of the trainee from multiple dimensions; and the modular management unit flexibly manages and dispatches each functional module. According to the invention, innovative design is carried out based on the TRIZ theory, the authenticity of practical training is improved, the flexibility and expansibility of the system are enhanced, the evaluation scientificity of the practical training effect is improved, and the emergency processing capability of railway workers can be effectively improved.

The invention discloses a situational medical care emergency training method based on an intelligent decision tree, and the method comprises the following steps: S1, collecting and preprocessing medical care emergency historical case data, and extracting an expert path; s2, constructing a medical emergency situation virtual environment based on the structured data and initializing an intelligent decision tree; s3, performing evolution operation on the plurality of decision paths by adopting a genetic algorithm to generate a decision path set; s4, fusing the decision path and the expert path by adopting a belief propagation algorithm to generate an emergency decision path; s5, emergency training is carried out in the virtual environment, recording and evaluation are carried out, and an adjusted path is formed; and S6, redeploying the adjusted path to the decision tree, and carrying out targeted drilling. According to the method, the intelligent decision tree integrating genetic optimization and a belief propagation mechanism is constructed, so that accurate and efficient training and path optimization of medical staff in a situational emergency environment are realized.

The invention relates to the technical field of turbine emergency training, in particular to an intelligent training device for a turbine emergency trip system, which comprises a hydraulic oil module connected with a plurality of emergency trip training modules and used for providing kinetic energy for the plurality of emergency trip modules, and a control module connected with the emergency trip modules and used for providing kinetic energy for the plurality of emergency trip modules. The control modules are in one-to-one correspondence with the crisis interruption modules; the control module is used for sending a control instruction to the crisis interruption module based on a preset control logic so as to simulate a crisis working condition to carry out training of crisis interruption actions; and the emergency interruption module is used for receiving the control instruction of the control module and executing an emergency interruption operation. According to the invention, the crisis interruption module is hydraulically driven, the control module is combined to collect the operation state and execute the preset logic, and interruption operation simulation and visual demonstration under the crisis working condition are realized.

The utility model relates to the technical field of practice teaching molds, and discloses a compression hemostasis teaching aid for adolescent emergency training, which is provided with a liquid bag, a simulated artery blood vessel, a simulated vein blood vessel, a simulated capillary and a micro pump, the liquid bag is used for storing simulated blood; the simulated artery blood vessel, the simulated vein blood vessel and the simulated capillary blood vessel are all of transparent structures and are respectively connected with the liquid bag, and the simulated artery blood vessel, the simulated vein blood vessel and the simulated capillary blood vessel are respectively connected with valves for controlling the on / off state of a pipeline; the micro pump is used for outputting pumping pressure to the liquid bag, and the pumping pressure of the micro pump is adjustable corresponding to the set flow velocity of the simulated artery blood vessel, the simulated vein blood vessel and the simulated capillary blood vessel. The first-aid training device can simulate different blood vessels of a human body and press the corresponding blood vessels to force blood flow in the corresponding blood vessels to be stopped, so that teenagers can practice operation in training, and the teaching effect of first-aid training of the teenagers is effectively improved.

This invention belongs to the field of medical teaching aids technology, specifically a cardiopulmonary resuscitation (CPR) first aid skills training device, including a head training module, a neck connection module, a chest training module, a base platform, and a control module. The head module includes a head shell, a simulated oral cavity, an angle sliding shaft, and a sensing unit. The neck module is equipped with an automatic closing device to achieve coordinated airway opening and closing. The chest module incorporates a compression simulation unit, a vibration module, and electrode pressure pads. The control module coordinates data transmission and feedback from all units. This invention solves the problems of existing CPR training devices, such as limited functionality, inaccurate operation detection, unrealistic scenario simulation, delayed feedback, and scattered assessment data. These devices fail to provide comprehensive error correction guidance for trainees, struggle to recreate realistic scenarios such as airway obstruction and insufficient ventilation, resulting in poor training effectiveness and failing to meet the needs of precise clinical emergency training. This invention achieves accurate capture of the entire operation process, real-time feedback, and standardized assessment, improving the professionalism and practicality of the training.

This invention discloses a virtual reality inspection and emergency response method and system for pressure vessel safety operation, specifically relating to the field of virtual reality technology. It addresses the problem of distorted causal chains in virtual emergency training by utilizing visualization technology to intuitively display fault information and trigger playback through gaze-based pauses, enhancing the operator's perception of fault trigger points and paths. It divides independent timelines based on fault processes and material failure mechanisms, dynamically adjusting the time flow rate to ensure the simulation's physical logic is consistent. The fault model and intervention model run in parallel within the virtual engine, responding to operator behavior in real time and generating branch fault evolution scenarios, improving the dynamic adaptability of training. By constructing a fault propagation vector field and comparing it with a preset benchmark, it generates a causal deviation isosurface projection, providing personalized optimization guidance for operators. This effectively enhances the connection between virtual training and actual operation, comprehensively improving the operator's emergency response capabilities.

This invention discloses an intelligent chemical fire response training system, relating to the field of fire emergency training technology. It includes a realistic physical model of a chemical facility; a fire physics simulation model module is equipped with flame and smoke injection modules based on the actual fire location within the chemical facility, used to simulate different types of fires by spraying flames and smoke and adjusting their size and concentration. By setting up modules such as a chemical facility physical model, a fire physics simulation model, fire extinguishing equipment, environmental monitoring, and fire extinguishing behavior monitoring, this invention simulates different types of fires on a realistic chemical facility physical model. Furthermore, by monitoring and analyzing the differences between firefighters' firefighting behavior and standard behavior, it identifies weaknesses in firefighters' firefighting actions and recommends targeted training for corresponding chemical fire scenarios, thereby improving training effectiveness.

This invention discloses a dual-layer liquid crystal display device and method for simulating pupil size, belonging to the field of human simulation displays. It comprises an integrated module coaxially stacked from an upper liquid crystal panel, a lower liquid crystal panel, a background film, a backlight panel, a fixing plate, and a main control board. The module is embedded and coplanar with the simulated human eyeball, and is fully sealed and dustproof. The upper liquid crystal panel features coaxial circular and annular light-shielding patterns, while the lower liquid crystal panel features an annular light-shielding pattern; all three are sized to be compatible. The main control board independently drives the two liquid crystal panels, achieving seamless switching between three clinical pupil states (dilated, moderate, and constricted) through the superposition of the light-shielding areas. This invention eliminates display gaps, resulting in smooth and natural pupil edges. It boasts strong structural adaptability and reliable control, significantly enhancing the realism and professionalism of emergency training.

The present invention relates to a method to establish vital sign prediction models to predict future vital signs of a patient. The method comprises training an attention-based architecture with a vital sign training dataset comprising multiple vital sign training data, each of which has a training input and a training ground truth, wherein the multiple training data comprise multiple control training data of multiple first patients without critical conditions and multiple emergency training data of multiple second patients with critical conditions. The present invention also provides an application of the established vital sign prediction models to realize an early warning system to predict cardiac arrest at earlier time points.

1. Name of the product in this design: First Aid Training Vehicle. 2. Purpose of this design: A device for teaching the Heimlich maneuver. 3. The key design features of this product are the combination of shape and pattern. 4. The image or photograph that best illustrates the design's key points: a 3D model.

The invention relates to a coal mine emergency drilling method and system based on dynamic catastrophe chain simulation, and belongs to the field of mine emergency rescue simulation training drilling. In order to solve the technical problems that in existing coal and gas outburst accident emergency drilling, static scene simulation cannot truly reproduce disaster burstiness and dynamic evolution characteristics, catastrophe chain type propagation process real-time simulation is lacked, drilling immersion is poor, and co-processing ability training is insufficient, the method comprises the steps that a mine three-dimensional scene is constructed, outburst parameters are input, and the coal and gas outburst accident emergency drilling is completed. The process of shock wave propagation, crushed coal body throwing and gas diffusion is dynamically simulated, and the damage state of equipment is simulated based on shock wave pressure, so that high-fidelity dynamic reduction of the whole coal and gas outburst process is realized. According to the method and the system, the consistency of a drilling scene and real catastrophe is effectively improved, the fidelity and effectiveness of emergency training are remarkably enhanced, and high-quality informatization technical support is provided for the emergency decision-making and co-processing capability of mine workers under the complex catastrophe condition.

The invention discloses a practical training system and a practical training method for simulating multi-place refueling operation, and aims to solve the problems of single scene, insufficient emergency training and one-sided evaluation of the existing aviation oil practical training scene. The system adopts a layered architecture and comprises a data layer, a scene construction module, a task allocation module, a collaborative operation module, a dynamic event module and an evaluation analysis module, a multi-airport collaborative guarantee scene can be restored, targeted tasks are allocated according to roles of managers and operators, and dynamic emergency simulation is integrated. According to the practical training method, a practical training effect is evaluated by generating a practical training project, making a scheme by a manager, splitting a task chain by a system, dynamically handling emergencies and combining with a multi-dimensional scoring model. The technology fills the gap between the existing practical training and the actual cooperation demand, improves the resource scheduling, emergency disposal and cooperation capabilities of trainees, does not need to depend on real equipment, and reduces the safety risk and practical training cost.

The invention relates to an emergency training drilling method and system based on three-dimensional simulation. The method comprises the following steps: based on a physical environment state parameter and a user operation instruction set of a previous period, analyzing the occurrence condition of an emergency of the current period, and obtaining emergency identification information of the current period; obtaining a three-dimensional drilling scene of the current period based on the physical environment state parameters of the previous period, the user operation instruction set, preset current environment parameters and emergency identification information of the current period; acquiring a user operation instruction set and a current physiological signal when the three-dimensional drilling scene of the current period is executed; based on the emergency identification information of the current period, the user operation instruction set, the physical environment state parameters and the current physiological signals, the emergency operation condition of the user is evaluated, and an operation matching result and a cognitive load evaluation result of the current period are obtained. By adopting the method, actual combat pertinence and training effectiveness of drilling can be improved.

This invention discloses a method for generating planar layout diagrams and 3D models for large-scale scenes, relating to the fields of 3D vision and layout diagram generation. The invention proposes a hierarchical scene layout generation method that explicitly decouples room topology and geometry to achieve planar layout generation for large scenes. It designs a "2D layout generation + 3D scene transformation" technical route to complete the generation of 3D models for large scenes; it proposes a size-aware semantic centroid heatmap representation, fusing room location and size information predicted by a graph transformer to ensure strong semantic alignment between the generated results and input constraints. It realizes the entire process of planar diagram vectorization and 3D transformation, achieving high-fidelity generation from 2D layout to 3D scene, and uses a large language model to realize the transformation of intelligent furniture layout and natural language description to scene diagram. This method can handle large scenes with more than ten rooms and is applicable to fields such as building information modeling, extended reality, and virtual emergency training.

The application discloses a kind of course resource management systems for public health skill training examination, including multi-agent game confrontation module, stress level quantification module, decision quality evaluation module, stress and decision quality correlation analysis module and information pollution simulation module;By constructing the multi-type game intelligent agent of panic crowd with independent interest appeal, intervention administration, emotional media, the stress level is quantified from four dimensions of time, information contradiction, resource constraint, morality, and the stress and decision quality decay curve is established, to determine the decision resilience critical point and capability elasticity interval;At the same time, using biological transmission and information transmission cross-infection model, controllable information noise is actively injected, to train the students' traceability reasoning ability in the information pollution environment;The application significantly improves the authenticity of public health emergency training, the accuracy of evaluation and the individualization level of training.

The invention relates to the technical field of infant Hemricker first-aid training devices, in particular to an infant Hemricker first-aid training device capable of simulating multi-foreign-matter obstruction, which comprises a human-shaped model, a head is arranged at the top of the human-shaped model, and an oral cavity is arranged in an inner cavity of the head; limiting on the replaceable simulation blocking plate is removed by rotating the locking sleeve, then the replaceable simulation blocking plate is moved, the foreign matter is introduced into the foreign matter pipe to simulate the foreign matter blocking condition, the push rod on the fixing sleeve is pushed, the push rod drives the rotating sleeve to rotate, and the rotating sleeve drives the outer pipe to slide and contract. The outer tube slides and shrinks to extrude the inner tube to change the diameter of the inner tube, and the replaceable simulation blocking plate can be conveniently replaced to simulate complete blocking and partial blocking, so that the effect of simulating tracheal blocking conditions of children of different ages is achieved; the problem that an existing infant Hemricker first-aid training device is poor in trachea simulation design and adaptability is solved.

The invention relates to the technical field of emergency training and emergency response, in particular to an interactive emergency scene simulation and emergency processing guidance platform which comprises a multi-mode sensing module, a dynamic scene generation module, an intelligent decision guidance module, an interactive feedback module and a data storage and analysis module. The multi-mode sensing module is used for collecting user operation behaviors, physiological states and environmental parameters; the dynamic scene generation module dynamically adjusts the scene difficulty and the event process based on the real-time collected data and a preset first-aid scene template; the intelligent decision guidance module fuses an emergency knowledge base and a deep learning model, and provides personalized and real-time emergency operation guidance for the user; the interaction feedback module outputs feedback information to the user through the multi-sensory channel; and the data storage and analysis module records training / emergency data and performs effect evaluation. The problems that an existing emergency simulation system is fixed in scene, poor in interactivity, lack of pertinence in guidance and the like are solved.

The invention provides a cardiac resuscitation assessment method, equipment and a program product, which can be applied to the crossing field of medical emergency training and artificial intelligence technology. The method comprises the steps that under the condition that the difference value between a first pressing parameter and a second pressing parameter for conducting cardiac resuscitation on a simulation object meets a preset condition, key point coordinates in position movement sequences corresponding to multiple key points are corrected, and a corrected position movement sequence is obtained, the first pressing parameter is collected by a pressure sensor, the second pressing parameter and the position movement sequence are collected by a visual sensor, and the pressure sensor is arranged in the chest of the simulation object; according to the respective correction position movement sequences of the multiple key points, visual sign parameters are determined, and the visual sign parameters represent the accuracy of the cardiac resuscitation posture; and determining an evaluation result according to respective evaluation values of the visual sign parameter, the first pressing parameter and a gas flow parameter determined based on the gas sensor.

The application discloses a meta-universe-based management simulation system and method for dealing with chemical industrial park explosion, and belongs to the technical field of chemical emergency management. The system solves the problems of existing exercise system script rigidity and weak cooperation. The system comprises a virtual real-time monitoring and prevention module and a virtual interactive exercise disposal module. The former builds a digital twin model of the chemical industrial park through AR real scene scanning, and fuses accident cause analysis and dynamic Bayesian network of system theory to perform real-time probability reasoning, interpretable attribution and early warning on the explosion risk coupled with multiple factors. The latter adopts an event-driven deduction engine to decompose the exercise process into an atomic event directed probability graph, to drive real-time adaptive deduction of non-fixed scripts by user decision, and to realize decision timeliness monitoring, conflict detection and resolution through meta-decision agents. The application realizes real-time dynamic assessment and interpretable early warning of the explosion risk of the chemical industrial park, supports immersive collaborative exercise with thousands of faces, and significantly improves the pertinence, authenticity and fluency of emergency training.

The application discloses a nuclear safety emergency virtual simulation system and method based on an emergency framework, and belongs to the technical field of computer simulation; the nuclear safety emergency virtual simulation method based on the emergency framework comprises the following steps: dynamic scene generation; screening of emergency rules based on a rule triggering correlation degree formula, initial scene parameters are generated; and scene parameter dynamic iterative updating is realized through a scene superposition influence formula and a parameter updating formula; according to the application, an adaptive emergency scene is dynamically generated based on real-time monitoring data, extreme and composite accidents can be accurately coped with, and the pain point of the lack of authenticity of a traditional scene is solved; a deduction logic verification module can effectively identify and correct logical deviation and resource scheduling risk, and ensures that deduction is rigorous and reliable; and an abstract parameter is converted into an intuitive interface through a visual output module, and the practicality of emergency training is improved.

This invention discloses a multimodal perception fusion-based emergency training virtual reality closed-loop control system and method, belonging to the field of virtual reality technology. It includes: a multi-source data synchronous acquisition module, which synchronously acquires trainees' eye-tracking data, visual three-dimensional skeletal posture key point data, and wrist-worn physiological sensor data; a virtual-real space dynamic registration and multimodal feature extraction engine, which calculates mapping relationships and extracts feature vectors representing visual attention allocation patterns, kinematic features of movements, and autonomic nervous system stress response parameters; a real-time state quantification assessment module, which outputs a real-time state assessment vector containing a comprehensive risk avoidance index and a state stability coefficient; a virtual environment dynamic control module, which matches teaching intervention strategies and generates scene control instructions; and an immersive situational cognition guidance and feedback module, which, when the state stability coefficient is determined to be lower than a preset stress safety threshold, prohibits the triggering of new preset environmental disaster events and activates a parameterized flexible situational guidance mechanism.

The invention belongs to the field of industrial digital twinning, and mainly relates to an emergency training situation deduction method based on digital twinning, and the method comprises the steps: deploying a plurality of types of data sensors in a chemical plant, collecting an equipment state and environment parameters in real time, fusing a factory design drawing, and constructing a high-precision digital twinning body consistent with a physical site; a fault propagation mechanism is established, so that a simulation situation can automatically, intelligently and dynamically evolve according to initial conditions; real-time sensor data are continuously fused into the digital twin, the state of the virtual model is driven to be synchronously updated, and disaster evolution paths and key parameters are dynamically adjusted according to real data flow; the AR technology is combined, so that the training personnel can operate the virtual equipment personally on the scene; identifying potential hidden dangers of the factory by combining an AI algorithm; the method not only improves the training effect, but also assists the implementation of risk identification and predictive maintenance, and forms a closed-loop management mechanism from situational simulation to risk prevention and control.

The application belongs to the technical field of simulation training, and particularly relates to a simulation training system, which can simulate real situations, meet the needs of multiple people to cooperatively carry out emergency disposal training, and further improve the emergency disposal ability of the people; can realize the effective structure of training and actual combat, facilitate the convenience and normalization of emergency training, and further achieve the effect of improving the emergency disposal ability of the employees; the architecture of the simulation training system can greatly relieve the data transmission pressure of the cloud data server, improve the efficiency of data update service, and ensure the efficient performance of the training.

The invention discloses a big data processing system and method based on emergency training and troubleshooting driven consumption, and belongs to the technical field of big data. The user portrait module obtains historical risk data of the user and constructs a user risk portrait based on the historical risk data of the user; the risk database module obtains commodity information, and constructs historical risk data of a user and a mapping data list of the commodity information based on a preset mapping relation; and the commodity matching module compares the user risk portrait with the field risk data to obtain difference data, updates the user risk portrait based on the difference data to obtain an updated user risk portrait, and performs matching based on the updated user risk portrait and the mapping data list to obtain a recommended commodity list. According to the method, the specific condition of each family can be controlled, consumption is promoted by constructing the mapping data list, meanwhile, the problem of data islands is solved, and the data processing efficiency is improved.

The invention provides a crew emotion recognition method in an emergency scene based on EEG-DSRnet, and the method comprises the steps: constructing a maritime emergency scene through employing a virtual reality technology, and actively inducing the emotion of a crew; collecting electroencephalogram signals of the sailors in the emergency scene through an electroencephalograph, and preprocessing the electroencephalogram signals; and constructing an EEG-DSRnet model, carrying out feature extraction and classification identification on the preprocessed electroencephalogram signals, and identifying the fear emotion of the sailors in the emergency scene according to the classification result of the model. Wherein the EEG-DSRnet model is combined with depth separable convolution, a SENet attention mechanism and residual error connection, and three-classification recognition of the emergency emotion is achieved. The EEG-DSRnet model adopts a compact convolutional neural network architecture, and can effectively extract key features in the electroencephalogram signals of the sailors. The EEG-DSRnet model provided by the invention is compact in structure and high in calculation efficiency, has good generalization ability, can effectively improve the accuracy and stability of sailor emotion recognition in an emergency scene, provides technical support for maritime emergency management, and is suitable for sailor emergency training.

This invention provides a virtual scene toxic gas detection simulation training method, device, and simulation training platform. It generates and stores toxic gas diffusion concentration distribution data for virtual 3D scene simulation training; retrieves the stored toxic gas diffusion concentration distribution data according to a preset training task, and performs grid-based matching between the toxic gas diffusion concentration distribution data and the introduced virtual 3D scene; establishes a toxic gas equipment response model to obtain the response modes of different detection devices for different types of toxic gases in the virtual 3D scene; and sends the toxic gas diffusion concentration distribution data at different grids in the virtual 3D scene to the toxic gas equipment response model to obtain and display the corresponding detection device's response mode. This method can reflect the toxic gas distribution environment and equipment response modes under complex conditions, while avoiding the large amount of data calculation required for on-site simulation training, providing an effective toxic gas detection simulation method for chemical accident emergency training.

The application relates to the field of medical simulation systems, in particular to a pre-hospital comprehensive trauma first-aid training simulation system and method. The system comprises a plurality of training projects corresponding to different rescue operations; a scene setting module comprising a character physical parameter setting module, an environment setting module and a process editing module; a scene performance module for showing the conditions of character physical signs and first-aid environment to prompt the trainer to judge the current training project and take corresponding rescue operations, the condition of the character physical signs corresponding to the character physical parameter; the human body model is also used for the operator to implement the rescue operation; a rescue information acquisition module for acquiring the rescue operation information of the trainer corresponding to each training project; and a scoring module for comparing the rescue operation information with a preset standard rescue operation specification, calculating the completion degree of each training project and giving the score. The system can improve the flexibility and diversity of the rescue training, improve the authenticity of the practical training effect and exercise the ability of the trainer to use first-aid knowledge on the spot.

This invention provides a method for recognizing crew emotions in emergency scenarios based on EEG-DSRnet, comprising: constructing a maritime emergency scenario using virtual reality technology to actively induce crew emotions; collecting and preprocessing the crew's electroencephalogram (EEG) signals in the emergency scenario using an EEG analyzer; constructing an EEG-DSRnet model to extract features and classify the preprocessed EEG signals; and identifying the crew's fear emotions in the emergency scenario based on the model's classification results. The EEG-DSRnet model combines deep separable convolutions, SENet attention mechanisms, and residual connections to achieve three-class classification of emergency emotions. The EEG-DSRnet model employs a compact convolutional neural network architecture, effectively extracting key features from the crew's EEG signals. The proposed EEG-DSRnet model is compact, computationally efficient, and possesses good generalization ability, effectively improving the accuracy and stability of crew emotion recognition in emergency scenarios, providing technical support for maritime emergency management, and is suitable for crew emergency training.

The utility model provides a cardio-pulmonary resuscitation training device with a feedback function, which relates to the technical field of medical emergency training and comprises a trunk body, a simulated neck and a simulated human head. The human body main control board is arranged on the bottom side in the trunk main body; the voice recognition module is arranged in the training device, and when a student sends a statement including environment safety and 120 dialing, the voice recognition module recognizes and makes a response; the key switch is arranged on the simulated neck and is used for judging whether the student touches the carotid artery or not; the angle sensor is arranged on the simulated neck and is used for detecting the backward leaning angle of the head and the airway opening action; the touch sensing switch is arranged in the middle of the chest of the training device and at the middle point of the connecting line of the two nipples and used for feeding back whether the pressing position of the student is accurate. By integrating the functions of voice recognition, touch induction, angle detection and the like, the comprehensive feedback and guidance for the operation process of trainees are realized, and the training effect is improved.