9028results about "Simulators" 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 provides an intelligent driving scene adaptive teaching method and system based on reinforcement learning, and relates to the technical field of reinforcement learning, and the method comprises the steps: training a plurality of scene recognition models based on historical data, carrying out the scene classification of the historical data, and generating a training sample set with labels; and training by using a reinforcement learning algorithm to obtain an intelligent driving decision model for different scene types. In the actual driving process, the current driving scene is recognized according to the information such as the vehicle position, the vehicle speed and the acceleration which are collected in real time, and the corresponding decision model is selected to output the standard driving behavior sequence. And comparing the actual behavior of the driver with the standard behavior, calculating a deviation value, determining a teaching feedback strategy according to the deviation value, outputting driving guidance information in real time, and using the feedback of the driver to update the decision model. Personalized teaching can be provided according to different driving scenes, the driving skill of a driver is improved, and the driving safety is enhanced.

The invention relates to the field of flight training data processing, in particular to a flight training regulation and control method and system, and the method comprises the steps: collecting a physiological signal, an electroencephalogram signal and a visual signal of a pilot, and generating comprehensive feature data through multi-modal feature fusion; time dependence analysis is carried out through a recurrent neural network, a comprehensive pressure trend is generated in combination with historical pressure data, the psychological pressure of the pilot is further evaluated through a deep learning model, and the training intensity is adjusted based on real-time feedback data; in the virtual training, the situation is dynamically adjusted based on reinforcement learning, and a personalized training scheme is generated in combination with personalized analysis, so that the training effect of the pilot is optimized; according to the invention, comprehensive monitoring and personalized training regulation and control of the physiological state and psychological stress of the pilot are realized, and the adaptability and safety of flight training are improved.

A method, computer program product, and computer system for receiving, by a computing device, a design scenario for execution on one or more internet based platforms. Seed data may be injected into the one or more internet based platforms during execution based upon, at least in part, the design scenario. Performance of the scenario may be monitored. A report may be generated based upon, at least in part, the performance.

The invention provides a cardio-pulmonary resuscitation training system based on multi-modal artificial intelligence in combination with a virtual reality technology, and relates to the technical field of virtual reality, and the system comprises a multi-modal sensing module which is used for collecting posture data, mechanical data and environment data; the multi-source data collaboration module is used for generating an operation quality evaluation parameter set and establishing a mapping relation between the operation posture and the pressing efficiency; the virtual scene construction module is used for generating a virtual first-aid environment according to a preset first-aid scene template and the operation quality evaluation parameter set; the decision module is used for generating a feedback control signal; and the interactive closed-loop execution module is used for inputting the feedback control signal into the virtual first-aid environment and updating the operation quality evaluation parameter set according to the operation data after feedback response. According to the invention, standardized, intelligent and scene-diversified cardiopulmonary resuscitation skill training can be realized, and the technical problems of inaccurate posture evaluation, non-personalized feedback, single scene, high resource dependence and the like in traditional training are solved.

The invention relates to the technical field of power system operation training, and discloses a virtual reality-based power grid fault simulation training system and method, and the system comprises a virtual scene modeling module which is used for constructing a three-dimensional model of power grid equipment and an operation environment thereof, and providing a vivid training environment for subsequent modules; and the interaction and operation module is connected with the virtual scene modeling module and realizes interaction between the trainee and the virtual environment by using a VR head-mounted display, a handle and a motion capture device. By adopting a high-precision three-dimensional modeling technology, PBR material rendering and an LOD optimization strategy, high simulation of power grid equipment and an operation environment is realized, students can experience a vivid visual effect and immersion in a virtual reality scene, and meanwhile, by combining a gesture recognition technology realized by motion capture equipment and a convolutional neural network, the real-time simulation of the power grid equipment and the operation environment is realized. Operation actions of trainees can be accurately captured, a natural and visual interaction mode is provided, and the authenticity and operation experience of the training system are greatly improved.

A control unit for an aircraft capable of hovering or for a flight simulation system of the aircraft is described; the control unit is programmed to:receive in input a plurality of data associated with equipment and / or kits actually installed or simulated on the aircraft and / or with the operating configuration of the equipment and / or kits; the equipment and / or kits causing a reduction of the actual or simulated forward velocity of the aircraft;store a table defining a correspondence between each datum and a respective value of a first signal associated with a value of maximum forward velocity of the aircraft; anddisplay the lowest of the first signals.

The invention provides a scene reproduction and augmented reality simulation training method for floating installation. The method comprises the following steps: acquiring an external environment and an equipment state in real time; acquiring operation behavior data of the trainee in the training process, performing timestamp matching on the operation behavior data and the dynamic simulation scene, constructing a synchronous model, calculating a key performance index based on the synchronized data to quantify the operation effect of the trainee, and obtaining an operation performance record; when it is detected that the student fails to operate, a failure scene of the student is reconstructed based on currently collected operation behavior data and a dynamic simulation scene, and a failure path is analyzed by using a reinforcement learning model; generating an optimized floating track and an optimized posture adjustment path according to the failure scene of the reconstructed student and the optimization suggestion; and the trainee completes the floating support installation operation according to the optimized path displayed by the augmented reality equipment. According to the invention, the efficiency and effect of floating support installation training can be greatly improved, and a more efficient and intelligent solution is provided for the ocean engineering field.

The invention discloses a driving skill training method constructed based on a diversified virtual examination room, and relates to the technical field of data processing, and the method comprises the steps: constructing a system based on the diversified virtual examination room, constructing a virtual examination room scene to carry out the driving training of a training user, outputting a driving behavior data set in real time, and carrying out the scoring, and analyzing the data according to the driving score, generating a personalized training path in combination with historical data when the driving score does not reach the standard, and training the user to carry out training step by step according to the training path until a preset skill scoring target is achieved. The technical problems that in the prior art, a traditional driving training method cannot dynamically adjust a training path to meet the actual skill requirements of trainees, consequently, training content lacks pertinence and is low in efficiency are solved, the individuation and pertinence of driving skill training are improved, it is ensured that the training content is highly matched with the actual skill requirements of the trainees, and the driving skill training efficiency is improved. And the training efficiency and effect are improved.

The invention discloses an acute and critical disease nursing training system and method based on vr, and relates to the technical field of medical systems. A learning mode and an assessment mode are selected through a handle trigger; in the learning mode, the nursing operation process is dynamically displayed through vr glasses and a scene generation engine, and the scene generation engine constructs a disease evolution path based on a knowledge graph and associates user historical data to match personalized teaching cases; receiving a selection instruction of a user for an assessment item in the assessment mode, receiving an operation instruction of the user at the same time, recording time sequence data of an operation path and selecting a behavior logic chain; generating a score according to a dynamic scoring algorithm including an operation track accuracy parameter and a decision timeliness parameter; the user is personally on the scene to carry out nursing training and examination on acute and critical diseases, and trial and error in a highly-simulated critical scene are carried out; a targeted training scene is intelligently pushed according to the specialty and ability of the user; and the speed and quality of acute and critical disease nursing are balanced through multi-dimensional scoring.

The invention relates to the technical field of medical simulation training, in particular to an anesthesia puncture virtual simulation operation training and analysis system which comprises a force feedback calibration unit, a force feedback adjustment unit and a force feedback output unit. A theoretical force feedback value is calculated based on a human tissue mechanical model library, tissue levels and characteristics are accurately considered, in a deviation correction link, a force perception deviation value is periodically recalculated, data are processed by applying a sliding window averaging method, overall deviation and local deviation are distinguished and correspondingly adjusted, and the overall deviation is uniformly corrected; functional fine adjustment is locally set according to puncture depth sections, time-dependent force feedback of tissue viscoelasticity is considered, components are calculated through convolution integral and synthesized into final values with elasticity and inertia components, force feedback accuracy is improved comprehensively, individual differences and operation details of trainees are fitted, and anesthesia puncture training quality and effect are improved efficiently.

The invention discloses a 500kV standardized switching operation method based on a VR virtual reality technology, and aims to solve the problems of unreal environment, incomplete evaluation and low efficiency in the switching operation training of an existing 500kV transformer substation. The method comprises the following steps: constructing a full-immersive virtual reality scene, collecting actual environment data of a transformer substation, and constructing and optimizing a high-precision model; designing multi-modal interaction of the standardized switching operation process, wherein the multi-modal interaction comprises visual guidance, a multi-modal interaction interface and an intelligent sensing function; dynamic action scoring and intelligent behavior evaluation are realized, actions are captured in real time by using high-precision action capture equipment, an instant score is generated by comparing with a standard, and dynamic feedback is provided; and real-time optimization and learning migration of the virtual character model are realized, user operation habits are captured, virtual character actions are optimized, and multi-scene migration and adaptation are realized. The method is suitable for VR-based 500kV standardized switching operation work, and the training authenticity and efficiency are improved.

The invention provides a PICC puncture virtual simulation training system and method constructed based on XR. A nursing skill simulation training platform and an intelligent training room based on augmented reality (XR) combine a simulation medical technology, an artificial intelligence large model, XR intelligent hardware, intelligent agent application, space calculation, computer vision and a mainstream technology of Internet of Things in scheme planning and design. According to the PICC puncture virtual simulation training platform, the ground practice, standardization, high virtual simulation and adaptive application of PICC puncture virtual simulation training are realized, and the intelligent development process and teaching concept of PICC puncture teaching are improved. According to the PICC puncture teaching system, intelligent virtual tutors, puncture teaching holographic three-dimensional sharing, virtual reality fusion technologies and the like are provided, an interactive teaching mode can be brought to PICC puncture teaching, the interest of students in teaching and clear operation guidance are improved, the theory and practice are fused, and the clinical cooperation ability is improved.

The invention discloses a fan fault simulation and diagnosis training system and method. A plurality of modules are integrated to realize comprehensive fan fault simulation, diagnosis and training functions. The virtual reality simulation environment module is responsible for creating a fan three-dimensional model and an operation environment and collecting operation data of students; the multi-modal sensor fusion module is used for collecting multi-dimensional data of the running state of the fan; the fault generation and diagnosis module receives the data, generates a simulation fault scene, performs intelligent diagnosis, and feeds back a result to the virtual reality simulation environment module for student reference; the quantum enhancement prediction and optimization module carries out fault prediction according to historical and real-time data of fan operation and provides optimization suggestions; the self-adaptive learning and evaluation module dynamically adjusts the training content and difficulty according to the performance of the trainee; the multi-scale digital twin platform simulates a fan system in an omnibearing manner and shares data with each module; the system provides a vivid training environment for trainees, and is helpful for improving fan fault processing skills.

A control unit for an aircraft capable of hovering or for a flight simulation system of the aircraft is described, the control unit is programmed to receive at input at least a first signal associated with real or simulated flight parameters of the aircraft and to provide at output a second signal associated with a forward velocity to never exceed of the aircraft; the control unit is programmed to process a third signal associated with an actual or simulated weight of the aircraft; to associate plurality of tables to respective intervals of values of the third signal; each table associating a plurality of values of the second signal with a respective first signal; and to process the second signal, based on the table associated with the relative interval of the third signal and the respective first signals.

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 provides an intelligent driving system and method and electronic equipment, relates to the technical field of intelligent driving, and realizes personalized improvement of driver ability and safety guarantee of a driving environment through three cooperative mechanisms including a teaching strategy module, a safety perception module and a behavior management module. Analyzing the multi-dimensional student data through a teaching strategy module by using a multi-modal large language model, and generating a personalized teaching strategy adaptive to the ability of the student; a driving environment is monitored through a safety sensing module, when a specific complex scene is detected, a multi-source heterogeneous sensor data fusion strategy is adjusted according to a scene type and a preset intervention degree, and then a safety coping strategy matched with environment interference is generated; the driving behavior data are recognized through the behavior management module, and multi-mode interaction feedback is generated in combination with the physiological data and the state data of the driver and used for guiding and correcting the driving behavior.

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 provides a virtual reality simulation training method, system and equipment for wind power plant operation and maintenance personnel and a medium. The virtual reality simulation training method comprises the following steps: step 1, constructing a virtual wind power plant; 2, realizing man-machine interaction between the user and the virtual wind power plant; 3, generating a virtual coach with professional knowledge and training experience, and guiding the operation of the user to realize simulation training of the operation and maintenance personnel of the wind power plant; according to the method, the application potential of emerging technologies such as virtual reality and artificial intelligence in the field of wind power operation and maintenance training is fully exerted, and the method has great theoretical significance and practical value in the aspects of improving industry talent quality, reducing training cost, promoting green and low-carbon development and the like.

The invention discloses an adaptive driving behavior evaluation and training system based on a multi-modal large model. Comprising a multi-mode driving data acquisition and situation awareness module, a data storage module, a driving behavior real-time evaluation and feedback module, an adaptive training strategy generation module, a cloud large model driven self-learning module and a driver psychological state monitoring and adjusting module. The driving behavior real-time evaluation and feedback module is used for carrying out real-time evaluation on the driving behavior of the driver through a machine learning evaluation large model and providing instant feedback; according to the invention, a multi-modal large model technology is combined, multi-modal data of a driving vehicle and a driver are collected in real time, personalized training tasks and learning strategies are generated according to changes of driving situations and real-time evaluation of driver performance, the training tasks are dynamically adjusted in different complex situations, and the training efficiency is improved. Training tasks are adjusted by analyzing the psychological state of the driver, and the system can provide detailed feedback for behaviors of the driver.

The invention relates to the technical field of intelligent teaching, in particular to an intelligent teaching system for traditional Chinese medicine clinical skill cultivation. The system comprises a virtual reality simulation module, an operation interaction module, an operation data analysis module, an adaptive learning feedback module and a teaching evaluation module. The virtual reality simulation module constructs a vivid traditional Chinese medicine skill training scene through three-dimensional modeling, ray tracing and physical simulation technologies, and the vivid traditional Chinese medicine skill training scene covers pulse feeling, acupuncture and moxibustion, massage and other operations. The operation interaction module collects user operation data and extracts features in combination with a variational auto-encoder. The operation data analysis module analyzes user operation deviation by using a graph neural network and a generative adversarial network, the adaptive learning feedback module generates a personalized learning strategy, and the teaching evaluation module evaluates a learning effect through fuzzy evaluation and analytic hierarchy process. According to the invention, intelligence, individuation and high efficiency of traditional Chinese medicine clinical skill cultivation are realized, the fidelity of teaching and the accuracy of feedback are improved, and the skill level and the training effect of learners are also improved.

The invention relates to the technical field of automobile education virtual practical training, in particular to a virtual practical training method for automobile vocational education. According to the technical scheme, the method comprises the following steps: initializing a multi-modal interaction system, specifically comprising the following steps: starting a virtual reality module, and creating an automobile practical training scene, including whole automobile internal structure display, engine operation simulation and automobile driving environment simulation; starting an augmented reality module, and preparing to superpose virtual information on a real automobile model; and starting the mixed reality module. Through the steps of multi-modal interaction system initialization, trainee practical training operation, intelligent cooperative tutoring network analysis, ability evaluation and course adjustment, dynamic updating and continuous learning and virtual competition module setting, a vivid practical training scene, personalized tutoring and learning paths are provided for trainees, learning enthusiasm and competition awareness are stimulated, and the training efficiency is improved. The ability of trainees is accurately evaluated, the teaching content is ensured to closely follow the industry development, and the effect of automobile vocational education is significantly improved.

The invention provides a medical skill assessment and training method and device based on a virtual patient, and relates to the technical field of digital computation.The method comprises the steps that image data, pathological data and physiological signal data corresponding to historical patients are obtained, and a virtual patient three-dimensional model is generated; performing multi-scale feature coding on the operation track, the instrument contact pressure and the biological tissue deformation parameter corresponding to the historical operation data of the target user to generate an operation feature vector with time sequence relevance; inputting the operation feature vector into a virtual patient three-dimensional model, and obtaining a physiological parameter change sequence corresponding to the operation feature vector; performing conjoint analysis on the operation feature vector and the physiological parameter change sequence to obtain an evaluation index matrix; generating an adaptive training scene according to the evaluation index matrix; the adaptive training scene comprises complication simulation information, abnormal sign triggering information and emergency state intervention information, so as to train the target user according to the mixed reality interaction equipment.

The invention provides an electrical integration comprehensive training method and system based on digital twinning, and relates to the technical field of digital twinning, and the method comprises the steps: building a digital twinning model of electrical integration equipment, updating operation parameters in real time, generating a simulation module, and setting a plurality of training scenes to correspond to different fault types. Historical fault data are analyzed by using a deep learning algorithm, fault features are extracted and implanted into a scene, and the training effect is improved. The state response is performed through the training instruction, the training process is evaluated based on the scoring rule, and the promotion suggestion is automatically generated, so that the fault judgment and maintenance efficiency of students is effectively improved.

The invention belongs to the technical field of new energy automobile teaching, and particularly relates to a VR interactive new energy automobile high-voltage electrical principle teaching method, system and equipment, and the method comprises the steps: obtaining the physical parameter data and dynamic circuit simulation data of a new energy automobile high-voltage electrical system; constructing a high-precision 3D model according to the physical parameter data, inputting dynamic circuit simulation data into the model, and generating interactive principle annotations and particle effect animations; based on a gesture recognition model and a new energy automobile VR interaction technology, circuit state changes in the particle effect animation are obtained, a new energy automobile high-voltage system principle and a signal flow are displayed, a practical operation simulation training scene is constructed, student operation data are recorded according to the practical operation simulation training scene, an AI evaluation model is trained, and an evaluation report is obtained. And adjusting interaction feedback parameters of the training scene, and meanwhile, generating a personalized learning report of the trainee. Therefore, the problems of safety risk, teaching lag, abstraction obstacle and the like in the prior art are solved.

The invention provides a VR-based primary and secondary school student multi-person safety education training method and system, and relates to the technical field of VR education, and the method comprises the steps: obtaining the behavior data of each student in a historical safety education training process, and carrying out the evaluation of the safety literacy capability of each student according to a preset safety literacy evaluation model, the safety literacy level of each student is obtained, a safety education training project recommendation sorting result for each student is obtained, and the students are allocated to corresponding safety education training projects according to the recommendation sorting result; real-time synchronous rendering is carried out on virtual avatars of the multiple students in the target VR system through the head-mounted display device, and cooperative training of the multiple students is realized; and after each student completes the safety education training project, scoring the completion condition of the safety education training task of each student by using a preset training task evaluation model, and generating a corresponding personalized evaluation report.

The present disclosure relates to processing data streams from a surgical procedure using multiple interconnected data structures to generate and / or continuously update an electronic output. Each surgical data structure is used to determine a current node associated with a characteristic of a surgical procedure and present relevant metadata associated with the surgical procedure. Each surgical data structure includes at least one node interconnected to one or more nodes of another data structure. The interconnected nodes between one or more data structures includes relational metadata associated with the surgical procedure.

The invention discloses a pump station maintenance-oriented dismounting path practical training method and system, and relates to the technical field of pump station dismounting. The method comprises the following steps: constructing a virtual-real simulation environment of pump station equipment, carrying out dynamic dismounting monitoring identification on pump station parts in the pump station equipment based on the virtual-real simulation environment, and determining a dismounting path; the method comprises the following steps: acquiring operation track data of a training person in real time through a motion capture device, obtaining a somatosensory interaction motion signal, mapping the somatosensory interaction motion signal to a virtual-real simulation environment for disassembly and assembly analysis, and generating a disassembly and assembly motion deviation parameter set; and performing dynamic optimization based on the disassembly and assembly action deviation parameter set in combination with disassembly and assembly multi-dimensional feedback data, generating multi-stage practical training difficulty, performing adaptation on practical training personnel according to a disassembly and assembly path according to the multi-stage practical training difficulty, and determining a multi-stage practical training scheme. The technical problems that in the prior art, pump station maintenance dismounting practical training lacks real scene simulation, and efficient skill training is difficult to achieve are solved, and the technical effect of improving the practical training effect is achieved.

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 Multi-agent-based psychological counseling platform and method. The counseling platform comprises an evaluation agent used for dynamically extracting psychological features based on dialogue behaviors of a visitor agent and updating results to a traits library module; the planning agent is used for constructing a personalized psychological counseling scheme based on the traits library module and dynamically adjusting a counseling process and a strategy according to counseling feedback; the consultant agent is used for carrying out dialogue interaction with the visitor agent according to the personalized consultation scheme and implementing emotion pacification and psychological intervention; the visitor agent is used for expressing psychological troubles, feeding back psychological state changes and promoting the consultation process; the historical dialogue long and short-term memory module is used for storing multiple rounds of psychological counseling interaction contents and comprises historical dialogue short-term memory and historical dialogue long-term memory; and the dynamic probability memory retrieval module is used for generating probability distribution based on the current consultation context and dynamically calling memory nodes from the historical dialogue long and short term memory module or the traits library module.