161 results about "Closed loop design" patented technology

The invention relates to the technical field of aero-engines, and discloses an automatic design method for aero-engine turbine blades, which analyzes design requirements through a language large model, combines a retrieval enhancement technology and a turbine blade expert knowledge base, performs interdisciplinary coupling verification by utilizing a step-by-step reasoning template, and generates and optimizes part design schemes and parameters. And then calling parametric modeling and an AI simulation agent model to carry out multi-physics field prediction, comparing a result with a requirement, if the result meets the requirement, outputting design, otherwise, automatically iterating and adjusting parameters until the parameters reach the standard or reach the maximum number of iterations. According to the method, end-to-end intelligent closed-loop design from design requirements to design results can be realized, manual intervention is reduced, a design scheme meeting performance requirements can be quickly generated, the design efficiency can be improved, the design cost can be reduced, and the design quality can be improved.

The invention relates to an unmanned aerial vehicle simulation training method for video guidance and track deviation evaluation based on deep learning. The method specifically comprises the following steps: S1, data acquisition and input; s2, generating and prompting a path visible area; s3, track deviation evaluation of image and flight control fusion; s4, trajectory behavior modeling and score analysis; s5, training a feedback output mechanism; and S6, carrying out personalized training recommendation and playback analysis. According to the invention, space-level deviation evaluation is realized by fusing the image and the flight control data, and the judgment is more accurate; the real-time visual feedback and voice prompt system can improve the training instantaneity and the interaction experience; a Transform-based trajectory scoring mechanism is close to the nature of an operation behavior, and multi-dimension evaluation is carried out; differentiated task recommendation is supported, and teaching pertinence and training efficiency are improved; the whole process is visual and can be repeated, and the teaching closed-loop design is optimized.

According to the brittleness baking control process based on the three-section variable-temperature hot air, the hot air flow field and material moisture migration are accurately regulated and controlled, and integrated control over brittleness structure shaping and energy-saving baking of products such as pet chews and jerky is achieved. A hardware architecture surrounds a'sensing-decision-execution 'closed-loop design, each part is tightly coupled with a central controller through an industrial bus, a dual-objective optimization system of brittleness formation and energy consumption control is constructed according to the high-protein and multi-fiber material characteristics of pet food, and the energy consumption of the pet food is controlled on the premise of ensuring that the brittleness index C of the pet food is greater than or equal to 65. Through a heat recovery unit, intermittent countercurrent air supply and LSTM feedforward control, the comprehensive energy consumption is reduced compared with the traditional process, and the unit brittleness energy consumption is reduced.

The invention discloses a multi-source heterogeneous data fusion-based garment production place intelligent identification and tracing method. According to the method, deep mining of the data value is realized through multi-link collaborative linkage. In the aspect of data processing, multi-dimensional information is collected from a source, isomerism is eliminated through standardized preprocessing, and then knowledge graph mining hidden association is constructed by means of a graph neural network, so that dispersed data form an organic whole. A dynamic weighted aggregation mechanism under a federated learning architecture enables each production node to cooperatively train a model on the premise of not sharing original data, data privacy is protected, the learning ability of the model for key features is improved, and a feature importance and data volume two-factor weighting strategy further ensures the reasonability of model parameter aggregation. The production place identification result is closer to the actual production scene, the closed-loop design of the tracing system forms a complete improved loop from data input to decision output to system upgrading, and the whole method has sustainable evolution ability in actual application.

The invention belongs to the technical field of software detection and repair, and discloses a reinforcement learning-based patch generation system, which comprises a code analysis module, a code defect detection unit, a defect verification module, a reinforcement learning training unit, a patch generation unit and a test and verification module. The code analysis module is used for extracting a source code from an input code file and generating an abstract syntax tree corresponding to the source code; and the code defect detection unit is connected with the code analysis module and is used for identifying the defect position and type in the target code. According to the scheme, end-to-end processing from defect positioning identification to repair is realized through a closed-loop design of code analysis, defect detection, reinforcement learning repair and test verification, a multi-module collaborative architecture is adopted, the defect detection accuracy is ensured by adopting a multi-mode defect detection and defect verification technology, the false alarm rate is reduced, and the detection efficiency is improved. And generating a high-quality repair patch through an interpretable reinforcement learning framework.

The embodiment of the invention provides a new energy inspection robot node positioning method and system, and the method comprises the steps: firstly carrying out the dual confidence degree dynamic evaluation of GPS and SLAM data, and quantifying the respective reliability in real time; and then, inputting the confidence into a fusion state machine decision engine, so that the fusion state machine decision engine can intelligently decide that the system should be in an optimal fusion state such as GPS leading, pure SLAM or GPS recovery transition. Finally, the state decision directly guides the adaptive adjustment of the measurement covariance matrix in the extended Kalman filtering, thereby dynamically adjusting the weights of different sensors at the algorithm level. According to the closed-loop design from state perception to strategy decision and then to parameter self-adaption, positioning impact caused by GPS signal sudden change can be effectively restrained, smooth transition during signal recovery is achieved, and therefore it is guaranteed that a positioning result has high precision, high continuity and high accuracy under various working conditions.

The invention discloses a lightweight piston thermal-structure coupling stability gradient design method, and relates to the technical field of internal combustion engine pistons, and the lightweight piston thermal-structure coupling stability gradient design method comprises the following steps: constructing an asymmetric load adaptive gradient structure, establishing a multi-physical field coupling stability criterion system, and implementing an intelligent response type gradient design process; according to the method, the limitation of traditional symmetric design and static analysis is broken through by constructing an asymmetric load adaptive gradient structure, establishing a multi-physics coupling stability criterion and combining an intelligent response type closed-loop design process based on a convolutional neural network, and the stability of the multi-physics coupling stability criterion is improved by utilizing mechanisms such as negative Poisson's ratio dynamic softening, inertial mass tuned damping and cross-scale interface strengthening. And deformation energy homogenization and dynamic stiffness self-adaptive regulation and control are achieved, the problems of local-overall response mismatch and steady-state-dynamic model disjunction are solved, real-time feedback regulation is introduced for the first time, and the thermal-structural coupling stability of the lightweight piston under the asymmetric working condition is improved through structural function integration.

The invention discloses an intelligent voice outbound system capable of realizing automatic adjustment, and relates to the technical field of intelligent voice interaction, the system comprises a voice acquisition and preprocessing module, a voiceprint analysis and emotion recognition module, a dynamic verbal skill generation module, a verbal skill real-time optimization module and a voice synthesis and outbound module; the communication efficiency and personalized service are improved through a'generation-optimization-feedback 'closed-loop design, the system generates scene-fitting verbal skills according to customer emotions, historical records and demands, adjusts strategies according to instant feedback of customers, reduces invalid conversations, reduces customer conflicts, shortens the communication period, and meanwhile, improves the user experience. Voiceprint features are decomposed into four quantifiable dimensions, emotion is accurately recognized in combination with a combination rule, limitation of a single index is avoided, the dynamic verbal skill generation module is based on a generative adversarial network, high-quality verbal skill can be learned, the dynamic verbal skill generation module adapts to multiple scenes, customization cost is reduced, and intelligent outbound large-scale application is promoted.

The invention provides a live broadcast automobile marketing flow fluctuation prediction method and system, and relates to the technical field of cross-domain fusion, and the method comprises the steps: synchronously collecting data in a live broadcast platform and cross-domain extension data, and generating a platform data set and a cross-domain data set; based on the cross-domain data set, constructing an association space of the social hot events and the vehicle type attributes through a mirror image algorithm, and when the event feature intensity of the association space exceeds a preset threshold value, generating an event influence feature value; based on the event influence characteristic value and the platform data set, generating a basic flow prediction curve according to a fixed period and selecting a key point set; and processing the key point set through a convex hull algorithm to generate a convex polygon region. According to the invention, through constructing a full-link closed-loop design of data acquisition-event association-traffic prediction-parameter optimization-promotion triggering-verbal skill adjustment, accurate control of live broadcast automobile marketing traffic fluctuation and improvement of the marketing effect are realized.

The invention relates to the field of electronic competition and data processing, and discloses a competition dynamic priority grouping and intelligent arrangement system, which comprises an event twinborn body construction module used for aggregating multi-modal data in real time and constructing a competition panoramic digital mirror image; the dynamic narrative position potential field generation module is used for quantifying and modeling multi-dimensional narrative values of all potential games in the future, such as quick cold, perennial enemy and the like, on the basis of event twinborn body data; the intelligent arrangement decision-making module takes the competition state and the narrative position potential field as input, and outputs an optimal arrangement scheme by taking maximization of competition fairness, audience participation degree and narrative value as targets through a reinforcement learning algorithm; and the narrative intervention module is used for identifying narrative opportunity points by analyzing the potential field gradient and generating an executable operation strategy to actively improve the competition attraction. Through the closed-loop design of "intervention-feedback-enhancement", the system can be continuously self-optimized, and the ornamental value and commercial value of the competition are significantly improved.

The invention relates to the technical field of preparation and cyclic utilization of high polymer materials, in particular to a preparation method and application of a bio-based polyurethane material capable of being regenerated in a closed loop mode. And a novel polyurethane system with self-repairing, controllable degradation and efficient regeneration capabilities is constructed. Reversible crosslinking of the material is realized by utilizing the dynamic property of an acetal bond, a citric acid and malic acid buffer solution degradation strategy is combined, so that the waste material can be efficiently decomposed and monomers are recycled, and high-purity recycling of the regenerated prepolymer is realized by virtue of bipolar membrane electrodialysis and membrane separation technologies. The process not only solves the industrial problem that a traditional polyurethane material is difficult to recycle, but also remarkably reduces resource consumption and environmental pollution through closed-loop design, and is suitable for the fields of buildings, electronic packaging, medical equipment and the like with high requirements on sustainable materials.

The invention relates to the technical field of steel rust removal, in particular to a steel rust removal device for constructional engineering, which comprises a machining table, two symmetrical supporting plates are fixedly connected to the top end of the machining table, one of the two supporting plates is located at a feeding position, and the other supporting plate is located at a discharging position; the detection mechanism comprises a first connecting ring capable of moving back and forth, detection frames are symmetrically arranged on the inner wall of the first connecting ring in a staggered mode, electromagnetic plates are arranged in the detection frames, the other ends of the electromagnetic plates are fixedly connected with plastic springs, and the other ends of the plastic springs are fixedly connected with permanent magnet blocks. According to the device, through the closed-loop design of detection, analysis, adjustment and execution, rust layer thickness detection and grinding parameters (pressure and speed) are dynamically associated, automatic and precise rust removal is achieved, and meanwhile the operation quality and efficiency are further improved through the pretreatment mechanism, the environment optimization design and the stable conveying structure.

The invention discloses a large language model agent system and method and related equipment. The large language model agent system comprises an input analyzer module, a strategy generation module, an execution controller module, a task result evaluation module, an reflection module and a strategy rewriting module, and a self-adaptive optimization closed loop for task execution is formed through the reflection module and the strategy rewriting module. Wherein the reflection module can generate a report containing failure reasons, and the problem of failure diagnosis is solved; the strategy rewriting module optimizes a plan according to a report, adjusts tool calling, and realizes self-learning and strategy reconstruction; the closed-loop design forms a complete cognitive process, and an input analyzer guarantees the stability of prompt. According to the system, the task completion rate, the execution stability and the scene adaptability are remarkably improved, the robustness and the error tolerance in a multi-step complex task are particularly enhanced, and the key blank of an existing language model agent system in the aspects of self-reflection and self-optimization is filled.

The invention discloses a forestry ground multi-robot cooperative full-coverage path planning method and device based on a diffusion model, electronic equipment and a storage medium. The method comprises the following steps: constructing an enhanced environment model containing passing cost and reachability probability through multi-source sensor fusion; based on the model, generating a global path probability field with coherence and environmental adaptability by using a diffusion model; further realizing multi-robot self-adaptive task region division through a path flow field gradient; a local diffusion replanning mechanism is introduced for dynamic obstacles to carry out rapid path repair; and performing multi-objective optimization on the path in combination with a robot center Euclidean symbol distance field, and outputting an executable path meeting safety, smoothness and kinematics constraints. According to the method, through closed-loop design of perception, modeling, generation, division, re-planning and optimization, high-coverage, high-collaboration and high-robustness autonomous inspection of multiple robots in a complex forest region environment is realized, and reliable technical support is provided for smart forestry.

The present application provides a kind of spontaneous combustion coal gangue aggregate concrete and the bonding slip test method of reinforcing steel, belong to building material performance test technical field, method includes: S1.existing test piece parameter and material characteristic actual measurement;S2.test equipment debugging and parameter setting;S3.loading test and original data acquisition;S4.based on the bonding slip data processing of fusion algorithm;S5.test result verification and analysis.The present application realizes the scientific quantification of spontaneous combustion coal gangue aggregate concrete and reinforcing steel bonding slip characteristics by closed-loop design and precision control, provides strong support for engineering application.

The invention provides an electrode charging battery critical charging early warning method based on ultrasonic monitoring, and relates to the technical field of charging early warning. Comprising the following steps: acquiring the amplitude and propagation time of an echo signal in real time so as to reversely deduce the electrolyte concentration and polarization degree in a battery cell; performing cross verification according to the electrolyte concentration, the polarization degree and the SOC estimated value of the BMS, and correcting accumulated errors caused by temperature and aging; establishing a full power critical criterion according to the accurate SOC calibration value and the impedance change characteristics of the ultrasonic monitoring battery cell at the last stage of charging and discharging; according to the actual capacity attenuation data of the battery cell, the full-power critical criterion and the user driving working condition, calculating the remaining endurance demands under different working conditions, and adjusting a low electric quantity early warning threshold value; and when the real-time SOC of the battery cell is smaller than an early warning threshold value, triggering electrode charging safety early warning and pushing endurance to the vehicle-mounted terminal. According to the invention, through the full-link closed-loop design, accurate, dynamic and safe early warning guarantee is provided for the polar charging scene.

The invention provides a multi-mode collaborative freezing and fresh-keeping method and system based on aquatic product type identification, and the method comprises the steps: collecting multi-source data of aquatic products in a sealed fresh-keeping cabin, recognizing the types of the aquatic products based on a deep learning algorithm according to the multi-source data, and generating a fresh-keeping control strategy containing environmental parameters; and regulating and controlling environmental parameters in the sealed fresh-keeping cabin according to the fresh-keeping control strategy. The system is composed of a sealed fresh-keeping cabin, a multi-source sensing module, an intelligent control module and a multi-mode execution module, and all the modules work cooperatively to achieve full-process automation from data collection to environment regulation and control. According to the method, through the closed-loop design of multi-source data acquisition, intelligent identification and dynamic regulation and control, the precision and intelligence of the fresh-keeping process are realized. The fresh-keeping effect is remarkably improved, the control precision is optimized, the energy consumption is reduced, and the user experience is improved.

The invention relates to the technical field of transportation, in particular to a workpiece transportation circulation type production line for an assembly workshop and a circulation method. A return line body; the transfer part is arranged at the end parts of the station side line body and the return line body; the transfer part is used for transferring a jig between the station side line body and the return line body so as to form a production line capable of circulating the jig; the transfer part comprises a base plate; the first driving assembly and the second driving assembly are arranged on the base plate in parallel. By means of the closed-loop design of the station side line body, the transfer part, the return line body, the transfer part and the station side line body, jigs can be reused in a circulating mode, spare jigs do not need to be additionally reserved, and only the basic operation number needs to be maintained; the transfer part drives the first transfer assembly and the second transfer assembly to form two sets of independent transfer channels through the first drive assembly and the second drive assembly correspondingly, and the first transfer assembly and the second transfer assembly do not depend on each other and can work synchronously.

This invention discloses a method for designing transmembrane regulatory proteins based on cueing strategies and generative models, belonging to the field of bioinformatics. It includes a target survey stage and a closed-loop design stage. In the target survey stage, a generative diffusion model is used to generate virtual probes targeting the membrane protein. A set of complex conformations is obtained by combining sequence design and structure prediction models, and binding hotspot regions are identified based on the spatial distribution density of the probes, overcoming the dependence on manually specified binding sites. In the closed-loop design stage, based on the identified hotspot regions, an initial backbone is generated using a generative diffusion model. A structure cueing strategy guides the sequence design and structure prediction models to perform closed-loop iterative optimization, generating sequences that selectively bind to the transmembrane domains of membrane proteins and regulate their functions. This invention achieves automated, function-guided design of transmembrane regulatory proteins, effectively expanding the range of designable targets and significantly improving the stability and functional specificity of the designed products in the membrane environment.

The invention discloses a multi-area linkage fresh air handling unit cooperative control system and method, and relates to the technical field of building environment control, and the auxiliary method comprises the specific steps that a multi-source data real-time collection module collects and transmits multiple types of data through distributed equipment; the data fusion processing module cleans and fuses the data to form a structured data set; the intelligent scene analysis and game modeling module identifies scenes, evaluates requirements, detects conflicts and quantifies utility values; the control mode decision module determines an optimal mode and parameters; the execution regulation and control module adjusts parameters, executes operation and feeds back data to form a closed loop; a multi-source data acquisition fusion framework is constructed, traditional limitation is broken through, an intelligent module automatically recognizes scenes, quantifies requirements, detects conflicts and optimizes resource allocation, meanwhile, full-process automation is achieved through closed-loop design, control economy is ensured through an algorithm, airflow interaction is optimized, energy consumption is reduced, energy efficiency and comfort are improved, and the method is suitable for large-scale popularization and application. And technical support is provided for efficient operation of green buildings.

This invention discloses an apparatus for preparing high specific surface area calcium hydroxide, comprising a lime premixing tank and a digestion reactor. The lime premixing tank contains a ribbon agitator connected to a stirring motor at the top of the tank. Steam is conveyed to the premixing tank via a Venturi mixer I. A powder distributor and baffles within the reactor ensure uniform material distribution and gas-solid separation. A closed-loop tail gas treatment system is employed, with a sawtooth distributor and spiral nozzles in the scrubbing tower providing efficient dust removal. Purified wastewater is recycled to Venturi mixer II via a booster pump for reuse. Water is atomized and replenished in the reaction zone via spiral nozzle II to enhance the three-phase reaction. The product settles via baffles and is discharged under control by a rotary valve, then collected after cooling by a screw conveyor. This invention, through a closed-loop design of premixing-steam conveying-tail water reuse-separation, achieves continuous production and efficient resource utilization, significantly improving the specific surface area and production efficiency of calcium hydroxide.

This invention discloses a closed-loop system for the storage, transportation, and hydrolysis hydrogen supply of metallic fuels, belonging to the field of hydrogen energy storage and transportation technology. This invention aims to solve the problems of high cost, infrastructure dependence, and lack of recyclability in existing hydrogen storage technologies. The system includes: a porous metallic fuel preparation unit for preparing standardized porous metallic fuel flakes from metal powder; a hydrolysis hydrogen supply device for containing the fuel flakes and controllingly circulating water to carry out the hydrolysis reaction, generating hydrogen and metal hydroxide; a metal hydroxide recovery unit for collecting the metal hydroxide; and a metal regeneration unit for converting the metal hydroxide into metal powder for return, or for purification and sale, with new powder purchased as a replacement. The fuel flakes are stacked or wound, with micron-level gaps between the layers, and a catalyst is added to accelerate the reaction. Through system integration and closed-loop design, this invention achieves efficient recycling of metallic fuels, low storage and transportation costs, and completely eliminates dependence on hydrogen refueling stations and hydrogen pipelines, providing a new path for large-scale, low-cost, and cross-regional deployment of hydrogen energy.

The invention relates to the technical field of energy data processing and artificial intelligence, and particularly discloses an AI-based energy data multi-source heterogeneous fusion method, system and equipment, and the method comprises the steps: screening a historical fusion error case, and judging a coupling reconstruction cause; dividing quantitative change / working condition reconstruction coupling reconstruction; determining a distribution offset comprehensive index critical value of offset reconstruction; pre-training a working condition reconstruction exclusive AI fusion model; the current fusion adaptation is adapted in real time and differentiated, fusion errors caused by coupling reconstruction are accurately recognized through closed-loop design of error screening, reconstruction classification, critical value determination, model pre-training and real-time adaptation, and a differentiated AI strategy is adopted for offset and working condition reconstruction, so that the accuracy of fusion is improved. The problems that in the prior art, dynamic changes of the coupling relation cannot be coped with, the fusion precision is low, and the stability is poor are solved, the precision and robustness of energy data multi-source heterogeneous fusion are remarkably improved, and the method adapts to complex and changeable energy system working conditions.

The invention belongs to the technical field of grain processing, particularly relates to a continuous high-temperature processing grain deep processing technology and equipment thereof, and aims to overcome the defects of inaccurate temperature control, non-linkage synchronization of cooking and stir-frying operations, disjunction of grinding and purification links, process dispersion, insufficient equipment connection and the like in traditional grain processing. The process comprises the steps of grading screening, high-pressure spraying and cleaning, precise steam cooking, high stir-frying, multi-stage grinding and polishing, secondary purification and the like. The equipment comprises a special grading and screening device, a high-pressure spraying and cleaning device, a precise temperature control steam cooking device, a constant-temperature stir-frying device, a secondary grinding device, an airflow polishing device, a precise screening device, a CCD color sorting device and the like. Through the design of temperature gradient control, multi-stage grinding and polishing and a whole-process closed loop, the uniformity and taste of finished product particles can be improved, impurity residues can be reduced, the processing time can be shortened, the labor cost can be reduced, meanwhile, the multi-stage grinding and polishing machine can adapt to various cereal raw materials, and the technical problem of a traditional processing mode is solved.

The application relates to the technical field of blood protein detection, in particular to a blood protein detection kit for early diagnosis of new-onset diabetes and pancreatic cancer, which comprises a kit and test tubes, a water tank is arranged on the upper portion of the kit, a plurality of guide cylinders are arranged in the water tank, the top end of the guide cylinder is provided with a boss mounted on the top wall of the kit, the boss is in communication with the inside of the guide cylinder, and the outer surface of the test tube is provided with flexible spiral leaves and is inserted into the boss and the guide cylinder. Through five core advantages of accurate temperature control, efficient mixed coating, intelligent pollution washing, closed-loop gas path design and structure optimization, the stability, efficiency, precision and convenience of detection are comprehensively improved; the automatic design reduces human errors, the environment-friendly closed-loop design takes into account practicability and safety, and is suitable for the precise detection requirements of early diagnosis of diabetes and pancreatic cancer.

The application discloses a co-entropy ceramic protective coating sintering temperature and aerodynamic thermal load cooperative control system and relates to the technical field of sintering temperature control. The system comprises an information acquisition module: acquiring previous sintering information, wherein the previous sintering information comprises sintering temperature and performance results, and the performance results are the performance of aerodynamic thermal load. The application considers coating material and structure information and environmental information to formulate a reference directory under different basic information in the whole process, and the sintering temperature is regulated according to the aerodynamic thermal load of the coating material structure and environmental manufacturing demand, and then the density, interface bonding and residual stress distribution of the coating are realized through the controllable sintering temperature curve at the preparation end, so that the aerodynamic thermal load of the coating in use is ensured, the sintering temperature is designed and optimized, the response characteristics of the coating to the aerodynamic thermal load in use are within the user demand, and the closed-loop design of optimizing the response of the service end by controlling the manufacturing end is embodied.

The present application relates to the technical fields of semiconductor automation testing, in particular to a PMU and reference voltage source dual-function circuit based on ATE testing, comprising an AD5522 chip, a function switching module, a multi-DUT expansion module, a precision optimization module and a control module; the whole adopts single chip function multiplexing design, solves the pain point of large PCB space occupation, achieves the effect of significant space reduction, adopts single PMU multi-DUT expansion design, solves the pain point of high DUT test cost, achieves the effect of significant test cost reduction, adopts Kelvin four-wire and feedback closed loop design, solves the problem of low reference voltage precision, adopts relay switching and programming control design, solves the problem of poor function flexibility.

The invention discloses a rehabilitation walking assisting robot device and relates to the technical field of medical instruments, energy recovery and gait assisting of rehabilitation exoskeleton are achieved by means of pure mechanical closed-loop design of an energy processing assembly and a centrifugal control execution assembly, and the rehabilitation walking assisting robot device is different from a passive response type scheme of a traditional sensor, an electric control unit and a motor. Energy management and power-assisted control are more accurate, efficient and reliable; firstly, a coupling structure of the differential planet gear row and the double one-way clutches is utilized to achieve full capture of forward-swing and backward-swing two-way speed reduction kinetic energy of the swing leg, and in cooperation with the torque angle characteristics that a scroll type clockwork spring is steep in the initial stage and gentle in the later stage, energy can be effectively stored and recycled, the human body swing phase can be accurately matched, and the energy recovery effect is achieved. And then, the real-time speed change of the swinging leg is directly sensed through the centrifugal block, so that mechanical closed-loop control completely based on body sensing is formed, and the risks of delay, misjudgment, electromagnetic interference and crash of an electric control system are completely eradicated.

The invention relates to the technical field of body-equipped robots, in particular to a body-equipped intelligent mechanical arm handicapped assisting system and method.The method comprises the steps that electromyographic signals are collected in real time, electromyographic features are extracted, and the fatigue degree score and the future trend of a user are predicted through a layered deep learning model; based on the prediction result, establishing an adaptive compensation strategy, and dynamically amplifying the original control signal attenuated due to fatigue; continuously evaluating the signal-to-noise ratio and the stability of the compensated signal; if the effect is not good, triggering parameter fine tuning; and after the user state is recovered and the control performance reaches the standard, starting a progressive exit program, and smoothly cancelling compensation. According to the method, the complete closed-loop design of perception-prediction-compensation-evaluation is constructed, the accuracy and stability during control over the mechanical arm with the body are effectively improved, and the handicapped user can remarkably adapt to control over the mechanical arm with the body.

The invention discloses an intelligent driving camera calibration error analysis and calibration system based on a simulation system, and relates to the technical field of intelligent driving, the intelligent driving camera calibration error analysis and calibration system comprises six core modules, and a calibration parameter module stores and manages calibration parameters and associated information; the driving key point monitoring and triggering module collects multi-source data and marks an abnormal time window; the simulation module generates ideal pairing training data with deviation distortion; the AI neural network module is pre-trained and activated and then outputs a calibration change value, that is, the computing power is released; the hierarchical calibration decision and execution module judges a risk level and executes a corresponding calibration strategy; the cloud data module processes real vehicle data to optimize simulation parameters and an AI model. The system improves the calibration precision and reliability, reduces the resource consumption, guarantees the intelligent driving safety, and meets the full-life-cycle calibration demands through the closed-loop design of vehicle-end independent real-time calibration and cloud iterative optimization.