93results about How to "Achieve real-time" patented technology

The invention relates to the technical field of information management, in particular to a material digital management system and method based on a cloud platform. The method comprises the following steps: acquiring material data; distributing a material storage space by using the material data; receiving an operation message of the storage space, and pushing the operation message to an inventory database; creating a circulation record table and an inventory state table; using the operation message in the inventory database to update a circulation record table, and recording circulation data; automatically updating an inventory state table according to the circulation data so as to determine the material inventory capacity; when the material inventory capacity is lower than or equal to a preset safety inventory threshold value, management early warning information is generated; and when the material inventory capacity is higher than a preset safety inventory threshold value, updating the management safety field of the inventory state table. The material inventory is monitored in real time based on the information management technology, the replenishment information is intelligently generated, inventory dynamic management is achieved, and the material management efficiency is improved.

The present invention relates to the field of die-casting optimization technology, and discloses a die-casting process parameter optimization method and system based on digital twin. The method includes: arranging sensors to collect die-casting equipment operation parameters and die-casting part quality data in real time to form multi-source die-casting production data. According to the multi-source die-casting production data, establish a multi-physics field simulation model and construct a digital twin model. Compare the virtual prediction results with the measured quality data, and construct a virtual-real difference compensation network to correct the parameters of the digital twin model. Based on the compensated digital twin model, perform a multi-objective reinforcement learning method to generate the optimal die-casting process parameters. Apply the optimal die-casting process parameters to the die-casting equipment for verification, and update the virtual-real difference compensation network according to the verification results. This application realizes the intelligent optimization and continuous self-evolution of die-casting process parameters, and improves the casting forming accuracy, energy efficiency utilization rate and production stability.

This invention belongs to the field of conveying equipment technology, specifically disclosing a conveying device and method for egg supply, including a conveyor belt machine, a chamber, and a blower. The conveyor belt machine's external belt consists of three sets of circular tracks that wrap around the conveyor belt machine. The circular tracks have notches spaced evenly along their circular paths. The chamber is fixedly installed above the conveyor belt machine and near its center. A ventilation component is installed above the chamber. A U-shaped frame is fixedly mounted above the conveyor belt machine and below the ventilation component. A crack visual detection marking component is installed above the U-shaped frame and corresponding to each circular track. This invention integrates wiping, flipping, drying, visual detection, and marking functions, enabling online identification and marking of cracked eggs produced after cleaning. This effectively prevents cracked eggs from being mixed with qualified products, significantly improving the overall quality and automation level of egg supply.

The application discloses an emotion recognition method based on online cross-modal knowledge distillation, comprising the following steps: acquiring electroencephalogram and electrocardiogram original signals and windowing and cutting; constructing electroencephalogram and electrocardiogram student models, extracting intermediate features from each modal data segment through an encoder, and obtaining non-normalized prediction output through a classifier; constructing a teacher probability distribution through a joint encoder fusion; introducing adaptive contrast loss to align the cross-modal intermediate features, introducing distillation loss to constrain the prediction probability distribution of each modal to align with the teacher probability distribution; synchronously optimizing new student model parameters through online collaborative training; and performing actual inference prediction based on the student model after training. The application combines double modal signals to make up for the defects of single modal information, excavates the complementarity of modes, realizes dynamic generation of teacher supervision signals and real-time collaborative learning of modes through online distillation, does not increase test calculation overhead, effectively improves the recognition accuracy, model robustness and generalization ability, and has good application prospect.

This invention relates to the field of industrial Internet of Things (IoT) technology, and more particularly to an interactive system for tracking and providing feedback on maintenance strategies and tasks. The system includes a data hub and fusion module, a health assessment and early warning module, a maintenance strategy intelligent generation module, a task tracking and execution feedback module, a feedback optimization and knowledge base module, and a visualization push module. By constructing a multi-module collaborative intelligent maintenance platform, this invention achieves closed-loop management of the entire process, including equipment status monitoring, health assessment, maintenance decision-making, task execution, and knowledge optimization. It solves the problems of traditional systems relying on fixed rules and lacking continuous improvement; it also addresses the issues of low information transmission efficiency and insufficient decision support, ultimately achieving comprehensive optimization of equipment reliability, maintenance costs, and operational management efficiency.

The application discloses a kind of for the method, device, equipment and medium of tab abnormality detection in battery cell production process, comprising: the tab area image collected in battery cell production process is segmented to generate tab mask;Based on the tab mask extraction multi-scale pixel-level feature vector, and the multi-scale pixel-level feature vector is input into unsupervised probability GMM model to identify pixel-level abnormal point;The pixel-level abnormal point is analyzed to obtain candidate abnormal area, and the parameter index of the candidate abnormal area is obtained;Determine whether the parameter index meets the set tab abnormality judgment rule, if meet, it is judged as tab abnormality, and tab abnormality result is output.Therefore, the application can be widely applied to the detection of tab folding, crease, fracture, misplacement and other abnormalities on battery cell production line.

This invention discloses an intelligent exercise assessment and early warning system based on multi-source biosignal fusion, belonging to the field of exercise risk early warning technology. It collects multi-source data, including electromyography (EMG), heart rate, blood oxygen, skin conductance, and acceleration, from various wearable sensors to assess muscle fatigue, cardiovascular load, exercise status, and environmental factors. After preprocessing, the system uses quantitative models such as the muscle fatigue correction index and the cardiovascular load dynamic coefficient to calculate a comprehensive exercise risk early warning index by integrating physiological state and environmental factors. This results in a normalized risk classification, corresponding to low, medium, and high risk levels and marked with different color icons. This system overcomes the limitations of single signals, considering the synergistic effects of multi-dimensional physiological indicators and the influence of environmental factors, improving the accuracy of assessment in complex scenarios. It can effectively intervene before risks develop and is suitable for scenarios such as mass fitness and professional training. It is integrated into lightweight wearable devices without interfering with the exercise process.

The application relates to the technical field of welding equipment, and discloses a self-walking welding robot, a control method and system thereof, and a storage medium, wherein the control method of the self-walking welding robot comprises the following steps: a data acquisition board acquires a welding data set in a welding process, the welding data set comprises at least two types of welding data, and the welding data set is transmitted to a touch control device through a preset communication protocol; the touch control device displays different types of welding data in corresponding display areas, receives operation instructions input by a user through the display areas, and sends the operation instructions to a PLC controller; and the PLC controller generates corresponding control signals according to the operation instructions, and controls the self-walking welding robot to perform corresponding welding actions and / or walking actions. The centralized control and man-machine interaction of various function modules of the welding robot are realized, so that the system response speed, operation intuitiveness and controllability of the welding process are improved.

This invention discloses a method for calculating the structural strength of a fiberglass tower, comprising the following steps: acquiring real-time sensor data and static design parameters of the fiberglass tower; constructing a structural digital twin model synchronously mapped to the physical entity of the fiberglass tower based on the real-time sensor data and static design parameters; injecting the real-time sensor data as boundary conditions into the digital twin model; driving the digital twin model to perform structural strength evolution analysis under multiple working conditions; and calculating the dynamic safety factor of the fiberglass tower based on the structural failure boundary and real-time sensor data. This invention also discloses a structural strength calculation system, comprising: a data acquisition module, a digital twin model construction module, a digital twin engine module, a safety assessment module, and a human-computer interaction module. This invention achieves real-time and accurate assessment of the structural strength of fiberglass towers by constructing a digital twin model, solving the technical problem that traditional calculation methods cannot dynamically reflect the structural performance degradation process.

This invention provides a three-trailer collaborative aircraft transfer method and system based on multi-sensor fusion. This invention relates to the field of aircraft ground support technology, specifically to a three-trailer collaborative aircraft transfer method based on multi-sensor fusion, applicable to short-haul aircraft ground transport to hangars. Through multi-sensor data fusion and multi-trailer collaborative control, it improves transfer accuracy, safety, and efficiency. The method specifically includes the following steps: system setup and sensor calibration; trailer attitude initialization and collaborative parameter configuration; real-time acquisition and preprocessing of multi-sensor data; multi-sensor data fusion and state estimation; dynamic path planning based on fused data; attitude error quantification and calibration based on complex statistics; multi-trailer collaborative driving control and traction distribution; real-time environmental monitoring and risk warning; precise docking at the hangar entrance and attitude fine-tuning; and parking and system review and optimization.

This invention provides a stacker crane for aisle storage, including a traveling base beam and a stacking device on the traveling base beam. A buffer device is also provided on the traveling base beam, and an adjustment device is installed at the outer end of the buffer device. The buffer device includes a buffer frame on the traveling base beam, with multiple sets of buffer crossbeams fixedly connected to both sides of the buffer frame, defining multiple buffer levels distributed vertically within the buffer frame. Buffer plates are fixedly connected to the multiple sets of buffer crossbeams, and multiple sets of goods are placed on the buffer plates. A conveying component is provided on the buffer plates, and scanning components are provided on the multiple sets of buffer crossbeams. A contact component is provided at one end of each set of buffer crossbeams. This invention improves storage and retrieval efficiency through multi-level buffering and path optimization, achieves real-time monitoring and automatic correction of goods status through intelligent scanning and pressure sensing fusion, and completes high-precision automatic docking based on laser ranging and electromechanical linkage. Ultimately, it constructs a highly efficient, reliable, and fully automated intelligent warehousing and stacking system.

A method for planning an autonomous landing safe trajectory suitable for UAV inspection is proposed. After the UAV takes off, it acquires the current pose of the UAV, the point cloud map information of the surrounding environment, and the spatial orientation of the target point. By establishing the spatial transformation relationship between the camera coordinate system and the body coordinate system, the orientation vector relative to the ground target is calculated, and the target point is generated within the radar-sensible area. Based on the generated target point, an optimization function that minimizes the fourth derivative is constructed based on multiple high-order polynomials to generate a smooth trajectory with continuous position, velocity, and acceleration. The initial trajectory is transformed into a B-spline curve, and local trajectory segments with collision risk are optimized. A segmented penalty mechanism is designed based on the boundary threshold to guide the trajectory away from the boundary area. The time span is adjusted by calculating the trajectory derivative over-limit ratio, and a trajectory similarity cost function is introduced to ensure that the final optimized trajectory maintains the original geometric structure, thereby achieving trajectory control optimization and safe landing of the UAV.

A multifunctional waterproof board steel reinforcement trolley, the controller, the fire water tank, the water pump, the camera, the working face range finder, the second lining range finder, the inverted arch range finder bolted and fixed on the waterproof board steel reinforcement trolley; the water pump, the longitudinal pipeline are connected through the pipeline connection; the automatic drooping fire nozzle, the automatic ordinary fire nozzle are connected with the longitudinal pipeline; the second lining range board is bolted on the front end of the second lining concrete trolley, and the inverted arch range board is bolted on the side of the trestle girder. Through the recognition of the fire, the fire nozzle is controlled to extinguish the fire in the first time, the safety of the place where the tunnel is most prone to fire is realized; through the real-time measurement of the laser range finder, the relative distance between the working face and the inverted arch and the second lining concrete is calculated, the automatic and real-time measurement of the safety step and the early warning are realized, and the safety of the tunnel construction is ensured through the related functions and methods of the multifunctional waterproof board steel reinforcement trolley.

The invention discloses an industrial control system anomaly detection method based on digital twinborn and reinforcement learning, and aims to solve the problems that in the prior art, abnormal samples are scarce, the false alarm rate is high under a dynamic working condition, and the generalization ability of a single detection model is insufficient. Generating synthetic data by simulating anomalies in the twinborn body, and mixing the synthetic data with normal data to form a training set after space-time and distribution alignment; based on the real-time data, generating a time sequence prediction residual error, a distribution reconstruction error and classification confidence multi-source evidence in parallel; constructing a reinforcement learning environment, constructing a state through multi-source evidence and the like, and guiding an agent to learn a fusion strategy through an asymmetric reward function; and training the intelligent agent to obtain a detection model and performing online deployment. According to the method, the multi-source evidence is adaptively fused through the reinforcement learning agent, so that the robustness, the accuracy and the adaptive capability of anomaly detection under the dynamic working condition are remarkably improved, and missing report and false report are effectively reduced.

This invention relates to the field of artificial intelligence technology, specifically to a personalized, in-depth cultural tourism planning system and method based on a large-scale artificial intelligence model. It includes a multi-source data fusion unit for constructing a dynamic cultural tourism knowledge graph; the experience nodes of the dynamic cultural tourism knowledge graph include hidden experience nodes obtained through data mining; a user intent understanding unit generates multi-dimensional user profile vectors; an intelligent planning and optimization unit generates personalized spatiotemporal travel plans, personal baggage preparation suggestions, global optimization of resource allocation, and dynamic personalized guidelines based on the dynamic cultural tourism knowledge graph and multi-dimensional user profile vectors; and a closed-loop feedback and evolution unit collects feedback data to update user profiles and optimize planning decisions. This system achieves automated mining and real-time fusion of multi-source unstructured data, thereby generating personalized plans that not only conform to users' deep cultural interests but are also highly feasible under actual spatiotemporal and resource constraints.

The application discloses a CNN-LSTM-based phase calibration method for mode division multiplexing optical fiber communication and belongs to the technical field of optical fiber communication. By constructing a double-input CNN-LSTM hybrid neural network architecture, MIMO input signals and original target signals of mode division multiplexing optical fiber communication are acquired, data preprocessing is carried out, the spatial feature extraction capability of a convolutional neural network and the time series modeling capability of a long short-term memory network are combined, effective compensation of phase noise in long-distance strong coupling mode division multiplexing optical fiber communication is realized, complex MIMO signals are separated into real and imaginary parts and sliding window training samples are generated, and a double-branch network containing an image input layer, a convolutional layer, an LSTM layer, a deep connection layer and a self-defined phase calibration layer is constructed. The problems that the phase noise compensation capability of a traditional algorithm is limited and the convergence performance is poor under a strong coupling condition are effectively solved, and the equalization performance and transmission quality of a mode division multiplexing optical fiber communication system are significantly improved.

The application discloses a kind of underwater acoustic open architecture under underwater acoustic component dynamic configuration management method, belong to underwater acoustic system technical field, comprising: establishing underwater acoustic component warehouse, for carrying out full life cycle tracking management to underwater acoustic component;Establish dynamic access control model, based on component identifier and version number, underwater acoustic component is divided into different security levels and operation categories, and the permission rule of each underwater acoustic component instance is configured dynamically adjustable;When receiving the operation request for target underwater acoustic component, the permission check of the operation request is carried out through dynamic access control model;When executing the operation to any underwater acoustic component, operation log is recorded in real time;When monitoring that the version of currently deployed underwater acoustic component causes system exception, automatically trigger rollback operation.The application can automatically trigger rollback operation when monitoring component defect, quickly restore system to previous stable state, significantly improve the robustness and service continuity of underwater acoustic system.

This invention relates to the field of unmanned aerial vehicle (UAV) technology, specifically to a UAV servo flap system, a UAV wing, and the UAV itself. The system includes a flap actuator, an inertial measurement module, an airspeed detection module, and an onboard control module. The onboard control module fuses inertial data and airspeed data in real time through a data fusion unit, employing a composite filtering architecture combining a Kalman filter and a complementary filter. A dynamic flap angle calculation unit, based on an aerodynamic model and flight state parameters, uses a gradient descent method to optimize and solve for the optimal flap deflection angle. An error compensation unit corrects inertial measurement errors and the effects of structural elastic deformation online, thereby achieving accurate perception and real-time estimation of flight state, improving flap control accuracy and response speed, and enhancing the reliability of the UAV under complex flight conditions.

This invention relates to the field of fire-fighting equipment technology and provides an automatic buckle device for fire hoses, including a fire hydrant, a control display, a sealed box, a drive system, an automatic buckle connector, a fire hose fastener, a magnetic positioning sleeve, a transmission rod one, a transmission rod two, and a threaded rod. The gear plate and the dynamic axial locking buckle in the automatic buckle connector are fixedly mounted on the surface of the hose body. The transmission rod two is connected to the gear plate. The inner wall of the magnetic positioning sleeve has a positioning groove, and a pressure sensor is embedded at the bottom of the positioning groove. A magnetic core one is embedded at the end of the magnetic positioning sleeve opposite to the automatic buckle connector. A positioning key is provided on the surface of the fire hose fastener, which can be inserted into the positioning groove. A static axial locking buckle is fixedly mounted on the inner wall of the fire hose fastener. There are three sets of both the dynamic and static axial locking buckles, symmetrically distributed about the center of the magnetic positioning sleeve, achieving real-time feedback and automatic adjustment of the connection status.

This invention relates to a method and system for accessing the trusted space of inland waterway shipping data under zero-trust conditions. It includes defining the shipping trust status and transformation rules of participating entities, constructing a risk scoring model to calculate the risk score of shipping behavior, introducing federated learning to improve the accuracy of the shipping behavior risk score, constructing a trust calculation function to calculate dynamic trust values ​​in real time, designing hierarchical access decision rules for hierarchical authorization to achieve access control, and submitting the hash value of logs to the blockchain to drive the update of shipping trust status, forming a closed loop of credit update and access control. This invention provides a systematic solution for the Jianghuai inland waterway shipping industry that balances strict security, business efficiency, and compliance requirements, achieving the coordinated evolution and proactive improvement of the security defense capabilities of the entire Jianghuai inland waterway shipping ecosystem.

The utility model proposes a kind of thermostat for chemical reagent experiment, including support load plate, the upper surface of support load plate is fixedly installed with temperature control seat, the inside of temperature control seat is equipped with support cover, the upper surface of support cover is opened with multiple placing holes, the inside of temperature control seat is opened with cavity, the inner bottom wall of cavity is fixedly installed with multiple temperature sensors, the bottom surface of temperature control seat is fixedly embedded with refrigeration guide plate, the bottom surface of refrigeration guide plate is fixedly installed with semiconductor refrigeration sheet, it is related to chemical reagent experiment field.The utility model is by the cavity of temperature control seat inside setting, can inject water liquid, utilize the good heat conductivity of water, can make the heat generated by annular electric heating wire evenly conduct to reagent, avoid local overheating, in addition by the cooperation of semiconductor refrigeration sheet and refrigeration guide plate, water liquid can be cooled directly, the problem that it is difficult to cool quickly after heating is solved, and then guarantee the experimental effect of chemical reagent.

This invention relates to an integrated testing platform and method for water pumps and oil pumps. The testing platform comprises a drive system, a media supply system, a measurement system, a temperature control system, a control system, and a data management platform. The drive system includes an interconnected power control cabinet and pump motors. The media supply system includes a water pump, an oil pump, a water tank, and an oil tank. The measurement system includes inlet and outlet pressure gauges, flow meters, pressure transmitters, and temperature transmitters installed on the pump's test circuit. The temperature control system includes heat exchangers, cooling pipes, and cooling coils in the oil and water tanks. The control system includes pump start / stop switches and valves. The data management platform includes an interconnected industrial computer and a data processing platform. This invention improves system integration; by switching valves, simultaneous testing of the water pump, oil pump, and water / oil pump can be achieved, further reducing the overall space occupancy. Simultaneously, the water pump circuit serves as a cooling circuit for the oil pump media, further improving testing efficiency.

This invention belongs to the field of pulmonary rehabilitation training assessment technology, specifically involving a method for postoperative pulmonary rehabilitation training assessment and guidance guided by ultrasound in the lung and diaphragm system. By comparing postoperative parameters with baseline datasets, this invention can identify areas of diaphragmatic movement disorder and abnormal lung ventilation, overcoming the limitations of traditional assessment methods that rely solely on single indicators or subjective symptoms. Based on a sliding window mechanism, it calculates deviations in movement and ventilation parameters and matches them with standardized training parameters, initially establishing a correlation between the training program and the patient's degree of functional impairment. Furthermore, by collecting the patient's adaptation parameters under free training to generate sensitivity coefficients, the standardized training parameters are dynamically corrected until the patient reaches a stable adaptation state. This fully considers individual patient differences and real-time physiological feedback, transforming the training program from standardized to personalized, and achieving real-time quantitative monitoring and guidance of both the diaphragm and lung tissue.

This invention provides a system and method for monitoring intentional misbehavior based on electroencephalogram (EEG) signals. The system includes an EEG acquisition device, an EEG signal processing and classification component, a response device, and a data storage unit. The EEG signal processing and classification component analyzes the frequency and time domain characteristics of the subject's EEG signals, assesses the subject's perceived benefit, cognitive state, and emotional fluctuations, and delivers the processed data to the response device and data storage unit. It integrates a Conv1d & Dilated Convolution deep learning module, fusing 1D convolution and dilated convolution to improve detection accuracy. This invention applies the perceived benefit test method to intentional misbehavior monitoring, improving prediction accuracy and introducing an instant feedback mechanism to achieve real-time early warning and intervention for intentional misbehavior, reducing operational risks and ensuring the accuracy and reliability of the acquired EEG signals and intentional misbehavior data, providing a solid foundation for monitoring.

This invention relates to a real-time detection method for encryption hijacking on Linux platforms based on multi-dimensional behavioral characteristics. This method relies on a closed-loop governance system formed by the collaborative analysis and processing module and the decision output module. The triggering logic of the three-layer cascaded analysis is as follows: the resource monitoring layer performs real-time monitoring and initial anomaly screening of system-level hardware resource indicators, outputting system-level risk status identifiers; when any monitoring indicator is abnormal, the behavior analysis layer is activated; the behavior analysis layer collects and analyzes process-level behavioral characteristics, outputting a list of suspicious processes and their risk scores; when the process risk score exceeds a set threshold, the essence detection layer is triggered; the essence detection layer performs encryption hijacking essence behavior verification on suspicious processes, completing the final decision. The main objective of this invention is to eliminate reliance on variable features and instead construct a detection mechanism that is difficult to circumvent, has a low false alarm rate, and can respond in real time based on the core essence behavior of encryption hijacking.

This application relates to the field of microfluidic biosensing technology, and discloses a data acquisition and control system based on organ-on-a-chip microfluidics. The system includes a rhythm-locked loop module, a phase-controlled acquisition module, an impedance detection module, a data compensation module, and a closed-loop control module. The system generates a phase-locked clock by analyzing the pulse rhythm of the microfluidic pump drive current and chamber pressure timing data and aligning it with time-domain phase-locking. During the steady-state window of the laminar flow, it performs phase-controlled synchronous acquisition of the sensor array to obtain the raw biochemical dataset. During the low-level interval of the clock, it performs electrochemical impedance spectroscopy to obtain a fouling compensation factor. Based on this factor, it compensates and calibrates the data of each modality to obtain a biological phenotypic feature matrix, which is then input into a model predictive controller to achieve adaptive microfluidic closed-loop control. This application effectively improves the signal-to-noise ratio of data acquisition and the robustness of microenvironment control during long-term operation of organ-on-a-chip systems.

The utility model discloses a kind of multi-view camera layout structures for sweeper.The structure includes the close-range monitoring camera of being arranged in multiple parts of vehicle body, lateral monitoring camera, traffic light recognition camera and remote driving camera, various cameras are installed with preset angle on vehicle body and form cross field of view area, and construct multi-angle perception network covering vehicle body periphery.The recognition of traffic signal lamp of different distance is realized by traffic light camera distribution in right front side of vehicle head, and remote camera is respectively arranged in vehicle head, tail and left and right side, and provide multi-directional picture when remote driving.Various cameras are summarized to data processing module after the image data collected by it, and unified analysis is carried out, and output to control system for automatic driving and cleaning operation control.The structure design is scientific, installation is convenient, and the environmental perception ability and operation intelligent level of sweeper can be effectively improved, and it is suitable for large-scale sweeper with unmanned driving function.

A 3D digital transfer management cloud platform, management method, equipment, and medium include: a project management module for creating new projects and using a directory template to allocate project data uploaded by each participant at each stage to the corresponding directory structure; a deliverables transfer module for performing data quality review and optimization processing on the digital deliverables to be transferred selected in the project management module, and transferring the reviewed and optimized digital deliverables to the digital asset management module; a digital asset management module for receiving digital deliverables from the deliverables transfer module, performing asset coding, classification, and attribute information entry, and storing them in a 3D design general model library; and a data display module for obtaining the transferred models from the digital asset management module, performing 3D model browsing, and model-image linkage. The deliverables transfer module of this application supports data transfer, quality review, and optimization processing to ensure the accuracy, completeness, and usability of the transferred data.