36results about How to "Real-time capture" patented technology

The invention discloses a fiber bragg grating strain measurement method and system based on deep learning, designs a double-grating structure and a deep learning analysis module, and separates temperature and strain components in grating wavelengths in real time. The system comprises a fiber grating sensor module, a data acquisition module, a deep learning analysis module and a display module, high-precision separation and real-time compensation of strain and temperature are realized through high-precision data acquisition and deep learning model processing, and the system is widely applied to the field of health monitoring of engineering structures such as bridges and tunnels.

The invention relates to an identification method, in particular to a photovoltaic panel dust deposition detection and pollutant identification method based on an unmanned aerial vehicle-mounted hyperspectrum. The method comprises the following steps: collecting spectral data; preprocessing the spectral data; extracting effective spectral features; change detection; judging whether pollutants exist or not; carrying out pollutant comparison; and evaluating ash deposition and giving an alarm. According to the invention, through combination of hyperspectral imaging and spectral variation analysis, automatic and non-contact monitoring of the accumulated dust and pollutants on the photovoltaic panel is realized, and tiny spectral change on the surface of the photovoltaic panel can be captured in real time and with high precision, so that the degree and the type of the accumulated dust and pollutants are accurately detected, the detection precision and the real-time performance are improved, and the detection efficiency is improved. And the maintenance cost is effectively reduced, unnecessary cleaning operation is avoided, and maintenance suggestions can be provided in time according to the detection result, so that the energy conversion efficiency of the photovoltaic panel is further improved.

The invention discloses an interaction method, an interaction system, computing equipment and a computer readable storage medium. The interaction method comprises the following steps: acquiring first question information; and generating and / or outputting interaction information corresponding to the first problem information according to a response strategy corresponding to a target service scene when the target service scene corresponding to the first problem information is identified to be different from the current service scene through the AIGC large model. According to the invention, whether the obtained problem information updates or changes the current service scene can be conveniently and accurately judged through the AIGC large model, and when the current service scene is updated or changed, the user intention corresponding to the problem information can be accurately understood according to the service processing logic corresponding to the updated or changed target service scene, so that the user experience is improved. And outputting the corresponding interaction information so as to execute the business event corresponding to the target business scene, thereby meeting the actual demand of the user. The user intention understanding ability can be improved in the interaction service, and the user experience is improved.

The invention discloses a machine tool digital twin health monitoring system and method, and relates to the technical field of machine tool monitoring. The machine tool digital twin health monitoring system comprises a sensor module, a data collection module, a model construction module, a fault injection module, a fault evaluation module and an output module. The invention further discloses a machine tool digital twinning health monitoring method, accurate fault diagnosis can be achieved under the condition of insufficient data by means of interpretability and visualization of the digital twinning model, analysis such as fault positioning, fault quantification and fault traceability is carried out, and the machine tool digital twinning health monitoring method is high in practicability. A numerical control machine tool digital twinborn model, real-time sensing monitoring data and a related machine learning algorithm are integrated, online and real-time fault diagnosis of the numerical control machine tool is realized, the starting rate and the working efficiency of the numerical control machine tool are improved, and the monitoring maintenance and repair cost is reduced.

The invention discloses a man-machine collaborative public opinion monitoring method and system based on reinforcement learning. The system comprises a allusion, television and harmonic reference analysis module, a public opinion data processing module, a model recognition module, a public opinion risk assessment module, a public opinion propagation analysis module, a learning optimization module and a deployment configuration module. The public opinion data processing module is used for collecting, cleaning, sorting, storing and preprocessing public opinion related data; the public opinion data storage module is used for managing and storing a large amount of public opinion data; through a reinforcement learning algorithm, the model can adapt to different public opinion environments, through repeated annotation and feedback of public opinions identification experts, the expert ability is solidified, dependence on manual annotation of the experts is reduced, through continuous iterative optimization, the model performance can be continuously improved, the model adapts to changes of the public opinion environments, and the method is suitable for popularization and application. Modern technical means such as deep pre-training, reinforcement learning and reward models are adopted, and innovation and breakthrough of the public opinion monitoring technology are achieved.

The invention relates to the technical field of rock-soil and deep underground space engineering monitoring, in particular to an in-situ engineering rock mass information advanced sensing system which comprises a sensing pipe which is of a tubular structure and used for stretching into a hole to sense and monitor the hole. The sensing pipe comprises a power excitation mechanism, an in-situ echo elastic wave acquisition mechanism, an autonomous walking mechanism and a visual sensing mechanism; the power excitation mechanism comprises a first driving unit and an excitation unit, and when the excitation unit abuts against the inner wall of the hole, the excitation unit can knock the inner wall of the hole and is used for providing an impact signal with adjustable power for the inner wall of the hole; according to the invention, sound waves generated by the power excitation mechanism are utilized to test and analyze rock and soil materials, so that the problems that the existing device is single in test index and cannot comprehensively monitor and evaluate internal information of a rock mass are solved.

The invention relates to the field of unmanned aerial vehicle identification, and provides an unmanned aerial vehicle identification method based on a YOLO v10-DID model, the YOLO v10-DID model in the method is established based on a YOLO v10 target detection model, the YOLO v10-DID model comprises an OFIE module, an MFF module and a DT module, the OFIE module is introduced to carry out optical flow estimation, motion information (optical flow information) between each pair of continuous frames in an image frame sequence can be effectively captured, and the motion information can be accurately identified. Gaussian filtering smoothing processing is carried out on optical flow information, the influence of noise motion information on a detection result can be reduced, target motion information and visual information are fused through an attention channel fusion module, the complementary advantages of the target motion information and the visual information are played, comprehensive and deep feature extraction of the unmanned aerial vehicle target is realized, and the detection accuracy is improved. And the detection precision and robustness of the YOLO v10 model on the moving unmanned aerial vehicle target are obviously improved.

The invention discloses a double-cold-trap operation monitoring method, a double-cold-trap control system, a medium and a product, and relates to electric digital data processing.The method comprises the steps that first cold trap temperature and humidity data, first condensate water cumulant, second cold trap temperature and humidity data and second condensate water cumulant are obtained; determining a first cold trap dehumidification efficiency, a second cold trap dehumidification efficiency, a first temperature gradient, a second temperature gradient and a condensate water cumulant change rate; determining a first operation defect of the first cold trap and / or a second operation defect of the second cold trap according to a preset parameter standard value; and based on the first operation defect of the first cold trap and / or the second operation defect of the second cold trap, searching a double-cold-trap processing scheme of which the relevancy is higher than a preset relevancy threshold in a preset operation defect processing scheme database. By implementing the method, the accuracy of double-cold-trap operation monitoring can be improved.

A material arranging device is fixed to a workbench and arranged at the output end of a conveying part and comprises a channel assembly, a sorting sensor set and at least one distribution mechanism, and the channel assembly is communicated with the conveying part and extends in the advancing direction of workpieces; the distribution mechanism is fixed above the transmission part and is movably arranged relative to the transmission part; the conveyed workpieces are divided through the channel assembly arranged at the output end of the conveying part, so that the requirement that the multiple overturning parts work at the same time is met; by means of the distributing mechanism arranged above the conveying part, the workpieces in the conveying process can be distributed, then conveying channels and parallel conveying of the multiple workpieces are achieved, parallel operation of multiple operation procedures is achieved, and the efficiency of the machining equipment is remarkably improved.

The present invention discloses a paper folding control method and system based on machine vision, which relate to the technical field of paper product processing. The method comprises: collecting and preprocessing paper towel data to obtain preprocessed paper towel image data; constructing a paper towel feature extraction model to obtain paper towel image features; calculating paper towel geometric features according to the preprocessed paper towel image data, and checking whether there is a deviation in the paper towel rotation angle; if there is a deviation in the paper towel rotation angle, calculating the deviation angle, and outputting a PID rotation adjustment parameter to a PID control system to correct the deviation angle; constructing a crease position detection model to calculate the crease position, and comparing it with the expected crease position to check whether there is a crease deviation; if there is a crease deviation, correcting the crease deviation through a PID control system; the present invention aims to solve the problem of poor folding effect caused by inaccurate control of the steering angle and crease position in traditional paper towel folding methods.

The present invention provides a DRAM test machine and method based on embedded logic analysis. An embedded logic analyzer is integrated in an ATE test control chip. The embedded logic analyzer is integrated in an ATE test control chip having a main control unit, a test vector generator, and a test result processor. The defects in the prior art are overcome, and the signals of the DRAM chip can be captured and analyzed in real time, so as to help test engineers quickly find problems and improve test efficiency. A plurality of signal channels can be monitored at the same time, so as to improve in-depth analysis capability, and specific trigger conditions can be set to capture key data. The complex timing behaviors of various DRAMs can be decoded and analyzed, so as to save test time. The machine is compactly integrated, does not occupy additional space, reduces costs, and improves benefits. The machine can quickly provide test results and feedback, and is helpful to shorten the test time of the DRAM chip and accelerate the test progress.

The invention provides an online fault early warning method and system based on fluid dynamics of a storage tank floating disc and spectral analysis of a sealing device of the storage tank floating disc, and the method comprises the steps: collecting structure parameters and operation parameters of the storage tank floating disc, and calculating fluid dynamics parameters for the quantitative evaluation of an inclination state, a buoyancy state and a friction state of the storage tank floating disc; collecting a plurality of vibration time domain signals of the sealing device on the floating disc, and converting the vibration time domain signals into frequency domain signals to obtain a frequency spectrum curve; constructing a frequency spectrum feature library based on the frequency spectrum curves in different operation states, comparing the actually monitored frequency spectrum curves with the frequency spectrum feature library, and identifying differentiated frequency spectrum features and corresponding fault types; and performing comprehensive evaluation by combining a quantitative evaluation result of the hydrodynamic parameters and a spectral analysis identification result, thereby realizing intelligent fault early warning of the storage tank floating tray system. The method solves the technical problems that the existing storage tank floating disc operation state monitoring cannot accurately find the early-stage potential fault hidden danger of the floating disc in real time, and floating disc faults and even safety accidents are easily caused.

The present application relates to the technical field related to optical deformation measurement equipment, and discloses a freely expandable fiber Bragg grating strain sensor. In order to solve the problem that the sensor is not easy to place in the deep hole area, two freely movable detection gear row arms are arranged on the mounting frame. When the deep hole needs to be inspected, it is only necessary to fix the mounting frame, and then use the two detection gear row arms to extend into the hole and support it. Since the length of the detection gear row arms can be adjusted according to the use requirements, it is possible to detect in the deep hole. After the detection gear row arms are supported on the part to be tested in the hole, the strain detection plate is fixed between the limit seats reserved to the outside of the hole. When the part to be tested is deformed, the deformation is transmitted to the strain detection plate outside the hole by using the detection gear row arms. The fiber Bragg grating sensor in the strain detection plate reflects the strain size and outputs it to the control end, and finally achieves the effect of expansion in the hole of the detection fixture and detection outside the hole.

The invention belongs to the technical field of biomedical experimental equipment, and discloses a real-time monitoring isolator for studying influence of microorganisms on host behaviors based on sterile mice, which comprises a mobile operation table, a support, a soft transparent isolator and a hard transparent glass isolator are arranged on the mobile operation table, the soft transparent isolator is communicated with the hard transparent glass isolator, and the support is provided with a plurality of through holes; partition plates are arranged in the hard transparent glass isolator so as to divide the internal space into a plurality of experiment areas. An infrared camera and a sound recognition sensor are mounted on the bracket and are used for monitoring multi-dimensional behaviors such as movement tracks, social interaction and sound characteristics of sterile mice in an experimental area in real time; and the upper computer is used for processing and analyzing the data. According to the isolator, a sterile environment is maintained, the problems of microbial interference, poor reliability of experimental results, equipment limitation, imperfect monitoring means and the like in the prior art are solved, and a more efficient, accurate and reliable experimental tool is provided for research on the relationship between intestinal flora and animal behaviors.

The invention discloses an event-assisted unmanned aerial vehicle night precise landing system and method. The system comprises a high-frequency dynamic infrared sign array module, an event camera module, a pose resolving module and a landing control module. The system takes a high-frequency dynamic infrared mark array as a positioning reference, an event camera carried on the unmanned aerial vehicle captures an optical event flow with unique time sequence characteristics by accurately controlling the independent flicker frequency of each infrared light source, then the pose of the unmanned aerial vehicle is calculated by using an N-point perspective method, and finally accurate landing is realized by a landing control module. According to the invention, the event camera and the high-frequency dynamic infrared sign array are innovatively combined, the cooperative working mechanism of the event camera and the high-frequency dynamic infrared sign array is utilized, sub-millisecond-level positioning feedback is realized in a complex environment, the limitation of a traditional static optical sign is broken through, the positioning precision and reliability are improved, and the method is suitable for accurate take-off, landing and positioning of the unmanned aerial vehicle at night and in the complex environment.

The invention relates to a water transmission and distribution dynamic scheduling optimization method, which comprises the following steps that a water transmission and distribution test area is established, the water transmission and distribution test area comprises a test branch pipe, a gas pumping unit and a test user side, and two ends of the test branch pipe are respectively connected with a target water plant and the test user side; performing water hammer disturbance effect analysis on the test branch pipe to obtain a water hammer focus of the test branch pipe; air is pumped into the test branch pipe based on the air pumping unit, and vibration parameters and cutoff parameters of the water hammer focus are obtained through strain vibration monitoring and underwater sound cutoff monitoring; establishing an interference factor modulation unit, and performing interference parameter correction on the vibration parameter and the cutoff parameter based on the interference factor modulation unit to obtain a training parameter; circularly executing the previous step to obtain multiple groups of training data, and constructing and training based on the obtained training data to obtain a filtering matching unit; establishing a water transmission and distribution optimization network in the target pipe network area; and managing and optimizing water supply scheduling in the target pipe network domain based on the water transmission and distribution optimization network.

This invention relates to an efficient intelligent material library retrieval method and system based on multimodal vector fusion, applied in the field of information retrieval technology. The method includes: responding to user queries and displaying a result set; monitoring implicit interaction behaviors to generate behavioral sequence features; determining the target modality of the user's intent through an intent determination network; synchronously performing dynamic weight coordination and incremental index updates based on this; fusing behavioral features and queries to generate a refined query vector; and using the new weights to retrieve the main index and incremental index in parallel, then merging and sorting the results before outputting the final result. The system includes functional modules corresponding to the method, such as an initial retrieval module, a behavior monitoring and feature extraction module, and a real-time intent determination module. This invention achieves real-time personalized retrieval and system self-evolution by analyzing implicit behaviors and utilizing synchronous coordination and incremental indexing mechanisms, thereby improving retrieval accuracy and long-term performance.

The present invention discloses a non-tax special account supervision system and method based on electronic accounting vouchers, which relates to the field of data security supervision technology, including a supervision center, wherein the supervision center is communicatively connected with a data integration module, a data storage module, a data integration module, an anomaly detection module, an anomaly handling response module and a report analysis module, wherein the modules are connected by electrical signals. The present invention significantly improves the supervision efficiency through automated data integration and anomaly detection mechanisms, can monitor and analyze a large amount of electronic accounting voucher data in real time, and quickly identify abnormal situations. Compared with manual audit methods, the automated process reduces the possibility of human errors and omissions, and also reduces the work pressure of supervisors. In addition, a built-in risk warning mechanism immediately triggers the warning process once an abnormality or potential risk is found, which helps to take measures quickly to prevent the risk from expanding and spreading.

The invention provides an epilepsy clinical nursing early warning method and system, and relates to the technical field of medical information processing, the epilepsy clinical nursing early warning method comprises the following steps: obtaining multi-modal physiological signal data of an epilepsy patient, the multi-modal physiological signal data comprising electroencephalogram signal data and limb movement signal data; performing principal component analysis processing on the electroencephalogram signal data to obtain dimensionality-reduced electroencephalogram characteristic data; performing time-frequency decomposition on the dimensionality-reduced electroencephalogram characteristic data to obtain energy distribution of a plurality of frequency bands; calculating an information entropy value based on the energy distribution of the plurality of frequency bands; according to the information entropy and the limb movement signal data, the current state of the epileptic is judged through a decision tree model; determining a corresponding hidden danger level according to the current state and generating early warning information; according to the method, electroencephalogram artifacts are eliminated through principal component analysis, the state of the threatened period is recognized before epileptic seizure, and the problems of early warning lag and unstable response in the prior art are solved.

This utility model discloses a functional testing device for a mechanical massage mechanism component, including a worktable, several load units, a mounting mold, a rotation measuring instrument, and a displacement measuring instrument. The worktable includes an upper plate, a lower plate, and several support columns. The upper and lower ends of the support columns are fixedly connected to the upper and lower plates, respectively. The load unit includes a rotating shaft, a mounting plate, a stop block, and several counterweights. The lower end of the rotating shaft passes through the upper plate and is fixedly connected to the mounting plate. The stop block is installed on the rotating shaft above the upper plate, and the counterweights are sleeved on the rotating shaft above the stop block. The mounting mold includes several upper molds and lower molds. The upper mold is installed at the lower end of the mounting plate, and the lower mold is installed on the lower plate. The lower end of the upper mold is provided with an upper mounting groove, and the upper end of the lower mold is provided with a lower mounting groove. An installation rod is rotatably mounted on the upper end of the rotating shaft. A rotation measuring instrument is mounted on the installation rod. A displacement measuring instrument is mounted on the upper plate above the mounting plate.

In order to obtain an influence rule of formation and development of a strain localization shear band in a rock-soil body on mechanical properties, the invention aims to provide a triaxial test sample shear deformation process reconstruction method based on visual perception. The method has the advantages that the rock-soil body strain localization shear band forming process and related discrete-continuous medium related motion characteristics can be captured in a non-contact intelligent and lossless mode, and complex microstructure information can be obtained while sample surface displacement and strain are intelligently sensed. According to the technology, real-time shooting is carried out on the rock-soil body sample shearing process through multi-view external load visual identification equipment, threshold segmentation calculation and binarization processing are carried out after shot images are screened, and then the formation of non-uniform deformation of a soil body and the development condition of a non-continuous deformation failure form are intelligently measured. And intelligent calculation of a local concentrated strain distribution area is realized based on a visual algorithm.

The invention belongs to the technical field of aircraft cargo compartment smoke detection, and particularly relates to an airborne video monitoring system suitable for aircraft cargo compartment smoke detection. The system comprises a visible light / infrared video monitoring camera, a humidity sensor, an infrared thermal imaging detector, an infrared supplementary lighting device, a video processing computer, a cockpit display, a cockpit control panel and the like. The system has cargo hold video monitoring functions such as cargo hold cargo loading and unloading process monitoring, flight process cargo hold video monitoring and the like, and also can realize cargo hold smoke detection function by analyzing multi-source data, namely visible light / infrared video images, infrared thermal imaging images and humidity sensor data. Compared with a traditional airborne photoelectric smoke detector, the smoke detection response time is effectively shortened, the false alarm rate can be reduced, and the comprehensive performance of a smoke detection system is improved.

The invention discloses an intelligent cashier system transaction data classification and analysis method based on artificial intelligence, and the method comprises the following steps: S1, carrying out the preprocessing of the attributes of transaction data, and forming a dynamic space-time oscillogram; s2, forming a dynamic transaction graph through a self-adaptive space-time curved surface generator; s3, capturing the implicit state of the dynamic transaction graph based on the implicit state self-generation reasoning network, and automatically generating an implicit state mode in the transaction data; s4, performing multi-level classification based on the implicit state fluctuation matrix, and automatically generating and adjusting a classification strategy in combination with a spatio-temporal fluctuation learning algorithm; s5, reasoning is carried out through a self-driven reasoning engine, and path optimization is carried out; s6, performing future state deduction based on a high-order implicit state, identifying potential abnormal fluctuation in real time, and performing deep analysis; and S7, generating a visual chart through a multi-layer waveform visualization technology. According to the method, intelligent transaction data classification, anomaly detection and prediction analysis are realized by utilizing multi-dimensional space-time mapping and an implicit state reasoning network.

The utility model discloses an online automatic screw locking machine belongs to the technical field of automation equipment, and it includes work plane, intelligent electric screwdriver and product positioning system, including Y axis positioning mechanism, it is by Y axis positioning cylinder one drive Y axis positioning long piece, Y axis positioning cylinder two drive Y axis positioning block constitutes, and the product is clamped in cooperation, X axis positioning mechanism, and it is by X axis positioning cylinder drive X axis positioning block and is positioned, still includes pressing material mechanism, and pressing material lifting motor passes through the belt drive pressing material lifting plate lifting, and pressing material stretches out cylinder drive pressing material rod and stretches out and presses the product tightly. The utility model discloses through the cooperative work of X-Y axis self -adaptation positioning mechanism and Z axis pressing material mechanism, and the vision system is matched, has solved the problem that equipment compatibility is poor, and the problem that the replacement adjustment is complicated, can carry out the full -automatic screw locking of quick, accurate to different length width height's product on line, and production efficiency and automation level are high.

The utility model belongs to the technical field of detection devices, and particularly relates to a nylon 66 salt melting point measuring device. Comprising a miniature screw feeder, a hot melting sealing machine, a positioning device and a heating measuring device, the positioning device comprises a sliding rail, and a clamp is connected to the sliding rail; the heating measuring device comprises an electromagnetic heating device, a heating groove is formed in the electromagnetic heating device, and a temperature sensor and an optical fiber sensor are arranged in the heating groove. According to the device, by integrating a miniature spiral feeding system, a hot melting sealing system, an accurate positioning system, an automatic heating measurement system and other systems, the accuracy, operation convenience and measurement stability of nylon 66 salt melting point measurement are remarkably improved, meanwhile, automatic control over the measurement process is achieved, and the universality and adaptability of the device are enhanced.

The invention discloses a tissue inner surface displacement and strain measurement device and method, and the device comprises a simulated tissue which comprises a bionic polymer, a connecting liquid, and a to-be-measured tissue; the space between the to-be-detected tissue and the bionic polymer is filled with connecting liquid and then packaged; the loading device comprises an impact rod and a transmission rod, the impact rod is arranged at one end of the simulated tissue, and the transmission rod is arranged at the other end of the simulated tissue; the feature making tool is used for making two speckles randomly distributed on the two curved surfaces, the two speckles are transparent under natural light and present two different colors under illumination with a certain bandwidth, and the imaged curved surface picture has high contrast; the calibration tool is used for calibrating internal parameters and external parameters of the camera; and the data processing module is used for calculating the displacement and strain mechanical quantity of the acquired image and correcting a calculation result. The device solves the problems that when a contact impact object is measured, the measurement object and the impact object shield each other, the internal mechanical response of the object is difficult to capture, and the distortion error of the observation object is large.

The invention discloses an intelligent port and navigation management service integrated platform system. The platform system comprises a port and navigation operation monitoring module, a navigation channel integrated management module, a navigation intelligent transaction module and a port intelligent service module. The port navigation operation monitoring module is used for realizing unified operation monitoring of safety, production, scheduling and operation conditions of subordinate ports, channels, ship locks and logistics parks of the port affair group; the channel comprehensive management module is used for coordinating a channel maintenance project, a channel construction project and a related safety supervision project; the shipping smart transaction is used for optimizing the whole process of shipping transaction by creating a shipping transaction management platform; and the port intelligent service module is used for comprehensively supporting service requests of different business modes and different customer types of each business unit. According to the method, a unified data architecture and a business portal are constructed, cross-link and cross-system data sharing and one-stop operation are supported, and the problem that traditional business systems run independently and are difficult to co-schedule is solved.

This invention discloses a multi-source low-oxygen heat pump device for fruits and vegetables and its usage method, belonging to the field of fruit and vegetable drying technology. The device includes a multi-source gas supply system, a low-oxygen drying chamber, a heat pump temperature and humidity control system, an online weighing system, a material morphology detection system, and an intelligent control system. The multi-source gas supply system injects nitrogen, carbon dioxide, and air. The intelligent control system calculates the drying rate and shrinkage rate based on data from various sensors, dynamically adjusting the gas composition and the temperature and humidity inside the chamber to maintain an oxygen concentration of 1-11%, a temperature of 30-70℃, and a relative humidity of 10-40%. This invention enables precise and coordinated control of the fruit and vegetable drying process, mainly used for drying leafy vegetables and fruits, reducing oxidative deterioration and shrinkage, and improving drying quality.

The invention provides a voltage regulation and control method and device for light-storage-vehicle multi-agent cooperation, and relates to the technical field of power distribution network operation and control. The method comprises the following steps: constructing a secure Markov game model based on a multi-agent collaborative voltage regulation process, the multi-agent comprising a photovoltaic inverter, a battery energy storage system and an electric vehicle cluster in a power distribution network, the secure Markov game model comprises an agent set, a state and observation set, an action set, a secure action set, a secure transfer function and a reward function; constructing a light-storage-vehicle multi-agent decision-making framework, wherein the light-storage-vehicle multi-agent decision-making framework comprises an encoder based on a self-attention mechanism, a strategy network based on encoder driving and an evaluation network based on the encoder; and solving the secure Markov game model by using a light-storage-vehicle multi-agent decision-making architecture to realize a multi-agent collaborative voltage regulation and control strategy. According to the invention, the regulation and control accuracy can be improved.

The present invention provides a data processing method, device, equipment and readable medium for dealing with emergencies, which captures different data sources, processes the data of the different data sources to form a comprehensive data pool; screens the data in the comprehensive data pool to generate a data set; analyzes and calculates the data set to generate a specific character portrait; scores the specific character portrait using an evaluation model; and determines whether the specific character portrait needs to be processed. The present invention breaks the information barriers between the different data sources, forms a comprehensive data acquisition system, realizes real-time and accurate capture of crowd activity trajectories, and greatly improves the coverage and response speed of public security management.