109results about How to "Fast track" patented technology

The invention provides an information management method and system for an access control card chip. The method comprises the following steps: providing an anonymous identifier, initializing an authentication process, and laying a foundation for privacy protection and a data link; mutual trust authentication of the access control card and the equipment is completed, and authentication challenge data is provided for follow-up behavior recording and tracing; based on a result and challenge data generated after authentication is completed, generating a complete encryption behavior record and establishing a chained hash structure; storing the encrypted behavior record and the chained hash value locally or synchronizing the encrypted behavior record and the chained hash value to a server to ensure the reliability and traceability of the behavior record; and detecting abnormal behaviors and supporting traceability verification by using complete behavior chain data. Dynamic identity generation, encryption behavior chain storage and a bidirectional authentication mechanism are integrated in the access control card chip, so that the privacy protection capability, the safety and the tracing efficiency of the access control system are remarkably improved.

The invention discloses a drainage pipe network pollution traceability and alarm system based on invariant analysis, which belongs to the field of data communication of a data center and comprises a data collection module, a cloud platform processing module, an invariant analysis module, an abnormal emission identification and alarm module and a decision support system. The supervision efficiency of the drainage pipe network is improved, environmental pollution is reduced, and sustainable utilization of water resources is guaranteed; according to the system, various sensors are installed at key nodes of a drainage pipe network, data such as water quality, water level, water volume and flow velocity are collected in real time, and the data are transmitted to a cloud platform through a wireless communication technology; by utilizing the data processing capability of the cloud computing platform and combining with an invariant analysis algorithm, the system can quickly position a pollution source, track a pollution path and give an alarm to related personnel in time; the monitoring, management and pollution prevention and control capabilities of the drainage pipe network are effectively improved, and powerful technical support is provided for urban water resource management and environmental protection.

The invention discloses a multi-agent cooperative control system based on multi-mode brain-computer interface-visual tracking, and the system comprises the following modules: a signal collection and processing module which employs an 8-lead electroencephalogram cap to collect electroencephalogram original data, selects occipital region parts (PO7, PO8, P3, P4, Pz, O1, O2 and Oz) as an electroencephalogram data collection region, and carries out the EEG data collection; the feature extraction and classification module is used for extracting SSVEP signal features by using a space-time convolutional network, optimizing classification precision in combination with an integrated learning strategy, extracting EOG signals based on a Transform model, integrating an LMS adaptive filter and denoising the EEG signals in combination with wavelet transform, expanding the frequency tracking range of the adaptive filter, and reducing signal loss to the greatest extent; the cooperative control strategy design module is used for mapping the electroencephalogram signals into control instructions of different intelligent agents, and cooperative control over the unmanned aerial vehicle and the trolley is achieved; and the target detection and tracking module is used for optimizing an unmanned aerial vehicle visual tracking system based on a PP-YOLOE model and realizing accurate tracking and automatic adjustment of the trolley.

The embodiment of the invention relates to the field of trajectory tracking, and discloses a target detection tracking method, system and device and a storage medium, and the method comprises the steps: obtaining a plurality of image frames in a video or image sequence; performing detection by using a target detection model to obtain feature detection information of each image frame; inputting the feature detection information into a trajectory tracking model for analysis and processing, and establishing and tracking a motion trajectory of the target object; wherein the method specifically comprises the following steps of: associating the target object by utilizing the frame similarity among the plurality of bounding boxes; and establishing and tracking a motion track of the target object based on an association result. According to the method disclosed by the invention, the technical problems that the tracking object is difficult to accurately detect and the calculation time is relatively long and relatively large computing power resources need to be occupied are solved, the computing power can be reasonably distributed, the balance of high-precision detection and real-time monitoring is realized, the target object is quickly sensed in a complex shielding environment, and the target object detection and tracking effect is improved.

The invention relates to the technical field of machine vision, in particular to an image segmentation method and system for liquid crystal screen display. The method comprises the following steps: acquiring basic data of the liquid crystal screen; performing screen response characteristic analysis according to the basic data of the liquid crystal screen to obtain screen response characteristic data; performing multi-scale image acquisition according to the basic data of the liquid crystal screen to generate multi-scale image data; performing characteristic classification on the liquid crystal display according to the screen response characteristic data, and performing edge compensation analysis on the multi-scale image data to obtain edge characteristic compensation data; acquiring real-time data of the touch screen; and performing touch interference identification analysis on the real-time data of the touch screen according to the edge feature compensation data to generate touch interference mask data. By analyzing the screen response characteristics and performing edge compensation analysis, the phenomenon of edge blurring caused by liquid crystal response time limitation is reduced, and the accuracy of edge detection is improved.

The invention discloses a backstepping active-disturbance-rejection control method and device for a permanent magnet synchronous motor and a medium, and relates to the field of motor control. The invention aims to solve the problem of overshoot in the control process of the traditional three-phase motor. The invention relates to a backstepping active-disturbance-rejection control method for a permanent magnet synchronous motor. The method comprises the following steps: constructing a permanent magnet synchronous motor second-order dynamics simplified model with an error disturbance factor; de-noising the model by using a differential tracker; observing the denoised model by using a first-order extended state observer; obtaining an error disturbance factor of the motor control system by using a nonlinear state error feedback control law based on the observation result, and compensating the error disturbance factor to obtain external disturbance of the motor control system after compensation; and designing a backstepping controller of the permanent magnet synchronous motor by adopting a backstepping method on the basis of the compensated external disturbance of the motor control system, obtaining a control quantity by utilizing the backstepping controller of the permanent magnet synchronous motor, and further controlling a rotating speed ring in vector control of the permanent magnet synchronous motor.

The invention discloses an electric energy metering method and device based on harmonic self-adaptive observation and zero point tracking type SOGI-FLL. The electric energy metering method comprises the following steps: step 1, carrying out ADC sampling on voltage and current signals of a power grid; 2, performing frequency rapid estimation on the voltage signal based on a zero point tracking frequency-locked loop, and obtaining a fundamental wave angular frequency of a power grid in real time; step 3, constructing adaptive observers of voltage and current by using the fundamental wave angular frequency, and estimating parameters of fundamental waves, harmonic waves and direct current components in voltage and current signals in real time through an adaptive law based on Lyapunov stability; 4, according to the parameter estimation value, the amplitude and phase of the voltage and current are calculated; and step 5, calculating active power and reactive power of each harmonic based on the voltage and current amplitudes and phases obtained in the step 4, and summing to obtain total active power and total reactive power so as to realize metering of active electric energy and reactive electric energy. According to the invention, rapid and accurate metering of fundamental wave and harmonic wave electric energy under complex working conditions is realized.

The invention discloses a four-rotor unmanned aerial vehicle perception and control method and system under a complex visual condition, and belongs to the technical field of unmanned aerial vehicle control. According to the invention, by combining the KCF algorithm and the YOLO algorithm, more accurate and more robust target tracking is realized, and the defects of insufficient anti-interference performance of the traditional KCF algorithm in a complex environment and the limitation of the YOLO algorithm are overcome, so that the real-time sensing ability of the unmanned aerial vehicle to the target is improved; a robust PID control algorithm is used as a control part, accurate control over the speed and the position of the unmanned aerial vehicle is achieved, the stability and the accuracy of flight control are optimized, meanwhile, the calculation complexity of the system is reduced, and the real-time performance and the applicability of the system are improved; the method is not only suitable for the field of unmanned aerial vehicles, but also can be expanded to other application scenes requiring target tracking and accurate control.

The utility model discloses a pipe rod storage device which comprises a bottom beam, a first stand column, a second stand column and a middle stand column are welded to the upper portion of the bottom beam to form a pipe rod storage space, a hoisting mechanism is fixed to the first stand column, and a stacking mechanism is installed on the middle stand column. A clamping groove for containing the groove-shaped transverse pad and the pressing mechanism is formed between the second stand column and the middle stand column, tooth grooves matched with the pipe rod are formed in the groove-shaped transverse pad and the pressing mechanism, and an inserting hole mechanism is installed at the bottom of the bottom beam. The pipe rod storage device achieves storage work of pipe rods, facilitates storage and transportation of the pipe rods, avoids damage to end threads caused by mutual collision of the pipe rods in the layer-by-layer stacking process of the pipe rods, can achieve automatic boxing and automatic box unloading through a mechanical arm matched with the pipe rods, overcomes defects in an existing production process, reduces labor intensity of workers, and improves production efficiency. And the working efficiency is improved. And each pipe rod is marked during boxing, so that the required pipe rod can be conveniently and quickly tracked.

The invention discloses a three-phase electrode current preset time intelligent loop control method for an electric smelting furnace for magnesia, which specifically comprises the following steps: 1) selecting the electric smelting furnace for magnesia as a research object and analyzing the characteristics of equipment, and taking the electric smelting furnace as a representative as the production index of the smelting process of major energy-consuming equipment in the smelting process, namely the electric energy consumed by each ton of qualified products, namely the unit energy consumption; (2) controlled objects of a control system of the electrical smelting furnace for magnesium comprise unit energy consumption of the electrical smelting furnace for magnesium and three-phase electrode current of the electrical smelting furnace for magnesium, the controlled quantity is the rotating speed and direction of a three-phase dragging motor of the electrical smelting furnace for magnesium, and the unit energy consumption of a product is directly influenced by the magnitude and the stability degree of the three-phase electrode current value in the smelting process; and (3) analyzing the relationship between the three-phase electrode current of the electric smelting magnesium furnace and the rotating speed of the three-phase dragging motor, and calculating the rotating speed of the three-phase dragging motor according to the deviation between the actual three-phase electrode current value and the three-phase electrode current set value under the heating and melting working condition. A preset time consistency control algorithm based on self-adjusting gain is adopted to obtain the rotating speed and direction of the three-phase dragging motor under the heating and melting working condition; and (4) adjusting parameters of the preset time consistency control scheme in the step (3), performing preset time algorithm verification, and performing corresponding comparison with a PID algorithm of a traditional control method.

The invention belongs to the technical field of heterogeneous multi-agent trajectory tracking control, and particularly discloses a heterogeneous multi-agent instruction filtering fuzzy adaptive constraint control method and system. Aiming at the multi-unmanned aerial vehicle-multi-unmanned vehicle trajectory tracking control problem with unknown parameters and external interference, the invention designs an instruction filtering fuzzy adaptive controller based on state constraint so as to track a target position, and utilizes a fuzzy logic theory to process unknown nonlinear terms in a system so as to realize the tracking of the target position. A method of combining an instruction filtering technology and an error compensation mechanism is adopted, the problem of'calculation explosion 'occurring in a traditional backstepping method is solved, the influence of filtering errors is eliminated, and an output state is constrained in a given space based on a barrier Lyapunov function. According to the invention, the control performance of the multi-unmanned aerial vehicle-multi-unmanned vehicle formation system is improved, and meanwhile, it is ensured that the semi-global consistency of the multi-agent system is finally bounded.

The invention relates to the technical field of motion simulation platforms, in particular to a seven-axis motion simulation platform which comprises an upper platform, a lower platform, a supporting leg assembly and a one-dimensional rotary table assembly, a plurality of first hinge assemblies are arranged on the upper platform at intervals, and a plurality of second hinge assemblies are arranged on the lower platform at intervals; the top of the supporting leg assembly is rotatably connected to the first hinge assembly, and the bottom of the supporting leg assembly is rotatably connected to the second hinge assembly. The one-dimensional rotary table assembly is arranged above the upper platform; the first hinge assembly and the second hinge assembly have the azimuth rotation freedom degree with the axis in the horizontal direction and the pitching rotation freedom degree with the axis in the vertical direction correspondingly, and the supporting leg assembly can stretch out and draw back in the axis direction of the supporting leg assembly. Therefore, by combining the multi-axis parallel motion simulation platform and the single-axis one-dimensional turntable assembly, multi-degree-of-freedom, high-precision and high-stability small-range rapid motion trajectory tracking around any space rotation center and 360-degree large-range azimuth working condition switching of different measured target points are realized at the same time.

A sight and a pattern structure thereof, the pattern structure comprising a first pattern and a second pattern. The first pattern is a first geometric shape composed of a first light source unit and has a first color. The second pattern is a second geometric shape composed of the first light source unit. An inner side edge of the second pattern is oppositely arranged along an outer side edge of the first pattern, wherein the outer side edge of the first pattern and the inner side edge of the second pattern have a first characteristic interval between corresponding positions of each other, and the first characteristic interval between the corresponding positions is the same. The second pattern has a first end and a second end, the first end and the second end are oppositely arranged and connected to the inner side edge of the second pattern respectively, and the first end and the second end are separated by a second characteristic interval.

The invention provides a product data multi-dimensional full-period management method, system and device and a medium, and relates to the technical field of product data management, and the method comprises the steps: constructing a preset module; receiving project configuration information input by a user, calling and executing a corresponding clipping rule from a preset module based on the project configuration information, and dynamically generating a project baseline; on the basis of the project base line, constructing an incidence relation graph between the deliverables, and on the basis of the incidence relation graph and the dynamic Bayesian network, establishing a change influence probability propagation model between the deliverables; when it is monitored that the target deliverable is changed, based on a change influence probability propagation model, quantitative influence values of the change source deliverable on the associated deliverable in quality, progress and cost dimensions are calculated, and a change influence analysis report is generated; and outputting visual results of the project base line, the incidence relation graph and the change influence analysis report. Product data management is realized or assisted through an automatic system, and the management efficiency and effect of the product data are improved.

The application relates to an FPGA prototype verification method and system of a smart meter chip, and belongs to the field of integrated circuit testing and electric power metering. The method aims to solve the problems of ASIC design transplantation to an FPGA platform, large difference between a verification environment and a real power grid, and lack of a real-time closed-loop verification mechanism. A technical scheme efficiently transplants the design to the FPGA by optimizing ASIC front-end synthesis constraints and adopting a netlist-level IP replacement strategy; a hardware-in-the-loop system is constructed, which comprises a real power grid signal source, a separation device simulation front end, an FPGA verification board, a high-precision standard electric energy meter and a host computer. The system can generate a real power grid excitation and realize synchronous collection of prototype output and the standard meter, real-time error analysis and dynamic adjustment of parameters, thereby forming a closed-loop verification. The application significantly improves code transplantation efficiency, provides a highly consistent real power grid verification environment, and greatly improves verification iteration and defect positioning speed.

The invention relates to a dual-module intercooler type fuel cell cathode inlet temperature and humidity cooperative control method. The method comprises the steps that fuel cell cathode air inlet real-time state parameters and operation parameters are obtained, a multivariable coupling prediction model is constructed after preprocessing, and a temperature and humidity reference and an oxygen stoichiometric ratio target reference are set in combination with heat exchange characteristics of a dual-module intercooler; then the core body heat exchange distribution proportion is regulated and controlled, humidification adjustment is matched, and the core body heat exchange distribution proportion and the humidification adjustment intensity are dynamically adjusted according to the real-time working condition; comparing the deviation between the adjusted actual temperature and humidity and the target temperature and humidity reference, and correcting the heat exchange distribution proportion and the humidifying adjustment parameter through a dynamic constraint correction model; cooperative regulation and control of cathode inlet temperature and humidity are realized, dynamic change of working conditions is adapted, and stable operation of the fuel cell is guaranteed.

The invention relates to an energy storage converter parallel operation method, system and device and a storage medium, and belongs to the technical field of energy storage converter parallel operation, and the method comprises the steps: collecting three-phase voltage and current data of an energy storage converter side and a power grid side; according to the collected voltage and current data, actual active power and actual reactive power are obtained through calculation; calculating an output voltage and an output frequency according to the actual active power and the actual reactive power; carrying out DQ conversion on the output voltage, and converting the output voltage into a voltage given value under a DQ coordinate; the virtual impedance of the output line is calculated according to the voltage given value, the calculated virtual impedance is superposed to the voltage given value, and the final voltage input quantity is obtained; carrying out double closed-loop control of a voltage and current loop on the given value of the input voltage to generate a modulation wave; and generating a PWM signal of the switching tube according to the generated modulation wave, and controlling the conduction of the switching tube by the PWM signal so as to control the output power of the energy storage converter.

This invention discloses a wind vane-based drone flight control method, device, medium, and drone. The method includes: when a multi-rotor high-speed drone is cruising, acquiring the orientation of a wind vane mounted on the drone's fuselage in real time, and then determining the angle between the drone's flight speed direction and its central axis; determining whether the drone's flight speed direction and the central axis are aligned based on this angle; if so, maintaining the angle of the drone's rotatable wings unchanged; if not, adjusting the angle of the drone's rotatable wings based on the angle, and then performing a wind vane detection step. This invention solves the problem of existing multi-rotor high-speed drones being unable to quickly and accurately track targets during high-speed cruising.

The present application is applicable to the field of control technology, and provides a maximum power tracking method and device for a photovoltaic component. The method includes: obtaining a first output power value of the photovoltaic component at the current sampling moment, and a sampled power value of the photovoltaic component at the previous sampling moment; calculating a first power fluctuation coefficient of the photovoltaic component based on the first output power value and the sampled power value; obtaining a maximum reference voltage value corresponding to the global maximum power value of the photovoltaic component in the current environment when the first power fluctuation coefficient is greater than or equal to the first rated fluctuation coefficient; sending the maximum reference voltage value to the photovoltaic component as the operating reference voltage value, and the photovoltaic component is used to perform maximum power tracking according to the operating reference voltage value. The embodiment of the present application can enable the photovoltaic component to quickly track the maximum power value when the environment in which the photovoltaic component is located changes, thereby improving the speed at which the photovoltaic component tracks the maximum power value, thereby improving the working efficiency of the photovoltaic component.

The present invention discloses a method for simplified identification and performance prediction of uplink interference in a wireless system, comprising the following steps: step 1, determining the interference model required for simplified identification and performance prediction of interference; step 2, collecting user data generated when the wireless system is running; step 3, simplified interference identification; step 4, wireless performance prediction. The advantages of the present invention are that simplified interference identification is proposed, with signal user indication vector, interference user indication vector and power offset vector as features, UL-SINR measurement as labels, and supervised machine learning algorithm is used for training to obtain link-level interference relations, and a complete and accurate uplink interference relationship modeling scheme is provided without the need for additional physical equipment and user complete measurement reports, thereby realizing low-complexity, fast, accurate and complete link-level interference identification.

The invention belongs to the technical field of power systems. A full-automatic warehouse for metering assets of a power supply station is characterized by comprising a warehouse body, a rotary cabinet, an automatic grabbing mechanical arm, an RFID automatic recognition device, a service all-in-one machine and a conveying line. The warehouse is internally provided with a storage space, the warehouse is provided with a door and an asset access window, and the asset access window is provided with a window outer door and a window inner door; the rotary cabinet, the automatic grabbing mechanical arm, the RFID automatic recognition device and the conveying line are all located in the storeroom. One end of the conveying line is located at the asset access window, the RFID automatic identification device is installed on the automatic grabbing manipulator, and the automatic grabbing manipulator is located between the rotary cabinet and the conveying line; the business all-in-one machine is mounted on the outer side of the warehouse; the rotary cabinet, the automatic grabbing mechanical arm, the RFID automatic recognition device and the conveying line are all in communication connection with the service all-in-one machine. The method has the characteristic of improving the working efficiency and accuracy.

This invention belongs to the field of power system frequency stability analysis technology. It provides a method for tracking the renewable energy carrying capacity boundary of a power grid based on frequency stability constraints. It constructs a system aggregated frequency response model that integrates various frequency regulation resources, including synchronous generator units, wind power virtual inertia control units, grid-connected photovoltaic energy storage units, and independent energy storage systems. Based on this model, it establishes an explicit correlation between the minimum and maximum frequency change rates and the renewable energy penetration rate. A sensitivity-guided binary search algorithm is used to quickly track the carrying capacity boundary when operating conditions change. The normalized marginal improvement sensitivity of various frequency regulation resources to the carrying capacity boundary is calculated, and a resource allocation priority list is output. This invention unifies the modeling of multi-source heterogeneous frequency regulation resources, makes frequency dynamic constraints explicit, achieves efficient online tracking of the carrying capacity boundary and adaptive correction of model parameters, and provides quantitative decision support for the optimal allocation of frequency regulation resources.

The invention discloses a fuel cell fault diagnosis method and device based on a sensor signal and a medium, belongs to the technical field of fuel cells, and is used for solving the technical problem that the diagnosis accuracy is difficult to improve due to the fact that existing fuel cell fault diagnosis is limited to information of the sensor signal in a two-dimensional space. The method comprises: acquiring a sensor signal of a fuel cell; performing time-frequency transformation on the sensor signal to obtain a time-frequency spectrum image; feature points of the time-frequency spectrum image are obtained through feature extraction; the method comprises the following steps: acquiring a time-frequency spectrum image, copying the time-frequency spectrum image to obtain a first time-frequency spectrum image and a second time-frequency spectrum image, placing the first time-frequency spectrum image on a first plane, placing the second time-frequency spectrum image on a second plane, connecting mutually matched feature points to obtain a feature landscape, and determining the fault type of the fuel cell based on the feature landscape. According to the method, the limitation of observing the state information of the fuel cell from a low-dimensional angle is overcome, and the fault diagnosis accuracy of the fuel cell is improved.

This invention relates to the field of in-situ impedance testing technology for energy storage batteries. To address the current difficulties in achieving rapid tracking of wideband excitation signals and the inaccurate identification and measurement of electrochemical parameters, it provides a battery in-situ impedance testing method and system based on adaptive phase compensation. The method includes acquiring the initial reference current and actual sampled current of the battery charging and testing system; iteratively calculating the real-time phase lag angle and generating a corrected reference current command accordingly; predicting the current response in two steps based on a discrete mathematical model of the full-bridge converter in continuous conduction mode; and optimizing the switching state corresponding to the voltage vector that minimizes the composite cost function to drive the switching transistors of the full-bridge converter. This method balances fast dynamic response with zero phase error tracking, meeting the high-precision requirements of in-situ EIS testing of energy storage batteries.

The present invention proposes an information management method and system for access card chips, the method comprising: providing an anonymous identifier, initializing the authentication process, laying the foundation for privacy protection and data chain; completing mutual trust authentication between the access card and the device, and providing authentication challenge data for subsequent behavior recording and tracing; based on the results and challenge data generated after the authentication is completed, generating a complete encrypted behavior record and establishing a chain hash structure; storing the encrypted behavior record and the chain hash value locally or synchronizing them to a server to ensure the reliability and traceability of the behavior record; using the complete behavior chain data, detecting abnormal behavior and supporting traceability verification. The present invention significantly improves the privacy protection capability, security and tracing efficiency of the access control system by integrating dynamic identity generation, encrypted behavior chain storage and a two-way authentication mechanism in the access card chip.

The application belongs to the technical field of power system frequency modulation control, and discloses a hybrid energy storage control method for thermal power combined AGC frequency modulation, a thermal power unit AGC frequency modulation full-working-condition nonlinear dynamic model is constructed based on deep learning and an attention mechanism, the AGC regulation capacity boundary is calibrated in real time, and the actual operation characteristics of the unit are accurately matched; an improved adaptive VMD-wavelet packet multi-scale decomposition algorithm is used to split the frequency modulation instruction into three types of time scale components, and the execution subject is distributed in a targeted manner; the unit output is compensated in advance, the regulation dead zone is borne by the energy storage in full power, and the medium and high frequency instruction components can be tracked quickly; meanwhile, the power grid frequency disturbance is predicted and the instruction is corrected, so that the AGC regulation rate, accuracy and response time are improved; through cooperative power pre-distribution, the equipment fatigue accumulation and wear rate are reduced; for the hybrid energy storage, a three-target optimization model of SOC balance, minimum life loss and highest response priority is constructed, and differential life control is implemented.

The invention discloses a lithium battery state estimation method and system based on a PNGV model and a DEKF algorithm, and the method comprises the steps: firstly, carrying out the systematic offline test of a battery, and obtaining an open-circuit voltage-state of charge curve of the battery and the equivalent capacitance of a second-order PNGV equivalent circuit model; secondly, discretizing a continuous state equation of the model into a difference equation through bilinear transformation, and identifying other model parameters of the battery in different charge states by applying a recursive least square method; and finally, constructing a state filter and a parameter filter by adopting a double-extended Kalman filtering algorithm, and realizing collaborative estimation of the charge state and the health state through data interaction and feedback of the two filters. According to the method, through a progressive process of parameter identification and cooperative state estimation, the problems of time-varying characteristics and state coupling of battery model parameters are effectively solved, and the joint estimation precision and robustness of the state of charge and the state of health of the lithium battery under complex working conditions are remarkably improved.

The application discloses an adaptive industrial park power equipment intelligent management system, comprising: a park equipment information acquisition module for constructing a mapping relationship between equipment rooms and equipment types; a multifunctional linkage control module for generating a linkage priority list between multifunctional groups; an equipment state evaluation module for constructing an equipment state evaluation model and identifying the state type of the equipment; a linkage control sequencing module for determining the execution sequence of each equipment in the linkage control process; a linkage control execution module for generating an initial linkage control strategy and updating a control topology state; a patrol task management module for executing a patrol task and updating a patrol state and a linkage control instruction; and an equipment alarm and processing module for generating an alarm event list and classifying and distributing alarm information. The application effectively solves the problems of lack of dynamic adjustment of linkage control and low patrol efficiency in traditional power equipment management, and significantly improves equipment operation stability and management efficiency.

The application belongs to the technical field of intelligent manufacturing, and discloses a production quality online monitoring and tracing method and system for color steel profiled plates and aluminum-magnesium-manganese roof plates. Special sensing equipment is deployed in the whole link of raw material entering, profile forming and coating curing. Terahertz spectrum sensors, laser composite sensing units, infrared thermal imagers and other devices work together, and are matched with adaptive adjustment and self-calibration technologies to ensure the accuracy of process parameters and defect information collection. Cross-modal feature extraction and double-branch models are used for defect identification, which can accurately identify subtle surface defects, accurately locate internal micro-cracks and plate shape deviations, and realize full-process online monitoring. A hybrid trusted architecture combining blockchain, NFT and RFID is used to configure a unique identifier and digital certificate for each batch of plates, embed core quality information, and implant a special chip on the surface of the plate to support fast reading and writing in all scenarios.

The invention provides an article tracing method, device and equipment. The article tracing method provided by the invention comprises the following steps: acquiring a video image in a target area, and extracting at least one video frame from the video image; identifying each video frame in the at least one video frame by using a visual large model to obtain an identification result of the at least one video frame; according to the identification result, establishing an archive file of each article in the at least one video; and when a tracing request for tracing the target article is received, obtaining a target archive file of the target article from the established archive files, and returning the target archive file. According to the article tracing method, device and equipment provided by the invention, article tracing can be quickly and accurately carried out.